Evaluation of SMART sensor displays for multidimensional precision control of Space Shuttle remote manipulator

NASA Technical Reports Server (NTRS)

Bejczy, A. K.; Brown, J. W.; Lewis, J. L.

1982-01-01

An enhanced proximity sensor and display system was developed at the Jet Propulsion Laboratory (JPL) and tested on the full scale Space Shuttle Remote Manipulator at the Johnson Space Center (JSC) Manipulator Development Facility (MDF). The sensor system, integrated with a four-claw end effector, measures range error up to 6 inches, and pitch and yaw alignment errors within + or 15 deg., and displays error data on both graphic and numeric displays. The errors are referenced to the end effector control axes through appropriate data processing by a dedicated microcomputer acting on the sensor data in real time. Both display boxes contain a green lamp which indicates whether the combination of range, pitch and yaw errors will assure a successful grapple. More than 200 test runs were completed in early 1980 by three operators at JSC for grasping static and capturing slowly moving targets. The tests have indicated that the use of graphic/numeric displays of proximity sensor information improves precision control of grasp/capture range by more than a factor of two for both static and dynamic grapple conditions.

A pressure and shear sensor system for stress measurement at lower limb residuum/socket interface.

PubMed

Laszczak, P; McGrath, M; Tang, J; Gao, J; Jiang, L; Bader, D L; Moser, D; Zahedi, S

2016-07-01

A sensor system for measurement of pressure and shear at the lower limb residuum/socket interface is described. The system comprises of a flexible sensor unit and a data acquisition unit with wireless data transmission capability. Static and dynamic performance of the sensor system was characterised using a mechanical test machine. The static calibration results suggest that the developed sensor system presents high linearity (linearity error ≤ 3.8%) and resolution (0.9 kPa for pressure and 0.2 kPa for shear). Dynamic characterisation of the sensor system shows hysteresis error of approximately 15% for pressure and 8% for shear. Subsequently, a pilot amputee walking test was conducted. Three sensors were placed at the residuum/socket interface of a knee disarticulation amputee and simultaneous measurements were obtained during pilot amputee walking test. The pressure and shear peak values as well as their temporal profiles are presented and discussed. In particular, peak pressure and shear of approximately 58 kPa and 27 kPa, respectively, were recorded. Their temporal profiles also provide dynamic coupling information at this critical residuum/socket interface. These preliminary amputee test results suggest strong potential of the developed sensor system for exploitation as an assistive technology to facilitate socket design, socket fit and effective monitoring of lower limb residuum health. Copyright © 2016 IPEM. Published by Elsevier Ltd. All rights reserved.

Pre-shaping of the Fingertip of Robot Hand Covered with Net Structure Proximity Sensor

NASA Astrophysics Data System (ADS)

Suzuki, Kenji; Suzuki, Yosuke; Hasegawa, Hiroaki; Ming, Aiguo; Ishikawa, Masatoshi; Shimojo, Makoto

To achieve skillful tasks with multi-fingered robot hands, many researchers have been working on sensor-based control of them. Vision sensors and tactile sensors are indispensable for the tasks, however, the correctness of the information from the vision sensors decreases as a robot hand approaches to a grasping object because of occlusion. This research aims to achieve seamless detection for reliable grasp by use of proximity sensors: correcting the positional error of the hand in vision-based approach, and contacting the fingertip in the posture for effective tactile sensing. In this paper, we propose a method for adjusting the posture of the fingertip to the surface of the object. The method applies “Net-Structure Proximity Sensor” on the fingertip, which can detect the postural error in the roll and pitch axes between the fingertip and the object surface. The experimental result shows that the postural error is corrected in the both axes even if the object dynamically rotates.

Multi-sensor calibration of low-cost magnetic, angular rate and gravity systems.

PubMed

Lüken, Markus; Misgeld, Berno J E; Rüschen, Daniel; Leonhardt, Steffen

2015-10-13

We present a new calibration procedure for low-cost nine degrees-of-freedom (9DOF) magnetic, angular rate and gravity (MARG) sensor systems, which relies on a calibration cube, a reference table and a body sensor network (BSN). The 9DOF MARG sensor is part of our recently-developed "Integrated Posture and Activity Network by Medit Aachen" (IPANEMA) BSN. The advantage of this new approach is the use of the calibration cube, which allows for easy integration of two sensor nodes of the IPANEMA BSN. One 9DOF MARG sensor node is thereby used for calibration; the second 9DOF MARG sensor node is used for reference measurements. A novel algorithm uses these measurements to further improve the performance of the calibration procedure by processing arbitrarily-executed motions. In addition, the calibration routine can be used in an alignment procedure to minimize errors in the orientation between the 9DOF MARG sensor system and a motion capture inertial reference system. A two-stage experimental study is conducted to underline the performance of our calibration procedure. In both stages of the proposed calibration procedure, the BSN data, as well as reference tracking data are recorded. In the first stage, the mean values of all sensor outputs are determined as the absolute measurement offset to minimize integration errors in the derived movement model of the corresponding body segment. The second stage deals with the dynamic characteristics of the measurement system where the dynamic deviation of the sensor output compared to a reference system is Sensors 2015, 15 25920 corrected. In practical validation experiments, this procedure showed promising results with a maximum RMS error of 3.89°.

Processing Dynamic Image Sequences from a Moving Sensor.

DTIC Science & Technology

1984-02-01

65 Roadsign Image Sequence ..... ................ ... 70 Roadsign Sequence with Redundant Features .. ........ . 79 Roadsign Subimage...Selected Feature Error Values .. ........ 66 2c. Industrial Image Selected Feature Local Search Values. .. .... 67 3ab. Roadsign Image Error Values...72 3c. Roadsign Image Local Search Values ............. 73 4ab. Roadsign Redundant Feature Error Values. ............ 8 4c. Roadsign

Dynamic Tasking of Networked Sensors Using Covariance Information

DTIC Science & Technology

2010-09-01

has been created under an effort called TASMAN (Tasking Autonomous Sensors in a Multiple Application Network). One of the first studies utilizing this...environment was focused on a novel resource management approach, namely covariance-based tasking. Under this scheme, the state error covariance of...resident space objects (RSO), sensor characteristics, and sensor- target geometry were used to determine the effectiveness of future observations in

Multi-Sensor Calibration of Low-Cost Magnetic, Angular Rate and Gravity Systems

PubMed Central

Lüken, Markus; Misgeld, Berno J.E.; Rüschen, Daniel; Leonhardt, Steffen

2015-01-01

We present a new calibration procedure for low-cost nine degrees-of-freedom (9DOF) magnetic, angular rate and gravity (MARG) sensor systems, which relies on a calibration cube, a reference table and a body sensor network (BSN). The 9DOF MARG sensor is part of our recently-developed “Integrated Posture and Activity Network by Medit Aachen” (IPANEMA) BSN. The advantage of this new approach is the use of the calibration cube, which allows for easy integration of two sensor nodes of the IPANEMA BSN. One 9DOF MARG sensor node is thereby used for calibration; the second 9DOF MARG sensor node is used for reference measurements. A novel algorithm uses these measurements to further improve the performance of the calibration procedure by processing arbitrarily-executed motions. In addition, the calibration routine can be used in an alignment procedure to minimize errors in the orientation between the 9DOF MARG sensor system and a motion capture inertial reference system. A two-stage experimental study is conducted to underline the performance of our calibration procedure. In both stages of the proposed calibration procedure, the BSN data, as well as reference tracking data are recorded. In the first stage, the mean values of all sensor outputs are determined as the absolute measurement offset to minimize integration errors in the derived movement model of the corresponding body segment. The second stage deals with the dynamic characteristics of the measurement system where the dynamic deviation of the sensor output compared to a reference system is corrected. In practical validation experiments, this procedure showed promising results with a maximum RMS error of 3.89°. PMID:26473873

Modeling SMAP Spacecraft Attitude Control Estimation Error Using Signal Generation Model

NASA Technical Reports Server (NTRS)

Rizvi, Farheen

2016-01-01

Two ground simulation software are used to model the SMAP spacecraft dynamics. The CAST software uses a higher fidelity model than the ADAMS software. The ADAMS software models the spacecraft plant, controller and actuator models, and assumes a perfect sensor and estimator model. In this simulation study, the spacecraft dynamics results from the ADAMS software are used as CAST software is unavailable. The main source of spacecraft dynamics error in the higher fidelity CAST software is due to the estimation error. A signal generation model is developed to capture the effect of this estimation error in the overall spacecraft dynamics. Then, this signal generation model is included in the ADAMS software spacecraft dynamics estimate such that the results are similar to CAST. This signal generation model has similar characteristics mean, variance and power spectral density as the true CAST estimation error. In this way, ADAMS software can still be used while capturing the higher fidelity spacecraft dynamics modeling from CAST software.

A Dynamic Precision Evaluation Method for the Star Sensor in the Stellar-Inertial Navigation System.

PubMed

Lu, Jiazhen; Lei, Chaohua; Yang, Yanqiang

2017-06-28

Integrating the advantages of INS (inertial navigation system) and the star sensor, the stellar-inertial navigation system has been used for a wide variety of applications. The star sensor is a high-precision attitude measurement instrument; therefore, determining how to validate its accuracy is critical in guaranteeing its practical precision. The dynamic precision evaluation of the star sensor is more difficult than a static precision evaluation because of dynamic reference values and other impacts. This paper proposes a dynamic precision verification method of star sensor with the aid of inertial navigation device to realize real-time attitude accuracy measurement. Based on the gold-standard reference generated by the star simulator, the altitude and azimuth angle errors of the star sensor are calculated for evaluation criteria. With the goal of diminishing the impacts of factors such as the sensors' drift and devices, the innovative aspect of this method is to employ static accuracy for comparison. If the dynamic results are as good as the static results, which have accuracy comparable to the single star sensor's precision, the practical precision of the star sensor is sufficiently high to meet the requirements of the system specification. The experiments demonstrate the feasibility and effectiveness of the proposed method.

Conditional Entropy and Location Error in Indoor Localization Using Probabilistic Wi-Fi Fingerprinting.

PubMed

Berkvens, Rafael; Peremans, Herbert; Weyn, Maarten

2016-10-02

Localization systems are increasingly valuable, but their location estimates are only useful when the uncertainty of the estimate is known. This uncertainty is currently calculated as the location error given a ground truth, which is then used as a static measure in sometimes very different environments. In contrast, we propose the use of the conditional entropy of a posterior probability distribution as a complementary measure of uncertainty. This measure has the advantage of being dynamic, i.e., it can be calculated during localization based on individual sensor measurements, does not require a ground truth, and can be applied to discrete localization algorithms. Furthermore, for every consistent location estimation algorithm, both the location error and the conditional entropy measures must be related, i.e., a low entropy should always correspond with a small location error, while a high entropy can correspond with either a small or large location error. We validate this relationship experimentally by calculating both measures of uncertainty in three publicly available datasets using probabilistic Wi-Fi fingerprinting with eight different implementations of the sensor model. We show that the discrepancy between these measures, i.e., many location estimates having a high location error while simultaneously having a low conditional entropy, is largest for the least realistic implementations of the probabilistic sensor model. Based on the results presented in this paper, we conclude that conditional entropy, being dynamic, complementary to location error, and applicable to both continuous and discrete localization, provides an important extra means of characterizing a localization method.

Conditional Entropy and Location Error in Indoor Localization Using Probabilistic Wi-Fi Fingerprinting

PubMed Central

Berkvens, Rafael; Peremans, Herbert; Weyn, Maarten

2016-01-01

Localization systems are increasingly valuable, but their location estimates are only useful when the uncertainty of the estimate is known. This uncertainty is currently calculated as the location error given a ground truth, which is then used as a static measure in sometimes very different environments. In contrast, we propose the use of the conditional entropy of a posterior probability distribution as a complementary measure of uncertainty. This measure has the advantage of being dynamic, i.e., it can be calculated during localization based on individual sensor measurements, does not require a ground truth, and can be applied to discrete localization algorithms. Furthermore, for every consistent location estimation algorithm, both the location error and the conditional entropy measures must be related, i.e., a low entropy should always correspond with a small location error, while a high entropy can correspond with either a small or large location error. We validate this relationship experimentally by calculating both measures of uncertainty in three publicly available datasets using probabilistic Wi-Fi fingerprinting with eight different implementations of the sensor model. We show that the discrepancy between these measures, i.e., many location estimates having a high location error while simultaneously having a low conditional entropy, is largest for the least realistic implementations of the probabilistic sensor model. Based on the results presented in this paper, we conclude that conditional entropy, being dynamic, complementary to location error, and applicable to both continuous and discrete localization, provides an important extra means of characterizing a localization method. PMID:27706099

Modeling and Error Analysis of a Superconducting Gravity Gradiometer.

DTIC Science & Technology

1979-08-01

fundamental limit to instrument - -1- sensitivity is the thermal noise of the sensor . For the gradiometer design outlined above, the best sensitivity...Mapoles at Stanford. Chapter IV determines the relation between dynamic range, the sensor Q, and the thermal noise of the cryogenic accelerometer. An...C.1 Accelerometer Optimization (1) Development and optimization of the loaded diaphragm sensor . (2) Determination of the optimal values of the

Self-Evaluation of PANDA-FBG Based Sensing System for Dynamic Distributed Strain and Temperature Measurement.

PubMed

Zhu, Mengshi; Murayama, Hideaki; Wada, Daichi

2017-10-12

A novel method is introduced in this work for effectively evaluating the performance of the PANDA type polarization-maintaining fiber Bragg grating (PANDA-FBG) distributed dynamic strain and temperature sensing system. Conventionally, the errors during the measurement are unknown or evaluated by using other sensors such as strain gauge and thermocouples. This will make the sensing system complicated and decrease the efficiency since more than one kind of sensor is applied for the same measurand. In this study, we used the approximately constant ratio of primary errors in strain and temperature measurement and realized the self-evaluation of the sensing system, which can significantly enhance the applicability, as well as the reliability in strategy making.

Analysis of using EMG and mechanical sensors to enhance intent recognition in powered lower limb prostheses

NASA Astrophysics Data System (ADS)

Young, A. J.; Kuiken, T. A.; Hargrove, L. J.

2014-10-01

Objective. The purpose of this study was to determine the contribution of electromyography (EMG) data, in combination with a diverse array of mechanical sensors, to locomotion mode intent recognition in transfemoral amputees using powered prostheses. Additionally, we determined the effect of adding time history information using a dynamic Bayesian network (DBN) for both the mechanical and EMG sensors. Approach. EMG signals from the residual limbs of amputees have been proposed to enhance pattern recognition-based intent recognition systems for powered lower limb prostheses, but mechanical sensors on the prosthesis—such as inertial measurement units, position and velocity sensors, and load cells—may be just as useful. EMG and mechanical sensor data were collected from 8 transfemoral amputees using a powered knee/ankle prosthesis over basic locomotion modes such as walking, slopes and stairs. An offline study was conducted to determine the benefit of different sensor sets for predicting intent. Main results. EMG information was not as accurate alone as mechanical sensor information (p < 0.05) for any classification strategy. However, EMG in combination with the mechanical sensor data did significantly reduce intent recognition errors (p < 0.05) both for transitions between locomotion modes and steady-state locomotion. The sensor time history (DBN) classifier significantly reduced error rates compared to a linear discriminant classifier for steady-state steps, without increasing the transitional error, for both EMG and mechanical sensors. Combining EMG and mechanical sensor data with sensor time history reduced the average transitional error from 18.4% to 12.2% and the average steady-state error from 3.8% to 1.0% when classifying level-ground walking, ramps, and stairs in eight transfemoral amputee subjects. Significance. These results suggest that a neural interface in combination with time history methods for locomotion mode classification can enhance intent recognition performance; this strategy should be considered for future real-time experiments.

Optimal Control of a Surge-Mode WEC in Random Waves

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chertok, Allan; Ceberio, Olivier; Staby, Bill

2016-08-30

The objective of this project was to develop one or more real-time feedback and feed-forward (MPC) control algorithms for an Oscillating Surge Wave Converter (OSWC) developed by RME called SurgeWEC™ that leverages recent innovations in wave energy converter (WEC) control theory to maximize power production in random wave environments. The control algorithms synthesized innovations in dynamic programming and nonlinear wave dynamics using anticipatory wave sensors and localized sensor measurements; e.g. position and velocity of the WEC Power Take Off (PTO), with predictive wave forecasting data. The result was an advanced control system that uses feedback or feed-forward data from anmore » array of sensor channels comprised of both localized and deployed sensors fused into a single decision process that optimally compensates for uncertainties in the system dynamics, wave forecasts, and sensor measurement errors.« less

Accuracy Enhancement of Inertial Sensors Utilizing High Resolution Spectral Analysis

PubMed Central

Noureldin, Aboelmagd; Armstrong, Justin; El-Shafie, Ahmed; Karamat, Tashfeen; McGaughey, Don; Korenberg, Michael; Hussain, Aini

2012-01-01

In both military and civilian applications, the inertial navigation system (INS) and the global positioning system (GPS) are two complementary technologies that can be integrated to provide reliable positioning and navigation information for land vehicles. The accuracy enhancement of INS sensors and the integration of INS with GPS are the subjects of widespread research. Wavelet de-noising of INS sensors has had limited success in removing the long-term (low-frequency) inertial sensor errors. The primary objective of this research is to develop a novel inertial sensor accuracy enhancement technique that can remove both short-term and long-term error components from inertial sensor measurements prior to INS mechanization and INS/GPS integration. A high resolution spectral analysis technique called the fast orthogonal search (FOS) algorithm is used to accurately model the low frequency range of the spectrum, which includes the vehicle motion dynamics and inertial sensor errors. FOS models the spectral components with the most energy first and uses an adaptive threshold to stop adding frequency terms when fitting a term does not reduce the mean squared error more than fitting white noise. The proposed method was developed, tested and validated through road test experiments involving both low-end tactical grade and low cost MEMS-based inertial systems. The results demonstrate that in most cases the position accuracy during GPS outages using FOS de-noised data is superior to the position accuracy using wavelet de-noising.

Operational support for Upper Atmosphere Research Satellite (UARS) attitude sensors

NASA Technical Reports Server (NTRS)

Lee, M.; Garber, A.; Lambertson, M.; Raina, P.; Underwood, S.; Woodruff, C.

1994-01-01

The Upper Atmosphere Research Satellite (UARS) has several sensors that can provide observations for attitude determination: star trackers, Sun sensors (gimbaled as well as fixed), magnetometers, Earth sensors, and gyroscopes. The accuracy of these observations is important for mission success. Analysts on the Flight Dynamics Facility (FDF) UARS Attitude task monitor these data to evaluate the performance of the sensors taking corrective action when appropriate. Monitoring activities range from examining the data during real-time passes to constructing long-term trend plots. Increasing residuals (differences) between the observed and expected quantities is a prime indicator of sensor problems. Residual increases may be due to alignment shifts and/or degradation in sensor output. Residuals from star tracker data revealed and anomalous behavior that contributes to attitude errors. Compensating for this behavior has significantly reduced the attitude errors. This paper discusses the methods used by the FDF UARS attitude task for maintenance of the attitude sensors, including short- and long-term monitoring, trend analysis, and calibration methods, and presents the results obtained through corrective action.

Analysis and Compensation of Modulation Angular Rate Error Based on Missile-Borne Rotation Semi-Strapdown Inertial Navigation System.

PubMed

Zhang, Jiayu; Li, Jie; Zhang, Xi; Che, Xiaorui; Huang, Yugang; Feng, Kaiqiang

2018-05-04

The Semi-Strapdown Inertial Navigation System (SSINS) provides a new solution to attitude measurement of a high-speed rotating missile. However, micro-electro-mechanical-systems (MEMS) inertial measurement unit (MIMU) outputs are corrupted by significant sensor errors. In order to improve the navigation precision, a rotation modulation technology method called Rotation Semi-Strapdown Inertial Navigation System (RSSINS) is introduced into SINS. In fact, the stability of the modulation angular rate is difficult to achieve in a high-speed rotation environment. The changing rotary angular rate has an impact on the inertial sensor error self-compensation. In this paper, the influence of modulation angular rate error, including acceleration-deceleration process, and instability of the angular rate on the navigation accuracy of RSSINS is deduced and the error characteristics of the reciprocating rotation scheme are analyzed. A new compensation method is proposed to remove or reduce sensor errors so as to make it possible to maintain high precision autonomous navigation performance by MIMU when there is no external aid. Experiments have been carried out to validate the performance of the method. In addition, the proposed method is applicable for modulation angular rate error compensation under various dynamic conditions.

Extended Kalman filter for attitude estimation of the earth radiation budget satellite

NASA Technical Reports Server (NTRS)

Deutschmann, Julie; Bar-Itzhack, Itzhack Y.

1989-01-01

The design and testing of an Extended Kalman Filter (EKF) for ground attitude determination, misalignment estimation and sensor calibration of the Earth Radiation Budget Satellite (ERBS) are described. Attitude is represented by the quaternion of rotation and the attitude estimation error is defined as an additive error. Quaternion normalization is used for increasing the convergence rate and for minimizing the need for filter tuning. The development of the filter dynamic model, the gyro error model and the measurement models of the Sun sensors, the IR horizon scanner and the magnetometers which are used to generate vector measurements are also presented. The filter is applied to real data transmitted by ERBS sensors. Results are presented and analyzed and the EKF advantages as well as sensitivities are discussed. On the whole the filter meets the expected synergism, accuracy and robustness.

A software solution to dynamically reduce metallic distortions of electromagnetic tracking systems for image-guided surgery.

PubMed

Li, Mengfei; Hansen, Christian; Rose, Georg

2017-09-01

Electromagnetic tracking systems (EMTS) have achieved a high level of acceptance in clinical settings, e.g., to support tracking of medical instruments in image-guided interventions. However, tracking errors caused by movable metallic medical instruments and electronic devices are a critical problem which prevents the wider application of EMTS for clinical applications. We plan to introduce a method to dynamically reduce tracking errors caused by metallic objects in proximity to the magnetic sensor coil of the EMTS. We propose a method using ramp waveform excitation based on modeling the conductive distorter as a resistance-inductance circuit. Additionally, a fast data acquisition method is presented to speed up the refresh rate. With the current approach, the sensor's positioning mean error is estimated to be 3.4, 1.3 and 0.7 mm, corresponding to a distance between the sensor and center of the transmitter coils' array of up to 200, 150 and 100 mm, respectively. The sensor pose error caused by different medical instruments placed in proximity was reduced by the proposed method to a level lower than 0.5 mm in position and [Formula: see text] in orientation. By applying the newly developed fast data acquisition method, we achieved a system refresh rate up to approximately 12.7 frames per second. Our software-based approach can be integrated into existing medical EMTS seamlessly with no change in hardware. It improves the tracking accuracy of clinical EMTS when there is a metallic object placed near the sensor coil and has the potential to improve the safety and outcome of image-guided interventions.

Use of Tekscan K-Scan Sensors for Retropatellar Pressure Measurement Avoiding Errors during Implantation and the Effects of Shear Forces on the Measurement Precision

PubMed Central

Wilharm, A.; Hurschler, Ch.; Dermitas, T.; Bohnsack, M.

2013-01-01

Pressure-sensitive K-Scan 4000 sensors (Tekscan, USA) provide new possibilities for the dynamic measurement of force and pressure in biomechanical investigations. We examined the sensors to determine in particular whether they are also suitable for reliable measurements of retropatellar forces and pressures. Insertion approaches were also investigated and a lateral parapatellar arthrotomy supplemented by parapatellar sutures proved to be the most reliable method. The ten human cadaver knees were tested in a knee-simulating machine at a torque of 30 and 40 Nm. Each test cycle involved a dynamic extension from 120° flexion. All recorded parameters showed a decrease of 1-2% per measurement cycle. Although we supplemented the sensors with a Teflon film, the decrease, which was likely caused by shear force, was significant. We evaluated 12 cycles and observed a linear decrease in parameters up to 17.2% (coefficient of regression 0.69–0.99). In our opinion, the linear decrease can be considered a systematic error and can therefore be quantified and accounted for in subsequent experiments. That will ensure reliable retropatellar usage of Tekscan sensors and distinguish the effects of knee joint surgeries from sensor wear-related effects. PMID:24369018

An Improved Method for Dynamic Measurement of Deflections of the Vertical Based on the Maintenance of Attitude Reference

PubMed Central

Dai, Dongkai; Wang, Xingshu; Zhan, Dejun; Huang, Zongsheng

2014-01-01

A new method for dynamic measurement of deflections of the vertical (DOV) is proposed in this paper. The integration of an inertial navigation system (INS) and global navigation satellite system (GNSS) is constructed to measure the body's attitude with respect to the astronomical coordinates. Simultaneously, the attitude with respect to the geodetic coordinates is initially measured by a star sensor under quasi-static condition and then maintained by the laser gyroscope unit (LGU), which is composed of three gyroscopes in the INS, when the vehicle travels along survey lines. Deflections of the vertical are calculated by using the difference between the attitudes with respect to the geodetic coordinates and astronomical coordinates. Moreover, an algorithm for removing the trend error of the vertical deflections is developed with the aid of Earth Gravitational Model 2008 (EGM2008). In comparison with traditional methods, the new method required less accurate GNSS, because the dynamic acceleration calculation is avoided. The errors of inertial sensors are well resolved in the INS/GNSS integration, which is implemented by a Rauch–Tung–Striebel (RTS) smoother. In addition, a single-axis indexed INS is adopted to improve the observability of the system errors and to restrain the inertial sensor errors. The proposed method is validated by Monte Carlo simulations. The results show that deflections of the vertical can achieve a precision of better than 1″ for a single survey line. The proposed method can be applied to a gravimetry system based on a ground vehicle or ship with a speed lower than 25 m/s. PMID:25192311

An improved method for dynamic measurement of deflections of the vertical based on the maintenance of attitude reference.

PubMed

Dai, Dongkai; Wang, Xingshu; Zhan, Dejun; Huang, Zongsheng

2014-09-03

A new method for dynamic measurement of deflections of the vertical (DOV) is proposed in this paper. The integration of an inertial navigation system (INS) and global navigation satellite system (GNSS) is constructed to measure the body's attitude with respect to the astronomical coordinates. Simultaneously, the attitude with respect to the geodetic coordinates is initially measured by a star sensor under quasi-static condition and then maintained by the laser gyroscope unit (LGU), which is composed of three gyroscopes in the INS, when the vehicle travels along survey lines. Deflections of the vertical are calculated by using the difference between the attitudes with respect to the geodetic coordinates and astronomical coordinates. Moreover, an algorithm for removing the trend error of the vertical deflections is developed with the aid of Earth Gravitational Model 2008 (EGM2008). In comparison with traditional methods, the new method required less accurate GNSS, because the dynamic acceleration calculation is avoided. The errors of inertial sensors are well resolved in the INS/GNSS integration, which is implemented by a Rauch-Tung-Striebel (RTS) smoother. In addition, a single-axis indexed INS is adopted to improve the observability of the system errors and to restrain the inertial sensor errors. The proposed method is validated by Monte Carlo simulations. The results show that deflections of the vertical can achieve a precision of better than 1″ for a single survey line. The proposed method can be applied to a gravimetry system based on a ground vehicle or ship with a speed lower than 25 m/s.

Dynamic Method for Identifying Collected Sample Mass

NASA Technical Reports Server (NTRS)

Carson, John

2008-01-01

G-Sample is designed for sample collection missions to identify the presence and quantity of sample material gathered by spacecraft equipped with end effectors. The software method uses a maximum-likelihood estimator to identify the collected sample's mass based on onboard force-sensor measurements, thruster firings, and a dynamics model of the spacecraft. This makes sample mass identification a computation rather than a process requiring additional hardware. Simulation examples of G-Sample are provided for spacecraft model configurations with a sample collection device mounted on the end of an extended boom. In the absence of thrust knowledge errors, the results indicate that G-Sample can identify the amount of collected sample mass to within 10 grams (with 95-percent confidence) by using a force sensor with a noise and quantization floor of 50 micrometers. These results hold even in the presence of realistic parametric uncertainty in actual spacecraft inertia, center-of-mass offset, and first flexibility modes. Thrust profile knowledge is shown to be a dominant sensitivity for G-Sample, entering in a nearly one-to-one relationship with the final mass estimation error. This means thrust profiles should be well characterized with onboard accelerometers prior to sample collection. An overall sample-mass estimation error budget has been developed to approximate the effect of model uncertainty, sensor noise, data rate, and thrust profile error on the expected estimate of collected sample mass.

Vehicle dynamic prediction systems with on-line identification of vehicle parameters and road conditions.

PubMed

Hsu, Ling-Yuan; Chen, Tsung-Lin

2012-11-13

This paper presents a vehicle dynamics prediction system, which consists of a sensor fusion system and a vehicle parameter identification system. This sensor fusion system can obtain the six degree-of-freedom vehicle dynamics and two road angles without using a vehicle model. The vehicle parameter identification system uses the vehicle dynamics from the sensor fusion system to identify ten vehicle parameters in real time, including vehicle mass, moment of inertial, and road friction coefficients. With above two systems, the future vehicle dynamics is predicted by using a vehicle dynamics model, obtained from the parameter identification system, to propagate with time the current vehicle state values, obtained from the sensor fusion system. Comparing with most existing literatures in this field, the proposed approach improves the prediction accuracy both by incorporating more vehicle dynamics to the prediction system and by on-line identification to minimize the vehicle modeling errors. Simulation results show that the proposed method successfully predicts the vehicle dynamics in a left-hand turn event and a rollover event. The prediction inaccuracy is 0.51% in a left-hand turn event and 27.3% in a rollover event.

Vehicle Dynamic Prediction Systems with On-Line Identification of Vehicle Parameters and Road Conditions

PubMed Central

Hsu, Ling-Yuan; Chen, Tsung-Lin

2012-01-01

This paper presents a vehicle dynamics prediction system, which consists of a sensor fusion system and a vehicle parameter identification system. This sensor fusion system can obtain the six degree-of-freedom vehicle dynamics and two road angles without using a vehicle model. The vehicle parameter identification system uses the vehicle dynamics from the sensor fusion system to identify ten vehicle parameters in real time, including vehicle mass, moment of inertial, and road friction coefficients. With above two systems, the future vehicle dynamics is predicted by using a vehicle dynamics model, obtained from the parameter identification system, to propagate with time the current vehicle state values, obtained from the sensor fusion system. Comparing with most existing literatures in this field, the proposed approach improves the prediction accuracy both by incorporating more vehicle dynamics to the prediction system and by on-line identification to minimize the vehicle modeling errors. Simulation results show that the proposed method successfully predicts the vehicle dynamics in a left-hand turn event and a rollover event. The prediction inaccuracy is 0.51% in a left-hand turn event and 27.3% in a rollover event. PMID:23202231

A Dynamic Range Enhanced Readout Technique with a Two-Step TDC for High Speed Linear CMOS Image Sensors.

PubMed

Gao, Zhiyuan; Yang, Congjie; Xu, Jiangtao; Nie, Kaiming

2015-11-06

This paper presents a dynamic range (DR) enhanced readout technique with a two-step time-to-digital converter (TDC) for high speed linear CMOS image sensors. A multi-capacitor and self-regulated capacitive trans-impedance amplifier (CTIA) structure is employed to extend the dynamic range. The gain of the CTIA is auto adjusted by switching different capacitors to the integration node asynchronously according to the output voltage. A column-parallel ADC based on a two-step TDC is utilized to improve the conversion rate. The conversion is divided into coarse phase and fine phase. An error calibration scheme is also proposed to correct quantization errors caused by propagation delay skew within -T(clk)~+T(clk). A linear CMOS image sensor pixel array is designed in the 0.13 μm CMOS process to verify this DR-enhanced high speed readout technique. The post simulation results indicate that the dynamic range of readout circuit is 99.02 dB and the ADC achieves 60.22 dB SNDR and 9.71 bit ENOB at a conversion rate of 2 MS/s after calibration, with 14.04 dB and 2.4 bit improvement, compared with SNDR and ENOB of that without calibration.

Absolute vs. relative error characterization of electromagnetic tracking accuracy

NASA Astrophysics Data System (ADS)

Matinfar, Mohammad; Narayanasamy, Ganesh; Gutierrez, Luis; Chan, Raymond; Jain, Ameet

2010-02-01

Electromagnetic (EM) tracking systems are often used for real time navigation of medical tools in an Image Guided Therapy (IGT) system. They are specifically advantageous when the medical device requires tracking within the body of a patient where line of sight constraints prevent the use of conventional optical tracking. EM tracking systems are however very sensitive to electromagnetic field distortions. These distortions, arising from changes in the electromagnetic environment due to the presence of conductive ferromagnetic surgical tools or other medical equipment, limit the accuracy of EM tracking, in some cases potentially rendering tracking data unusable. We present a mapping method for the operating region over which EM tracking sensors are used, allowing for characterization of measurement errors, in turn providing physicians with visual feedback about measurement confidence or reliability of localization estimates. In this instance, we employ a calibration phantom to assess distortion within the operating field of the EM tracker and to display in real time the distribution of measurement errors, as well as the location and extent of the field associated with minimal spatial distortion. The accuracy is assessed relative to successive measurements. Error is computed for a reference point and consecutive measurement errors are displayed relative to the reference in order to characterize the accuracy in near-real-time. In an initial set-up phase, the phantom geometry is calibrated by registering the data from a multitude of EM sensors in a non-ferromagnetic ("clean") EM environment. The registration results in the locations of sensors with respect to each other and defines the geometry of the sensors in the phantom. In a measurement phase, the position and orientation data from all sensors are compared with the known geometry of the sensor spacing, and localization errors (displacement and orientation) are computed. Based on error thresholds provided by the operator, the spatial distribution of localization errors are clustered and dynamically displayed as separate confidence zones within the operating region of the EM tracker space.

Error compensation of single-antenna attitude determination using GNSS for Low-dynamic applications

NASA Astrophysics Data System (ADS)

Chen, Wen; Yu, Chao; Cai, Miaomiao

2017-04-01

GNSS-based single-antenna pseudo-attitude determination method has attracted more and more attention from the field of high-dynamic navigation due to its low cost, low system complexity, and no temporal accumulated errors. Related researches indicate that this method can be an important complement or even an alternative to the traditional sensors for general accuracy requirement (such as small UAV navigation). The application of single-antenna attitude determining method to low-dynamic carrier has just started. Different from the traditional multi-antenna attitude measurement technique, the pseudo-attitude attitude determination method calculates the rotation angle of the carrier trajectory relative to the earth. Thus it inevitably contains some deviations comparing with the real attitude angle. In low-dynamic application, these deviations are particularly noticeable, which may not be ignored. The causes of the deviations can be roughly classified into three categories, including the measurement error, the offset error, and the lateral error. Empirical correction strategies for the formal two errors have been promoted in previous study, but lack of theoretical support. In this paper, we will provide quantitative description of the three type of errors and discuss the related error compensation methods. Vehicle and shipborne experiments were carried out to verify the feasibility of the proposed correction methods. Keywords: Error compensation; Single-antenna; GNSS; Attitude determination; Low-dynamic

Optimum Sensors Integration for Multi-Sensor Multi-Target Environment for Ballistic Missile Defense Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Imam, Neena; Barhen, Jacob; Glover, Charles Wayne

2012-01-01

Multi-sensor networks may face resource limitations in a dynamically evolving multiple target tracking scenario. It is necessary to task the sensors efficiently so that the overall system performance is maximized within the system constraints. The central sensor resource manager may control the sensors to meet objective functions that are formulated to meet system goals such as minimization of track loss, maximization of probability of target detection, and minimization of track error. This paper discusses the variety of techniques that may be utilized to optimize sensor performance for either near term gain or future reward over a longer time horizon.

Analysis and Compensation of Modulation Angular Rate Error Based on Missile-Borne Rotation Semi-Strapdown Inertial Navigation System

PubMed Central

Zhang, Jiayu; Li, Jie; Zhang, Xi; Che, Xiaorui; Huang, Yugang; Feng, Kaiqiang

2018-01-01

The Semi-Strapdown Inertial Navigation System (SSINS) provides a new solution to attitude measurement of a high-speed rotating missile. However, micro-electro-mechanical-systems (MEMS) inertial measurement unit (MIMU) outputs are corrupted by significant sensor errors. In order to improve the navigation precision, a rotation modulation technology method called Rotation Semi-Strapdown Inertial Navigation System (RSSINS) is introduced into SINS. In fact, the stability of the modulation angular rate is difficult to achieve in a high-speed rotation environment. The changing rotary angular rate has an impact on the inertial sensor error self-compensation. In this paper, the influence of modulation angular rate error, including acceleration-deceleration process, and instability of the angular rate on the navigation accuracy of RSSINS is deduced and the error characteristics of the reciprocating rotation scheme are analyzed. A new compensation method is proposed to remove or reduce sensor errors so as to make it possible to maintain high precision autonomous navigation performance by MIMU when there is no external aid. Experiments have been carried out to validate the performance of the method. In addition, the proposed method is applicable for modulation angular rate error compensation under various dynamic conditions. PMID:29734707

Online Soft Sensor of Humidity in PEM Fuel Cell Based on Dynamic Partial Least Squares

PubMed Central

Long, Rong; Chen, Qihong; Zhang, Liyan; Ma, Longhua; Quan, Shuhai

2013-01-01

Online monitoring humidity in the proton exchange membrane (PEM) fuel cell is an important issue in maintaining proper membrane humidity. The cost and size of existing sensors for monitoring humidity are prohibitive for online measurements. Online prediction of humidity using readily available measured data would be beneficial to water management. In this paper, a novel soft sensor method based on dynamic partial least squares (DPLS) regression is proposed and applied to humidity prediction in PEM fuel cell. In order to obtain data of humidity and test the feasibility of the proposed DPLS-based soft sensor a hardware-in-the-loop (HIL) test system is constructed. The time lag of the DPLS-based soft sensor is selected as 30 by comparing the root-mean-square error in different time lag. The performance of the proposed DPLS-based soft sensor is demonstrated by experimental results. PMID:24453923

A High Performance Piezoelectric Sensor for Dynamic Force Monitoring of Landslide.

PubMed

Li, Ming; Cheng, Wei; Chen, Jiangpan; Xie, Ruili; Li, Xiongfei

2017-02-17

Due to the increasing influence of human engineering activities, it is important to monitor the transient disturbance during the evolution process of landslide. For this purpose, a high-performance piezoelectric sensor is presented in this paper. To adapt the high static and dynamic stress environment in slope engineering, two key techniques, namely, the self-structure pressure distribution method (SSPDM) and the capacitive circuit voltage distribution method (CCVDM) are employed in the design of the sensor. The SSPDM can greatly improve the compressive capacity and the CCVDM can quantitatively decrease the high direct response voltage. Then, the calibration experiments are conducted via the independently invented static and transient mechanism since the conventional testing machines cannot match the calibration requirements. The sensitivity coefficient is obtained and the results reveal that the sensor has the characteristics of high compressive capacity, stable sensitivities under different static preload levels and wide-range dynamic measuring linearity. Finally, to reduce the measuring error caused by charge leakage of the piezoelectric element, a low-frequency correction method is proposed and experimental verified. Therefore, with the satisfactory static and dynamic properties and the improving low-frequency measuring reliability, the sensor can complement dynamic monitoring capability of the existing landslide monitoring and forecasting system.

Improved Correction System for Vibration Sensitive Inertial Angle of Attack Measurement Devices

NASA Technical Reports Server (NTRS)

Crawford, Bradley L.; Finley, Tom D.

2000-01-01

Inertial angle of attack (AoA) devices currently in use at NASA Langley Research Center (LaRC) are subject to inaccuracies due to centrifugal accelerations caused by model dynamics, also known as sting whip. Recent literature suggests that these errors can be as high as 0.25 deg. With the current AoA accuracy target at LaRC being 0.01 deg., there is a dire need for improvement. With other errors in the inertial system (temperature, rectification, resolution, etc.) having been reduced to acceptable levels, a system is currently being developed at LaRC to measure and correct for the sting-whip-induced errors. By using miniaturized piezoelectric accelerometers and magnetohydrodynamic rate sensors, not only can the total centrifugal acceleration be measured, but yaw and pitch dynamics in the tunnel can also be characterized. These corrections can be used to determine a tunnel's past performance and can also indicate where efforts need to be concentrated to reduce these dynamics. Included in this paper are data on individual sensors, laboratory testing techniques, package evaluation, and wind tunnel test results on a High Speed Research (HSR) model in the Langley 16-Foot Transonic Wind Tunnel.

Kinematic model for the space-variant image motion of star sensors under dynamical conditions

NASA Astrophysics Data System (ADS)

Liu, Chao-Shan; Hu, Lai-Hong; Liu, Guang-Bin; Yang, Bo; Li, Ai-Jun

2015-06-01

A kinematic description of a star spot in the focal plane is presented for star sensors under dynamical conditions, which involves all necessary parameters such as the image motion, velocity, and attitude parameters of the vehicle. Stars at different locations of the focal plane correspond to the slightly different orientation and extent of motion blur, which characterize the space-variant point spread function. Finally, the image motion, the energy distribution, and centroid extraction are numerically investigated using the kinematic model under dynamic conditions. A centroid error of eight successive iterations <0.002 pixel is used as the termination criterion for the Richardson-Lucy deconvolution algorithm. The kinematic model of a star sensor is useful for evaluating the compensation algorithms of motion-blurred images.

Evaluation of passenger health risk assessment of sustainable indoor air quality monitoring in metro systems based on a non-Gaussian dynamic sensor validation method.

PubMed

Kim, MinJeong; Liu, Hongbin; Kim, Jeong Tai; Yoo, ChangKyoo

2014-08-15

Sensor faults in metro systems provide incorrect information to indoor air quality (IAQ) ventilation systems, resulting in the miss-operation of ventilation systems and adverse effects on passenger health. In this study, a new sensor validation method is proposed to (1) detect, identify and repair sensor faults and (2) evaluate the influence of sensor reliability on passenger health risk. To address the dynamic non-Gaussianity problem of IAQ data, dynamic independent component analysis (DICA) is used. To detect and identify sensor faults, the DICA-based squared prediction error and sensor validity index are used, respectively. To restore the faults to normal measurements, a DICA-based iterative reconstruction algorithm is proposed. The comprehensive indoor air-quality index (CIAI) that evaluates the influence of the current IAQ on passenger health is then compared using the faulty and reconstructed IAQ data sets. Experimental results from a metro station showed that the DICA-based method can produce an improved IAQ level in the metro station and reduce passenger health risk since it more accurately validates sensor faults than do conventional methods. Copyright © 2014 Elsevier B.V. All rights reserved.

Sensor fault detection and recovery in satellite attitude control

NASA Astrophysics Data System (ADS)

Nasrolahi, Seiied Saeed; Abdollahi, Farzaneh

2018-04-01

This paper proposes an integrated sensor fault detection and recovery for the satellite attitude control system. By introducing a nonlinear observer, the healthy sensor measurements are provided. Considering attitude dynamics and kinematic, a novel observer is developed to detect the fault in angular rate as well as attitude sensors individually or simultaneously. There is no limit on type and configuration of attitude sensors. By designing a state feedback based control signal and Lyapunov stability criterion, the uniformly ultimately boundedness of tracking errors in the presence of sensor faults is guaranteed. Finally, simulation results are presented to illustrate the performance of the integrated scheme.

Non-Linearity in Wide Dynamic Range CMOS Image Sensors Utilizing a Partial Charge Transfer Technique.

PubMed

Shafie, Suhaidi; Kawahito, Shoji; Halin, Izhal Abdul; Hasan, Wan Zuha Wan

2009-01-01

The partial charge transfer technique can expand the dynamic range of a CMOS image sensor by synthesizing two types of signal, namely the long and short accumulation time signals. However the short accumulation time signal obtained from partial transfer operation suffers of non-linearity with respect to the incident light. In this paper, an analysis of the non-linearity in partial charge transfer technique has been carried, and the relationship between dynamic range and the non-linearity is studied. The results show that the non-linearity is caused by two factors, namely the current diffusion, which has an exponential relation with the potential barrier, and the initial condition of photodiodes in which it shows that the error in the high illumination region increases as the ratio of the long to the short accumulation time raises. Moreover, the increment of the saturation level of photodiodes also increases the error in the high illumination region.

Calibration Of An Omnidirectional Vision Navigation System Using An Industrial Robot

NASA Astrophysics Data System (ADS)

Oh, Sung J.; Hall, Ernest L.

1989-09-01

The characteristics of an omnidirectional vision navigation system were studied to determine position accuracy for the navigation and path control of a mobile robot. Experiments for calibration and other parameters were performed using an industrial robot to conduct repetitive motions. The accuracy and repeatability of the experimental setup and the alignment between the robot and the sensor provided errors of less than 1 pixel on each axis. Linearity between zenith angle and image location was tested at four different locations. Angular error of less than 1° and radial error of less than 1 pixel were observed at moderate speed variations. The experimental information and the test of coordinated operation of the equipment provide understanding of characteristics as well as insight into the evaluation and improvement of the prototype dynamic omnivision system. The calibration of the sensor is important since the accuracy of navigation influences the accuracy of robot motion. This sensor system is currently being developed for a robot lawn mower; however, wider applications are obvious. The significance of this work is that it adds to the knowledge of the omnivision sensor.

Dynamic Vertical Mapping with Crowdsourced Smartphone Sensor Data

PubMed Central

Moslehi Rad, Omid Reza; Prehofer, Christian; Hugentobler, Urs

2018-01-01

In this paper, we present our novel approach for the crowdsourced dynamic vertical mapping of buildings. For achieving this, we use the barometric sensor of smartphones to estimate altitude differences and the moment of the outdoor to indoor transition to extract reference pressure. We have identified the outdoor–indoor transition (OITransition) via the fusion of four different sensors. Our approach has been evaluated extensively over a period of 6 months in different humidity, temperature, and cloud-coverage situations, as well as over different hours of the day, and it is found that it can always predict the correct number of floors, while it can approximate the altitude with an average error of 0.5 m. PMID:29415472

Spatio-Temporal Field Estimation Using Kriged Kalman Filter (KKF) with Sparsity-Enforcing Sensor Placement.

PubMed

Roy, Venkat; Simonetto, Andrea; Leus, Geert

2018-06-01

We propose a sensor placement method for spatio-temporal field estimation based on a kriged Kalman filter (KKF) using a network of static or mobile sensors. The developed framework dynamically designs the optimal constellation to place the sensors. We combine the estimation error (for the stationary as well as non-stationary component of the field) minimization problem with a sparsity-enforcing penalty to design the optimal sensor constellation in an economic manner. The developed sensor placement method can be directly used for a general class of covariance matrices (ill-conditioned or well-conditioned) modelling the spatial variability of the stationary component of the field, which acts as a correlated observation noise, while estimating the non-stationary component of the field. Finally, a KKF estimator is used to estimate the field using the measurements from the selected sensing locations. Numerical results are provided to exhibit the feasibility of the proposed dynamic sensor placement followed by the KKF estimation method.

High Accuracy Acoustic Relative Humidity Measurement in Duct Flow with Air

PubMed Central

van Schaik, Wilhelm; Grooten, Mart; Wernaart, Twan; van der Geld, Cees

2010-01-01

An acoustic relative humidity sensor for air-steam mixtures in duct flow is designed and tested. Theory, construction, calibration, considerations on dynamic response and results are presented. The measurement device is capable of measuring line averaged values of gas velocity, temperature and relative humidity (RH) instantaneously, by applying two ultrasonic transducers and an array of four temperature sensors. Measurement ranges are: gas velocity of 0–12 m/s with an error of ±0.13 m/s, temperature 0–100 °C with an error of ±0.07 °C and relative humidity 0–100% with accuracy better than 2 % RH above 50 °C. Main advantage over conventional humidity sensors is the high sensitivity at high RH at temperatures exceeding 50 °C, with accuracy increasing with increasing temperature. The sensors are non-intrusive and resist highly humid environments. PMID:22163610

High accuracy acoustic relative humidity measurement in duct flow with air.

PubMed

van Schaik, Wilhelm; Grooten, Mart; Wernaart, Twan; van der Geld, Cees

2010-01-01

An acoustic relative humidity sensor for air-steam mixtures in duct flow is designed and tested. Theory, construction, calibration, considerations on dynamic response and results are presented. The measurement device is capable of measuring line averaged values of gas velocity, temperature and relative humidity (RH) instantaneously, by applying two ultrasonic transducers and an array of four temperature sensors. Measurement ranges are: gas velocity of 0-12 m/s with an error of ± 0.13 m/s, temperature 0-100 °C with an error of ± 0.07 °C and relative humidity 0-100% with accuracy better than 2 % RH above 50 °C. Main advantage over conventional humidity sensors is the high sensitivity at high RH at temperatures exceeding 50 °C, with accuracy increasing with increasing temperature. The sensors are non-intrusive and resist highly humid environments.

A High-Speed Vision-Based Sensor for Dynamic Vibration Analysis Using Fast Motion Extraction Algorithms.

PubMed

Zhang, Dashan; Guo, Jie; Lei, Xiujun; Zhu, Changan

2016-04-22

The development of image sensor and optics enables the application of vision-based techniques to the non-contact dynamic vibration analysis of large-scale structures. As an emerging technology, a vision-based approach allows for remote measuring and does not bring any additional mass to the measuring object compared with traditional contact measurements. In this study, a high-speed vision-based sensor system is developed to extract structure vibration signals in real time. A fast motion extraction algorithm is required for this system because the maximum sampling frequency of the charge-coupled device (CCD) sensor can reach up to 1000 Hz. Two efficient subpixel level motion extraction algorithms, namely the modified Taylor approximation refinement algorithm and the localization refinement algorithm, are integrated into the proposed vision sensor. Quantitative analysis shows that both of the two modified algorithms are at least five times faster than conventional upsampled cross-correlation approaches and achieve satisfactory error performance. The practicability of the developed sensor is evaluated by an experiment in a laboratory environment and a field test. Experimental results indicate that the developed high-speed vision-based sensor system can extract accurate dynamic structure vibration signals by tracking either artificial targets or natural features.

Evaluation of dynamic electromagnetic tracking deviation

NASA Astrophysics Data System (ADS)

Hummel, Johann; Figl, Michael; Bax, Michael; Shahidi, Ramin; Bergmann, Helmar; Birkfellner, Wolfgang

2009-02-01

Electromagnetic tracking systems (EMTS's) are widely used in clinical applications. Many reports have evaluated their static behavior and errors caused by metallic objects were examined. Although there exist some publications concerning the dynamic behavior of EMTS's the measurement protocols are either difficult to reproduce with respect of the movement path or only accomplished at high technical effort. Because dynamic behavior is of major interest with respect to clinical applications we established a simple but effective modal measurement easy to repeat at other laboratories. We built a simple pendulum where the sensor of our EMTS (Aurora, NDI, CA) could be mounted. The pendulum was mounted on a special bearing to guarantee that the pendulum path is planar. This assumption was tested before starting the measurements. All relevant parameters defining the pendulum motion such as rotation center and length are determined by static measurement at satisfactory accuracy. Then position and orientation data were gathered over a time period of 8 seconds and timestamps were recorded. Data analysis provided a positioning error and an overall error combining both position and orientation. All errors were calculated by means of the well know equations concerning pendulum movement. Additionally, latency - the elapsed time from input motion until the immediate consequences of that input are available - was calculated using well-known equations for mechanical pendulums for different velocities. We repeated the measurements with different metal objects (rods made of stainless steel type 303 and 416) between field generator and pendulum. We found a root mean square error (eRMS) of 1.02mm with respect to the distance of the sensor position to the fit plane (maximum error emax = 2.31mm, minimum error emin = -2.36mm). The eRMS for positional error amounted to 1.32mm while the overall error was 3.24 mm. The latency at a pendulum angle of 0° (vertical) was 7.8ms.

Image registration of naval IR images

NASA Astrophysics Data System (ADS)

Rodland, Arne J.

1996-06-01

In a real world application an image from a stabilized sensor on a moving platform will not be 100 percent stabilized. There will always be a small unknown error in the stabilization due to factors such as dynamic deformations in the structure between sensor and reference Inertial Navigation Unit, servo inaccuracies, etc. For a high resolution imaging sensor this stabilization error causes the image to move several pixels in unknown direction between frames. TO be able to detect and track small moving objects from such a sensor, this unknown movement of the sensor image must be estimated. An algorithm that searches for land contours in the image has been evaluated. The algorithm searches for high contrast points distributed over the whole image. As long as moving objects in the scene only cover a small area of the scene, most of the points are located on solid ground. By matching the list of points from frame to frame, the movement of the image due to stabilization errors can be estimated and compensated. The point list is searched for points with diverging movement from the estimated stabilization error. These points are then assumed to be located on moving objects. Points assumed to be located on moving objects are gradually exchanged with new points located in the same area. Most of the processing is performed on the list of points and not on the complete image. The algorithm is therefore very fast and well suited for real time implementation. The algorithm has been tested on images from an experimental IR scanner. Stabilization errors were added artificially to the image such that the output from the algorithm could be compared with the artificially added stabilization errors.

On a more rigorous gravity field processing for future LL-SST type gravity satellite missions

NASA Astrophysics Data System (ADS)

Daras, I.; Pail, R.; Murböck, M.

2013-12-01

In order to meet the augmenting demands of the user community concerning accuracies of temporal gravity field models, future gravity missions of low-low satellite-to-satellite tracking (LL-SST) type are planned to carry more precise sensors than their precedents. A breakthrough is planned with the improved LL-SST measurement link, where the traditional K-band microwave instrument of 1μm accuracy will be complemented by an inter-satellite ranging instrument of several nm accuracy. This study focuses on investigations concerning the potential performance of the new sensors and their impact in gravity field solutions. The processing methods for gravity field recovery have to meet the new sensor standards and be able to take full advantage of the new accuracies that they provide. We use full-scale simulations in a realistic environment to investigate whether the standard processing techniques suffice to fully exploit the new sensors standards. We achieve that by performing full numerical closed-loop simulations based on the Integral Equation approach. In our simulation scheme, we simulate dynamic orbits in a conventional tracking analysis to compute pseudo inter-satellite ranges or range-rates that serve as observables. Each part of the processing is validated separately with special emphasis on numerical errors and their impact in gravity field solutions. We demonstrate that processing with standard precision may be a limiting factor for taking full advantage of new generation sensors that future satellite missions will carry. Therefore we have created versions of our simulator with enhanced processing precision with primarily aim to minimize round-off system errors. Results using the enhanced precision show a big reduction of system errors that were present at the standard precision processing even for the error-free scenario, and reveal the improvements the new sensors will bring into the gravity field solutions. As a next step, we analyze the contribution of individual error sources to the system's error budget. More specifically we analyze sensor noise from the laser interferometer and the accelerometers, errors in the kinematic orbits and the background fields as well as temporal and spatial aliasing errors. We give special care on the assessment of error sources with stochastic behavior, such as the laser interferometer and the accelerometers, and their consistent stochastic modeling in frame of the adjustment process.

Ultrasound monitoring of inter-knee distances during gait.

PubMed

Lai, Daniel T H; Wrigley, Tim V; Palaniswami, M

2009-01-01

Knee osteoarthritis is an extremely common, debilitating disease associated with pain and loss of function. There is considerable interest in monitoring lower limb alignment due to its close association with joint overload leading to disease progression. The effects of gait modifications that can lower joint loading are of particular interest. Here we describe an ultrasound-based system for monitoring an important aspect of dynamic lower limb alignment, the inter-knee distance during walking. Monitoring this gait parameter should facilitate studies in reducing knee loading, a primary risk factor of knee osteoarthritis progression. The portable device is composed of an ultrasound sensor connected to an Intel iMote2 equipped with Bluetooth wireless capability. Static tests and calibration results show that the sensor possesses an effective beam envelope of 120 degrees, with maximum distance errors of 10% at the envelope edges. Dynamic walking trials reveal close correlation of inter-knee distance trends between that measured by an optical system (Optotrak Certus NDI) and the sensor device. The maximum average root mean square error was found to be 1.46 cm. Future work will focus on improving the accuracy of the device.

The MEMS process of a micro friction sensor

NASA Astrophysics Data System (ADS)

Yuan, Ming-Quan; Lei, Qiang; Wang, Xiong

2018-02-01

The research and testing techniques of friction sensor is an important support for hypersonic aircraft. Compared with the conventional skin friction sensor, the MEMS skin friction sensor has the advantages of small size, high sensitivity, good stability and dynamic response. The MEMS skin friction sensor can be integrated with other flow field sensors whose process is compatible with MEMS skin friction sensor to achieve multi-physical measurement of the flow field; and the micro-friction balance sensor array enable to achieve large area and accurate measurement for the near-wall flow. A MEMS skin friction sensor structure is proposed, which sensing element not directly contacted with the flow field. The MEMS fabrication process of the sensing element is described in detail. The thermal silicon oxide is used as the mask to solve the selection ratio problem of silicon DRIE. The optimized process parameters of silicon DRIE: etching power 1600W/LF power 100 W; SF6 flux 360 sccm; C4F8 flux 300 sccm; O2 flux 300 sccm. With Cr/Au mask, etch depth of glass shallow groove can be controlled in 30°C low concentration HF solution; the spray etch and wafer rotate improve the corrosion surface quality of glass shallow groove. The MEMS skin friction sensor samples were fabricated by the above MEMS process, and results show that the error of the length and width of the elastic cantilever is within 2 μm, the depth error of the shallow groove is less than 0.03 μm, and the static capacitance error is within 0.2 pF, which satisfy the design requirements.

Estimation of Attitude and External Acceleration Using Inertial Sensor Measurement During Various Dynamic Conditions

PubMed Central

Lee, Jung Keun; Park, Edward J.; Robinovitch, Stephen N.

2012-01-01

This paper proposes a Kalman filter-based attitude (i.e., roll and pitch) estimation algorithm using an inertial sensor composed of a triaxial accelerometer and a triaxial gyroscope. In particular, the proposed algorithm has been developed for accurate attitude estimation during dynamic conditions, in which external acceleration is present. Although external acceleration is the main source of the attitude estimation error and despite the need for its accurate estimation in many applications, this problem that can be critical for the attitude estimation has not been addressed explicitly in the literature. Accordingly, this paper addresses the combined estimation problem of the attitude and external acceleration. Experimental tests were conducted to verify the performance of the proposed algorithm in various dynamic condition settings and to provide further insight into the variations in the estimation accuracy. Furthermore, two different approaches for dealing with the estimation problem during dynamic conditions were compared, i.e., threshold-based switching approach versus acceleration model-based approach. Based on an external acceleration model, the proposed algorithm was capable of estimating accurate attitudes and external accelerations for short accelerated periods, showing its high effectiveness during short-term fast dynamic conditions. Contrariwise, when the testing condition involved prolonged high external accelerations, the proposed algorithm exhibited gradually increasing errors. However, as soon as the condition returned to static or quasi-static conditions, the algorithm was able to stabilize the estimation error, regaining its high estimation accuracy. PMID:22977288

Experimental Verification of Sparse Aperture Mask for Low Order Wavefront Sensing

NASA Astrophysics Data System (ADS)

Subedi, Hari; Kasdin, N. Jeremy

2017-01-01

To directly image exoplanets, future space-based missions are equipped with coronagraphs which manipulate the diffraction of starlight and create regions of high contrast called dark holes. Theoretically, coronagraphs can be designed to achieve the high level of contrast required to image exoplanets, which are billions of times dimmer than their host stars, however the aberrations caused by optical imperfections and thermal fluctuations cause the degradation of contrast in the dark holes. Focal plane wavefront control (FPWC) algorithms using deformable mirrors (DMs) are used to mitigate the quasi-static aberrations caused by optical imperfections. Although the FPWC methods correct the quasi-static aberrations, they are blind to dynamic errors caused by telescope jitter and thermal fluctuations. At Princeton's High Contrast Imaging Lab we have developed a new technique that integrates a sparse aperture mask with the coronagraph to estimate these low-order dynamic wavefront errors. This poster shows the effectiveness of a SAM Low-Order Wavefront Sensor in estimating and correcting these errors via simulation and experiment and compares the results to other methods, such as the Zernike Wavefront Sensor planned for WFIRST.

A High Performance Piezoelectric Sensor for Dynamic Force Monitoring of Landslide

PubMed Central

Li, Ming; Cheng, Wei; Chen, Jiangpan; Xie, Ruili; Li, Xiongfei

2017-01-01

Due to the increasing influence of human engineering activities, it is important to monitor the transient disturbance during the evolution process of landslide. For this purpose, a high-performance piezoelectric sensor is presented in this paper. To adapt the high static and dynamic stress environment in slope engineering, two key techniques, namely, the self-structure pressure distribution method (SSPDM) and the capacitive circuit voltage distribution method (CCVDM) are employed in the design of the sensor. The SSPDM can greatly improve the compressive capacity and the CCVDM can quantitatively decrease the high direct response voltage. Then, the calibration experiments are conducted via the independently invented static and transient mechanism since the conventional testing machines cannot match the calibration requirements. The sensitivity coefficient is obtained and the results reveal that the sensor has the characteristics of high compressive capacity, stable sensitivities under different static preload levels and wide-range dynamic measuring linearity. Finally, to reduce the measuring error caused by charge leakage of the piezoelectric element, a low-frequency correction method is proposed and experimental verified. Therefore, with the satisfactory static and dynamic properties and the improving low-frequency measuring reliability, the sensor can complement dynamic monitoring capability of the existing landslide monitoring and forecasting system. PMID:28218673

Relative Orientation and Position Detections Based on an RGB-D Sensor and Dynamic Cooperation Strategies for Jumping Sensor Nodes Recycling

PubMed Central

Zhang, Jun; Yang, Xi; Song, Guang-Ming; Chen, Tian-Yuan; Zhang, Yong

2015-01-01

This paper presents relative orientation and position detection methods for jumping sensor nodes (JSNs) recycling. The methods are based on motion captures of the JSNs by an RGB-D sensor mounted on a carrier robot and the dynamic cooperation between the carrier and the JSNs. A disc-like label with two different colored sides is mounted on the top of the JSNs. The RGB-D sensor can detect the motion of the label to calculate the orientations and positions of the JSNs and the carrier relative to each other. After the orientations and positions have been detected, the JSNs jump into a cabin mounted on the carrier in dynamic cooperation with the carrier for recycling. The performances of the proposed methods are tested with a prototype system. The results show that the carrier can detect a JSN from up to 2 m away and sense its relative orientation and position successfully. The errors of the JSN’s orientation and position detections relative to the carrier could be reduced to the values smaller than 1° and 1 cm, respectively, by using the dynamic cooperation strategies. The proposed methods in this paper could also be used for other kinds of mobile sensor nodes and multi-robot systems. PMID:26393589

Thermal Property Analysis of Axle Load Sensors for Weighing Vehicles in Weigh-in-Motion System

PubMed Central

Burnos, Piotr; Gajda, Janusz

2016-01-01

Systems which permit the weighing of vehicles in motion are called dynamic Weigh-in-Motion scales. In such systems, axle load sensors are embedded in the pavement. Among the influencing factors that negatively affect weighing accuracy is the pavement temperature. This paper presents a detailed analysis of this phenomenon and describes the properties of polymer, quartz and bending plate load sensors. The studies were conducted in two ways: at roadside Weigh-in-Motion sites and at a laboratory using a climate chamber. For accuracy assessment of roadside systems, the reference vehicle method was used. The pavement temperature influence on the weighing error was experimentally investigated as well as a non-uniform temperature distribution along and across the Weigh-in-Motion site. Tests carried out in the climatic chamber allowed the influence of temperature on the sensor intrinsic error to be determined. The results presented clearly show that all kinds of sensors are temperature sensitive. This is a new finding, as up to now the quartz and bending plate sensors were considered insensitive to this factor. PMID:27983704

Design of a Capacitive Flexible Weighing Sensor for Vehicle WIM System

PubMed Central

Cheng, Lu; Zhang, Hongjian; Li, Qing

2007-01-01

With the development of the Highway Transportation and Business Trade, vehicle weigh-in-motion (WIM) technology has become a key technology and trend of measuring traffic loads. In this paper, a novel capacitive flexible weighing sensor which is light weight, smaller volume and easy to carry was applied in the vehicle WIM system. The dynamic behavior of the sensor is modeled using the Maxwell-Kelvin model because the materials of the sensor are rubbers which belong to viscoelasticity. A signal processing method based on the model is presented to overcome effects of rubber mechanical properties on the dynamic weight signal. The results showed that the measurement error is less than ±10%. All the theoretic analysis and numerical results demonstrated that appliance of this system to weigh in motion is feasible and convenient for traffic inspection.

Combined Dynamic Time Warping with Multiple Sensors for 3D Gesture Recognition

PubMed Central

2017-01-01

Cyber-physical systems, which closely integrate physical systems and humans, can be applied to a wider range of applications through user movement analysis. In three-dimensional (3D) gesture recognition, multiple sensors are required to recognize various natural gestures. Several studies have been undertaken in the field of gesture recognition; however, gesture recognition was conducted based on data captured from various independent sensors, which rendered the capture and combination of real-time data complicated. In this study, a 3D gesture recognition method using combined information obtained from multiple sensors is proposed. The proposed method can robustly perform gesture recognition regardless of a user’s location and movement directions by providing viewpoint-weighted values and/or motion-weighted values. In the proposed method, the viewpoint-weighted dynamic time warping with multiple sensors has enhanced performance by preventing joint measurement errors and noise due to sensor measurement tolerance, which has resulted in the enhancement of recognition performance by comparing multiple joint sequences effectively. PMID:28817094

Combined Dynamic Time Warping with Multiple Sensors for 3D Gesture Recognition.

PubMed

Choi, Hyo-Rim; Kim, TaeYong

2017-08-17

Cyber-physical systems, which closely integrate physical systems and humans, can be applied to a wider range of applications through user movement analysis. In three-dimensional (3D) gesture recognition, multiple sensors are required to recognize various natural gestures. Several studies have been undertaken in the field of gesture recognition; however, gesture recognition was conducted based on data captured from various independent sensors, which rendered the capture and combination of real-time data complicated. In this study, a 3D gesture recognition method using combined information obtained from multiple sensors is proposed. The proposed method can robustly perform gesture recognition regardless of a user's location and movement directions by providing viewpoint-weighted values and/or motion-weighted values. In the proposed method, the viewpoint-weighted dynamic time warping with multiple sensors has enhanced performance by preventing joint measurement errors and noise due to sensor measurement tolerance, which has resulted in the enhancement of recognition performance by comparing multiple joint sequences effectively.

Miniature low-power inertial sensors: promising technology for implantable motion capture systems.

PubMed

Lambrecht, Joris M; Kirsch, Robert F

2014-11-01

Inertial and magnetic sensors are valuable for untethered, self-contained human movement analysis. Very recently, complete integration of inertial sensors, magnetic sensors, and processing into single packages, has resulted in miniature, low power devices that could feasibly be employed in an implantable motion capture system. We developed a wearable sensor system based on a commercially available system-in-package inertial and magnetic sensor. We characterized the accuracy of the system in measuring 3-D orientation-with and without magnetometer-based heading compensation-relative to a research grade optical motion capture system. The root mean square error was less than 4° in dynamic and static conditions about all axes. Using four sensors, recording from seven degrees-of-freedom of the upper limb (shoulder, elbow, wrist) was demonstrated in one subject during reaching motions. Very high correlation and low error was found across all joints relative to the optical motion capture system. Findings were similar to previous publications using inertial sensors, but at a fraction of the power consumption and size of the sensors. Such ultra-small, low power sensors provide exciting new avenues for movement monitoring for various movement disorders, movement-based command interfaces for assistive devices, and implementation of kinematic feedback systems for assistive interventions like functional electrical stimulation.

Virtual Passive Controller for Robot Systems Using Joint Torque Sensors

NASA Technical Reports Server (NTRS)

Aldridge, Hal A.; Juang, Jer-Nan

1997-01-01

This paper presents a control method based on virtual passive dynamic control that will stabilize a robot manipulator using joint torque sensors and a simple joint model. The method does not require joint position or velocity feedback for stabilization. The proposed control method is stable in the sense of Lyaponov. The control method was implemented on several joints of a laboratory robot. The controller showed good stability robustness to system parameter error and to the exclusion of nonlinear dynamic effects on the joints. The controller enhanced position tracking performance and, in the absence of position control, dissipated joint energy.

Design and evaluation of a robust dynamic neurocontroller for a multivariable aircraft control problem

NASA Technical Reports Server (NTRS)

Troudet, T.; Garg, S.; Merrill, W.

1992-01-01

The design of a dynamic neurocontroller with good robustness properties is presented for a multivariable aircraft control problem. The internal dynamics of the neurocontroller are synthesized by a state estimator feedback loop. The neurocontrol is generated by a multilayer feedforward neural network which is trained through backpropagation to minimize an objective function that is a weighted sum of tracking errors, and control input commands and rates. The neurocontroller exhibits good robustness through stability margins in phase and vehicle output gains. By maintaining performance and stability in the presence of sensor failures in the error loops, the structure of the neurocontroller is also consistent with the classical approach of flight control design.

Evaluation of glued-diaphragm fibre optic pressure sensors in a shock tube

NASA Astrophysics Data System (ADS)

Sharifian, S. Ahmad; Buttsworth, David R.

2007-02-01

Glued-diaphragm fibre optic pressure sensors that utilize standard telecommunications components which are based on Fabry-Perot interferometry are appealing in a number of respects. Principally, they have high spatial and temporal resolution and are low in cost. These features potentially make them well suited to operation in extreme environments produced in short-duration high-enthalpy wind tunnel facilities where spatial and temporal resolution are essential, but attrition rates for sensors are typically very high. The sensors we consider utilize a zirconia ferrule substrate and a thin copper foil which are bonded together using an adhesive. The sensors show a fast response and can measure fluctuations with a frequency up to 250 kHz. The sensors also have a high spatial resolution on the order of 0.1 mm. However, with the interrogation and calibration processes adopted in this work, apparent errors of up to 30% of the maximum pressure have been observed. Such errors are primarily caused by mechanical hysteresis and adhesive viscoelasticity. If a dynamic calibration is adopted, the maximum measurement error can be limited to about 10% of the maximum pressure. However, a better approach is to eliminate the adhesive from the construction process or design the diaphragm and substrate in a way that does not require the adhesive to carry a significant fraction of the mechanical loading.

Calibrating airborne measurements of airspeed, pressure and temperature using a Doppler laser air-motion sensor

NASA Astrophysics Data System (ADS)

Cooper, W. A.; Spuler, S. M.; Spowart, M.; Lenschow, D. H.; Friesen, R. B.

2014-03-01

A new laser air-motion sensor measures the true airspeed with an uncertainty of less than 0.1 m s-1 (standard error) and so reduces uncertainty in the measured component of the relative wind along the longitudinal axis of the aircraft to about the same level. The calculated pressure expected from that airspeed at the inlet of a pitot tube then provides a basis for calibrating the measurements of dynamic and static pressure, reducing standard-error uncertainty in those measurements to less than 0.3 hPa and the precision applicable to steady flight conditions to about 0.1 hPa. These improved measurements of pressure, combined with high-resolution measurements of geometric altitude from the Global Positioning System, then indicate (via integrations of the hydrostatic equation during climbs and descents) that the offset and uncertainty in temperature measurement for one research aircraft are +0.3 ± 0.3 °C. For airspeed, pressure and temperature these are significant reductions in uncertainty vs. those obtained from calibrations using standard techniques. Finally, it is shown that the new laser air-motion sensor, combined with parametrized fits to correction factors for the measured dynamic and ambient pressure, provides a measurement of temperature that is independent of any other temperature sensor.

System Dynamic Analysis of a Wind Tunnel Model with Applications to Improve Aerodynamic Data Quality

NASA Technical Reports Server (NTRS)

Buehrle, Ralph David

1997-01-01

The research investigates the effect of wind tunnel model system dynamics on measured aerodynamic data. During wind tunnel tests designed to obtain lift and drag data, the required aerodynamic measurements are the steady-state balance forces and moments, pressures, and model attitude. However, the wind tunnel model system can be subjected to unsteady aerodynamic and inertial loads which result in oscillatory translations and angular rotations. The steady-state force balance and inertial model attitude measurements are obtained by filtering and averaging data taken during conditions of high model vibrations. The main goals of this research are to characterize the effects of model system dynamics on the measured steady-state aerodynamic data and develop a correction technique to compensate for dynamically induced errors. Equations of motion are formulated for the dynamic response of the model system subjected to arbitrary aerodynamic and inertial inputs. The resulting modal model is examined to study the effects of the model system dynamic response on the aerodynamic data. In particular, the equations of motion are used to describe the effect of dynamics on the inertial model attitude, or angle of attack, measurement system that is used routinely at the NASA Langley Research Center and other wind tunnel facilities throughout the world. This activity was prompted by the inertial model attitude sensor response observed during high levels of model vibration while testing in the National Transonic Facility at the NASA Langley Research Center. The inertial attitude sensor cannot distinguish between the gravitational acceleration and centrifugal accelerations associated with wind tunnel model system vibration, which results in a model attitude measurement bias error. Bias errors over an order of magnitude greater than the required device accuracy were found in the inertial model attitude measurements during dynamic testing of two model systems. Based on a theoretical modal approach, a method using measured vibration amplitudes and measured or calculated modal characteristics of the model system is developed to correct for dynamic bias errors in the model attitude measurements. The correction method is verified through dynamic response tests on two model systems and actual wind tunnel test data.

Real-time monitoring system of composite aircraft wings utilizing Fibre Bragg Grating sensor

NASA Astrophysics Data System (ADS)

Vorathin, E.; Hafizi, Z. M.; Che Ghani, S. A.; Lim, K. S.

2016-10-01

Embedment of Fibre Bragg Grating (FBG) sensor in composite aircraft wings leads to the advancement of structural condition monitoring. The monitored aircraft wings have the capability to give real-time response under critical loading circumstances. The main objective of this paper is to develop a real-time FBG monitoring system for composite aircraft wings to view real-time changes when the structure undergoes some static loadings and dynamic impact. The implementation of matched edge filter FBG interrogation system to convert wavelength variations to strain readings shows that the structure is able to response instantly in real-time when undergoing few loadings and dynamic impact. This smart monitoring system is capable of updating the changes instantly in real-time and shows the weight induced on the composite aircraft wings instantly without any error. It also has a good agreement with acoustic emission (AE) sensor in the dynamic test.

A Polymer Optical Fiber Temperature Sensor Based on Material Features.

PubMed

Leal-Junior, Arnaldo; Frizera-Netoc, Anselmo; Marques, Carlos; Pontes, Maria José

2018-01-19

This paper presents a polymer optical fiber (POF)-based temperature sensor. The operation principle of the sensor is the variation in the POF mechanical properties with the temperature variation. Such mechanical property variation leads to a variation in the POF output power when a constant stress is applied to the fiber due to the stress-optical effect. The fiber mechanical properties are characterized through a dynamic mechanical analysis, and the output power variation with different temperatures is measured. The stress is applied to the fiber by means of a 180° curvature, and supports are positioned on the fiber to inhibit the variation in its curvature with the temperature variation. Results show that the sensor proposed has a sensitivity of 1.04 × 10 -3 °C -1 , a linearity of 0.994, and a root mean squared error of 1.48 °C, which indicates a relative error of below 2%, which is lower than the ones obtained for intensity-variation-based temperature sensors. Furthermore, the sensor is able to operate at temperatures up to 110 °C, which is higher than the ones obtained for similar POF sensors in the literature.

Dynamic response tests of inertial and optical wind-tunnel model attitude measurement devices

NASA Technical Reports Server (NTRS)

Buehrle, R. D.; Young, C. P., Jr.; Burner, A. W.; Tripp, J. S.; Tcheng, P.; Finley, T. D.; Popernack, T. G., Jr.

1995-01-01

Results are presented for an experimental study of the response of inertial and optical wind-tunnel model attitude measurement systems in a wind-off simulated dynamic environment. This study is part of an ongoing activity at the NASA Langley Research Center to develop high accuracy, advanced model attitude measurement systems that can be used in a dynamic wind-tunnel environment. This activity was prompted by the inertial model attitude sensor response observed during high levels of model vibration which results in a model attitude measurement bias error. Significant bias errors in model attitude measurement were found for the measurement using the inertial device during wind-off dynamic testing of a model system. The amount of bias present during wind-tunnel tests will depend on the amplitudes of the model dynamic response and the modal characteristics of the model system. Correction models are presented that predict the vibration-induced bias errors to a high degree of accuracy for the vibration modes characterized in the simulated dynamic environment. The optical system results were uncorrupted by model vibration in the laboratory setup.

Development of response models for the Earth Radiation Budget Experiment (ERBE) sensors. Part 1: Dynamic models and computer simulations for the ERBE nonscanner, scanner and solar monitor sensors

NASA Technical Reports Server (NTRS)

Halyo, Nesim; Choi, Sang H.; Chrisman, Dan A., Jr.; Samms, Richard W.

1987-01-01

Dynamic models and computer simulations were developed for the radiometric sensors utilized in the Earth Radiation Budget Experiment (ERBE). The models were developed to understand performance, improve measurement accuracy by updating model parameters and provide the constants needed for the count conversion algorithms. Model simulations were compared with the sensor's actual responses demonstrated in the ground and inflight calibrations. The models consider thermal and radiative exchange effects, surface specularity, spectral dependence of a filter, radiative interactions among an enclosure's nodes, partial specular and diffuse enclosure surface characteristics and steady-state and transient sensor responses. Relatively few sensor nodes were chosen for the models since there is an accuracy tradeoff between increasing the number of nodes and approximating parameters such as the sensor's size, material properties, geometry, and enclosure surface characteristics. Given that the temperature gradients within a node and between nodes are small enough, approximating with only a few nodes does not jeopardize the accuracy required to perform the parameter estimates and error analyses.

Sensor selection cost optimisation for tracking structurally cyclic systems: a P-order solution

NASA Astrophysics Data System (ADS)

Doostmohammadian, M.; Zarrabi, H.; Rabiee, H. R.

2017-08-01

Measurements and sensing implementations impose certain cost in sensor networks. The sensor selection cost optimisation is the problem of minimising the sensing cost of monitoring a physical (or cyber-physical) system. Consider a given set of sensors tracking states of a dynamical system for estimation purposes. For each sensor assume different costs to measure different (realisable) states. The idea is to assign sensors to measure states such that the global cost is minimised. The number and selection of sensor measurements need to ensure the observability to track the dynamic state of the system with bounded estimation error. The main question we address is how to select the state measurements to minimise the cost while satisfying the observability conditions. Relaxing the observability condition for structurally cyclic systems, the main contribution is to propose a graph theoretic approach to solve the problem in polynomial time. Note that polynomial time algorithms are suitable for large-scale systems as their running time is upper-bounded by a polynomial expression in the size of input for the algorithm. We frame the problem as a linear sum assignment with solution complexity of ?.

Nonlinear software sensor for monitoring genetic regulation processes with noise and modeling errors

NASA Astrophysics Data System (ADS)

Ibarra-Junquera, V.; Torres, L. A.; Rosu, H. C.; Argüello, G.; Collado-Vides, J.

2005-07-01

Nonlinear control techniques by means of a software sensor that are commonly used in chemical engineering could be also applied to genetic regulation processes. We provide here a realistic formulation of this procedure by introducing an additive white Gaussian noise, which is usually found in experimental data. Besides, we include model errors, meaning that we assume we do not know the nonlinear regulation function of the process. In order to illustrate this procedure, we employ the Goodwin dynamics of the concentrations [B. C. Goodwin, Temporal Oscillations in Cells (Academic, New York, 1963)] in the simple form recently applied to single gene systems and some operon cases [H. De Jong, J. Comput. Biol. 9, 67 (2002)], which involves the dynamics of the mRNA, given protein and metabolite concentrations. Further, we present results for a three gene case in coregulated sets of transcription units as they occur in prokaryotes. However, instead of considering their full dynamics, we use only the data of the metabolites and a designed software sensor. We also show, more generally, that it is possible to rebuild the complete set of nonmeasured concentrations despite the uncertainties in the regulation function or, even more, in the case of not knowing the mRNA dynamics. In addition, the rebuilding of concentrations is not affected by the perturbation due to the additive white Gaussian noise and also we managed to filter the noisy output of the biological system.

Bio-inspired sensing and control for disturbance rejection and stabilization

NASA Astrophysics Data System (ADS)

Gremillion, Gregory; Humbert, James S.

2015-05-01

The successful operation of small unmanned aircraft systems (sUAS) in dynamic environments demands robust stability in the presence of exogenous disturbances. Flying insects are sensor-rich platforms, with highly redundant arrays of sensors distributed across the insect body that are integrated to extract rich information with diminished noise. This work presents a novel sensing framework in which measurements from an array of accelerometers distributed across a simulated flight vehicle are linearly combined to directly estimate the applied forces and torques with improvements in SNR. In simulation, the estimation performance is quantified as a function of sensor noise level, position estimate error, and sensor quantity.

Improved Spatial Registration and Target Tracking Method for Sensors on Multiple Missiles.

PubMed

Lu, Xiaodong; Xie, Yuting; Zhou, Jun

2018-05-27

Inspired by the problem that the current spatial registration methods are unsuitable for three-dimensional (3-D) sensor on high-dynamic platform, this paper focuses on the estimation for the registration errors of cooperative missiles and motion states of maneuvering target. There are two types of errors being discussed: sensor measurement biases and attitude biases. Firstly, an improved Kalman Filter on Earth-Centered Earth-Fixed (ECEF-KF) coordinate algorithm is proposed to estimate the deviations mentioned above, from which the outcomes are furtherly compensated to the error terms. Secondly, the Pseudo Linear Kalman Filter (PLKF) and the nonlinear scheme the Unscented Kalman Filter (UKF) with modified inputs are employed for target tracking. The convergence of filtering results are monitored by a position-judgement logic, and a low-pass first order filter is selectively introduced before compensation to inhibit the jitter of estimations. In the simulation, the ECEF-KF enhancement is proven to improve the accuracy and robustness of the space alignment, while the conditional-compensation-based PLKF method is demonstrated to be the optimal performance in target tracking.

Evaluation of Alternate Concepts for Synthetic Vision Flight Displays With Weather-Penetrating Sensor Image Inserts During Simulated Landing Approaches

NASA Technical Reports Server (NTRS)

Parrish, Russell V.; Busquets, Anthony M.; Williams, Steven P.; Nold, Dean E.

2003-01-01

A simulation study was conducted in 1994 at Langley Research Center that used 12 commercial airline pilots repeatedly flying complex Microwave Landing System (MLS)-type approaches to parallel runways under Category IIIc weather conditions. Two sensor insert concepts of 'Synthetic Vision Systems' (SVS) were used in the simulated flights, with a more conventional electro-optical display (similar to a Head-Up Display with raster capability for sensor imagery), flown under less restrictive visibility conditions, used as a control condition. The SVS concepts combined the sensor imagery with a computer-generated image (CGI) of an out-the-window scene based on an onboard airport database. Various scenarios involving runway traffic incursions (taxiing aircraft and parked fuel trucks) and navigational system position errors (both static and dynamic) were used to assess the pilots' ability to manage the approach task with the display concepts. The two SVS sensor insert concepts contrasted the simple overlay of sensor imagery on the CGI scene without additional image processing (the SV display) to the complex integration (the AV display) of the CGI scene with pilot-decision aiding using both object and edge detection techniques for detection of obstacle conflicts and runway alignment errors.

A general model for attitude determination error analysis

NASA Technical Reports Server (NTRS)

Markley, F. Landis; Seidewitz, ED; Nicholson, Mark

1988-01-01

An overview is given of a comprehensive approach to filter and dynamics modeling for attitude determination error analysis. The models presented include both batch least-squares and sequential attitude estimation processes for both spin-stabilized and three-axis stabilized spacecraft. The discussion includes a brief description of a dynamics model of strapdown gyros, but it does not cover other sensor models. Model parameters can be chosen to be solve-for parameters, which are assumed to be estimated as part of the determination process, or consider parameters, which are assumed to have errors but not to be estimated. The only restriction on this choice is that the time evolution of the consider parameters must not depend on any of the solve-for parameters. The result of an error analysis is an indication of the contributions of the various error sources to the uncertainties in the determination of the spacecraft solve-for parameters. The model presented gives the uncertainty due to errors in the a priori estimates of the solve-for parameters, the uncertainty due to measurement noise, the uncertainty due to dynamic noise (also known as process noise or measurement noise), the uncertainty due to the consider parameters, and the overall uncertainty due to all these sources of error.

Heading Estimation for Pedestrian Dead Reckoning Based on Robust Adaptive Kalman Filtering.

PubMed

Wu, Dongjin; Xia, Linyuan; Geng, Jijun

2018-06-19

Pedestrian dead reckoning (PDR) using smart phone-embedded micro-electro-mechanical system (MEMS) sensors plays a key role in ubiquitous localization indoors and outdoors. However, as a relative localization method, it suffers from the problem of error accumulation which prevents it from long term independent running. Heading estimation error is one of the main location error sources, and therefore, in order to improve the location tracking performance of the PDR method in complex environments, an approach based on robust adaptive Kalman filtering (RAKF) for estimating accurate headings is proposed. In our approach, outputs from gyroscope, accelerometer, and magnetometer sensors are fused using the solution of Kalman filtering (KF) that the heading measurements derived from accelerations and magnetic field data are used to correct the states integrated from angular rates. In order to identify and control measurement outliers, a maximum likelihood-type estimator (M-estimator)-based model is used. Moreover, an adaptive factor is applied to resist the negative effects of state model disturbances. Extensive experiments under static and dynamic conditions were conducted in indoor environments. The experimental results demonstrate the proposed approach provides more accurate heading estimates and supports more robust and dynamic adaptive location tracking, compared with methods based on conventional KF.

Gradient-based interpolation method for division-of-focal-plane polarimeters.

PubMed

Gao, Shengkui; Gruev, Viktor

2013-01-14

Recent advancements in nanotechnology and nanofabrication have allowed for the emergence of the division-of-focal-plane (DoFP) polarization imaging sensors. These sensors capture polarization properties of the optical field at every imaging frame. However, the DoFP polarization imaging sensors suffer from large registration error as well as reduced spatial-resolution output. These drawbacks can be improved by applying proper image interpolation methods for the reconstruction of the polarization results. In this paper, we present a new gradient-based interpolation method for DoFP polarimeters. The performance of the proposed interpolation method is evaluated against several previously published interpolation methods by using visual examples and root mean square error (RMSE) comparison. We found that the proposed gradient-based interpolation method can achieve better visual results while maintaining a lower RMSE than other interpolation methods under various dynamic ranges of a scene ranging from dim to bright conditions.

Updating finite element dynamic models using an element-by-element sensitivity methodology

NASA Technical Reports Server (NTRS)

Farhat, Charbel; Hemez, Francois M.

1993-01-01

A sensitivity-based methodology for improving the finite element model of a given structure using test modal data and a few sensors is presented. The proposed method searches for both the location and sources of the mass and stiffness errors and does not interfere with the theory behind the finite element model while correcting these errors. The updating algorithm is derived from the unconstrained minimization of the squared L sub 2 norms of the modal dynamic residuals via an iterative two-step staggered procedure. At each iteration, the measured mode shapes are first expanded assuming that the model is error free, then the model parameters are corrected assuming that the expanded mode shapes are exact. The numerical algorithm is implemented in an element-by-element fashion and is capable of 'zooming' on the detected error locations. Several simulation examples which demonstate the potential of the proposed methodology are discussed.

A bronchoscopic navigation system using bronchoscope center calibration for accurate registration of electromagnetic tracker and CT volume without markers.

PubMed

Luo, Xiongbiao

2014-06-01

Various bronchoscopic navigation systems are developed for diagnosis, staging, and treatment of lung and bronchus cancers. To construct electromagnetically navigated bronchoscopy systems, registration of preoperative images and an electromagnetic tracker must be performed. This paper proposes a new marker-free registration method, which uses the centerlines of the bronchial tree and the center of a bronchoscope tip where an electromagnetic sensor is attached, to align preoperative images and electromagnetic tracker systems. The chest computed tomography (CT) volume (preoperative images) was segmented to extract the bronchial centerlines. An electromagnetic sensor was fixed at the bronchoscope tip surface. A model was designed and printed using a 3D printer to calibrate the relationship between the fixed sensor and the bronchoscope tip center. For each sensor measurement that includes sensor position and orientation information, its corresponding bronchoscope tip center position was calculated. By minimizing the distance between each bronchoscope tip center position and the bronchial centerlines, the spatial alignment of the electromagnetic tracker system and the CT volume was determined. After obtaining the spatial alignment, an electromagnetic navigation bronchoscopy system was established to real-timely track or locate a bronchoscope inside the bronchial tree during bronchoscopic examinations. The electromagnetic navigation bronchoscopy system was validated on a dynamic bronchial phantom that can simulate respiratory motion with a breath rate range of 0-10 min(-1). The fiducial and target registration errors of this navigation system were evaluated. The average fiducial registration error was reduced from 8.7 to 6.6 mm. The average target registration error, which indicates all tracked or navigated bronchoscope position accuracy, was much reduced from 6.8 to 4.5 mm compared to previous registration methods. An electromagnetically navigated bronchoscopy system was constructed with accurate registration of an electromagnetic tracker and the CT volume on the basis of an improved marker-free registration approach that uses the bronchial centerlines and bronchoscope tip center information. The fiducial and target registration errors of our electromagnetic navigation system were about 6.6 and 4.5 mm in dynamic bronchial phantom validation.

A bronchoscopic navigation system using bronchoscope center calibration for accurate registration of electromagnetic tracker and CT volume without markers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Luo, Xiongbiao, E-mail: xiongbiao.luo@gmail.com

2014-06-15

Purpose: Various bronchoscopic navigation systems are developed for diagnosis, staging, and treatment of lung and bronchus cancers. To construct electromagnetically navigated bronchoscopy systems, registration of preoperative images and an electromagnetic tracker must be performed. This paper proposes a new marker-free registration method, which uses the centerlines of the bronchial tree and the center of a bronchoscope tip where an electromagnetic sensor is attached, to align preoperative images and electromagnetic tracker systems. Methods: The chest computed tomography (CT) volume (preoperative images) was segmented to extract the bronchial centerlines. An electromagnetic sensor was fixed at the bronchoscope tip surface. A model wasmore » designed and printed using a 3D printer to calibrate the relationship between the fixed sensor and the bronchoscope tip center. For each sensor measurement that includes sensor position and orientation information, its corresponding bronchoscope tip center position was calculated. By minimizing the distance between each bronchoscope tip center position and the bronchial centerlines, the spatial alignment of the electromagnetic tracker system and the CT volume was determined. After obtaining the spatial alignment, an electromagnetic navigation bronchoscopy system was established to real-timely track or locate a bronchoscope inside the bronchial tree during bronchoscopic examinations. Results: The electromagnetic navigation bronchoscopy system was validated on a dynamic bronchial phantom that can simulate respiratory motion with a breath rate range of 0–10 min{sup −1}. The fiducial and target registration errors of this navigation system were evaluated. The average fiducial registration error was reduced from 8.7 to 6.6 mm. The average target registration error, which indicates all tracked or navigated bronchoscope position accuracy, was much reduced from 6.8 to 4.5 mm compared to previous registration methods. Conclusions: An electromagnetically navigated bronchoscopy system was constructed with accurate registration of an electromagnetic tracker and the CT volume on the basis of an improved marker-free registration approach that uses the bronchial centerlines and bronchoscope tip center information. The fiducial and target registration errors of our electromagnetic navigation system were about 6.6 and 4.5 mm in dynamic bronchial phantom validation.« less

Evaluation of dual-tip micromanometers during 21-day implantation in goats

NASA Technical Reports Server (NTRS)

Reister, C. A.; Koenig, S. C.; Schaub, J. D.; Ewert, D. L.; Swope, R. D.; Latham, R. D.; Fanton, J. W.; Convertino, V. A. (Principal Investigator)

1998-01-01

Investigative research efforts using a cardiovascular model required the determination of central circulatory haemodynamic and arterial system parameters for the evaluation of cardiovascular performance. These calculations required continuous beat-to-beat measurement of pressure within the four chambers of the heart and great vessels. Sensitivity and offset drift, longevity, and sources of error for eight 3F dual-tipped micromanometers were determined during 21 days of implantation in goats. Subjects were instrumented with pairs of chronically implanted fluid-filled access catheters in the left and right ventricles, through which dual-tipped (test) micromanometers were chronically inserted and single-tip (standard) micromanometers were acutely inserted. Acutely inserted sensors were calibrated daily and measured pressures were compared in vivo to the chronically inserted sensors. Comparison of the pre- and post-gain calibration of the chronically inserted sensors showed a mean sensitivity drift of 1.0 +/- 0.4% (99% confidence, n = 9 sensors) and mean offset drift of 5.0 +/- 1.5 mmHg (99% confidence, n = 9 sensors). Potential sources of error for these drifts were identified, and included measurement system inaccuracies, temperature drift, hydrostatic column gradients, and dynamic pressure changes. Based upon these findings, we determined that these micromanometers may be chronically inserted in high-pressure chambers for up to 17 days with an acceptable error, but should be limited to acute (hours) insertions in low-pressure applications.

Error modeling of precision orientation sensors in a fixed base simulation. Ph.D. Thesis; [models of noise and dynamic characteristics of a gyro and autocollimator for very small signals

NASA Technical Reports Server (NTRS)

Klinger, D. L.

1974-01-01

Models of noise and dynamic characteristics of gyro and autocollimator for very small signal levels are presented. Measurements were evaluated using spectral techniques for identifying noise from base motion. The experiment was constructed to measure the precession, due to relativistic effects, of an extremely precise earth-orbiting gyroscope. The design goal for nonrelativistic gyro drift is 0.001 arcsec per year. An analogous fixed base simulator was used in developing methods of instrument error modeling and performance evaluation applicable to the relativity experiment sensors and other precision pointing instruments. Analysis of autocollimator spectra uncovered the presence of a platform gimbal resonance. The source of resonance was isolated to gimbal bearing elastic restraint properties most apparent at very small levels of motion. A model of these properties which include both elastic and coulomb friction characteristics is discussed, and a describing function developed.

Geostationary Operational Environmental Satellite (GOES-N report). Volume 2: Technical appendix

NASA Technical Reports Server (NTRS)

1992-01-01

The contents include: operation with inclinations up to 3.5 deg to extend life; earth sensor improvements to reduce noise; sensor configurations studied; momentum management system design; reaction wheel induced dynamic interaction; controller design; spacecraft motion compensation; analog filtering; GFRP servo design - modern control approach; feedforward compensation as applied to GOES-1 sounder; discussion of allocation of navigation, inframe registration and image-to-image error budget overview; and spatial response and cloud smearing study.

An Adaptive Orientation Estimation Method for Magnetic and Inertial Sensors in the Presence of Magnetic Disturbances

PubMed Central

Fan, Bingfei; Li, Qingguo; Wang, Chao; Liu, Tao

2017-01-01

Magnetic and inertial sensors have been widely used to estimate the orientation of human segments due to their low cost, compact size and light weight. However, the accuracy of the estimated orientation is easily affected by external factors, especially when the sensor is used in an environment with magnetic disturbances. In this paper, we propose an adaptive method to improve the accuracy of orientation estimations in the presence of magnetic disturbances. The method is based on existing gradient descent algorithms, and it is performed prior to sensor fusion algorithms. The proposed method includes stationary state detection and magnetic disturbance severity determination. The stationary state detection makes this method immune to magnetic disturbances in stationary state, while the magnetic disturbance severity determination helps to determine the credibility of magnetometer data under dynamic conditions, so as to mitigate the negative effect of the magnetic disturbances. The proposed method was validated through experiments performed on a customized three-axis instrumented gimbal with known orientations. The error of the proposed method and the original gradient descent algorithms were calculated and compared. Experimental results demonstrate that in stationary state, the proposed method is completely immune to magnetic disturbances, and in dynamic conditions, the error caused by magnetic disturbance is reduced by 51.2% compared with original MIMU gradient descent algorithm. PMID:28534858

Dynamic testbed demonstration of WFIRST coronagraph low order wavefront sensing and control (LOWFS/C)

NASA Astrophysics Data System (ADS)

Shi, Fang; Cady, Eric; Seo, Byoung-Joon; An, Xin; Balasubramanian, Kunjithapatham; Kern, Brian; Lam, Raymond; Marx, David; Moody, Dwight; Mejia Prada, Camilo; Patterson, Keith; Poberezhskiy, Ilya; Shields, Joel; Sidick, Erkin; Tang, Hong; Trauger, John; Truong, Tuan; White, Victor; Wilson, Daniel; Zhou, Hanying

2017-09-01

To maintain the required performance of WFIRST Coronagraph in a realistic space environment, a Low Order Wavefront Sensing and Control (LOWFS/C) subsystem is necessary. The LOWFS/C uses a Zernike wavefront sensor (ZWFS) with the phase shifting disk combined with the starlight rejecting occulting mask. For wavefront error corrections, WFIRST LOWFS/C uses a fast steering mirror (FSM) for line-of-sight (LoS) correction, a focusing mirror for focus drift correction, and one of the two deformable mirrors (DM) for other low order wavefront error (WFE) correction. As a part of technology development and demonstration for WFIRST Coronagraph, a dedicated Occulting Mask Coronagraph (OMC) testbed has been built and commissioned. With its configuration similar to the WFIRST flight coronagraph instrument the OMC testbed consists of two coronagraph modes, Shaped Pupil Coronagraph (SPC) and Hybrid Lyot Coronagraph (HLC), a low order wavefront sensor (LOWFS), and an optical telescope assembly (OTA) simulator which can generate realistic LoS drift and jitter as well as low order wavefront error that would be induced by the WFIRST telescope's vibration and thermal changes. In this paper, we will introduce the concept of WFIRST LOWFS/C, describe the OMC testbed, and present the testbed results of LOWFS sensor performance. We will also present our recent results from the dynamic coronagraph tests in which we have demonstrated of using LOWFS/C to maintain the coronagraph contrast with the presence of WFIRST-like line-of-sight and low order wavefront disturbances.

Sediment Dynamics Over a Stable Point bar of the San Pedro River, Southeastern Arizona

NASA Astrophysics Data System (ADS)

Hamblen, J. M.; Conklin, M. H.

2002-12-01

Streams of the Southwest receive enormous inputs of sediment during storm events in the monsoon season due to the high intensity rainfall and large percentages of exposed soil in the semi-arid landscape. In the Upper San Pedro River, with a watershed area of approximately 3600 square kilometers, particle size ranges from clays to boulders with large fractions of sand and gravel. This study focuses on the mechanics of scour and fill on a stable point bar. An innovative technique using seven co-located scour chains and liquid-filled, load-cell scour sensors characterized sediment dynamics over the point bar during the monsoon season of July to September 2002. The sensors were set in two transects to document sediment dynamics near the head and toe of the bar. Scour sensors record area-averaged sediment depths while scour chains measure scour and fill at a point. The average area covered by each scour sensor is 11.1 square meters. Because scour sensors have never been used in a system similar to the San Pedro, one goal of the study was to test their ability to detect changes in sediment load with time in order to determine the extent of scour and fill during monsoonal storms. Because of the predominantly unconsolidated nature of the substrate it was hypothesized that dune bedforms would develop in events less than the 1-year flood. The weak 2002 monsoon season produced only two storms that completely inundated the point bar, both less than the 1-year flood event. The first event, 34 cms, produced net deposition in areas where Johnson grass had been present and was now buried. The scour sensor at the lowest elevation, in a depression which serves as a secondary channel during storm events, recorded scour during the rising limb of the hydrograph followed by pulses we interpret to be the passage of dunes. The second event, although smaller at 28 cms, resulted from rain more than 50 km upstream and had a much longer peak and a slowly declining falling limb. During the second flood, several areas with buried vegetation were scoured back to their original bed elevations. Pulses of sediment passed over the sensor in the secondary channel and the sensor in the vegetated zone. Scour sensor measurements agree with data from scour chains (error +/- 3 cm) and surveys (error +/- 0.6 cm) performed before and after the two storm events, within the range of error of each method. All load sensor data were recorded at five minute intervals. Use of a smaller interval could give more details about the shapes of sediment waves and aid in bedform determination. Results suggest that dune migration is the dominant mechanism for scour and backfill in the point bar setting. Scour sensors, when coupled with surveying and/or scour chains, are a tremendous addition to the geomorphologist's toolbox, allowing unattended real-time measurements of sediment depth with time.

Guidance Of A Mobile Robot Using An Omnidirectional Vision Navigation System

NASA Astrophysics Data System (ADS)

Oh, Sung J.; Hall, Ernest L.

1987-01-01

Navigation and visual guidance are key topics in the design of a mobile robot. Omnidirectional vision using a very wide angle or fisheye lens provides a hemispherical view at a single instant that permits target location without mechanical scanning. The inherent image distortion with this view and the numerical errors accumulated from vision components can be corrected to provide accurate position determination for navigation and path control. The purpose of this paper is to present the experimental results and analyses of the imaging characteristics of the omnivision system including the design of robot-oriented experiments and the calibration of raw results. Errors less than one picture element on each axis were observed by testing the accuracy and repeatability of the experimental setup and the alignment between the robot and the sensor. Similar results were obtained for four different locations using corrected results of the linearity test between zenith angle and image location. Angular error of less than one degree and radial error of less than one Y picture element were observed at moderate relative speed. The significance of this work is that the experimental information and the test of coordinated operation of the equipment provide a greater understanding of the dynamic omnivision system characteristics, as well as insight into the evaluation and improvement of the prototype sensor for a mobile robot. Also, the calibration of the sensor is important, since the results provide a cornerstone for future developments. This sensor system is currently being developed for a robot lawn mower.

Exposure Time Optimization for Highly Dynamic Star Trackers

PubMed Central

Wei, Xinguo; Tan, Wei; Li, Jian; Zhang, Guangjun

2014-01-01

Under highly dynamic conditions, the star-spots on the image sensor of a star tracker move across many pixels during the exposure time, which will reduce star detection sensitivity and increase star location errors. However, this kind of effect can be compensated well by setting an appropriate exposure time. This paper focuses on how exposure time affects the star tracker under highly dynamic conditions and how to determine the most appropriate exposure time for this case. Firstly, the effect of exposure time on star detection sensitivity is analyzed by establishing the dynamic star-spot imaging model. Then the star location error is deduced based on the error analysis of the sub-pixel centroiding algorithm. Combining these analyses, the effect of exposure time on attitude accuracy is finally determined. Some simulations are carried out to validate these effects, and the results show that there are different optimal exposure times for different angular velocities of a star tracker with a given configuration. In addition, the results of night sky experiments using a real star tracker agree with the simulation results. The summarized regularities in this paper should prove helpful in the system design and dynamic performance evaluation of the highly dynamic star trackers. PMID:24618776

Development of a Tri-Axial Cutting Force Sensor for the Milling Process

PubMed Central

Li, Yingxue; Zhao, Yulong; Fei, Jiyou; Zhao, You; Li, Xiuyuan; Gao, Yunxiang

2016-01-01

This paper presents a three-component fixed dynamometer based on a strain gauge, which reduces output errors produced by the cutting force imposed on different milling positions of the workpiece. A reformative structure of tri-layer cross beams is proposed, sensitive areas were selected, and corresponding measuring circuits were arranged to decrease the inaccuracy brought about by positional variation. To simulate the situation with a milling cutter moving on the workpiece and validate the function of reducing the output errors when the milling position changes, both static calibration and dynamic milling tests were implemented on different parts of the workpiece. Static experiment results indicate that with standard loads imposed, the maximal deviation between the measured forces and the standard inputs is 4.87%. The results of the dynamic milling test illustrate that with identical machining parameters, the differences in output variation between the developed sensor and standard dynamometer are no larger than 6.61%. Both static and dynamic experimental results demonstrate that the developed dynamometer is suitable for measuring milling force imposed on different positions of the workpiece, which shows potential applicability in machining a monitoring system. PMID:27007374

The coronagraphic Modal Wavefront Sensor: a hybrid focal-plane sensor for the high-contrast imaging of circumstellar environments

NASA Astrophysics Data System (ADS)

Wilby, M. J.; Keller, C. U.; Snik, F.; Korkiakoski, V.; Pietrow, A. G. M.

2017-01-01

The raw coronagraphic performance of current high-contrast imaging instruments is limited by the presence of a quasi-static speckle (QSS) background, resulting from instrumental Non-Common Path Errors (NCPEs). Rapid development of efficient speckle subtraction techniques in data reduction has enabled final contrasts of up to 10-6 to be obtained, however it remains preferable to eliminate the underlying NCPEs at the source. In this work we introduce the coronagraphic Modal Wavefront Sensor (cMWS), a new wavefront sensor suitable for real-time NCPE correction. This combines the Apodizing Phase Plate (APP) coronagraph with a holographic modal wavefront sensor to provide simultaneous coronagraphic imaging and focal-plane wavefront sensing with the science point-spread function. We first characterise the baseline performance of the cMWS via idealised closed-loop simulations, showing that the sensor is able to successfully recover diffraction-limited coronagraph performance over an effective dynamic range of ±2.5 radians root-mean-square (rms) wavefront error within 2-10 iterations, with performance independent of the specific choice of mode basis. We then present the results of initial on-sky testing at the William Herschel Telescope, which demonstrate that the sensor is capable of NCPE sensing under realistic seeing conditions via the recovery of known static aberrations to an accuracy of 10 nm (0.1 radians) rms error in the presence of a dominant atmospheric speckle foreground. We also find that the sensor is capable of real-time measurement of broadband atmospheric wavefront variance (50% bandwidth, 158 nm rms wavefront error) at a cadence of 50 Hz over an uncorrected telescope sub-aperture. When combined with a suitable closed-loop adaptive optics system, the cMWS holds the potential to deliver an improvement of up to two orders of magnitude over the uncorrected QSS floor. Such a sensor would be eminently suitable for the direct imaging and spectroscopy of exoplanets with both existing and future instruments, including EPICS and METIS for the E-ELT.

Design, experiments and simulation of voltage transformers on the basis of a differential input D-dot sensor.

PubMed

Wang, Jingang; Gao, Can; Yang, Jie

2014-07-17

Currently available traditional electromagnetic voltage sensors fail to meet the measurement requirements of the smart grid, because of low accuracy in the static and dynamic ranges and the occurrence of ferromagnetic resonance attributed to overvoltage and output short circuit. This work develops a new non-contact high-bandwidth voltage measurement system for power equipment. This system aims at the miniaturization and non-contact measurement of the smart grid. After traditional D-dot voltage probe analysis, an improved method is proposed. For the sensor to work in a self-integrating pattern, the differential input pattern is adopted for circuit design, and grounding is removed. To prove the structure design, circuit component parameters, and insulation characteristics, Ansoft Maxwell software is used for the simulation. Moreover, the new probe was tested on a 10 kV high-voltage test platform for steady-state error and transient behavior. Experimental results ascertain that the root mean square values of measured voltage are precise and that the phase error is small. The D-dot voltage sensor not only meets the requirement of high accuracy but also exhibits satisfactory transient response. This sensor can meet the intelligence, miniaturization, and convenience requirements of the smart grid.

A Quantitative Evaluation of Drive Pattern Selection for Optimizing EIT-Based Stretchable Sensors

PubMed Central

Nefti-Meziani, Samia; Carbonaro, Nicola

2017-01-01

Electrical Impedance Tomography (EIT) is a medical imaging technique that has been recently used to realize stretchable pressure sensors. In this method, voltage measurements are taken at electrodes placed at the boundary of the sensor and are used to reconstruct an image of the applied touch pressure points. The drawback with EIT-based sensors, however, is their low spatial resolution due to the ill-posed nature of the EIT reconstruction. In this paper, we show our performance evaluation of different EIT drive patterns, specifically strategies for electrode selection when performing current injection and voltage measurements. We compare voltage data with Signal-to-Noise Ratio (SNR) and Boundary Voltage Changes (BVC), and study image quality with Size Error (SE), Position Error (PE) and Ringing (RNG) parameters, in the case of one-point and two-point simultaneous contact locations. The study shows that, in order to improve the performance of EIT based sensors, the electrode selection strategies should dynamically change correspondingly to the location of the input stimuli. In fact, the selection of one drive pattern over another can improve the target size detection and position accuracy up to 4.7% and 18%, respectively. PMID:28858252

A Quantitative Evaluation of Drive Pattern Selection for Optimizing EIT-Based Stretchable Sensors.

PubMed

Russo, Stefania; Nefti-Meziani, Samia; Carbonaro, Nicola; Tognetti, Alessandro

2017-08-31

Electrical Impedance Tomography (EIT) is a medical imaging technique that has been recently used to realize stretchable pressure sensors. In this method, voltage measurements are taken at electrodes placed at the boundary of the sensor and are used to reconstruct an image of the applied touch pressure points. The drawback with EIT-based sensors, however, is their low spatial resolution due to the ill-posed nature of the EIT reconstruction. In this paper, we show our performance evaluation of different EIT drive patterns, specifically strategies for electrode selection when performing current injection and voltage measurements. We compare voltage data with Signal-to-Noise Ratio (SNR) and Boundary Voltage Changes (BVC), and study image quality with Size Error (SE), Position Error (PE) and Ringing (RNG) parameters, in the case of one-point and two-point simultaneous contact locations. The study shows that, in order to improve the performance of EIT based sensors, the electrode selection strategies should dynamically change correspondingly to the location of the input stimuli. In fact, the selection of one drive pattern over another can improve the target size detection and position accuracy up to 4.7% and 18%, respectively.

Sensor fusion of monocular cameras and laser rangefinders for line-based Simultaneous Localization and Mapping (SLAM) tasks in autonomous mobile robots.

PubMed

Zhang, Xinzheng; Rad, Ahmad B; Wong, Yiu-Kwong

2012-01-01

This paper presents a sensor fusion strategy applied for Simultaneous Localization and Mapping (SLAM) in dynamic environments. The designed approach consists of two features: (i) the first one is a fusion module which synthesizes line segments obtained from laser rangefinder and line features extracted from monocular camera. This policy eliminates any pseudo segments that appear from any momentary pause of dynamic objects in laser data. (ii) The second characteristic is a modified multi-sensor point estimation fusion SLAM (MPEF-SLAM) that incorporates two individual Extended Kalman Filter (EKF) based SLAM algorithms: monocular and laser SLAM. The error of the localization in fused SLAM is reduced compared with those of individual SLAM. Additionally, a new data association technique based on the homography transformation matrix is developed for monocular SLAM. This data association method relaxes the pleonastic computation. The experimental results validate the performance of the proposed sensor fusion and data association method.

Deep data fusion method for missile-borne inertial/celestial system

NASA Astrophysics Data System (ADS)

Zhang, Chunxi; Chen, Xiaofei; Lu, Jiazhen; Zhang, Hao

2018-05-01

Strap-down inertial-celestial integrated navigation system has the advantages of autonomy and high precision and is very useful for ballistic missiles. The star sensor installation error and inertial measurement error have a great influence for the system performance. Based on deep data fusion, this paper establishes measurement equations including star sensor installation error and proposes the deep fusion filter method. Simulations including misalignment error, star sensor installation error, IMU error are analyzed. Simulation results indicate that the deep fusion method can estimate the star sensor installation error and IMU error. Meanwhile, the method can restrain the misalignment errors caused by instrument errors.

A computer-aided telescope pointing system utilizing a video star tracker

NASA Technical Reports Server (NTRS)

Murphy, J. P.; Lorell, K. R.; Swift, C. D.

1975-01-01

The Video Inertial Pointing (VIP) System developed to satisfy the acquisition and pointing requirements of astronomical telescopes is described. A unique feature of the system is the use of a single sensor to provide information for the generation of three axis pointing error signals and for a cathode ray tube (CRT) display of the star field. The pointing error signals are used to update the telescope's gyro stabilization and the CRT display is used by an operator to facilitate target acquisition and to aid in manual positioning of the telescope optical axis. A model of the system using a low light level vidicon built and flown on a balloon-borne infrared telescope is briefly described from a state of the art charge coupled device (CCD) sensor. The advanced system hardware is described and an analysis of the multi-star tracking and three axis error signal generation, along with an analysis and design of the gyro update filter, are presented. Results of a hybrid simulation are described in which the advanced VIP system hardware is driven by a digital simulation of the star field/CCD sensor and an analog simulation of the telescope and gyro stabilization dynamics.

Simultaneous localization and calibration for electromagnetic tracking systems.

PubMed

Sadjadi, Hossein; Hashtrudi-Zaad, Keyvan; Fichtinger, Gabor

2016-06-01

In clinical environments, field distortion can cause significant electromagnetic tracking errors. Therefore, dynamic calibration of electromagnetic tracking systems is essential to compensate for measurement errors. It is proposed to integrate the motion model of the tracked instrument with redundant EM sensor observations and to apply a simultaneous localization and mapping algorithm in order to accurately estimate the pose of the instrument and create a map of the field distortion in real-time. Experiments were conducted in the presence of ferromagnetic and electrically-conductive field distorting objects and results compared with those of a conventional sensor fusion approach. The proposed method reduced the tracking error from 3.94±1.61 mm to 1.82±0.62 mm in the presence of steel, and from 0.31±0.22 mm to 0.11±0.14 mm in the presence of aluminum. With reduced tracking error and independence from external tracking devices or pre-operative calibrations, the approach is promising for reliable EM navigation in various clinical procedures. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

De-biasing the dynamic mode decomposition for applied Koopman spectral analysis of noisy datasets

NASA Astrophysics Data System (ADS)

Hemati, Maziar S.; Rowley, Clarence W.; Deem, Eric A.; Cattafesta, Louis N.

2017-08-01

The dynamic mode decomposition (DMD)—a popular method for performing data-driven Koopman spectral analysis—has gained increased popularity for extracting dynamically meaningful spatiotemporal descriptions of fluid flows from snapshot measurements. Often times, DMD descriptions can be used for predictive purposes as well, which enables informed decision-making based on DMD model forecasts. Despite its widespread use and utility, DMD can fail to yield accurate dynamical descriptions when the measured snapshot data are imprecise due to, e.g., sensor noise. Here, we express DMD as a two-stage algorithm in order to isolate a source of systematic error. We show that DMD's first stage, a subspace projection step, systematically introduces bias errors by processing snapshots asymmetrically. To remove this systematic error, we propose utilizing an augmented snapshot matrix in a subspace projection step, as in problems of total least-squares, in order to account for the error present in all snapshots. The resulting unbiased and noise-aware total DMD (TDMD) formulation reduces to standard DMD in the absence of snapshot errors, while the two-stage perspective generalizes the de-biasing framework to other related methods as well. TDMD's performance is demonstrated in numerical and experimental fluids examples. In particular, in the analysis of time-resolved particle image velocimetry data for a separated flow, TDMD outperforms standard DMD by providing dynamical interpretations that are consistent with alternative analysis techniques. Further, TDMD extracts modes that reveal detailed spatial structures missed by standard DMD.

Hybrid wavefront sensor for the fast detection of wavefront disturbances.

PubMed

Dong, Shihao; Haist, Tobias; Osten, Wolfgang

2012-09-01

Strongly aberrated wavefronts lead to inaccuracies and nonlinearities in holography-based modal wavefront sensing (HMWS). In this contribution, a low-resolution Shack-Hartmann sensor (LRSHS) is incorporated into HMWS via a compact holographic design to extend the dynamic range of HMWS. A static binary-phase computer-generated hologram is employed to generate the desired patterns for Shack-Hartmann sensing and HMWS. The low-order aberration modes dominating the wavefront error are first sensed with the LRSHS and corrected by the wavefront modulator. The system then switches to HMWS to obtain better sensor sensitivity and accuracy. Simulated as well as experimental results are shown for validating the proposed method.

Verification of real sensor motion for a high-dynamic 3D measurement inspection system

NASA Astrophysics Data System (ADS)

Breitbarth, Andreas; Correns, Martin; Zimmermann, Manuel; Zhang, Chen; Rosenberger, Maik; Schambach, Jörg; Notni, Gunther

2017-06-01

Inline three-dimensional measurements are a growing part of optical inspection. Considering increasing production capacities and economic aspects, dynamic measurements under motion are inescapable. Using a sequence of different pattern, like it is generally done in fringe projection systems, relative movements of the measurement object with respect to the 3d sensor between the images of one pattern sequence have to be compensated. Based on the application of fully automated optical inspection of circuit boards at an assembly line, the knowledge of the relative speed of movement between the measurement object and the 3d sensor system should be used inside the algorithms of motion compensation. Optimally, this relative speed is constant over the whole measurement process and consists of only one motion direction to avoid sensor vibrations. The quantified evaluation of this two assumptions and the error impact on the 3d accuracy are content of the research project described by this paper. For our experiments we use a glass etalon with non-transparent circles and transmitted light. Focused on the circle borders, this is one of the most reliable methods to determine subpixel positions using a couple of searching rays. The intersection point of all rays characterize the center of each circle. Based on these circle centers determined with a precision of approximately 1=50 pixel, the motion vector between two images could be calculated and compared with the input motion vector. Overall, the results are used to optimize the weight distribution of the 3d sensor head and reduce non-uniformly vibrations. Finally, there exists a dynamic 3d measurement system with an error of motion vectors about 4 micrometer. Based on this outcome, simulations result in a 3d standard deviation at planar object regions of 6 micrometers. The same system yields a 3d standard deviation of 9 µm without the optimization of weight distribution.

COBE attitude as seen from the FDF

NASA Technical Reports Server (NTRS)

Sedlak, J.; Chu, D.; Scheidker, E.

1990-01-01

The goal of the Flight Dynamics Facility (FDF) attitude support is twofold: to determine spacecraft attitude and to explain deviations from nominal attitude behavior. Attitude determination often requires resolving contradictions in the sensor observations. This may be accomplished by applying calibration corrections or by revising the observation models. After accounting for all known sources of error, solution accuracy should be limited only by observation and propagation noise. The second half of the goal is to explain why the attitude may not be as originally intended. Reasons for such deviations include sensor or actuator misalignments and control system performance. In these cases, the ability to explain the behavior should, in principle, be limited only by knowledge of the sensor and actuator data and external torques. Documented here are some results obtained to date in support of the Cosmic Background Explorer (COBE). Advantages and shortcomings of the integrated attitude determination/sensor calibration software are discussed. Some preliminary attitude solutions using data from the Diffuse Infrared Background Experiment (DIRBE) instrument are presented and compared to solutions using Sun and Earth sensors. A dynamical model is constructed to illustrate the relative importance of the various sensor imprefections. This model also shows the connection between the high- and low-frequency attitude oscillations.

Maximum-likelihood methods in wavefront sensing: stochastic models and likelihood functions

PubMed Central

Barrett, Harrison H.; Dainty, Christopher; Lara, David

2008-01-01

Maximum-likelihood (ML) estimation in wavefront sensing requires careful attention to all noise sources and all factors that influence the sensor data. We present detailed probability density functions for the output of the image detector in a wavefront sensor, conditional not only on wavefront parameters but also on various nuisance parameters. Practical ways of dealing with nuisance parameters are described, and final expressions for likelihoods and Fisher information matrices are derived. The theory is illustrated by discussing Shack–Hartmann sensors, and computational requirements are discussed. Simulation results show that ML estimation can significantly increase the dynamic range of a Shack–Hartmann sensor with four detectors and that it can reduce the residual wavefront error when compared with traditional methods. PMID:17206255

An accurate nonlinear stochastic model for MEMS-based inertial sensor error with wavelet networks

NASA Astrophysics Data System (ADS)

El-Diasty, Mohammed; El-Rabbany, Ahmed; Pagiatakis, Spiros

2007-12-01

The integration of Global Positioning System (GPS) with Inertial Navigation System (INS) has been widely used in many applications for positioning and orientation purposes. Traditionally, random walk (RW), Gauss-Markov (GM), and autoregressive (AR) processes have been used to develop the stochastic model in classical Kalman filters. The main disadvantage of classical Kalman filter is the potentially unstable linearization of the nonlinear dynamic system. Consequently, a nonlinear stochastic model is not optimal in derivative-based filters due to the expected linearization error. With a derivativeless-based filter such as the unscented Kalman filter or the divided difference filter, the filtering process of a complicated highly nonlinear dynamic system is possible without linearization error. This paper develops a novel nonlinear stochastic model for inertial sensor error using a wavelet network (WN). A wavelet network is a highly nonlinear model, which has recently been introduced as a powerful tool for modelling and prediction. Static and kinematic data sets are collected using a MEMS-based IMU (DQI-100) to develop the stochastic model in the static mode and then implement it in the kinematic mode. The derivativeless-based filtering method using GM, AR, and the proposed WN-based processes are used to validate the new model. It is shown that the first-order WN-based nonlinear stochastic model gives superior positioning results to the first-order GM and AR models with an overall improvement of 30% when 30 and 60 seconds GPS outages are introduced.

Flight Mechanics/Estimation Theory Symposium, 1992

NASA Technical Reports Server (NTRS)

Stengle, Thomas H. (Editor)

1993-01-01

This conference publication includes 40 papers and abstracts presented at the Flight Mechanics/Estimation Theory Symposium on May 5-7, 1992. Sponsored by the Flight Dynamics Division of Goddard Space Flight Center, this symposium featured technical papers on a wide range of issues related to orbit-attitude prediction, determination, and control; attitude sensor calibration; attitude determination error analysis; attitude dynamics; and orbit decay and maneuver strategy. Government, industry, and the academic community participated in the preparation and presentation of these papers.

Flight Mechanics/Estimation Theory Symposium 1996

NASA Technical Reports Server (NTRS)

Greatorex, Scott (Editor)

1996-01-01

This conference publication includes 34 papers and abstracts presented at the Flight Mechanics/ Estimation Theory Symposium on May 14-16, 1996. Sponsored by the Flight Dynamics Division of Goddard Space Flight Center, this symposium featured technical papers on a wide range of issues related to orbit-attitude prediction, determination, and control; attitude sensor calibration; attitude determination error analysis; attitude dynamics; and orbit decay and maneuver strategy. Government, industry, and the academic community participated in the preparation and presentation of these papers.

Flight Mechanics/Estimation Theory Symposium, 1994

NASA Technical Reports Server (NTRS)

Hartman, Kathy R. (Editor)

1994-01-01

This conference publication includes 41 papers and abstracts presented at the Flight Mechanics/Estimation Theory Symposium on May 17-19, 1994. Sponsored by the Flight Dynamics Division of Goddard Space Flight Center, this symposium featured technical papers on a wide range of issues related to orbit-attitude prediction, determination and control; attitude sensor calibration; attitude determination error analysis; attitude dynamics; and orbit decay and maneuver strategy. Government, industry, and the academic community participated in the preparation and presentation of these papers.

Flight Mechanics/Estimation Theory Symposium, 1990

NASA Technical Reports Server (NTRS)

Stengle, Thomas (Editor)

1990-01-01

This conference publication includes 32 papers and abstracts presented at the Flight Mechanics/Estimation Theory Symposium on May 22-25, 1990. Sponsored by the Flight Dynamics Division of Goddard Space Flight Center, this symposium features technical papers on a wide range of issues related to orbit-attitude prediction, determination and control; attitude sensor calibration; attitude determination error analysis; attitude dynamics; and orbit decay and maneuver strategy. Government, industry, and the academic community participated in the preparation and presentation of these papers.

Flight Mechanics/Estimation Theory Symposium 1995

NASA Technical Reports Server (NTRS)

Hartman, Kathy R. (Editor)

1995-01-01

This conference publication includes 41 papers and abstracts presented at the Flight Mechanics/ Estimation Theory Symposium on May 16-18, 1995. Sponsored by the Flight Dynamics Division of Goddard Space Flight Center, this symposium featured technical papers on a wide range of issues related to orbit-attitude prediction, determination, and control; attitude sensor calibration; attitude determination error analysis; attitude dynamics; and orbit decay and maneuver strategy. Government, industry, and the academic community participated in the preparation and presentation of these papers.

Modeling, Analyzing, and Mitigating Dissonance Between Alerting Systems

NASA Technical Reports Server (NTRS)

Song, Lixia; Kuchar, James K.

2003-01-01

Alerting systems are becoming pervasive in process operations, which may result in the potential for dissonance or conflict in information from different alerting systems that suggests different threat levels and/or actions to resolve hazards. Little is currently available to help in predicting or solving the dissonance problem. This thesis presents a methodology to model and analyze dissonance between alerting systems, providing both a theoretical foundation for understanding dissonance and a practical basis from which specific problems can be addressed. A state-space representation of multiple alerting system operation is generalized that can be tailored across a variety of applications. Based on the representation, two major causes of dissonance are identified: logic differences and sensor error. Additionally, several possible types of dissonance are identified. A mathematical analysis method is developed to identify the conditions for dissonance originating from logic differences. A probabilistic analysis methodology is developed to estimate the probability of dissonance originating from sensor error, and to compare the relative contribution to dissonance of sensor error against the contribution from logic differences. A hybrid model, which describes the dynamic behavior of the process with multiple alerting systems, is developed to identify dangerous dissonance space, from which the process can lead to disaster. Methodologies to avoid or mitigate dissonance are outlined. Two examples are used to demonstrate the application of the methodology. First, a conceptual In-Trail Spacing example is presented. The methodology is applied to identify the conditions for possible dissonance, to identify relative contribution of logic difference and sensor error, and to identify dangerous dissonance space. Several proposed mitigation methods are demonstrated in this example. In the second example, the methodology is applied to address the dissonance problem between two air traffic alert and avoidance systems: the existing Traffic Alert and Collision Avoidance System (TCAS) vs. the proposed Airborne Conflict Management system (ACM). Conditions on ACM resolution maneuvers are identified to avoid dynamic dissonance between TCAS and ACM. Also included in this report is an Appendix written by Lee Winder about recent and continuing work on alerting systems design. The application of Markov Decision Process (MDP) theory to complex alerting problems is discussed and illustrated with an abstract example system.

A curved edge diffraction-utilized displacement sensor for spindle metrology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, ChaBum, E-mail: clee@tntech.edu; Zhao, Rui; Jeon, Seongkyul

This paper presents a new dimensional metrological sensing principle for a curved surface based on curved edge diffraction. Spindle error measurement technology utilizes a cylindrical or spherical target artifact attached to the spindle with non-contact sensors, typically a capacitive sensor (CS) or an eddy current sensor, pointed at the artifact. However, these sensors are designed for flat surface measurement. Therefore, measuring a target with a curved surface causes error. This is due to electric fields behaving differently between a flat and curved surface than between two flat surfaces. In this study, a laser is positioned incident to the cylindrical surfacemore » of the spindle, and a photodetector collects the total field produced by the diffraction around the target surface. The proposed sensor was compared with a CS within a range of 500 μm. The discrepancy between the proposed sensor and CS was 0.017% of the full range. Its sensing performance showed a resolution of 14 nm and a drift of less than 10 nm for 7 min of operation. This sensor was also used to measure dynamic characteristics of the spindle system (natural frequency 181.8 Hz, damping ratio 0.042) and spindle runout (22.0 μm at 2000 rpm). The combined standard uncertainty was estimated as 85.9 nm under current experiment conditions. It is anticipated that this measurement technique allows for in situ health monitoring of a precision spindle system in an accurate, convenient, and low cost manner.« less

Real-Time Parameter Estimation Using Output Error

NASA Technical Reports Server (NTRS)

Grauer, Jared A.

2014-01-01

Output-error parameter estimation, normally a post- ight batch technique, was applied to real-time dynamic modeling problems. Variations on the traditional algorithm were investigated with the goal of making the method suitable for operation in real time. Im- plementation recommendations are given that are dependent on the modeling problem of interest. Application to ight test data showed that accurate parameter estimates and un- certainties for the short-period dynamics model were available every 2 s using time domain data, or every 3 s using frequency domain data. The data compatibility problem was also solved in real time, providing corrected sensor measurements every 4 s. If uncertainty corrections for colored residuals are omitted, this rate can be increased to every 0.5 s.

Experimental Robot Model Adjustments Based on Force–Torque Sensor Information

PubMed Central

2018-01-01

The computational complexity of humanoid robot balance control is reduced through the application of simplified kinematics and dynamics models. However, these simplifications lead to the introduction of errors that add to other inherent electro-mechanic inaccuracies and affect the robotic system. Linear control systems deal with these inaccuracies if they operate around a specific working point but are less precise if they do not. This work presents a model improvement based on the Linear Inverted Pendulum Model (LIPM) to be applied in a non-linear control system. The aim is to minimize the control error and reduce robot oscillations for multiple working points. The new model, named the Dynamic LIPM (DLIPM), is used to plan the robot behavior with respect to changes in the balance status denoted by the zero moment point (ZMP). Thanks to the use of information from force–torque sensors, an experimental procedure has been applied to characterize the inaccuracies and introduce them into the new model. The experiments consist of balance perturbations similar to those of push-recovery trials, in which step-shaped ZMP variations are produced. The results show that the responses of the robot with respect to balance perturbations are more precise and the mechanical oscillations are reduced without comprising robot dynamics. PMID:29534477

Fault detection and isolation in motion monitoring system.

PubMed

Kim, Duk-Jin; Suk, Myoung Hoon; Prabhakaran, B

2012-01-01

Pervasive computing becomes very active research field these days. A watch that can trace human movement to record motion boundary as well as to study of finding social life pattern by one's localized visiting area. Pervasive computing also helps patient monitoring. A daily monitoring system helps longitudinal study of patient monitoring such as Alzheimer's and Parkinson's or obesity monitoring. Due to the nature of monitoring sensor (on-body wireless sensor), however, signal noise or faulty sensors errors can be present at any time. Many research works have addressed these problems any with a large amount of sensor deployment. In this paper, we present the faulty sensor detection and isolation using only two on-body sensors. We have been investigating three different types of sensor errors: the SHORT error, the CONSTANT error, and the NOISY SENSOR error (see more details on section V). Our experimental results show that the success rate of isolating faulty signals are an average of over 91.5% on fault type 1, over 92% on fault type 2, and over 99% on fault type 3 with the fault prior of 30% sensor errors.

Design and Test of a Soil Profile Moisture Sensor Based on Sensitive Soil Layers.

PubMed

Gao, Zhenran; Zhu, Yan; Liu, Cheng; Qian, Hongzhou; Cao, Weixing; Ni, Jun

2018-05-21

To meet the demand of intelligent irrigation for accurate moisture sensing in the soil vertical profile, a soil profile moisture sensor was designed based on the principle of high-frequency capacitance. The sensor consists of five groups of sensing probes, a data processor, and some accessory components. Low-resistivity copper rings were used as components of the sensing probes. Composable simulation of the sensor’s sensing probes was carried out using a high-frequency structure simulator. According to the effective radiation range of electric field intensity, width and spacing of copper ring were set to 30 mm and 40 mm, respectively. A parallel resonance circuit of voltage-controlled oscillator and high-frequency inductance-capacitance (LC) was designed for signal frequency division and conditioning. A data processor was used to process moisture-related frequency signals for soil profile moisture sensing. The sensor was able to detect real-time soil moisture at the depths of 20, 30, and 50 cm and conduct online inversion of moisture in the soil layer between 0⁻100 cm. According to the calibration results, the degree of fitting ( R ²) between the sensor’s measuring frequency and the volumetric moisture content of soil sample was 0.99 and the relative error of the sensor consistency test was 0⁻1.17%. Field tests in different loam soils showed that measured soil moisture from our sensor reproduced the observed soil moisture dynamic well, with an R ² of 0.96 and a root mean square error of 0.04. In a sensor accuracy test, the R ² between the measured value of the proposed sensor and that of the Diviner2000 portable soil moisture monitoring system was higher than 0.85, with a relative error smaller than 5%. The R ² between measured values and inversed soil moisture values for other soil layers were consistently higher than 0.8. According to calibration test and field test, this sensor, which features low cost, good operability, and high integration, is qualified for precise agricultural irrigation with stable performance and high accuracy.

Design, Experiments and Simulation of Voltage Transformers on the Basis of a Differential Input D-dot Sensor

PubMed Central

Wang, Jingang; Gao, Can; Yang, Jie

2014-01-01

Currently available traditional electromagnetic voltage sensors fail to meet the measurement requirements of the smart grid, because of low accuracy in the static and dynamic ranges and the occurrence of ferromagnetic resonance attributed to overvoltage and output short circuit. This work develops a new non-contact high-bandwidth voltage measurement system for power equipment. This system aims at the miniaturization and non-contact measurement of the smart grid. After traditional D-dot voltage probe analysis, an improved method is proposed. For the sensor to work in a self-integrating pattern, the differential input pattern is adopted for circuit design, and grounding is removed. To prove the structure design, circuit component parameters, and insulation characteristics, Ansoft Maxwell software is used for the simulation. Moreover, the new probe was tested on a 10 kV high-voltage test platform for steady-state error and transient behavior. Experimental results ascertain that the root mean square values of measured voltage are precise and that the phase error is small. The D-dot voltage sensor not only meets the requirement of high accuracy but also exhibits satisfactory transient response. This sensor can meet the intelligence, miniaturization, and convenience requirements of the smart grid. PMID:25036333

Automatic control of positioning along the joint during EBW in conditions of action of magnetic fields

NASA Astrophysics Data System (ADS)

Druzhinina, A. A.; Laptenok, V. D.; Murygin, A. V.; Laptenok, P. V.

2016-11-01

Positioning along the joint during the electron beam welding is a difficult scientific and technical problem to achieve the high quality of welds. The final solution of this problem is not found. This is caused by weak interference protection of sensors of the joint position directly in the welding process. Frequently during the electron beam welding magnetic fields deflect the electron beam from the optical axis of the electron beam gun. The collimated X-ray sensor is used to monitor the beam deflection caused by the action of magnetic fields. Signal of X-ray sensor is processed by the method of synchronous detection. Analysis of spectral characteristics of the X-ray sensor showed that the displacement of the joint from the optical axis of the gun affects on the output signal of sensor. The authors propose dual-circuit system for automatic positioning of the electron beam on the joint during the electron beam welding in conditions of action of magnetic interference. This system includes a contour of joint tracking and contour of compensation of magnetic fields. The proposed system is stable. Calculation of dynamic error of system showed that error of positioning does not exceed permissible deviation of the electron beam from the joint plane.

Error Modeling and Experimental Study of a Flexible Joint 6-UPUR Parallel Six-Axis Force Sensor.

PubMed

Zhao, Yanzhi; Cao, Yachao; Zhang, Caifeng; Zhang, Dan; Zhang, Jie

2017-09-29

By combining a parallel mechanism with integrated flexible joints, a large measurement range and high accuracy sensor is realized. However, the main errors of the sensor involve not only assembly errors, but also deformation errors of its flexible leg. Based on a flexible joint 6-UPUR (a kind of mechanism configuration where U-universal joint, P-prismatic joint, R-revolute joint) parallel six-axis force sensor developed during the prephase, assembly and deformation error modeling and analysis of the resulting sensors with a large measurement range and high accuracy are made in this paper. First, an assembly error model is established based on the imaginary kinematic joint method and the Denavit-Hartenberg (D-H) method. Next, a stiffness model is built to solve the stiffness matrix. The deformation error model of the sensor is obtained. Then, the first order kinematic influence coefficient matrix when the synthetic error is taken into account is solved. Finally, measurement and calibration experiments of the sensor composed of the hardware and software system are performed. Forced deformation of the force-measuring platform is detected by using laser interferometry and analyzed to verify the correctness of the synthetic error model. In addition, the first order kinematic influence coefficient matrix in actual circumstances is calculated. By comparing the condition numbers and square norms of the coefficient matrices, the conclusion is drawn theoretically that it is very important to take into account the synthetic error for design stage of the sensor and helpful to improve performance of the sensor in order to meet needs of actual working environments.

Error Modeling and Experimental Study of a Flexible Joint 6-UPUR Parallel Six-Axis Force Sensor

PubMed Central

Zhao, Yanzhi; Cao, Yachao; Zhang, Caifeng; Zhang, Dan; Zhang, Jie

2017-01-01

By combining a parallel mechanism with integrated flexible joints, a large measurement range and high accuracy sensor is realized. However, the main errors of the sensor involve not only assembly errors, but also deformation errors of its flexible leg. Based on a flexible joint 6-UPUR (a kind of mechanism configuration where U-universal joint, P-prismatic joint, R-revolute joint) parallel six-axis force sensor developed during the prephase, assembly and deformation error modeling and analysis of the resulting sensors with a large measurement range and high accuracy are made in this paper. First, an assembly error model is established based on the imaginary kinematic joint method and the Denavit-Hartenberg (D-H) method. Next, a stiffness model is built to solve the stiffness matrix. The deformation error model of the sensor is obtained. Then, the first order kinematic influence coefficient matrix when the synthetic error is taken into account is solved. Finally, measurement and calibration experiments of the sensor composed of the hardware and software system are performed. Forced deformation of the force-measuring platform is detected by using laser interferometry and analyzed to verify the correctness of the synthetic error model. In addition, the first order kinematic influence coefficient matrix in actual circumstances is calculated. By comparing the condition numbers and square norms of the coefficient matrices, the conclusion is drawn theoretically that it is very important to take into account the synthetic error for design stage of the sensor and helpful to improve performance of the sensor in order to meet needs of actual working environments. PMID:28961209

Model of human dynamic orientation. Ph.D. Thesis; [associated with vestibular stimuli

NASA Technical Reports Server (NTRS)

Ormsby, C. C.

1974-01-01

The dynamics associated with the perception of orientation were modelled for near-threshold and suprathreshold vestibular stimuli. A model of the information available at the peripheral sensors which was consistent with available neurophysiologic data was developed and served as the basis for the models of the perceptual responses. The central processor was assumed to utilize the information from the peripheral sensors in an optimal (minimum mean square error) manner to produce the perceptual estimates of dynamic orientation. This assumption, coupled with the models of sensory information, determined the form of the model for the central processor. The problem of integrating information from the semi-circular canals and the otoliths to predict the perceptual response to motions which stimulated both organs was studied. A model was developed which was shown to be useful in predicting the perceptual response to multi-sensory stimuli.

Spacecraft attitude determination accuracy from mission experience

NASA Technical Reports Server (NTRS)

Brasoveanu, D.; Hashmall, J.

1994-01-01

This paper summarizes a compilation of attitude determination accuracies attained by a number of satellites supported by the Goddard Space Flight Center Flight Dynamics Facility. The compilation is designed to assist future mission planners in choosing and placing attitude hardware and selecting the attitude determination algorithms needed to achieve given accuracy requirements. The major goal of the compilation is to indicate realistic accuracies achievable using a given sensor complement based on mission experience. It is expected that the use of actual spacecraft experience will make the study especially useful for mission design. A general description of factors influencing spacecraft attitude accuracy is presented. These factors include determination algorithms, inertial reference unit characteristics, and error sources that can affect measurement accuracy. Possible techniques for mitigating errors are also included. Brief mission descriptions are presented with the attitude accuracies attained, grouped by the sensor pairs used in attitude determination. The accuracies for inactive missions represent a compendium of missions report results, and those for active missions represent measurements of attitude residuals. Both three-axis and spin stabilized missions are included. Special emphasis is given to high-accuracy sensor pairs, such as two fixed-head star trackers (FHST's) and fine Sun sensor plus FHST. Brief descriptions of sensor design and mode of operation are included. Also included are brief mission descriptions and plots summarizing the attitude accuracy attained using various sensor complements.

Modeling the Error of the Medtronic Paradigm Veo Enlite Glucose Sensor.

PubMed

Biagi, Lyvia; Ramkissoon, Charrise M; Facchinetti, Andrea; Leal, Yenny; Vehi, Josep

2017-06-12

Continuous glucose monitors (CGMs) are prone to inaccuracy due to time lags, sensor drift, calibration errors, and measurement noise. The aim of this study is to derive the model of the error of the second generation Medtronic Paradigm Veo Enlite (ENL) sensor and compare it with the Dexcom SEVEN PLUS (7P), G4 PLATINUM (G4P), and advanced G4 for Artificial Pancreas studies (G4AP) systems. An enhanced methodology to a previously employed technique was utilized to dissect the sensor error into several components. The dataset used included 37 inpatient sessions in 10 subjects with type 1 diabetes (T1D), in which CGMs were worn in parallel and blood glucose (BG) samples were analyzed every 15 ± 5 min Calibration error and sensor drift of the ENL sensor was best described by a linear relationship related to the gain and offset. The mean time lag estimated by the model is 9.4 ± 6.5 min. The overall average mean absolute relative difference (MARD) of the ENL sensor was 11.68 ± 5.07% Calibration error had the highest contribution to total error in the ENL sensor. This was also reported in the 7P, G4P, and G4AP. The model of the ENL sensor error will be useful to test the in silico performance of CGM-based applications, i.e., the artificial pancreas, employing this kind of sensor.

Flight Mechanics/Estimation Theory Symposium 1988

NASA Technical Reports Server (NTRS)

Stengle, Thomas (Editor)

1988-01-01

This conference publication includes 28 papers and abstracts presented at the Flight Mechanics/Estimation Theory Symposium on May 10 to 11, 1988. Sponsored by the Flight Dynamics Division of Goddard Space Flight Center, this symposium features technical papers on a wide range of issue related to orbit-attitude prediction, determination and control; attitude sensor calibration; attitude determination error analysis; attitude dynamics; and orbit decay and maneuver strategy. Government, industry, and the academic community participated in the preparation and presentation of these papers.

Flight Mechanics Symposium 1997

NASA Technical Reports Server (NTRS)

Walls, Donna M. (Editor)

1997-01-01

This conference publication includes papers and abstracts presented at the Flight Mechanics Symposium. This symposium featured technical papers on a wide range of issues related to orbit-attitude prediction, determination, and control; attitude sensor calibration; attitude determination error analysis; attitude dynamics; and orbit decay and maneuver strategy. Government, industry, and the academic community participated in the preparation and presentation of these papers.

Method and system for detecting a failure or performance degradation in a dynamic system such as a flight vehicle

NASA Technical Reports Server (NTRS)

Miller, Robert H. (Inventor); Ribbens, William B. (Inventor)

2003-01-01

A method and system for detecting a failure or performance degradation in a dynamic system having sensors for measuring state variables and providing corresponding output signals in response to one or more system input signals are provided. The method includes calculating estimated gains of a filter and selecting an appropriate linear model for processing the output signals based on the input signals. The step of calculating utilizes one or more models of the dynamic system to obtain estimated signals. The method further includes calculating output error residuals based on the output signals and the estimated signals. The method also includes detecting one or more hypothesized failures or performance degradations of a component or subsystem of the dynamic system based on the error residuals. The step of calculating the estimated values is performed optimally with respect to one or more of: noise, uncertainty of parameters of the models and un-modeled dynamics of the dynamic system which may be a flight vehicle or financial market or modeled financial system.

Dependence of the compensation error on the error of a sensor and corrector in an adaptive optics phase-conjugating system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kiyko, V V; Kislov, V I; Ofitserov, E N

2015-08-31

In the framework of a statistical model of an adaptive optics system (AOS) of phase conjugation, three algorithms based on an integrated mathematical approach are considered, each of them intended for minimisation of one of the following characteristics: the sensor error (in the case of an ideal corrector), the corrector error (in the case of ideal measurements) and the compensation error (with regard to discreteness and measurement noises and to incompleteness of a system of response functions of the corrector actuators). Functional and statistical relationships between the algorithms are studied and a relation is derived to ensure calculation of themore » mean-square compensation error as a function of the errors of the sensor and corrector with an accuracy better than 10%. Because in adjusting the AOS parameters, it is reasonable to proceed from the equality of the sensor and corrector errors, in the case the Hartmann sensor is used as a wavefront sensor, the required number of actuators in the absence of the noise component in the sensor error turns out 1.5 – 2.5 times less than the number of counts, and that difference grows with increasing measurement noise. (adaptive optics)« less

Solution to the SLAM problem in low dynamic environments using a pose graph and an RGB-D sensor.

PubMed

Lee, Donghwa; Myung, Hyun

2014-07-11

In this study, we propose a solution to the simultaneous localization and mapping (SLAM) problem in low dynamic environments by using a pose graph and an RGB-D (red-green-blue depth) sensor. The low dynamic environments refer to situations in which the positions of objects change over long intervals. Therefore, in the low dynamic environments, robots have difficulty recognizing the repositioning of objects unlike in highly dynamic environments in which relatively fast-moving objects can be detected using a variety of moving object detection algorithms. The changes in the environments then cause groups of false loop closing when the same moved objects are observed for a while, which means that conventional SLAM algorithms produce incorrect results. To address this problem, we propose a novel SLAM method that handles low dynamic environments. The proposed method uses a pose graph structure and an RGB-D sensor. First, to prune the falsely grouped constraints efficiently, nodes of the graph, that represent robot poses, are grouped according to the grouping rules with noise covariances. Next, false constraints of the pose graph are pruned according to an error metric based on the grouped nodes. The pose graph structure is reoptimized after eliminating the false information, and the corrected localization and mapping results are obtained. The performance of the method was validated in real experiments using a mobile robot system.

Improved Stratospheric Temperature Retrievals for Climate Reanalysis

NASA Technical Reports Server (NTRS)

Rokke, L.; Joiner, J.

1999-01-01

The Data Assimilation Office (DAO) is embarking on plans to generate a twenty year reanalysis data set of climatic atmospheric variables. One of the focus points will be in the evaluation of the dynamics of the stratosphere. The Stratospheric Sounding Unit (SSU), flown as part of the TIROS Operational Vertical Sounder (TOVS), is one of the primary stratospheric temperature sensors flown consistently throughout the reanalysis period. Seven unique sensors made the measurements over time, with individual instrument characteristics that need to be addressed. The stratospheric temperatures being assimilated across satellite platforms will profoundly impact the reanalysis dynamical fields. To attempt to quantify aspects of instrument and retrieval bias we are carefully collecting and analyzing all available information on the sensors, their instrument anomalies, forward model errors and retrieval biases. For the retrieval of stratospheric temperatures, we adapted the minimum variance approach of Jazwinski (1970) and Rodgers (1976) and applied it to the SSU soundings. In our algorithm, the state vector contains an initial guess of temperature from a model six hour forecast provided by the Goddard EOS Data Assimilation System (GEOS/DAS). This is combined with an a priori covariance matrix, a forward model parameterization, and specifications of instrument noise characteristics. A quasi-Newtonian iteration is used to obtain convergence of the retrieved state to the measurement vector. This algorithm also enables us to analyze and address the systematic errors associated with the unique characteristics of the cell pressures on the individual SSU instruments and the resolving power of the instruments to vertical gradients in the stratosphere. The preliminary results of the improved retrievals and their assimilation as well as baseline calculations of bias and rms error between the NESDIS operational product and col-located ground measurements will be presented.

Side-effects of a bad attitude: How GNSS spacecraft orientation errors affect solar radiation pressure modelling

NASA Astrophysics Data System (ADS)

Dilssner, Florian; Springer, Tim; Schönemann, Erik; Zandbergen, Rene; Enderle, Werner

2015-04-01

Solar radiation pressure (SRP) is the largest non-gravitational perturbation for Global Navigation Satellite System (GNSS) satellites, and can therefore have substantial impact on their orbital dynamics. Various SRP force models have been developed over the past 30 years for the purpose of precise orbit determination. They all rely upon the assumption that the satellites continuously maintain a Sun-Nadir pointing attitude with the navigation antenna boresight (body-fixed z-axis) pointing towards Earth center, and the solar panel rotation axis (body-fixed y-axis) being normal to the Sun direction. However, in reality, this is not perfectly the case. Reasons for a non-nominal spacecraft attitude may be eclipse maneuvers, commanded attitude biases and Sun/horizon sensor measurement errors, for example due to mounting misalignment or incorrectly calibrated sensor electronics. In this work the effect of GNSS spacecraft orientation errors on SRP modelling is investigated. Simplified mathematical functions describing the SRP force acting on the solar arrays in the presence of yaw-, pitch- and roll-biases are derived. Special attention is paid to the yaw-bias and its relationship to the SRP dynamics, particular in direction of the spacecraft y-axis ("y-bias force"). Analytical and experimental results gathered from orbit and attitude analyses of GPS Block II/IIA/IIF satellites demonstrate how sensitive the SRP coefficients are to changes in yaw.

Differential Laser Doppler based Non-Contact Sensor for Dimensional Inspection with Error Propagation Evaluation

PubMed Central

Mekid, Samir; Vacharanukul, Ketsaya

2006-01-01

To achieve dynamic error compensation in CNC machine tools, a non-contact laser probe capable of dimensional measurement of a workpiece while it is being machined has been developed and presented in this paper. The measurements are automatically fed back to the machine controller for intelligent error compensations. Based on a well resolved laser Doppler technique and real time data acquisition, the probe delivers a very promising dimensional accuracy at few microns over a range of 100 mm. The developed optical measuring apparatus employs a differential laser Doppler arrangement allowing acquisition of information from the workpiece surface. In addition, the measurements are traceable to standards of frequency allowing higher precision.

Temperature-compensated distributed hydrostatic pressure sensor with a thin-diameter polarization-maintaining photonic crystal fiber based on Brillouin dynamic gratings.

PubMed

Teng, Lei; Zhang, Hongying; Dong, Yongkang; Zhou, Dengwang; Jiang, Taofei; Gao, Wei; Lu, Zhiwei; Chen, Liang; Bao, Xiaoyi

2016-09-15

A temperature-compensated distributed hydrostatic pressure sensor based on Brillouin dynamic gratings (BDGs) is proposed and demonstrated experimentally for the first time, to the best of our knowledge. The principle is to measure the hydrostatic pressure induced birefringence changes through exciting and probing the BDGs in a thin-diameter pure silica polarization-maintaining photonic crystal fiber. The temperature cross-talk to the hydrostatic pressure sensing can be compensated through measuring the temperature-induced Brillouin frequency shift (BFS) changes using Brillouin optical time-domain analysis. A distributed measurement of hydrostatic pressure is demonstrated experimentally using a 4-m sensing fiber, which has a high sensitivity, with a maximum measurement error less than 0.03 MPa at a 20-cm spatial resolution.

Estimation of Center of Mass Trajectory using Wearable Sensors during Golf Swing.

PubMed

Najafi, Bijan; Lee-Eng, Jacqueline; Wrobel, James S; Goebel, Ruben

2015-06-01

This study suggests a wearable sensor technology to estimate center of mass (CoM) trajectory during a golf swing. Groups of 3, 4, and 18 participants were recruited, respectively, for the purpose of three validation studies. Study 1 examined the accuracy of the system to estimate a 3D body segment angle compared to a camera-based motion analyzer (Vicon®). Study 2 assessed the accuracy of three simplified CoM trajectory models. Finally, Study 3 assessed the accuracy of the proposed CoM model during multiple golf swings. A relatively high agreement was observed between wearable sensors and the reference (Vicon®) for angle measurement (r > 0.99, random error <1.2° (1.5%) for anterior-posterior; <0.9° (2%) for medial-lateral; and <3.6° (2.5%) for internal-external direction). The two-link model yielded a better agreement with the reference system compared to one-link model (r > 0.93 v. r = 0.52, respectively). On the same note, the proposed two-link model estimated CoM trajectory during golf swing with relatively good accuracy (r > 0.9, A-P random error <1cm (7.7%) and <2cm (10.4%) for M-L). The proposed system appears to accurately quantify the kinematics of CoM trajectory as a surrogate of dynamic postural control during an athlete's movement and its portability, makes it feasible to fit the competitive environment without restricting surface type. Key pointsThis study demonstrates that wearable technology based on inertial sensors are accurate to estimate center of mass trajectory in complex athletic task (e.g., golf swing)This study suggests that two-link model of human body provides optimum tradeoff between accuracy and minimum number of sensor module for estimation of center of mass trajectory in particular during fast movements.Wearable technologies based on inertial sensors are viable option for assessing dynamic postural control in complex task outside of gait laboratory and constraints of cameras, surface, and base of support.

On-board error correction improves IR earth sensor accuracy

NASA Astrophysics Data System (ADS)

Alex, T. K.; Kasturirangan, K.; Shrivastava, S. K.

1989-10-01

Infra-red earth sensors are used in satellites for attitude sensing. Their accuracy is limited by systematic and random errors. The sources of errors in a scanning infra-red earth sensor are analyzed in this paper. The systematic errors arising from seasonal variation of infra-red radiation, oblate shape of the earth, ambient temperature of sensor, changes in scan/spin rates have been analyzed. Simple relations are derived using least square curve fitting for on-board correction of these errors. Random errors arising out of noise from detector and amplifiers, instability of alignment and localized radiance anomalies are analyzed and possible correction methods are suggested. Sun and Moon interference on earth sensor performance has seriously affected a number of missions. The on-board processor detects Sun/Moon interference and corrects the errors on-board. It is possible to obtain eight times improvement in sensing accuracy, which will be comparable with ground based post facto attitude refinement.

Characterising a holographic modal phase mask for the detection of ocular aberrations

NASA Astrophysics Data System (ADS)

Corbett, A. D.; Leyva, D. Gil; Diaz-Santana, L.; Wilkinson, T. D.; Zhong, J. J.

2005-12-01

The accurate measurement of the double-pass ocular wave front has been shown to have a broad range of applications from LASIK surgery to adaptively corrected retinal imaging. The ocular wave front can be accurately described by a small number of Zernike circle polynomials. The modal wave front sensor was first proposed by Neil et al. and allows the coefficients of the individual Zernike modes to be measured directly. Typically the aberrations measured with the modal sensor are smaller than those seen in the ocular wave front. In this work, we investigated a technique for adapting a modal phase mask for the sensing of the ocular wave front. This involved extending the dynamic range of the sensor by increasing the pinhole size to 2.4mm and optimising the mask bias to 0.75λ. This was found to decrease the RMS error by up to a factor of three for eye-like aberrations with amplitudes up to 0.2μm. For aberrations taken from a sample of real-eye measurements a 20% decrease in the RMS error was observed.

Online Estimation of Allan Variance Coefficients Based on a Neural-Extended Kalman Filter

PubMed Central

Miao, Zhiyong; Shen, Feng; Xu, Dingjie; He, Kunpeng; Tian, Chunmiao

2015-01-01

As a noise analysis method for inertial sensors, the traditional Allan variance method requires the storage of a large amount of data and manual analysis for an Allan variance graph. Although the existing online estimation methods avoid the storage of data and the painful procedure of drawing slope lines for estimation, they require complex transformations and even cause errors during the modeling of dynamic Allan variance. To solve these problems, first, a new state-space model that directly models the stochastic errors to obtain a nonlinear state-space model was established for inertial sensors. Then, a neural-extended Kalman filter algorithm was used to estimate the Allan variance coefficients. The real noises of an ADIS16405 IMU and fiber optic gyro-sensors were analyzed by the proposed method and traditional methods. The experimental results show that the proposed method is more suitable to estimate the Allan variance coefficients than the traditional methods. Moreover, the proposed method effectively avoids the storage of data and can be easily implemented using an online processor. PMID:25625903

Wire-positioning algorithm for coreless Hall array sensors in current measurement

NASA Astrophysics Data System (ADS)

Chen, Wenli; Zhang, Huaiqing; Chen, Lin; Gu, Shanyun

2018-05-01

This paper presents a scheme of circular-arrayed, coreless Hall-effect current transformers. It can satisfy the demands of wide dynamic range and bandwidth current in the distribution system, as well as the demand of AC and DC simultaneous measurements. In order to improve the signal to noise ratio (SNR) of the sensor, a wire-positioning algorithm is proposed, which can improve the measurement accuracy based on the post-processing of measurement data. The simulation results demonstrate that the maximum errors are 70%, 6.1% and 0.95% corresponding to Ampère’s circuital method, approximate positioning algorithm and precise positioning algorithm, respectively. It is obvious that the accuracy of the positioning algorithm is significantly improved when compared with that of the Ampère’s circuital method. The maximum error of the positioning algorithm is smaller in the experiment.

Robotic joint experiments under ultravacuum

NASA Technical Reports Server (NTRS)

Borrien, A.; Petitjean, L.

1988-01-01

First, various aspects of a robotic joint development program, including gearbox technology, electromechanical components, lubrication, and test results, are discussed. Secondly, a test prototype of the joint allowing simulation of robotic arm dynamic effects is presented. This prototype is tested under vacuum with different types of motors and sensors to characterize the functional parameters: angular position error, mechanical backlash, gearbox efficiency, and lifetime.

Design and Test of a Soil Profile Moisture Sensor Based on Sensitive Soil Layers

PubMed Central

Liu, Cheng; Qian, Hongzhou; Cao, Weixing; Ni, Jun

2018-01-01

To meet the demand of intelligent irrigation for accurate moisture sensing in the soil vertical profile, a soil profile moisture sensor was designed based on the principle of high-frequency capacitance. The sensor consists of five groups of sensing probes, a data processor, and some accessory components. Low-resistivity copper rings were used as components of the sensing probes. Composable simulation of the sensor’s sensing probes was carried out using a high-frequency structure simulator. According to the effective radiation range of electric field intensity, width and spacing of copper ring were set to 30 mm and 40 mm, respectively. A parallel resonance circuit of voltage-controlled oscillator and high-frequency inductance-capacitance (LC) was designed for signal frequency division and conditioning. A data processor was used to process moisture-related frequency signals for soil profile moisture sensing. The sensor was able to detect real-time soil moisture at the depths of 20, 30, and 50 cm and conduct online inversion of moisture in the soil layer between 0–100 cm. According to the calibration results, the degree of fitting (R2) between the sensor’s measuring frequency and the volumetric moisture content of soil sample was 0.99 and the relative error of the sensor consistency test was 0–1.17%. Field tests in different loam soils showed that measured soil moisture from our sensor reproduced the observed soil moisture dynamic well, with an R2 of 0.96 and a root mean square error of 0.04. In a sensor accuracy test, the R2 between the measured value of the proposed sensor and that of the Diviner2000 portable soil moisture monitoring system was higher than 0.85, with a relative error smaller than 5%. The R2 between measured values and inversed soil moisture values for other soil layers were consistently higher than 0.8. According to calibration test and field test, this sensor, which features low cost, good operability, and high integration, is qualified for precise agricultural irrigation with stable performance and high accuracy. PMID:29883420

Modeling and Development of INS-Aided PLLs in a GNSS/INS Deeply-Coupled Hardware Prototype for Dynamic Applications

PubMed Central

Zhang, Tisheng; Niu, Xiaoji; Ban, Yalong; Zhang, Hongping; Shi, Chuang; Liu, Jingnan

2015-01-01

A GNSS/INS deeply-coupled system can improve the satellite signals tracking performance by INS aiding tracking loops under dynamics. However, there was no literature available on the complete modeling of the INS branch in the INS-aided tracking loop, which caused the lack of a theoretical tool to guide the selections of inertial sensors, parameter optimization and quantitative analysis of INS-aided PLLs. This paper makes an effort on the INS branch in modeling and parameter optimization of phase-locked loops (PLLs) based on the scalar-based GNSS/INS deeply-coupled system. It establishes the transfer function between all known error sources and the PLL tracking error, which can be used to quantitatively evaluate the candidate inertial measurement unit (IMU) affecting the carrier phase tracking error. Based on that, a steady-state error model is proposed to design INS-aided PLLs and to analyze their tracking performance. Based on the modeling and error analysis, an integrated deeply-coupled hardware prototype is developed, with the optimization of the aiding information. Finally, the performance of the INS-aided PLLs designed based on the proposed steady-state error model is evaluated through the simulation and road tests of the hardware prototype. PMID:25569751

Multi-Unmanned Aerial Vehicle (UAV) Cooperative Fault Detection Employing Differential Global Positioning (DGPS), Inertial and Vision Sensors.

PubMed

Heredia, Guillermo; Caballero, Fernando; Maza, Iván; Merino, Luis; Viguria, Antidio; Ollero, Aníbal

2009-01-01

This paper presents a method to increase the reliability of Unmanned Aerial Vehicle (UAV) sensor Fault Detection and Identification (FDI) in a multi-UAV context. Differential Global Positioning System (DGPS) and inertial sensors are used for sensor FDI in each UAV. The method uses additional position estimations that augment individual UAV FDI system. These additional estimations are obtained using images from the same planar scene taken from two different UAVs. Since accuracy and noise level of the estimation depends on several factors, dynamic replanning of the multi-UAV team can be used to obtain a better estimation in case of faults caused by slow growing errors of absolute position estimation that cannot be detected by using local FDI in the UAVs. Experimental results with data from two real UAVs are also presented.

Study of a MEMS-based Shack-Hartmann wavefront sensor with adjustable pupil sampling for astronomical adaptive optics.

PubMed

Baranec, Christoph; Dekany, Richard

2008-10-01

We introduce a Shack-Hartmann wavefront sensor for adaptive optics that enables dynamic control of the spatial sampling of an incoming wavefront using a segmented mirror microelectrical mechanical systems (MEMS) device. Unlike a conventional lenslet array, subapertures are defined by either segments or groups of segments of a mirror array, with the ability to change spatial pupil sampling arbitrarily by redefining the segment grouping. Control over the spatial sampling of the wavefront allows for the minimization of wavefront reconstruction error for different intensities of guide source and different atmospheric conditions, which in turn maximizes an adaptive optics system's delivered Strehl ratio. Requirements for the MEMS devices needed in this Shack-Hartmann wavefront sensor are also presented.

Filtering Methods for Error Reduction in Spacecraft Attitude Estimation Using Quaternion Star Trackers

NASA Technical Reports Server (NTRS)

Calhoun, Philip C.; Sedlak, Joseph E.; Superfin, Emil

2011-01-01

Precision attitude determination for recent and planned space missions typically includes quaternion star trackers (ST) and a three-axis inertial reference unit (IRU). Sensor selection is based on estimates of knowledge accuracy attainable from a Kalman filter (KF), which provides the optimal solution for the case of linear dynamics with measurement and process errors characterized by random Gaussian noise with white spectrum. Non-Gaussian systematic errors in quaternion STs are often quite large and have an unpredictable time-varying nature, particularly when used in non-inertial pointing applications. Two filtering methods are proposed to reduce the attitude estimation error resulting from ST systematic errors, 1) extended Kalman filter (EKF) augmented with Markov states, 2) Unscented Kalman filter (UKF) with a periodic measurement model. Realistic assessments of the attitude estimation performance gains are demonstrated with both simulation and flight telemetry data from the Lunar Reconnaissance Orbiter.

Human Activity Recognition by Combining a Small Number of Classifiers.

PubMed

Nazabal, Alfredo; Garcia-Moreno, Pablo; Artes-Rodriguez, Antonio; Ghahramani, Zoubin

2016-09-01

We consider the problem of daily human activity recognition (HAR) using multiple wireless inertial sensors, and specifically, HAR systems with a very low number of sensors, each one providing an estimation of the performed activities. We propose new Bayesian models to combine the output of the sensors. The models are based on a soft outputs combination of individual classifiers to deal with the small number of sensors. We also incorporate the dynamic nature of human activities as a first-order homogeneous Markov chain. We develop both inductive and transductive inference methods for each model to be employed in supervised and semisupervised situations, respectively. Using different real HAR databases, we compare our classifiers combination models against a single classifier that employs all the signals from the sensors. Our models exhibit consistently a reduction of the error rate and an increase of robustness against sensor failures. Our models also outperform other classifiers combination models that do not consider soft outputs and an Markovian structure of the human activities.

Effects of video compression on target acquisition performance

NASA Astrophysics Data System (ADS)

Espinola, Richard L.; Cha, Jae; Preece, Bradley

2008-04-01

The bandwidth requirements of modern target acquisition systems continue to increase with larger sensor formats and multi-spectral capabilities. To obviate this problem, still and moving imagery can be compressed, often resulting in greater than 100 fold decrease in required bandwidth. Compression, however, is generally not error-free and the generated artifacts can adversely affect task performance. The U.S. Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate recently performed an assessment of various compression techniques on static imagery for tank identification. In this paper, we expand this initial assessment by studying and quantifying the effect of various video compression algorithms and their impact on tank identification performance. We perform a series of controlled human perception tests using three dynamic simulated scenarios: target moving/sensor static, target static/sensor static, sensor tracking the target. Results of this study will quantify the effect of video compression on target identification and provide a framework to evaluate video compression on future sensor systems.

Error analysis on spinal motion measurement using skin mounted sensors.

PubMed

Yang, Zhengyi; Ma, Heather Ting; Wang, Deming; Lee, Raymond

2008-01-01

Measurement errors of skin-mounted sensors in measuring forward bending movement of the lumbar spines are investigated. In this investigation, radiographic images capturing the entire lumbar spines' positions were acquired and used as a 'gold' standard. Seventeen young male volunteers (21 (SD 1) years old) agreed to participate in the study. Light-weight miniature sensors of the electromagnetic tracking systems-Fastrak were attached to the skin overlying the spinous processes of the lumbar spine. With the sensors attached, the subjects were requested to take lateral radiographs in two postures: neutral upright and full flexion. The ranges of motions of lumbar spine were calculated from two sets of digitized data: the bony markers of vertebral bodies and the sensors and compared. The differences between the two sets of results were then analyzed. The relative movement between sensor and vertebrae was decomposed into sensor sliding and titling, from which sliding error and titling error were introduced. Gross motion range of forward bending of lumbar spine measured from bony markers of vertebrae is 67.8 degrees (SD 10.6 degrees ) and that from sensors is 62.8 degrees (SD 12.8 degrees ). The error and absolute error for gross motion range were 5.0 degrees (SD 7.2 degrees ) and 7.7 degrees (SD 3.9 degrees ). The contributions of sensors placed on S1 and L1 to the absolute error were 3.9 degrees (SD 2.9 degrees ) and 4.4 degrees (SD 2.8 degrees ), respectively.

FBG based high sensitive pressure sensor and its low-cost interrogation system with enhanced resolution

NASA Astrophysics Data System (ADS)

Pachava, Vengal Rao; Kamineni, Srimannarayana; Madhuvarasu, Sai Shankar; Putha, Kishore; Mamidi, Venkata Reddy

2015-12-01

A fiber Bragg grating (FBG) pressure sensor with high sensitivity and resolution has been designed and demonstrated. The sensor is configured by firmly fixing the FBG with a metal bellows structure. The sensor works by means of measuring the Bragg wavelength shift of the FBG with respect to pressure change. From the experimental results, the pressure sensitivity of the sensor is found to be 90.6 pm/psi, which is approximately 4000 times as that of a bare fiber Bragg grating. A very good linearity of 99.86% is observed between the Bragg wavelength of the FBG and applied pressure. The designed sensor shows good repeatability with a negligible hysteresis error of ± 0.29 psi. A low-cost interrogation system that includes a long period grating (LPG) and a photodiode (PD) accompanied with simple electronic circuitry is demonstrated for the FBG sensor, which enables the sensor to attain high resolution of up to 0.025 psi. Thermal-strain cross sensitivity of the FBG pressure sensor is compensated using a reference FBG temperature sensor. The designed sensor can be used for liquid level, specific gravity, and static/dynamic low pressure measurement applications.

Precision analysis of autonomous orbit determination using star sensor for Beidou MEO satellite

NASA Astrophysics Data System (ADS)

Shang, Lin; Chang, Jiachao; Zhang, Jun; Li, Guotong

2018-04-01

This paper focuses on the autonomous orbit determination accuracy of Beidou MEO satellite using the onboard observations of the star sensors and infrared horizon sensor. A polynomial fitting method is proposed to calibrate the periodic error in the observation of the infrared horizon sensor, which will greatly influence the accuracy of autonomous orbit determination. Test results show that the periodic error can be eliminated using the polynomial fitting method. The User Range Error (URE) of Beidou MEO satellite is less than 2 km using the observations of the star sensors and infrared horizon sensor for autonomous orbit determination. The error of the Right Ascension of Ascending Node (RAAN) is less than 60 μrad and the observations of star sensors can be used as a spatial basis for Beidou MEO navigation constellation.

Expected accuracy of proximal and distal temperature estimated by wireless sensors, in relation to their number and position on the skin.

PubMed

Longato, Enrico; Garrido, Maria; Saccardo, Desy; Montesinos Guevara, Camila; Mani, Ali R; Bolognesi, Massimo; Amodio, Piero; Facchinetti, Andrea; Sparacino, Giovanni; Montagnese, Sara

2017-01-01

A popular method to estimate proximal/distal temperature (TPROX and TDIST) consists in calculating a weighted average of nine wireless sensors placed on pre-defined skin locations. Specifically, TPROX is derived from five sensors placed on the infra-clavicular and mid-thigh area (left and right) and abdomen, and TDIST from four sensors located on the hands and feet. In clinical practice, the loss/removal of one or more sensors is a common occurrence, but limited information is available on how this affects the accuracy of temperature estimates. The aim of this study was to determine the accuracy of temperature estimates in relation to number/position of sensors removed. Thirteen healthy subjects wore all nine sensors for 24 hours and reference TPROX and TDIST time-courses were calculated using all sensors. Then, all possible combinations of reduced subsets of sensors were simulated and suitable weights for each sensor calculated. The accuracy of TPROX and TDIST estimates resulting from the reduced subsets of sensors, compared to reference values, was assessed by the mean squared error, the mean absolute error (MAE), the cross-validation error and the 25th and 75th percentiles of the reconstruction error. Tables of the accuracy and sensor weights for all possible combinations of sensors are provided. For instance, in relation to TPROX, a subset of three sensors placed in any combination of three non-homologous areas (abdominal, right or left infra-clavicular, right or left mid-thigh) produced an error of 0.13°C MAE, while the loss/removal of the abdominal sensor resulted in an error of 0.25°C MAE, with the greater impact on the quality of the reconstruction. This information may help researchers/clinicians: i) evaluate the expected goodness of their TPROX and TDIST estimates based on the number of available sensors; ii) select the most appropriate subset of sensors, depending on goals and operational constraints.

Expected accuracy of proximal and distal temperature estimated by wireless sensors, in relation to their number and position on the skin

PubMed Central

Longato, Enrico; Garrido, Maria; Saccardo, Desy; Montesinos Guevara, Camila; Mani, Ali R.; Bolognesi, Massimo; Amodio, Piero; Facchinetti, Andrea; Sparacino, Giovanni

2017-01-01

A popular method to estimate proximal/distal temperature (TPROX and TDIST) consists in calculating a weighted average of nine wireless sensors placed on pre-defined skin locations. Specifically, TPROX is derived from five sensors placed on the infra-clavicular and mid-thigh area (left and right) and abdomen, and TDIST from four sensors located on the hands and feet. In clinical practice, the loss/removal of one or more sensors is a common occurrence, but limited information is available on how this affects the accuracy of temperature estimates. The aim of this study was to determine the accuracy of temperature estimates in relation to number/position of sensors removed. Thirteen healthy subjects wore all nine sensors for 24 hours and reference TPROX and TDIST time-courses were calculated using all sensors. Then, all possible combinations of reduced subsets of sensors were simulated and suitable weights for each sensor calculated. The accuracy of TPROX and TDIST estimates resulting from the reduced subsets of sensors, compared to reference values, was assessed by the mean squared error, the mean absolute error (MAE), the cross-validation error and the 25th and 75th percentiles of the reconstruction error. Tables of the accuracy and sensor weights for all possible combinations of sensors are provided. For instance, in relation to TPROX, a subset of three sensors placed in any combination of three non-homologous areas (abdominal, right or left infra-clavicular, right or left mid-thigh) produced an error of 0.13°C MAE, while the loss/removal of the abdominal sensor resulted in an error of 0.25°C MAE, with the greater impact on the quality of the reconstruction. This information may help researchers/clinicians: i) evaluate the expected goodness of their TPROX and TDIST estimates based on the number of available sensors; ii) select the most appropriate subset of sensors, depending on goals and operational constraints. PMID:28666029

Dynamic Vehicle Detection via the Use of Magnetic Field Sensors

PubMed Central

Markevicius, Vytautas; Navikas, Dangirutis; Zilys, Mindaugas; Andriukaitis, Darius; Valinevicius, Algimantas; Cepenas, Mindaugas

2016-01-01

The vehicle detection process plays the key role in determining the success of intelligent transport management system solutions. The measurement of distortions of the Earth’s magnetic field using magnetic field sensors served as the basis for designing a solution aimed at vehicle detection. In accordance with the results obtained from research into process modeling and experimentally testing all the relevant hypotheses an algorithm for vehicle detection using the state criteria was proposed. Aiming to evaluate all of the possibilities, as well as pros and cons of the use of anisotropic magnetoresistance (AMR) sensors in the transport flow control process, we have performed a series of experiments with various vehicles (or different series) from several car manufacturers. A comparison of 12 selected methods, based on either the process of determining the peak signal values and their concurrence in time whilst calculating the delay, or by measuring the cross-correlation of these signals, was carried out. It was established that the relative error can be minimized via the Z component cross-correlation and Kz criterion cross-correlation methods. The average relative error of vehicle speed determination in the best case did not exceed 1.5% when the distance between sensors was set to 2 m. PMID:26797615

Three-Dimensional Venturi Sensor for Measuring Extreme Winds

NASA Technical Reports Server (NTRS)

Zysko, Jan A.; Perotti, Jose M.; Amis, Christopher; Randazzo, John; Blalock, Norman; Eckhoff, Anthony

2003-01-01

A three-dimensional (3D) Venturi sensor is being developed as a compact, rugged means of measuring wind vectors having magnitudes of as much as 300 mph (134 m/s). This sensor also incorporates auxiliary sensors for measuring temperature from -40 to +120 F (-40 to +49 C), relative humidity from 0 to 100 percent, and atmospheric pressure from 846 to 1,084 millibar (85 to 108 kPa). Conventional cup-and-vane anemometers are highly susceptible to damage by both high wind forces and debris, due to their moving parts and large profiles. In addition, they exhibit slow recovery times contributing to an inaccurately high average-speed reading. Ultrasonic and hot-wire anemometers overcome some of the disadvantages of the cup and-vane anemometers, but they have other disadvantageous features, including limited dynamic range and susceptibility to errors caused by external acoustic noise and rain. In contrast, the novel 3D Venturi sensor is less vulnerable to wind damage because of its smaller profile and ruggedness. Since the sensor has no moving parts, it provides increased reliability and lower maintenance costs. It has faster response and recovery times to changing wind conditions than traditional systems. In addition, it offers wide dynamic range and is expected to be relatively insensitive to rain and acoustic energy. The Venturi effect in this sensor is achieved by the mirrored double-inflection curve, which is then rotated 360 to create the desired detection surfaces. The curve is optimized to provide a good balance of pressure difference between sensor ports and overall maximum fluid velocity while in the shape. Four posts are used to separate the two shapes, and their size and location were chosen to minimize effects on the pressure measurements. The 3D Venturi sensor has smart software algorithms to map the wind pressure exerted on the surfaces of the design. Using Bernoulli's equation, the speed of the wind is calculated from the differences among the pressure readings at the various ports. The direction of the wind is calculated from the spatial distribution and magnitude of the pressure readings. All of the pressure port sizes and locations have been optimized to minimize measurement errors and to reside in areas demonstrating a stable pressure reading proportional to the velocity range.

New generation of wearable goniometers for motion capture systems

PubMed Central

2014-01-01

Background Monitoring joint angles through wearable systems enables human posture and gesture to be reconstructed as a support for physical rehabilitation both in clinics and at the patient’s home. A new generation of wearable goniometers based on knitted piezoresistive fabric (KPF) technology is presented. Methods KPF single-and double-layer devices were designed and characterized under stretching and bending to work as strain sensors and goniometers. The theoretical working principle and the derived electromechanical model, previously proved for carbon elastomer sensors, were generalized to KPF. The devices were used to correlate angles and piezoresistive fabric behaviour, to highlight the differences in terms of performance between the single layer and the double layer sensors. A fast calibration procedure is also proposed. Results The proposed device was tested both in static and dynamic conditions in comparison with standard electrogoniometers and inertial measurement units respectively. KPF goniometer capabilities in angle detection were experimentally proved and a discussion of the device measurement errors of is provided. The paper concludes with an analysis of sensor accuracy and hysteresis reduction in particular configurations. Conclusions Double layer KPF goniometers showed a promising performance in terms of angle measurements both in quasi-static and dynamic working mode for velocities typical of human movement. A further approach consisting of a combination of multiple sensors to increase accuracy via sensor fusion technique has been presented. PMID:24725669

Vibration Noise Modeling for Measurement While Drilling System Based on FOGs.

PubMed

Zhang, Chunxi; Wang, Lu; Gao, Shuang; Lin, Tie; Li, Xianmu

2017-10-17

Aiming to improve survey accuracy of Measurement While Drilling (MWD) based on Fiber Optic Gyroscopes (FOGs) in the long period, the external aiding sources are fused into the inertial navigation by the Kalman filter (KF) method. The KF method needs to model the inertial sensors' noise as the system noise model. The system noise is modeled as white Gaussian noise conventionally. However, because of the vibration while drilling, the noise in gyros isn't white Gaussian noise any more. Moreover, an incorrect noise model will degrade the accuracy of KF. This paper developed a new approach for noise modeling on the basis of dynamic Allan variance (DAVAR). In contrast to conventional white noise models, the new noise model contains both the white noise and the color noise. With this new noise model, the KF for the MWD was designed. Finally, two vibration experiments have been performed. Experimental results showed that the proposed vibration noise modeling approach significantly improved the estimated accuracies of the inertial sensor drifts. Compared the navigation results based on different noise model, with the DAVAR noise model, the position error and the toolface angle error are reduced more than 90%. The velocity error is reduced more than 65%. The azimuth error is reduced more than 50%.

An online input force time history reconstruction algorithm using dynamic principal component analysis

NASA Astrophysics Data System (ADS)

Prawin, J.; Rama Mohan Rao, A.

2018-01-01

The knowledge of dynamic loads acting on a structure is always required for many practical engineering problems, such as structural strength analysis, health monitoring and fault diagnosis, and vibration isolation. In this paper, we present an online input force time history reconstruction algorithm using Dynamic Principal Component Analysis (DPCA) from the acceleration time history response measurements using moving windows. We also present an optimal sensor placement algorithm to place limited sensors at dynamically sensitive spatial locations. The major advantage of the proposed input force identification algorithm is that it does not require finite element idealization of structure unlike the earlier formulations and therefore free from physical modelling errors. We have considered three numerical examples to validate the accuracy of the proposed DPCA based method. Effects of measurement noise, multiple force identification, different kinds of loading, incomplete measurements, and high noise levels are investigated in detail. Parametric studies have been carried out to arrive at optimal window size and also the percentage of window overlap. Studies presented in this paper clearly establish the merits of the proposed algorithm for online load identification.

Online machining error estimation method of numerical control gear grinding machine tool based on data analysis of internal sensors

NASA Astrophysics Data System (ADS)

Zhao, Fei; Zhang, Chi; Yang, Guilin; Chen, Chinyin

2016-12-01

This paper presents an online estimation method of cutting error by analyzing of internal sensor readings. The internal sensors of numerical control (NC) machine tool are selected to avoid installation problem. The estimation mathematic model of cutting error was proposed to compute the relative position of cutting point and tool center point (TCP) from internal sensor readings based on cutting theory of gear. In order to verify the effectiveness of the proposed model, it was simulated and experimented in gear generating grinding process. The cutting error of gear was estimated and the factors which induce cutting error were analyzed. The simulation and experiments verify that the proposed approach is an efficient way to estimate the cutting error of work-piece during machining process.

Macro-spin modeling and experimental study of spin-orbit torque biased magnetic sensors

NASA Astrophysics Data System (ADS)

Xu, Yanjun; Yang, Yumeng; Luo, Ziyan; Xu, Baoxi; Wu, Yihong

2017-11-01

We reported a systematic study of spin-orbit torque biased magnetic sensors based on NiFe/Pt bilayers through both macro-spin modeling and experiments. The simulation results show that it is possible to achieve a linear sensor with a dynamic range of 0.1-10 Oe, power consumption of 1 μW-1mW, and sensitivity of 0.1-0.5 Ω/Oe. These characteristics can be controlled by varying the sensor dimension and current density in the Pt layer. The latter is in the range of 1 × 105-107 A/cm2. Experimental results of fabricated sensors with selected sizes agree well with the simulation results. For a Wheatstone bridge sensor comprising of four sensing elements, a sensitivity up to 0.548 Ω/Oe, linearity error below 6%, and detectivity of about 2.8 nT/√Hz were obtained. The simple structure and ultrathin thickness greatly facilitate the integration of these sensors for on-chip applications. As a proof-of-concept experiment, we demonstrate its application in detection of current flowing in an on-chip Cu wire.

Indirect adaptive fuzzy fault-tolerant tracking control for MIMO nonlinear systems with actuator and sensor failures.

PubMed

Bounemeur, Abdelhamid; Chemachema, Mohamed; Essounbouli, Najib

2018-05-10

In this paper, an active fuzzy fault tolerant tracking control (AFFTTC) scheme is developed for a class of multi-input multi-output (MIMO) unknown nonlinear systems in the presence of unknown actuator faults, sensor failures and external disturbance. The developed control scheme deals with four kinds of faults for both sensors and actuators. The bias, drift, and loss of accuracy additive faults are considered along with the loss of effectiveness multiplicative fault. A fuzzy adaptive controller based on back-stepping design is developed to deal with actuator failures and unknown system dynamics. However, an additional robust control term is added to deal with sensor faults, approximation errors, and external disturbances. Lyapunov theory is used to prove the stability of the closed loop system. Numerical simulations on a quadrotor are presented to show the effectiveness of the proposed approach. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

The validity of the first and second generation Microsoft Kinect™ for identifying joint center locations during static postures.

PubMed

Xu, Xu; McGorry, Raymond W

2015-07-01

The Kinect™ sensor released by Microsoft is a low-cost, portable, and marker-less motion tracking system for the video game industry. Since the first generation Kinect sensor was released in 2010, many studies have been conducted to examine the validity of this sensor when used to measure body movement in different research areas. In 2014, Microsoft released the computer-used second generation Kinect sensor with a better resolution for the depth sensor. However, very few studies have performed a direct comparison between all the Kinect sensor-identified joint center locations and their corresponding motion tracking system-identified counterparts, the result of which may provide some insight into the error of the Kinect-identified segment length, joint angles, as well as the feasibility of adapting inverse dynamics to Kinect-identified joint centers. The purpose of the current study is to first propose a method to align the coordinate system of the Kinect sensor with respect to the global coordinate system of a motion tracking system, and then to examine the accuracy of the Kinect sensor-identified coordinates of joint locations during 8 standing and 8 sitting postures of daily activities. The results indicate the proposed alignment method can effectively align the Kinect sensor with respect to the motion tracking system. The accuracy level of the Kinect-identified joint center location is posture-dependent and joint-dependent. For upright standing posture, the average error across all the participants and all Kinect-identified joint centers is 76 mm and 87 mm for the first and second generation Kinect sensor, respectively. In general, standing postures can be identified with better accuracy than sitting postures, and the identification accuracy of the joints of the upper extremities is better than for the lower extremities. This result may provide some information regarding the feasibility of using the Kinect sensor in future studies. Copyright © 2015 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Dual-loop model of the human controller

NASA Technical Reports Server (NTRS)

Hess, R. A.

1978-01-01

A dual-loop model of the human controller in single-axis compensatory tracking tasks is introduced. This model possesses an inner-loop closure that involves feeding back that portion of controlled element output rate that is due to control activity. A novel feature of the model is the explicit appearance of the human's internal representation of the manipulator-controlled element dynamics in the inner loop. The sensor inputs to the human controller are assumed to be system error and control force. The former can be sensed via visual, aural, or tactile displays, whereas the latter is assumed to be sensed in kinesthetic fashion. A set of general adaptive characteristics for the model is hypothesized, including a method for selecting simplified internal models of the manipulator-controlled element dynamics. It is demonstrated that the model can produce controller describing functions that closely approximate those measured in four laboratory tracking tasks in which the controlled element dynamics vary considerably in terms of ease of control. An empirically derived expression for the normalized injected error remnant spectrum is introduced.

Development and validity of an instrumented handbike: initial results of propulsion kinetics.

PubMed

van Drongelen, Stefan; van den Berg, Jos; Arnet, Ursina; Veeger, Dirkjan H E J; van der Woude, Lucas H V

2011-11-01

To develop an instrumented handbike system to measure the forces applied to the handgrip during handbiking. A 6 degrees of freedom force sensor was built into the handgrip of an attach-unit handbike, together with two optical encoders to measure the orientation of the handgrip and crank in space. Linearity, precision, and percent error were determined for static and dynamic tests. High linearity was demonstrated for both the static and the dynamic condition (r=1.01). Precision was high under the static condition (standard deviation of 0.2N), however the precision decreased with higher loads during the dynamic condition. Percent error values were between 0.3 and 5.1%. This is the first instrumented handbike system that can register 3-dimensional forces. It can be concluded that the instrumented handbike system allows for an accurate force analysis based on forces registered at the handle bars. Copyright © 2011 IPEM. Published by Elsevier Ltd. All rights reserved.

Land surface dynamics monitoring using microwave passive satellite sensors

NASA Astrophysics Data System (ADS)

Guijarro, Lizbeth Noemi

Soil moisture, surface temperature and vegetation are variables that play an important role in our environment. There is growing demand for accurate estimation of these geophysical parameters for the research of global climate models (GCMs), weather, hydrological and flooding models, and for the application to agricultural assessment, land cover change, and a wide variety of other uses that meet the needs for the study of our environment. The different studies covered in this dissertation evaluate the capabilities and limitations of microwave passive sensors to monitor land surface dynamics. The first study evaluates the 19 GHz channel of the SSM/I instrument with a radiative transfer model and in situ datasets from the Illinois stations and the Oklahoma Mesonet to retrieve land surface temperature and surface soil moisture. The surface temperatures were retrieved with an average error of 5 K and the soil moisture with an average error of 6%. The results show that the 19 GHz channel can be used to qualitatively predict the spatial and temporal variability of surface soil moisture and surface temperature at regional scales. In the second study, in situ observations were compared with sensor observations to evaluate aspects of low and high spatial resolution at multiple frequencies with data collected from the Southern Great Plains Experiment (SGP99). The results showed that the sensitivity to soil moisture at each frequency is a function of wavelength and amount of vegetation. The results confirmed that L-band is more optimal for soil moisture, but each sensor can provide soil moisture information if the vegetation water content is low. The spatial variability of the emissivities reveals that resolution suffers considerably at higher frequencies. The third study evaluates C- and X-bands of the AMSR-E instrument. In situ datasets from the Soil Moisture Experiments (SMEX03) in South Central Georgia were utilized to validate the AMSR-E soil moisture product and to derive surface soil moisture with a radiative transfer model. The soil moisture was retrieved with an average error of 2.7% at X-band and 6.7% at C-band. The AMSR-E demonstrated its ability to successfully infer soil moisture during the SMEX03 experiment.

Discrete distributed strain sensing of intelligent structures

NASA Technical Reports Server (NTRS)

Anderson, Mark S.; Crawley, Edward F.

1992-01-01

Techniques are developed for the design of discrete highly distributed sensor systems for use in intelligent structures. First the functional requirements for such a system are presented. Discrete spatially averaging strain sensors are then identified as satisfying the functional requirements. A variety of spatial weightings for spatially averaging sensors are examined, and their wave number characteristics are determined. Preferable spatial weightings are identified. Several numerical integration rules used to integrate such sensors in order to determine the global deflection of the structure are discussed. A numerical simulation is conducted using point and rectangular sensors mounted on a cantilevered beam under static loading. Gage factor and sensor position uncertainties are incorporated to assess the absolute error and standard deviation of the error in the estimated tip displacement found by numerically integrating the sensor outputs. An experiment is carried out using a statically loaded cantilevered beam with five point sensors. It is found that in most cases the actual experimental error is within one standard deviation of the absolute error as found in the numerical simulation.

Sensor Spatial Distortion, Visual Latency, and Update Rate Effects on 3D Tracking in Virtual Environments

NASA Technical Reports Server (NTRS)

Ellis, S. R.; Adelstein, B. D.; Baumeler, S.; Jense, G. J.; Jacoby, R. H.; Trejo, Leonard (Technical Monitor)

1998-01-01

Several common defects that we have sought to minimize in immersing virtual environments are: static sensor spatial distortion, visual latency, and low update rates. Human performance within our environments during large amplitude 3D tracking was assessed by objective and subjective methods in the presence and absence of these defects. Results show that 1) removal of our relatively small spatial sensor distortion had minor effects on the tracking activity, 2) an Adapted Cooper-Harper controllability scale proved the most sensitive subjective indicator of the degradation of dynamic fidelity caused by increasing latency and decreasing frame rates, and 3) performance, as measured by normalized RMS tracking error or subjective impressions, was more markedly influenced by changing visual latency than by update rate.

Improving control and estimation for distributed parameter systems utilizing mobile actuator-sensor network.

PubMed

Mu, Wenying; Cui, Baotong; Li, Wen; Jiang, Zhengxian

2014-07-01

This paper proposes a scheme for non-collocated moving actuating and sensing devices which is unitized for improving performance in distributed parameter systems. By Lyapunov stability theorem, each moving actuator/sensor agent velocity is obtained. To enhance state estimation of a spatially distributes process, two kinds of filters with consensus terms which penalize the disagreement of the estimates are considered. Both filters can result in the well-posedness of the collective dynamics of state errors and can converge to the plant state. Numerical simulations demonstrate that the effectiveness of such a moving actuator-sensor network in enhancing system performance and the consensus filters converge faster to the plant state when consensus terms are included. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Hand-writing motion tracking with vision-inertial sensor fusion: calibration and error correction.

PubMed

Zhou, Shengli; Fei, Fei; Zhang, Guanglie; Liu, Yunhui; Li, Wen J

2014-08-25

The purpose of this study was to improve the accuracy of real-time ego-motion tracking through inertial sensor and vision sensor fusion. Due to low sampling rates supported by web-based vision sensor and accumulation of errors in inertial sensors, ego-motion tracking with vision sensors is commonly afflicted by slow updating rates, while motion tracking with inertial sensor suffers from rapid deterioration in accuracy with time. This paper starts with a discussion of developed algorithms for calibrating two relative rotations of the system using only one reference image. Next, stochastic noises associated with the inertial sensor are identified using Allan Variance analysis, and modeled according to their characteristics. Finally, the proposed models are incorporated into an extended Kalman filter for inertial sensor and vision sensor fusion. Compared with results from conventional sensor fusion models, we have shown that ego-motion tracking can be greatly enhanced using the proposed error correction model.

Experience from the in-flight calibration of the Extreme Ultraviolet Explorer (EUVE) and Upper Atmosphere Research Satellite (UARS) fixed head star trackers (FHSTs)

NASA Technical Reports Server (NTRS)

Lee, Michael

1995-01-01

Since the original post-launch calibration of the FHSTs (Fixed Head Star Trackers) on EUVE (Extreme Ultraviolet Explorer) and UARS (Upper Atmosphere Research Satellite), the Flight Dynamics task has continued to analyze the FHST performance. The algorithm used for inflight alignment of spacecraft sensors is described and the equations for the errors in the relative alignment for the simple 2 star tracker case are shown. Simulated data and real data are used to compute the covariance of the relative alignment errors. Several methods for correcting the alignment are compared and results analyzed. The specific problems seen on orbit with UARS and EUVE are then discussed. UARS has experienced anomalous tracker performance on an FHST resulting in continuous variation in apparent tracker alignment. On EUVE, the FHST residuals from the attitude determination algorithm showed a dependence on the direction of roll during survey mode. This dependence is traced back to time tagging errors and the original post launch alignment is found to be in error due to the impact of the time tagging errors on the alignment algorithm. The methods used by the FDF (Flight Dynamics Facility) to correct for these problems is described.

Grating-assisted demodulation of interferometric optical sensors.

PubMed

Yu, Bing; Wang, Anbo

2003-12-01

Accurate and dynamic control of the operating point of an interferometric optical sensor to produce the highest sensitivity is crucial in the demodulation of interferometric optical sensors to compensate for manufacturing errors and environmental perturbations. A grating-assisted operating-point tuning system has been designed that uses a diffraction grating and feedback control, functions as a tunable-bandpass optical filter, and can be used as an effective demodulation subsystem in sensor systems based on optical interferometers that use broadband light sources. This demodulation method has no signal-detection bandwidth limit, a high tuning speed, a large tunable range, increased interference fringe contrast, and the potential for absolute optical-path-difference measurement. The achieved 40-nm tuning range, which is limited by the available source spectrum width, 400-nm/s tuning speed, and a step resolution of 0.4 nm, is sufficient for most practical measurements. A significant improvement in signal-to-noise ratio in a fiber Fabry-Perot acoustic-wave sensor system proved that the expected fringe contrast and sensitivity increase.

Locating hazardous gas leaks in the atmosphere via modified genetic, MCMC and particle swarm optimization algorithms

NASA Astrophysics Data System (ADS)

Wang, Ji; Zhang, Ru; Yan, Yuting; Dong, Xiaoqiang; Li, Jun Ming

2017-05-01

Hazardous gas leaks in the atmosphere can cause significant economic losses in addition to environmental hazards, such as fires and explosions. A three-stage hazardous gas leak source localization method was developed that uses movable and stationary gas concentration sensors. The method calculates a preliminary source inversion with a modified genetic algorithm (MGA) and has the potential to crossover with eliminated individuals from the population, following the selection of the best candidate. The method then determines a search zone using Markov Chain Monte Carlo (MCMC) sampling, utilizing a partial evaluation strategy. The leak source is then accurately localized using a modified guaranteed convergence particle swarm optimization algorithm with several bad-performing individuals, following selection of the most successful individual with dynamic updates. The first two stages are based on data collected by motionless sensors, and the last stage is based on data from movable robots with sensors. The measurement error adaptability and the effect of the leak source location were analyzed. The test results showed that this three-stage localization process can localize a leak source within 1.0 m of the source for different leak source locations, with measurement error standard deviation smaller than 2.0.

Indoor Trajectory Tracking Scheme Based on Delaunay Triangulation and Heuristic Information in Wireless Sensor Networks.

PubMed

Qin, Junping; Sun, Shiwen; Deng, Qingxu; Liu, Limin; Tian, Yonghong

2017-06-02

Object tracking and detection is one of the most significant research areas for wireless sensor networks. Existing indoor trajectory tracking schemes in wireless sensor networks are based on continuous localization and moving object data mining. Indoor trajectory tracking based on the received signal strength indicator ( RSSI ) has received increased attention because it has low cost and requires no special infrastructure. However, RSSI tracking introduces uncertainty because of the inaccuracies of measurement instruments and the irregularities (unstable, multipath, diffraction) of wireless signal transmissions in indoor environments. Heuristic information includes some key factors for trajectory tracking procedures. This paper proposes a novel trajectory tracking scheme based on Delaunay triangulation and heuristic information (TTDH). In this scheme, the entire field is divided into a series of triangular regions. The common side of adjacent triangular regions is regarded as a regional boundary. Our scheme detects heuristic information related to a moving object's trajectory, including boundaries and triangular regions. Then, the trajectory is formed by means of a dynamic time-warping position-fingerprint-matching algorithm with heuristic information constraints. Field experiments show that the average error distance of our scheme is less than 1.5 m, and that error does not accumulate among the regions.

Error measuring system of rotary Inductosyn

NASA Astrophysics Data System (ADS)

Liu, Chengjun; Zou, Jibin; Fu, Xinghe

2008-10-01

The inductosyn is a kind of high-precision angle-position sensor. It has important applications in servo table, precision machine tool and other products. The precision of inductosyn is calibrated by its error. It's an important problem about the error measurement in the process of production and application of the inductosyn. At present, it mainly depends on the method of artificial measurement to obtain the error of inductosyn. Therefore, the disadvantages can't be ignored such as the high labour intensity of the operator, the occurrent error which is easy occurred and the poor repeatability, and so on. In order to solve these problems, a new automatic measurement method is put forward in this paper which based on a high precision optical dividing head. Error signal can be obtained by processing the output signal of inductosyn and optical dividing head precisely. When inductosyn rotating continuously, its zero position error can be measured dynamically, and zero error curves can be output automatically. The measuring and calculating errors caused by man-made factor can be overcome by this method, and it makes measuring process more quickly, exactly and reliably. Experiment proves that the accuracy of error measuring system is 1.1 arc-second (peak - peak value).

Smart Braid Feedback for the Closed-Loop Control of Soft Robotic Systems.

PubMed

Felt, Wyatt; Chin, Khai Yi; Remy, C David

2017-09-01

This article experimentally investigates the potential of using flexible, inductance-based contraction sensors in the closed-loop motion control of soft robots. Accurate motion control remains a highly challenging task for soft robotic systems. Precise models of the actuation dynamics and environmental interactions are often unavailable. This renders open-loop control impossible, while closed-loop control suffers from a lack of suitable feedback. Conventional motion sensors, such as linear or rotary encoders, are difficult to adapt to robots that lack discrete mechanical joints. The rigid nature of these sensors runs contrary to the aspirational benefits of soft systems. As truly soft sensor solutions are still in their infancy, motion control of soft robots has so far relied on laboratory-based sensing systems such as motion capture, electromagnetic (EM) tracking, or Fiber Bragg Gratings. In this article, we used embedded flexible sensors known as Smart Braids to sense the contraction of McKibben muscles through changes in inductance. We evaluated closed-loop control on two systems: a revolute joint and a planar, one degree of freedom continuum manipulator. In the revolute joint, our proposed controller compensated for elasticity in the actuator connections. The Smart Braid feedback allowed motion control with a steady-state root-mean-square (RMS) error of [1.5]°. In the continuum manipulator, Smart Braid feedback enabled tracking of the desired tip angle with a steady-state RMS error of [1.25]°. This work demonstrates that Smart Braid sensors can provide accurate position feedback in closed-loop motion control suitable for field applications of soft robotic systems.

Computational Intelligence Based Data Fusion Algorithm for Dynamic sEMG and Skeletal Muscle Force Modelling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chandrasekhar Potluri,; Madhavi Anugolu; Marco P. Schoen

2013-08-01

In this work, an array of three surface Electrography (sEMG) sensors are used to acquired muscle extension and contraction signals for 18 healthy test subjects. The skeletal muscle force is estimated using the acquired sEMG signals and a Non-linear Wiener Hammerstein model, relating the two signals in a dynamic fashion. The model is obtained from using System Identification (SI) algorithm. The obtained force models for each sensor are fused using a proposed fuzzy logic concept with the intent to improve the force estimation accuracy and resilience to sensor failure or misalignment. For the fuzzy logic inference system, the sEMG entropy,more » the relative error, and the correlation of the force signals are considered for defining the membership functions. The proposed fusion algorithm yields an average of 92.49% correlation between the actual force and the overall estimated force output. In addition, the proposed fusionbased approach is implemented on a test platform. Experiments indicate an improvement in finger/hand force estimation.« less

Attitude Control System Design for the Solar Dynamics Observatory

NASA Technical Reports Server (NTRS)

Starin, Scott R.; Bourkland, Kristin L.; Kuo-Chia, Liu; Mason, Paul A. C.; Vess, Melissa F.; Andrews, Stephen F.; Morgenstern, Wendy M.

2005-01-01

The Solar Dynamics Observatory mission, part of the Living With a Star program, will place a geosynchronous satellite in orbit to observe the Sun and relay data to a dedicated ground station at all times. SDO remains Sun- pointing throughout most of its mission for the instruments to take measurements of the Sun. The SDO attitude control system is a single-fault tolerant design. Its fully redundant attitude sensor complement includes 16 coarse Sun sensors, a digital Sun sensor, 3 two-axis inertial reference units, 2 star trackers, and 4 guide telescopes. Attitude actuation is performed using 4 reaction wheels and 8 thrusters, and a single main engine nominally provides velocity-change thrust. The attitude control software has five nominal control modes-3 wheel-based modes and 2 thruster-based modes. A wheel-based Safehold running in the attitude control electronics box improves the robustness of the system as a whole. All six modes are designed on the same basic proportional-integral-derivative attitude error structure, with more robust modes setting their integral gains to zero. The paper details the mode designs and their uses.

An Improved Measurement Method for the Strength of Radiation of Reflective Beam in an Industrial Optical Sensor Based on Laser Displacement Meter.

PubMed

Bae, Youngchul

2016-05-23

An optical sensor such as a laser range finder (LRF) or laser displacement meter (LDM) uses reflected and returned laser beam from a target. The optical sensor has been mainly used to measure the distance between a launch position and the target. However, optical sensor based LRF and LDM have numerous and various errors such as statistical errors, drift errors, cyclic errors, alignment errors and slope errors. Among these errors, an alignment error that contains measurement error for the strength of radiation of returned laser beam from the target is the most serious error in industrial optical sensors. It is caused by the dependence of the measurement offset upon the strength of radiation of returned beam incident upon the focusing lens from the target. In this paper, in order to solve these problems, we propose a novel method for the measurement of the output of direct current (DC) voltage that is proportional to the strength of radiation of returned laser beam in the received avalanche photo diode (APD) circuit. We implemented a measuring circuit that is able to provide an exact measurement of reflected laser beam. By using the proposed method, we can measure the intensity or strength of radiation of laser beam in real time and with a high degree of precision.

An Improved Measurement Method for the Strength of Radiation of Reflective Beam in an Industrial Optical Sensor Based on Laser Displacement Meter

PubMed Central

Bae, Youngchul

2016-01-01

An optical sensor such as a laser range finder (LRF) or laser displacement meter (LDM) uses reflected and returned laser beam from a target. The optical sensor has been mainly used to measure the distance between a launch position and the target. However, optical sensor based LRF and LDM have numerous and various errors such as statistical errors, drift errors, cyclic errors, alignment errors and slope errors. Among these errors, an alignment error that contains measurement error for the strength of radiation of returned laser beam from the target is the most serious error in industrial optical sensors. It is caused by the dependence of the measurement offset upon the strength of radiation of returned beam incident upon the focusing lens from the target. In this paper, in order to solve these problems, we propose a novel method for the measurement of the output of direct current (DC) voltage that is proportional to the strength of radiation of returned laser beam in the received avalanche photo diode (APD) circuit. We implemented a measuring circuit that is able to provide an exact measurement of reflected laser beam. By using the proposed method, we can measure the intensity or strength of radiation of laser beam in real time and with a high degree of precision. PMID:27223291

A novel vibration structure for dynamic balancing measurement

NASA Astrophysics Data System (ADS)

Qin, Peng; Cai, Ping; Hu, Qinghan; Li, Yingxia

2006-11-01

Based on the conception of instantaneous motion center in theoretical mechanics, the paper presents a novel virtual vibration structure for dynamic balancing measurement with high precision. The structural features and the unbalancing response characteristics of this vibration structure are analyzed in depth. The relation between the real measuring system and the virtual one is emphatically expounded. Theoretical analysis indicates that the flexibly hinged integrative plate spring sets holds fixed vibration center, with the result that this vibration system has the most excellent effect of plane separation. In addition, the sensors are mounted on the same longitudinal section. Thus the influence of phase error on the primary unbalance reduction ratio is eliminated. Furthermore, the performance changes in sensors caused by environmental factor have less influence on the accuracy of the measurement. The result for this system is more accurate measurement with lower requirement for a second correction run.

An extrinsic fiber Fabry-Perot interferometer for dynamic displacement measurement

NASA Astrophysics Data System (ADS)

Pullteap, S.; Seat, H. C.

2015-03-01

A versatile fiber interferometer was proposed for high precision measurement. The sensor exploited a double-cavity within the unique sensing arm of an extrinsic-type fiber Fabry-Perot interferometer to produce the quadrature phase-shifted interference fringes. Interference signal processing was carried out using a modified zero-crossing (fringe) counting technique to demodulate two sets of fringes. The fiber interferometer has been successfully employed for dynamic displacement measurement under different displacement profiles over a range of 0.7 μm to 140 μm. A dedicated computer incorporating the demodulation algorithm was next used to interpret these detected data as well as plot the displacement information with a resolution of λ/64. A commercial displacement sensor was employed for comparison purposes with the experimental data obtained from the fiber interferometer as well as to gauge its performance, resulting in the maximum error of 2.8% over the entire displacement range studied.

Adaptive Sparse Representation for Source Localization with Gain/Phase Errors

PubMed Central

Sun, Ke; Liu, Yimin; Meng, Huadong; Wang, Xiqin

2011-01-01

Sparse representation (SR) algorithms can be implemented for high-resolution direction of arrival (DOA) estimation. Additionally, SR can effectively separate the coherent signal sources because the spectrum estimation is based on the optimization technique, such as the L1 norm minimization, but not on subspace orthogonality. However, in the actual source localization scenario, an unknown gain/phase error between the array sensors is inevitable. Due to this nonideal factor, the predefined overcomplete basis mismatches the actual array manifold so that the estimation performance is degraded in SR. In this paper, an adaptive SR algorithm is proposed to improve the robustness with respect to the gain/phase error, where the overcomplete basis is dynamically adjusted using multiple snapshots and the sparse solution is adaptively acquired to match with the actual scenario. The simulation results demonstrate the estimation robustness to the gain/phase error using the proposed method. PMID:22163875

Horizon sensors attitude errors simulation for the Brazilian Remote Sensing Satellite

NASA Astrophysics Data System (ADS)

Vicente de Brum, Antonio Gil; Ricci, Mario Cesar

Remote sensing, meteorological and other types of satellites require an increasingly better Earth related positioning. From the past experience it is well known that the thermal horizon in the 15 micrometer band provides conditions of determining the local vertical at any time. This detection is done by horizon sensors which are accurate instruments for Earth referred attitude sensing and control whose performance is limited by systematic and random errors amounting about 0.5 deg. Using the computer programs OBLATE, SEASON, ELECTRO and MISALIGN, developed at INPE to simulate four distinct facets of conical scanning horizon sensors, attitude errors are obtained for the Brazilian Remote Sensing Satellite (the first one, SSR-1, is scheduled to fly in 1996). These errors are due to the oblate shape of the Earth, seasonal and latitudinal variations of the 15 micrometer infrared radiation, electronic processing time delay and misalignment of sensor axis. The sensor related attitude errors are thus properly quantified in this work and will, together with other systematic errors (for instance, ambient temperature variation) take part in the pre-launch analysis of the Brazilian Remote Sensing Satellite, with respect to the horizon sensor performance.

Quantification of LiDAR measurement uncertainty through propagation of errors due to sensor sub-systems and terrain morphology

NASA Astrophysics Data System (ADS)

Goulden, T.; Hopkinson, C.

2013-12-01

The quantification of LiDAR sensor measurement uncertainty is important for evaluating the quality of derived DEM products, compiling risk assessment of management decisions based from LiDAR information, and enhancing LiDAR mission planning capabilities. Current quality assurance estimates of LiDAR measurement uncertainty are limited to post-survey empirical assessments or vendor estimates from commercial literature. Empirical evidence can provide valuable information for the performance of the sensor in validated areas; however, it cannot characterize the spatial distribution of measurement uncertainty throughout the extensive coverage of typical LiDAR surveys. Vendor advertised error estimates are often restricted to strict and optimal survey conditions, resulting in idealized values. Numerical modeling of individual pulse uncertainty provides an alternative method for estimating LiDAR measurement uncertainty. LiDAR measurement uncertainty is theoretically assumed to fall into three distinct categories, 1) sensor sub-system errors, 2) terrain influences, and 3) vegetative influences. This research details the procedures for numerical modeling of measurement uncertainty from the sensor sub-system (GPS, IMU, laser scanner, laser ranger) and terrain influences. Results show that errors tend to increase as the laser scan angle, altitude or laser beam incidence angle increase. An experimental survey over a flat and paved runway site, performed with an Optech ALTM 3100 sensor, showed an increase in modeled vertical errors of 5 cm, at a nadir scan orientation, to 8 cm at scan edges; for an aircraft altitude of 1200 m and half scan angle of 15°. In a survey with the same sensor, at a highly sloped glacial basin site absent of vegetation, modeled vertical errors reached over 2 m. Validation of error models within the glacial environment, over three separate flight lines, respectively showed 100%, 85%, and 75% of elevation residuals fell below error predictions. Future work in LiDAR sensor measurement uncertainty must focus on the development of vegetative error models to create more robust error prediction algorithms. To achieve this objective, comprehensive empirical exploratory analysis is recommended to relate vegetative parameters to observed errors.

Determining Methane Leak Locations and Rates with a Wireless Network Composed of Low-Cost, Printed Sensors

NASA Astrophysics Data System (ADS)

Smith, C. J.; Kim, B.; Zhang, Y.; Ng, T. N.; Beck, V.; Ganguli, A.; Saha, B.; Daniel, G.; Lee, J.; Whiting, G.; Meyyappan, M.; Schwartz, D. E.

2015-12-01

We will present our progress on the development of a wireless sensor network that will determine the source and rate of detected methane leaks. The targeted leak detection threshold is 2 g/min with a rate estimation error of 20% and localization error of 1 m within an outdoor area of 100 m2. The network itself is composed of low-cost, high-performance sensor nodes based on printed nanomaterials with expected sensitivity below 1 ppmv methane. High sensitivity to methane is achieved by modifying high surface-area-to-volume-ratio single-walled carbon nanotubes (SWNTs) with materials that adsorb methane molecules. Because the modified SWNTs are not perfectly selective to methane, the sensor nodes contain arrays of variously-modified SWNTs to build diversity of response towards gases with adsorption affinity. Methane selectivity is achieved through advanced pattern-matching algorithms of the array's ensemble response. The system is low power and designed to operate for a year on a single small battery. The SWNT sensing elements consume only microwatts. The largest power consumer is the wireless communication, which provides robust, real-time measurement data. Methane leak localization and rate estimation will be performed by machine-learning algorithms built with the aid of computational fluid dynamics simulations of gas plume formation. This sensor system can be broadly applied at gas wells, distribution systems, refineries, and other downstream facilities. It also can be utilized for industrial and residential safety applications, and adapted to other gases and gas combinations.

Passive Microwave Precipitation Retrieval Uncertainty Characterized based on Field Campaign Data over Complex Terrain

NASA Astrophysics Data System (ADS)

Derin, Y.; Anagnostou, E. N.; Anagnostou, M.; Kalogiros, J. A.; Casella, D.; Marra, A. C.; Panegrossi, G.; Sanò, P.

2017-12-01

Difficulties in representation of high rainfall variability over mountainous areas using ground based sensors make satellite remote sensing techniques attractive for hydrologic studies over these regions. Even though satellite-based rainfall measurements are quasi global and available at high spatial resolution, these products have uncertainties that necessitate use of error characterization and correction procedures based upon more accurate in situ rainfall measurements. Such measurements can be obtained from field campaigns facilitated by research quality sensors such as locally deployed weather radar and in situ weather stations. This study uses such high quality and resolution rainfall estimates derived from dual-polarization X-band radar (XPOL) observations from three field experiments in Mid-Atlantic US East Coast (NASA IPHEX experiment), the Olympic Peninsula of Washington State (NASA OLYMPEX experiment), and the Mediterranean to characterize the error characteristics of multiple passive microwave (PMW) sensor retrievals. The study first conducts an independent error analysis of the XPOL radar reference rainfall fields against in situ rain gauges and disdrometer observations available by the field experiments. Then the study evaluates different PMW precipitation products using the XPOL datasets (GR) over the three aforementioned complex terrain study areas. We extracted matchups of PMW/GR rainfall based on a matching methodology that identifies GR volume scans coincident with PMW field-of-view sampling volumes, and scaled GR parameters to the satellite products' nominal spatial resolution. The following PMW precipitation retrieval algorithms are evaluated: the NASA Goddard PROFiling algorithm (GPROF), standard and climatology-based products (V 3, 4 and 5) from four PMW sensors (SSMIS, MHS, GMI, and AMSR2), and the precipitation products based on the algorithms Cloud Dynamics and Radiation Database (CDRD) for SSMIS and Passive microwave Neural network Precipitation Retrieval (PNPR) for AMSU/MHS, developed at ISAC-CNR within the EUMETSAT H-SAF. We will present error analysis results for the different PMW rainfall retrievals and discuss dependences on precipitation type, elevation and precipitation microphysics (derived from XPOL).

Automotive Radar and Lidar Systems for Next Generation Driver Assistance Functions

NASA Astrophysics Data System (ADS)

Rasshofer, R. H.; Gresser, K.

2005-05-01

Automotive radar and lidar sensors represent key components for next generation driver assistance functions (Jones, 2001). Today, their use is limited to comfort applications in premium segment vehicles although an evolution process towards more safety-oriented functions is taking place. Radar sensors available on the market today suffer from low angular resolution and poor target detection in medium ranges (30 to 60m) over azimuth angles larger than ±30°. In contrast, Lidar sensors show large sensitivity towards environmental influences (e.g. snow, fog, dirt). Both sensor technologies today have a rather high cost level, forbidding their wide-spread usage on mass markets. A common approach to overcome individual sensor drawbacks is the employment of data fusion techniques (Bar-Shalom, 2001). Raw data fusion requires a common, standardized data interface to easily integrate a variety of asynchronous sensor data into a fusion network. Moreover, next generation sensors should be able to dynamically adopt to new situations and should have the ability to work in cooperative sensor environments. As vehicular function development today is being shifted more and more towards virtual prototyping, mathematical sensor models should be available. These models should take into account the sensor's functional principle as well as all typical measurement errors generated by the sensor.

Estimation of Center of Mass Trajectory using Wearable Sensors during Golf Swing

PubMed Central

Najafi, Bijan; Lee-Eng, Jacqueline; Wrobel, James S.; Goebel, Ruben

2015-01-01

This study suggests a wearable sensor technology to estimate center of mass (CoM) trajectory during a golf swing. Groups of 3, 4, and 18 participants were recruited, respectively, for the purpose of three validation studies. Study 1 examined the accuracy of the system to estimate a 3D body segment angle compared to a camera-based motion analyzer (Vicon®). Study 2 assessed the accuracy of three simplified CoM trajectory models. Finally, Study 3 assessed the accuracy of the proposed CoM model during multiple golf swings. A relatively high agreement was observed between wearable sensors and the reference (Vicon®) for angle measurement (r > 0.99, random error <1.2° (1.5%) for anterior-posterior; <0.9° (2%) for medial-lateral; and <3.6° (2.5%) for internal-external direction). The two-link model yielded a better agreement with the reference system compared to one-link model (r > 0.93 v. r = 0.52, respectively). On the same note, the proposed two-link model estimated CoM trajectory during golf swing with relatively good accuracy (r > 0.9, A-P random error <1cm (7.7%) and <2cm (10.4%) for M-L). The proposed system appears to accurately quantify the kinematics of CoM trajectory as a surrogate of dynamic postural control during an athlete’s movement and its portability, makes it feasible to fit the competitive environment without restricting surface type. Key points This study demonstrates that wearable technology based on inertial sensors are accurate to estimate center of mass trajectory in complex athletic task (e.g., golf swing) This study suggests that two-link model of human body provides optimum tradeoff between accuracy and minimum number of sensor module for estimation of center of mass trajectory in particular during fast movements. Wearable technologies based on inertial sensors are viable option for assessing dynamic postural control in complex task outside of gait laboratory and constraints of cameras, surface, and base of support. PMID:25983585

Dynamic Steering for Improved Sensor Autonomy and Catalogue Maintenance

NASA Astrophysics Data System (ADS)

Hobson, T.; Gordon, N.; Clarkson, I.; Rutten, M.; Bessell, T.

A number of international agencies endeavour to maintain catalogues of the man-made resident space objects (RSOs) currently orbiting the Earth. Such catalogues are primarily created to anticipate and avoid destructive collisions involving important space assets such as manned missions and active satellites. An agencys ability to achieve this objective is dependent on the accuracy, reliability and timeliness of the information used to update its catalogue. A primary means for gathering this information is by regularly making direct observations of the tens-of-thousands of currently detectable RSOs via networks of space surveillance sensors. But operational constraints sometimes prevent accurate and timely reacquisition of all known RSOs, which can cause them to become lost to the tracking system. Furthermore, when comprehensive acquisition of new objects does not occur, these objects, in addition to the lost RSOs, result in uncorrelated detections when next observed. Due to the rising number of space-missions and the introduction of newer, more capable space-sensors, the number of uncorrelated targets is at an all-time high. The process of differentiating uncorrelated detections caused by once-acquired now-lost RSOs from newly detected RSOs is a difficult and often labour intensive task. Current methods for overcoming this challenge focus on advancements in orbit propagation and object characterisation to improve prediction accuracy and target identification. In this paper, we describe a complementary approach that incorporates increased awareness of error and failed observations into the RSO tracking solution. Our methodology employs a technique called dynamic steering to improve the autonomy and capability of a space surveillance networks steerable sensors. By co-situating each sensor with a low-cost high-performance computer, the steerable sensor can quickly and intelligently decide how to steer itself. The sensor-system uses a dedicated parallel-processing architecture to enable it to compute a high-fidelity estimate of the targets prior state error distribution in real-time. Negative information, such as when an RSO is targeted for observation but it is not observed, is incorporated to improve the likelihood of reacquiring the target when attempting to observe the target in future. The sensor is consequently capable of improving its utility by planning each observation using a sensor steering solution that is informed by all prior attempts at observing the target. We describe the practical implementation of a single experimental sensor and offer the results of recent field trials. These trials involved reacquisition and constrained Initial Orbit Determination of RSOs, a number of months after prior observation and initial detection. Using the proposed approach, the system is capable of using targeting information that would be unusable by existing space surveillance networks. The system consequently offers a means of enhancing space surveillance for SSA via increased system capacity, a higher degree of autonomy and the ability to reacquire objects whose dynamics are insufficiently modelled to cue a conventional space surveillance system for observation and tracking.

Fiber Optic Distributed Sensors for High-resolution Temperature Field Mapping.

PubMed

Lomperski, Stephen; Gerardi, Craig; Lisowski, Darius

2016-11-07

The reliability of computational fluid dynamics (CFD) codes is checked by comparing simulations with experimental data. A typical data set consists chiefly of velocity and temperature readings, both ideally having high spatial and temporal resolution to facilitate rigorous code validation. While high resolution velocity data is readily obtained through optical measurement techniques such as particle image velocimetry, it has proven difficult to obtain temperature data with similar resolution. Traditional sensors such as thermocouples cannot fill this role, but the recent development of distributed sensing based on Rayleigh scattering and swept-wave interferometry offers resolution suitable for CFD code validation work. Thousands of temperature measurements can be generated along a single thin optical fiber at hundreds of Hertz. Sensors function over large temperature ranges and within opaque fluids where optical techniques are unsuitable. But this type of sensor is sensitive to strain and humidity as well as temperature and so accuracy is affected by handling, vibration, and shifts in relative humidity. Such behavior is quite unlike traditional sensors and so unconventional installation and operating procedures are necessary to ensure accurate measurements. This paper demonstrates implementation of a Rayleigh scattering-type distributed temperature sensor in a thermal mixing experiment involving two air jets at 25 and 45 °C. We present criteria to guide selection of optical fiber for the sensor and describe installation setup for a jet mixing experiment. We illustrate sensor baselining, which links readings to an absolute temperature standard, and discuss practical issues such as errors due to flow-induced vibration. This material can aid those interested in temperature measurements having high data density and bandwidth for fluid dynamics experiments and similar applications. We highlight pitfalls specific to these sensors for consideration in experiment design and operation.

Novel sensor for color control in solid state lighting applications

NASA Astrophysics Data System (ADS)

Gourevitch, Alex; Thurston, Thomas; Singh, Rajiv; Banachowicz, Bartosz; Korobov, Vladimir; Drowley, Cliff

2010-02-01

LED wavelength and luminosity shifts due to temperature, dimming, aging, and binning uncertainty can cause large color errors in open-loop light-mixing illuminators. Multispectral color light sensors combined with feedback circuits can compensate for these LED shifts. Typical color light sensor design variables include the choice of light-sensing material, filter configuration, and read-out circuitry. Cypress Semiconductor has designed and prototyped a color sensor chip that consists of photodiode arrays connected to a I/F (Current to Frequency) converter. This architecture has been chosen to achieve high dynamic range (~100dB) and provide flexibility for tailoring sensor response. Several different optical filter configurations were evaluated in this prototype. The color-sensor chip was incorporated into an RGB light color mixing system with closed-loop optical feedback. Color mixing accuracy was determined by calculating the difference between (u',v') set point values and CIE coordinates measured with a reference colorimeter. A typical color precision ▵u'v' less than 0.0055 has been demonstrated over a wide range of colors, a temperature range of 50C, and light dimming up to 80%.

Blade tip clearance measurement of the turbine engines based on a multi-mode fiber coupled laser ranging system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Guo, Haotian; Duan, Fajie; Wu, Guoxiu

2014-11-15

The blade tip clearance is a parameter of great importance to guarantee the efficiency and safety of the turbine engines. In this article, a laser ranging system designed for blade tip clearance measurement is presented. Multi-mode fiber is utilized for optical transmission to guarantee that enough optical power is received by the sensor probe. The model of the tiny sensor probe is presented. The error brought by the optical path difference of different modes of the fiber is estimated and the length of the fiber is limited to reduce this error. The measurement range in which the optical power receivedmore » by the probe remains essentially unchanged is analyzed. Calibration experiments and dynamic experiments are conducted. The results of the calibration experiments indicate that the resolution of the system is about 0.02 mm and the range of the system is about 9 mm.« less

Estimating plant area index for monitoring crop growth dynamics using Landsat-8 and RapidEye images

NASA Astrophysics Data System (ADS)

Shang, Jiali; Liu, Jiangui; Huffman, Ted; Qian, Budong; Pattey, Elizabeth; Wang, Jinfei; Zhao, Ting; Geng, Xiaoyuan; Kroetsch, David; Dong, Taifeng; Lantz, Nicholas

2014-01-01

This study investigates the use of two different optical sensors, the multispectral imager (MSI) onboard the RapidEye satellites and the operational land imager (OLI) onboard the Landsat-8 for mapping within-field variability of crop growth conditions and tracking the seasonal growth dynamics. The study was carried out in southern Ontario, Canada, during the 2013 growing season for three annual crops, corn, soybeans, and winter wheat. Plant area index (PAI) was measured at different growth stages using digital hemispherical photography at two corn fields, two winter wheat fields, and two soybean fields. Comparison between several conventional vegetation indices derived from concurrently acquired image data by the two sensors showed a good agreement. The two-band enhanced vegetation index (EVI2) and the normalized difference vegetation index (NDVI) were derived from the surface reflectance of the two sensors. The study showed that EVI2 was more resistant to saturation at high biomass range than NDVI. A linear relationship could be used for crop green effective PAI estimation from EVI2, with a coefficient of determination (R2) of 0.85 and root-mean-square error of 0.53. The estimated multitemporal product of green PAI was found to be able to capture the seasonal dynamics of the three crops.

An error-based micro-sensor capture system for real-time motion estimation

NASA Astrophysics Data System (ADS)

Yang, Lin; Ye, Shiwei; Wang, Zhibo; Huang, Zhipei; Wu, Jiankang; Kong, Yongmei; Zhang, Li

2017-10-01

A wearable micro-sensor motion capture system with 16 IMUs and an error-compensatory complementary filter algorithm for real-time motion estimation has been developed to acquire accurate 3D orientation and displacement in real life activities. In the proposed filter algorithm, the gyroscope bias error, orientation error and magnetic disturbance error are estimated and compensated, significantly reducing the orientation estimation error due to sensor noise and drift. Displacement estimation, especially for activities such as jumping, has been the challenge in micro-sensor motion capture. An adaptive gait phase detection algorithm has been developed to accommodate accurate displacement estimation in different types of activities. The performance of this system is benchmarked with respect to the results of VICON optical capture system. The experimental results have demonstrated effectiveness of the system in daily activities tracking, with estimation error 0.16 ± 0.06 m for normal walking and 0.13 ± 0.11 m for jumping motions. Research supported by the National Natural Science Foundation of China (Nos. 61431017, 81272166).

Inertial and time-of-arrival ranging sensor fusion.

PubMed

Vasilyev, Paul; Pearson, Sean; El-Gohary, Mahmoud; Aboy, Mateo; McNames, James

2017-05-01

Wearable devices with embedded kinematic sensors including triaxial accelerometers, gyroscopes, and magnetometers are becoming widely used in applications for tracking human movement in domains that include sports, motion gaming, medicine, and wellness. The kinematic sensors can be used to estimate orientation, but can only estimate changes in position over short periods of time. We developed a prototype sensor that includes ultra wideband ranging sensors and kinematic sensors to determine the feasibility of fusing the two sensor technologies to estimate both orientation and position. We used a state space model and applied the unscented Kalman filter to fuse the sensor information. Our results demonstrate that it is possible to estimate orientation and position with less error than is possible with either sensor technology alone. In our experiment we obtained a position root mean square error of 5.2cm and orientation error of 4.8° over a 15min recording. Copyright © 2017 Elsevier B.V. All rights reserved.

Study of an instrument for sensing errors in a telescope wavefront

NASA Technical Reports Server (NTRS)

Golden, L. J.; Shack, R. V.; Slater, D. N.

1973-01-01

Partial results are presented of theoretical and experimental investigations of different focal plane sensor configurations for determining the error in a telescope wavefront. The coarse range sensor and fine range sensors are used in the experimentation. The design of a wavefront error simulator is presented along with the Hartmann test, the shearing polarization interferometer, the Zernike test, and the Zernike polarization test.

An analysis of the Kalman filter in the Gamma Ray Observatory (GRO) onboard attitude determination subsystem

NASA Technical Reports Server (NTRS)

Snow, Frank; Harman, Richard; Garrick, Joseph

1988-01-01

The Gamma Ray Observatory (GRO) spacecraft needs a highly accurate attitude knowledge to achieve its mission objectives. Utilizing the fixed-head star trackers (FHSTs) for observations and gyroscopes for attitude propagation, the discrete Kalman Filter processes the attitude data to obtain an onboard accuracy of 86 arc seconds (3 sigma). A combination of linear analysis and simulations using the GRO Software Simulator (GROSS) are employed to investigate the Kalman filter for stability and the effects of corrupted observations (misalignment, noise), incomplete dynamic modeling, and nonlinear errors on Kalman filter. In the simulations, on-board attitude is compared with true attitude, the sensitivity of attitude error to model errors is graphed, and a statistical analysis is performed on the residuals of the Kalman Filter. In this paper, the modeling and sensor errors that degrade the Kalman filter solution beyond mission requirements are studied, and methods are offered to identify the source of these errors.

Nano-level instrumentation for analyzing the dynamic accuracy of a rolling element bearing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Z.; Hong, J.; Zhang, J.

2013-12-15

The rotational performance of high-precision rolling bearings is fundamental to the overall accuracy of complex mechanical systems. A nano-level instrument to analyze rotational accuracy of high-precision bearings of machine tools under working conditions was developed. In this instrument, a high-precision (error motion < 0.15 μm) and high-stiffness (2600 N axial loading capacity) aerostatic spindle was applied to spin the test bearing. Operating conditions could be simulated effectively because of the large axial loading capacity. An air-cylinder, controlled by a proportional pressure regulator, was applied to drive an air-bearing subjected to non-contact and precise loaded axial forces. The measurement results onmore » axial loading and rotation constraint with five remaining degrees of freedom were completely unconstrained and uninfluenced by the instrument's structure. Dual capacity displacement sensors with 10 nm resolution were applied to measure the error motion of the spindle using a double-probe error separation method. This enabled the separation of the spindle's error motion from the measurement results of the test bearing which were measured using two orthogonal laser displacement sensors with 5 nm resolution. Finally, a Lissajous figure was used to evaluate the non-repetitive run-out (NRRO) of the bearing at different axial forces and speeds. The measurement results at various axial loadings and speeds showed the standard deviations of the measurements’ repeatability and accuracy were less than 1% and 2%. Future studies will analyze the relationship between geometrical errors and NRRO, such as the ball diameter differences of and the geometrical errors in the grooves of rings.« less

Nano-level instrumentation for analyzing the dynamic accuracy of a rolling element bearing.

PubMed

Yang, Z; Hong, J; Zhang, J; Wang, M Y; Zhu, Y

2013-12-01

The rotational performance of high-precision rolling bearings is fundamental to the overall accuracy of complex mechanical systems. A nano-level instrument to analyze rotational accuracy of high-precision bearings of machine tools under working conditions was developed. In this instrument, a high-precision (error motion < 0.15 μm) and high-stiffness (2600 N axial loading capacity) aerostatic spindle was applied to spin the test bearing. Operating conditions could be simulated effectively because of the large axial loading capacity. An air-cylinder, controlled by a proportional pressure regulator, was applied to drive an air-bearing subjected to non-contact and precise loaded axial forces. The measurement results on axial loading and rotation constraint with five remaining degrees of freedom were completely unconstrained and uninfluenced by the instrument's structure. Dual capacity displacement sensors with 10 nm resolution were applied to measure the error motion of the spindle using a double-probe error separation method. This enabled the separation of the spindle's error motion from the measurement results of the test bearing which were measured using two orthogonal laser displacement sensors with 5 nm resolution. Finally, a Lissajous figure was used to evaluate the non-repetitive run-out (NRRO) of the bearing at different axial forces and speeds. The measurement results at various axial loadings and speeds showed the standard deviations of the measurements' repeatability and accuracy were less than 1% and 2%. Future studies will analyze the relationship between geometrical errors and NRRO, such as the ball diameter differences of and the geometrical errors in the grooves of rings.

Testing Accuracy of Long-Range Ultrasonic Sensors for Olive Tree Canopy Measurements

PubMed Central

Gamarra-Diezma, Juan Luis; Miranda-Fuentes, Antonio; Llorens, Jordi; Cuenca, Andrés; Blanco-Roldán, Gregorio L.; Rodríguez-Lizana, Antonio

2015-01-01

Ultrasonic sensors are often used to adjust spray volume by allowing the calculation of the crown volume of tree crops. The special conditions of the olive tree require the use of long-range sensors, which are less accurate and faster than the most commonly used sensors. The main objectives of the study were to determine the suitability of the sensor in terms of sound cone determination, angle errors, crosstalk errors and field measurements. Different laboratory tests were performed to check the suitability of a commercial long-range ultrasonic sensor, as were the experimental determination of the sound cone diameter at several distances for several target materials, the determination of the influence of the angle of incidence of the sound wave on the target and distance on the accuracy of measurements for several materials and the determination of the importance of the errors due to interference between sensors for different sensor spacings and distances for two different materials. Furthermore, sensor accuracy was tested under real field conditions. The results show that the studied sensor is appropriate for olive trees because the sound cone is narrower for an olive tree than for the other studied materials, the olive tree canopy does not have a large influence on the sensor accuracy with respect to distance and angle, the interference errors are insignificant for high sensor spacings and the sensor's field distance measurements were deemed sufficiently accurate. PMID:25635414

Hand-Writing Motion Tracking with Vision-Inertial Sensor Fusion: Calibration and Error Correction

PubMed Central

Zhou, Shengli; Fei, Fei; Zhang, Guanglie; Liu, Yunhui; Li, Wen J.

2014-01-01

The purpose of this study was to improve the accuracy of real-time ego-motion tracking through inertial sensor and vision sensor fusion. Due to low sampling rates supported by web-based vision sensor and accumulation of errors in inertial sensors, ego-motion tracking with vision sensors is commonly afflicted by slow updating rates, while motion tracking with inertial sensor suffers from rapid deterioration in accuracy with time. This paper starts with a discussion of developed algorithms for calibrating two relative rotations of the system using only one reference image. Next, stochastic noises associated with the inertial sensor are identified using Allan Variance analysis, and modeled according to their characteristics. Finally, the proposed models are incorporated into an extended Kalman filter for inertial sensor and vision sensor fusion. Compared with results from conventional sensor fusion models, we have shown that ego-motion tracking can be greatly enhanced using the proposed error correction model. PMID:25157546

Extended FDD-WT method based on correcting the errors due to non-synchronous sensing of sensors

NASA Astrophysics Data System (ADS)

Tarinejad, Reza; Damadipour, Majid

2016-05-01

In this research, a combinational non-parametric method called frequency domain decomposition-wavelet transform (FDD-WT) that was recently presented by the authors, is extended for correction of the errors resulting from asynchronous sensing of sensors, in order to extend the application of the algorithm for different kinds of structures, especially for huge structures. Therefore, the analysis process is based on time-frequency domain decomposition and is performed with emphasis on correcting time delays between sensors. Time delay estimation (TDE) methods are investigated for their efficiency and accuracy for noisy environmental records and the Phase Transform - β (PHAT-β) technique was selected as an appropriate method to modify the operation of traditional FDD-WT in order to achieve the exact results. In this paper, a theoretical example (3DOF system) has been provided in order to indicate the non-synchronous sensing effects of the sensors on the modal parameters; moreover, the Pacoima dam subjected to 13 Jan 2001 earthquake excitation was selected as a case study. The modal parameters of the dam obtained from the extended FDD-WT method were compared with the output of the classical signal processing method, which is referred to as 4-Spectral method, as well as other literatures relating to the dynamic characteristics of Pacoima dam. The results comparison indicates that values are correct and reliable.

A Missile-Borne Angular Velocity Sensor Based on Triaxial Electromagnetic Induction Coils

PubMed Central

Li, Jian; Wu, Dan; Han, Yan

2016-01-01

Aiming to solve the problem of the limited measuring range for angular motion parameters of high-speed rotating projectiles in the field of guidance and control, a self-adaptive measurement method for angular motion parameters based on the electromagnetic induction principle is proposed. First, a framework with type bent “I-shape” is used to design triaxial coils in a mutually orthogonal way. Under the condition of high rotational speed of a projectile, the induction signal of the projectile moving across a geomagnetic field is acquired by using coils. Second, the frequency of the pulse signal is adjusted self-adaptively. Angular velocity and angular displacement are calculated in the form of periodic pulse counting and pulse accumulation, respectively. Finally, on the basis of that principle prototype of the sensor is researched and developed, performance of measuring angular motion parameters are tested on the sensor by semi-physical and physical simulation experiments, respectively. Experimental results demonstrate that the sensor has a wide measuring range of angular velocity from 1 rps to 100 rps with a measurement error of less than 0.3%, and the angular displacement measurement error is lower than 0.2°. The proposed method satisfies measurement requirements for high-speed rotating projectiles with an extremely high dynamic range of rotational speed and high precision, and has definite value to engineering applications in the fields of attitude determination and geomagnetic navigation. PMID:27706039

A Missile-Borne Angular Velocity Sensor Based on Triaxial Electromagnetic Induction Coils.

PubMed

Li, Jian; Wu, Dan; Han, Yan

2016-09-30

Aiming to solve the problem of the limited measuring range for angular motion parameters of high-speed rotating projectiles in the field of guidance and control, a self-adaptive measurement method for angular motion parameters based on the electromagnetic induction principle is proposed. First, a framework with type bent "I-shape" is used to design triaxial coils in a mutually orthogonal way. Under the condition of high rotational speed of a projectile, the induction signal of the projectile moving across a geomagnetic field is acquired by using coils. Second, the frequency of the pulse signal is adjusted self-adaptively. Angular velocity and angular displacement are calculated in the form of periodic pulse counting and pulse accumulation, respectively. Finally, on the basis of that principle prototype of the sensor is researched and developed, performance of measuring angular motion parameters are tested on the sensor by semi-physical and physical simulation experiments, respectively. Experimental results demonstrate that the sensor has a wide measuring range of angular velocity from 1 rps to 100 rps with a measurement error of less than 0.3%, and the angular displacement measurement error is lower than 0.2°. The proposed method satisfies measurement requirements for high-speed rotating projectiles with an extremely high dynamic range of rotational speed and high precision, and has definite value to engineering applications in the fields of attitude determination and geomagnetic navigation.

Robust double gain unscented Kalman filter for small satellite attitude estimation

NASA Astrophysics Data System (ADS)

Cao, Lu; Yang, Weiwei; Li, Hengnian; Zhang, Zhidong; Shi, Jianjun

2017-08-01

Limited by the low precision of small satellite sensors, the estimation theories with high performance remains the most popular research topic for the attitude estimation. The Kalman filter (KF) and its extensions have been widely applied in the satellite attitude estimation and achieved plenty of achievements. However, most of the existing methods just take use of the current time-step's priori measurement residuals to complete the measurement update and state estimation, which always ignores the extraction and utilization of the previous time-step's posteriori measurement residuals. In addition, the uncertainty model errors always exist in the attitude dynamic system, which also put forward the higher performance requirements for the classical KF in attitude estimation problem. Therefore, the novel robust double gain unscented Kalman filter (RDG-UKF) is presented in this paper to satisfy the above requirements for the small satellite attitude estimation with the low precision sensors. It is assumed that the system state estimation errors can be exhibited in the measurement residual; therefore, the new method is to derive the second Kalman gain Kk2 for making full use of the previous time-step's measurement residual to improve the utilization efficiency of the measurement data. Moreover, the sequence orthogonal principle and unscented transform (UT) strategy are introduced to robust and enhance the performance of the novel Kalman Filter in order to reduce the influence of existing uncertainty model errors. Numerical simulations show that the proposed RDG-UKF is more effective and robustness in dealing with the model errors and low precision sensors for the attitude estimation of small satellite by comparing with the classical unscented Kalman Filter (UKF).

Dynamic Control of Adsorption Sensitivity for Photo-EMF-Based Ammonia Gas Sensors Using a Wireless Network

PubMed Central

Vashpanov, Yuriy; Choo, Hyunseung; Kim, Dongsoo Stephen

2011-01-01

This paper proposes an adsorption sensitivity control method that uses a wireless network and illumination light intensity in a photo-electromagnetic field (EMF)-based gas sensor for measurements in real time of a wide range of ammonia concentrations. The minimum measurement error for a range of ammonia concentration from 3 to 800 ppm occurs when the gas concentration magnitude corresponds with the optimal intensity of the illumination light. A simulation with LabView-engineered modules for automatic control of a new intelligent computer system was conducted to improve measurement precision over a wide range of gas concentrations. This gas sensor computer system with wireless network technology could be useful in the chemical industry for automatic detection and measurement of hazardous ammonia gas levels in real time. PMID:22346680

Bayesian integration of sensor information and a multivariate dynamic linear model for prediction of dairy cow mastitis.

PubMed

Jensen, Dan B; Hogeveen, Henk; De Vries, Albert

2016-09-01

Rapid detection of dairy cow mastitis is important so corrective action can be taken as soon as possible. Automatically collected sensor data used to monitor the performance and the health state of the cow could be useful for rapid detection of mastitis while reducing the labor needs for monitoring. The state of the art in combining sensor data to predict clinical mastitis still does not perform well enough to be applied in practice. Our objective was to combine a multivariate dynamic linear model (DLM) with a naïve Bayesian classifier (NBC) in a novel method using sensor and nonsensor data to detect clinical cases of mastitis. We also evaluated reductions in the number of sensors for detecting mastitis. With the DLM, we co-modeled 7 sources of sensor data (milk yield, fat, protein, lactose, conductivity, blood, body weight) collected at each milking for individual cows to produce one-step-ahead forecasts for each sensor. The observations were subsequently categorized according to the errors of the forecasted values and the estimated forecast variance. The categorized sensor data were combined with other data pertaining to the cow (week in milk, parity, mastitis history, somatic cell count category, and season) using Bayes' theorem, which produced a combined probability of the cow having clinical mastitis. If this probability was above a set threshold, the cow was classified as mastitis positive. To illustrate the performance of our method, we used sensor data from 1,003,207 milkings from the University of Florida Dairy Unit collected from 2008 to 2014. Of these, 2,907 milkings were associated with recorded cases of clinical mastitis. Using the DLM/NBC method, we reached an area under the receiver operating characteristic curve of 0.89, with a specificity of 0.81 when the sensitivity was set at 0.80. Specificities with omissions of sensor data ranged from 0.58 to 0.81. These results are comparable to other studies, but differences in data quality, definitions of clinical mastitis, and time windows make comparisons across studies difficult. We found the DLM/NBC method to be a flexible method for combining multiple sensor and nonsensor data sources to predict clinical mastitis and accommodate missing observations. Further research is needed before practical implementation is possible. In particular, the performance of our method needs to be improved in the first 2 wk of lactation. The DLM method produces forecasts that are based on continuously estimated multivariate normal distributions, which makes forecasts and forecast errors easy to interpret, and new sensors can easily be added. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

A Novel Error Model of Optical Systems and an On-Orbit Calibration Method for Star Sensors.

PubMed

Wang, Shuang; Geng, Yunhai; Jin, Rongyu

2015-12-12

In order to improve the on-orbit measurement accuracy of star sensors, the effects of image-plane rotary error, image-plane tilt error and distortions of optical systems resulting from the on-orbit thermal environment were studied in this paper. Since these issues will affect the precision of star image point positions, in this paper, a novel measurement error model based on the traditional error model is explored. Due to the orthonormal characteristics of image-plane rotary-tilt errors and the strong nonlinearity among these error parameters, it is difficult to calibrate all the parameters simultaneously. To solve this difficulty, for the new error model, a modified two-step calibration method based on the Extended Kalman Filter (EKF) and Least Square Methods (LSM) is presented. The former one is used to calibrate the main point drift, focal length error and distortions of optical systems while the latter estimates the image-plane rotary-tilt errors. With this calibration method, the precision of star image point position influenced by the above errors is greatly improved from 15.42% to 1.389%. Finally, the simulation results demonstrate that the presented measurement error model for star sensors has higher precision. Moreover, the proposed two-step method can effectively calibrate model error parameters, and the calibration precision of on-orbit star sensors is also improved obviously.

QOS-aware error recovery in wireless body sensor networks using adaptive network coding.

PubMed

Razzaque, Mohammad Abdur; Javadi, Saeideh S; Coulibaly, Yahaya; Hira, Muta Tah

2014-12-29

Wireless body sensor networks (WBSNs) for healthcare and medical applications are real-time and life-critical infrastructures, which require a strict guarantee of quality of service (QoS), in terms of latency, error rate and reliability. Considering the criticality of healthcare and medical applications, WBSNs need to fulfill users/applications and the corresponding network's QoS requirements. For instance, for a real-time application to support on-time data delivery, a WBSN needs to guarantee a constrained delay at the network level. A network coding-based error recovery mechanism is an emerging mechanism that can be used in these systems to support QoS at very low energy, memory and hardware cost. However, in dynamic network environments and user requirements, the original non-adaptive version of network coding fails to support some of the network and user QoS requirements. This work explores the QoS requirements of WBSNs in both perspectives of QoS. Based on these requirements, this paper proposes an adaptive network coding-based, QoS-aware error recovery mechanism for WBSNs. It utilizes network-level and user-/application-level information to make it adaptive in both contexts. Thus, it provides improved QoS support adaptively in terms of reliability, energy efficiency and delay. Simulation results show the potential of the proposed mechanism in terms of adaptability, reliability, real-time data delivery and network lifetime compared to its counterparts.

Execution monitoring for a mobile robot system

NASA Technical Reports Server (NTRS)

Miller, David P.

1990-01-01

Due to sensor errors, uncertainty, incomplete knowledge, and a dynamic world, robot plans will not always be executed exactly as planned. This paper describes an implemented robot planning system that enhances the traditional sense-think-act cycle in ways that allow the robot system monitor its behavior and react in emergencies in real-time. A proposal on how robot systems can completely break away from the traditional three-step cycle is also made.

The Development and Test of a Sensor for Measurement of the Working Level of Gas-Liquid Two-Phase Flow in a Coalbed Methane Wellbore Annulus.

PubMed

Wu, Chuan; Ding, Huafeng; Han, Lei

2018-02-14

Coalbed methane (CBM) is one kind of clean-burning gas and has been valued as a new form of energy that will be used widely in the near future. When producing CBM, the working level within a CBM wellbore annulus needs to be monitored to dynamically adjust the gas drainage and extraction processes. However, the existing method of measuring the working level does not meet the needs of accurate adjustment, so we designed a new sensor for this purpose. The principle of our sensor is a liquid pressure formula, i.e., the sensor monitors the two-phase flow patterns and obtains the mean density of the two-phase flow according to the pattern recognition result in the first step, and then combines the pressure data of the working level to calculate the working level using the liquid pressure formula. The sensor was tested in both the lab and on site, and the tests showed that the sensor's error was ±8% and that the sensor could function well in practical conditions and remain stable in the long term.

Pressure sensor based on the fiber-optic extrinsic Fabry-Perot interferometer

NASA Astrophysics Data System (ADS)

Yu, Qingxu; Zhou, Xinlei

2011-03-01

Pressure sensors based on fiber-optic extrinsic Fabry-Perot interferometer (EFPI) have been extensively applied in various industrial and biomedical fields. In this paper, some key improvements of EFPI-based pressure sensors such as the controlled thermal bonding technique, diaphragm-based EFPI sensors, and white light interference technology have been reviewed. Recent progress on signal demodulation method and applications of EFPI-based pressure sensors has been introduced. Signal demodulation algorithms based on the cross correlation and mean square error (MSE) estimation have been proposed for retrieving the cavity length of EFPI. Absolute measurement with a resolution of 0.08 nm over large dynamic range has been carried out. For downhole monitoring, an EFPI and a fiber Bragg grating (FBG) cascade multiplexing fiber-optic sensor system has been developed, which can operate in temperature 300 °C with a good long-term stability and extremely low temperature cross-sensitivity. Diaphragm-based EFPI pressure sensors have been successfully used for low pressure and acoustic wave detection. Experimental results show that a sensitivity of 31 mV/Pa in the frequency range of 100 Hz to 12.7 kHz for aeroacoustic wave detection has been obtained.

Kalman filter-based tracking of moving objects using linear ultrasonic sensor array for road vehicles

NASA Astrophysics Data System (ADS)

Li, Shengbo Eben; Li, Guofa; Yu, Jiaying; Liu, Chang; Cheng, Bo; Wang, Jianqiang; Li, Keqiang

2018-01-01

Detection and tracking of objects in the side-near-field has attracted much attention for the development of advanced driver assistance systems. This paper presents a cost-effective approach to track moving objects around vehicles using linearly arrayed ultrasonic sensors. To understand the detection characteristics of a single sensor, an empirical detection model was developed considering the shapes and surface materials of various detected objects. Eight sensors were arrayed linearly to expand the detection range for further application in traffic environment recognition. Two types of tracking algorithms, including an Extended Kalman filter (EKF) and an Unscented Kalman filter (UKF), for the sensor array were designed for dynamic object tracking. The ultrasonic sensor array was designed to have two types of fire sequences: mutual firing or serial firing. The effectiveness of the designed algorithms were verified in two typical driving scenarios: passing intersections with traffic sign poles or street lights, and overtaking another vehicle. Experimental results showed that both EKF and UKF had more precise tracking position and smaller RMSE (root mean square error) than a traditional triangular positioning method. The effectiveness also encourages the application of cost-effective ultrasonic sensors in the near-field environment perception in autonomous driving systems.

Autoregressive Modeling of Drift and Random Error to Characterize a Continuous Intravascular Glucose Monitoring Sensor.

PubMed

Zhou, Tony; Dickson, Jennifer L; Geoffrey Chase, J

2018-01-01

Continuous glucose monitoring (CGM) devices have been effective in managing diabetes and offer potential benefits for use in the intensive care unit (ICU). Use of CGM devices in the ICU has been limited, primarily due to the higher point accuracy errors over currently used traditional intermittent blood glucose (BG) measures. General models of CGM errors, including drift and random errors, are lacking, but would enable better design of protocols to utilize these devices. This article presents an autoregressive (AR) based modeling method that separately characterizes the drift and random noise of the GlySure CGM sensor (GlySure Limited, Oxfordshire, UK). Clinical sensor data (n = 33) and reference measurements were used to generate 2 AR models to describe sensor drift and noise. These models were used to generate 100 Monte Carlo simulations based on reference blood glucose measurements. These were then compared to the original CGM clinical data using mean absolute relative difference (MARD) and a Trend Compass. The point accuracy MARD was very similar between simulated and clinical data (9.6% vs 9.9%). A Trend Compass was used to assess trend accuracy, and found simulated and clinical sensor profiles were similar (simulated trend index 11.4° vs clinical trend index 10.9°). The model and method accurately represents cohort sensor behavior over patients, providing a general modeling approach to any such sensor by separately characterizing each type of error that can arise in the data. Overall, it enables better protocol design based on accurate expected CGM sensor behavior, as well as enabling the analysis of what level of each type of sensor error would be necessary to obtain desired glycemic control safety and performance with a given protocol.

Extension to the dynamic modeling of the large angle magnetic suspension test fixture. M.S. Thesis - Old Dominion Univ., May 1995 Progress Report, 1 Nov. 1994 - 30 Apr. 1995

NASA Technical Reports Server (NTRS)

Foster, Lucas E.; Britcher, Colin P.

1995-01-01

The Large Angle Magnetic Suspension Test Fixture (LAMSTF) is a laboratory scale proof-of-concept system. The configuration is unique in that the electromagnets are mounted in a circular planar array. A mathematical model of the system had previously been developed, but was shown to have inaccuracies. These inaccuracies showed up in the step responses. Eddy currents were found to be the major cause of the modeling errors. In the original system, eddy currents existed in the aluminum baseplate, iron cores, and the sensor support frame. An attempt to include the eddy current dynamics in the system model is presented. The dynamics of a dummy sensor ring were added to the system. Adding the eddy current dynamics to the simulation improves the way it compares to the actual experiment. Also presented is a new method of determining the yaw angle of the suspended element. From the coil currents the yaw angle can be determined and the controller can be updated to suspend at the new current. This method has been used to demonstrate a 360 degree yaw angle rotation.

Requirements for Coregistration Accuracy in On-Scalp MEG.

PubMed

Zetter, Rasmus; Iivanainen, Joonas; Stenroos, Matti; Parkkonen, Lauri

2018-06-22

Recent advances in magnetic sensing has made on-scalp magnetoencephalography (MEG) possible. In particular, optically-pumped magnetometers (OPMs) have reached sensitivity levels that enable their use in MEG. In contrast to the SQUID sensors used in current MEG systems, OPMs do not require cryogenic cooling and can thus be placed within millimetres from the head, enabling the construction of sensor arrays that conform to the shape of an individual's head. To properly estimate the location of neural sources within the brain, one must accurately know the position and orientation of sensors in relation to the head. With the adaptable on-scalp MEG sensor arrays, this coregistration becomes more challenging than in current SQUID-based MEG systems that use rigid sensor arrays. Here, we used simulations to quantify how accurately one needs to know the position and orientation of sensors in an on-scalp MEG system. The effects that different types of localisation errors have on forward modelling and source estimates obtained by minimum-norm estimation, dipole fitting, and beamforming are detailed. We found that sensor position errors generally have a larger effect than orientation errors and that these errors affect the localisation accuracy of superficial sources the most. To obtain similar or higher accuracy than with current SQUID-based MEG systems, RMS sensor position and orientation errors should be [Formula: see text] and [Formula: see text], respectively.

Staggered scheduling of sensor estimation and fusion for tracking over long-haul links

DOE PAGES

Liu, Qiang; Rao, Nageswara S. V.; Wang, Xin

2016-08-01

Networked sensing can be found in a multitude of real-world applications. Here, we focus on the communication-and computation-constrained long-haul sensor networks, where sensors are remotely deployed over a vast geographical area to perform certain tasks. Of special interest is a class of such networks where sensors take measurements of one or more dynamic targets and send their state estimates to a remote fusion center via long-haul satellite links. The severe loss and delay over such links can easily reduce the amount of sensor data received by the fusion center, thereby limiting the potential information fusion gain and resulting in suboptimalmore » tracking performance. In this paper, starting with the temporal-domain staggered estimation for an individual sensor, we explore the impact of the so-called intra-state prediction and retrodiction on estimation errors. We then investigate the effect of such estimation scheduling across different sensors on the spatial-domain fusion performance, where the sensing time epochs across sensors are scheduled in an asynchronous and staggered manner. In particular, the impact of communication delay and loss as well as sensor bias on such scheduling is explored by means of numerical and simulation studies that demonstrate the validity of our analysis.« less

A Low-Power Wide Dynamic-Range Current Readout Circuit for Ion-Sensitive FET Sensors.

PubMed

Son, Hyunwoo; Cho, Hwasuk; Koo, Jahyun; Ji, Youngwoo; Kim, Byungsub; Park, Hong-June; Sim, Jae-Yoon

2017-06-01

This paper presents an amplifier-less and digital-intensive current-to-digital converter for ion-sensitive FET sensors. Capacitance on the input node is utilized as a residue accumulator, and a clocked comparator is followed for quantization. Without any continuous-time feedback circuit, the converter performs a first-order noise shaping of the quantization error. In order to minimize static power consumption, the proposed circuit employs a single-ended current-steering digital-to-analog converter which flows only the same current as the input. By adopting a switching noise averaging algorithm, our dynamic element matching not only mitigates mismatch of current sources in the current-steering DAC, but also makes the effect of dynamic switching noise become an input-independent constant. The implemented circuit in 0.35 μm CMOS converts the current input with a range of 2.8 μ A to 15 b digital output in about 4 ms, showing a DNL of +0.24/-0.25 LSB and an INL of + 1.98/-1.98 LSB while consuming 16.8 μW.

An Adaptive Scheme for Robot Localization and Mapping with Dynamically Configurable Inter-Beacon Range Measurements

PubMed Central

Torres-González, Arturo; Martinez-de Dios, Jose Ramiro; Ollero, Anibal

2014-01-01

This work is motivated by robot-sensor network cooperation techniques where sensor nodes (beacons) are used as landmarks for range-only (RO) simultaneous localization and mapping (SLAM). This paper presents a RO-SLAM scheme that actuates over the measurement gathering process using mechanisms that dynamically modify the rate and variety of measurements that are integrated in the SLAM filter. It includes a measurement gathering module that can be configured to collect direct robot-beacon and inter-beacon measurements with different inter-beacon depth levels and at different rates. It also includes a supervision module that monitors the SLAM performance and dynamically selects the measurement gathering configuration balancing SLAM accuracy and resource consumption. The proposed scheme has been applied to an extended Kalman filter SLAM with auxiliary particle filters for beacon initialization (PF-EKF SLAM) and validated with experiments performed in the CONET Integrated Testbed. It achieved lower map and robot errors (34% and 14%, respectively) than traditional methods with a lower computational burden (16%) and similar beacon energy consumption. PMID:24776938

An adaptive scheme for robot localization and mapping with dynamically configurable inter-beacon range measurements.

PubMed

Torres-González, Arturo; Martinez-de Dios, Jose Ramiro; Ollero, Anibal

2014-04-25

This work is motivated by robot-sensor network cooperation techniques where sensor nodes (beacons) are used as landmarks for range-only (RO) simultaneous localization and mapping (SLAM). This paper presents a RO-SLAM scheme that actuates over the measurement gathering process using mechanisms that dynamically modify the rate and variety of measurements that are integrated in the SLAM filter. It includes a measurement gathering module that can be configured to collect direct robot-beacon and inter-beacon measurements with different inter-beacon depth levels and at different rates. It also includes a supervision module that monitors the SLAM performance and dynamically selects the measurement gathering configuration balancing SLAM accuracy and resource consumption. The proposed scheme has been applied to an extended Kalman filter SLAM with auxiliary particle filters for beacon initialization (PF-EKF SLAM) and validated with experiments performed in the CONET Integrated Testbed. It achieved lower map and robot errors (34% and 14%, respectively) than traditional methods with a lower computational burden (16%) and similar beacon energy consumption.

Phase-demodulation error of a fiber-optic Fabry-Perot sensor with complex reflection coefficients.

PubMed

Kilpatrick, J M; MacPherson, W N; Barton, J S; Jones, J D

2000-03-20

The influence of reflector losses attracts little discussion in standard treatments of the Fabry-Perot interferometer yet may be an important factor contributing to errors in phase-stepped demodulation of fiber optic Fabry-Perot (FFP) sensors. We describe a general transfer function for FFP sensors with complex reflection coefficients and estimate systematic phase errors that arise when the asymmetry of the reflected fringe system is neglected, as is common in the literature. The measured asymmetric response of higher-finesse metal-dielectric FFP constructions corroborates a model that predicts systematic phase errors of 0.06 rad in three-step demodulation of a low-finesse FFP sensor (R = 0.05) with internal reflector losses of 25%.

Intercomparison of cosmic-ray neutron sensors and water balance monitoring in an urban environment

NASA Astrophysics Data System (ADS)

Schrön, Martin; Zacharias, Steffen; Womack, Gary; Köhli, Markus; Desilets, Darin; Oswald, Sascha E.; Bumberger, Jan; Mollenhauer, Hannes; Kögler, Simon; Remmler, Paul; Kasner, Mandy; Denk, Astrid; Dietrich, Peter

2018-03-01

Sensor-to-sensor variability is a source of error common to all geoscientific instruments that needs to be assessed before comparative and applied research can be performed with multiple sensors. Consistency among sensor systems is especially critical when subtle features of the surrounding terrain are to be identified. Cosmic-ray neutron sensors (CRNSs) are a recent technology used to monitor hectometre-scale environmental water storages, for which a rigorous comparison study of numerous co-located sensors has not yet been performed. In this work, nine stationary CRNS probes of type CRS1000 were installed in relative proximity on a grass patch surrounded by trees, buildings, and sealed areas. While the dynamics of the neutron count rates were found to be similar, offsets of a few percent from the absolute average neutron count rates were found. Technical adjustments of the individual detection parameters brought all instruments into good agreement. Furthermore, we found a critical integration time of 6 h above which all sensors showed consistent dynamics in the data and their RMSE fell below 1 % of gravimetric water content. The residual differences between the nine signals indicated local effects of the complex urban terrain on the scale of several metres. Mobile CRNS measurements and spatial simulations with the URANOS neutron transport code in the surrounding area (25 ha) have revealed substantial sub-footprint heterogeneity to which CRNS detectors are sensitive despite their large averaging volume. The sealed and constantly dry structures in the footprint furthermore damped the dynamics of the CRNS-derived soil moisture. We developed strategies to correct for the sealed-area effect based on theoretical insights about the spatial sensitivity of the sensor. This procedure not only led to reliable soil moisture estimation during dry-out periods, it further revealed a strong signal of intercepted water that emerged over the sealed surfaces during rain events. The presented arrangement offered a unique opportunity to demonstrate the CRNS performance in complex terrain, and the results indicated great potential for further applications in urban climate research.

Examining Dense Data Usage near the Regions with Severe Storms in All-Sky Microwave Radiance Data Assimilation and Impacts on GEOS Hurricane Analyses

NASA Technical Reports Server (NTRS)

Kim, Min-Jeong; Jin, Jianjun; McCarty, Will; El Akkraoui, Amal; Todling, Ricardo; Gelaro, Ron

2018-01-01

Many numerical weather prediction (NWP) centers assimilate radiances affected by clouds and precipitation from microwave sensors, with the expectation that these data can provide critical constraints on meteorological parameters in dynamically sensitive regions to make significant impacts on forecast accuracy for precipitation. The Global Modeling and Assimilation Office (GMAO) at NASA Goddard Space Flight Center assimilates all-sky microwave radiance data from various microwave sensors such as all-sky GPM Microwave Imager (GMI) radiance in the Goddard Earth Observing System (GEOS) atmospheric data assimilation system (ADAS), which includes the GEOS atmospheric model, the Gridpoint Statistical Interpolation (GSI) atmospheric analysis system, and the Goddard Aerosol Assimilation System (GAAS). So far, most of NWP centers apply same large data thinning distances, that are used in clear-sky radiance data to avoid correlated observation errors, to all-sky microwave radiance data. For example, NASA GMAO is applying 145 km thinning distances for most of satellite radiance data including microwave radiance data in which all-sky approach is implemented. Even with these coarse observation data usage in all-sky assimilation approach, noticeable positive impacts from all-sky microwave data on hurricane track forecasts were identified in GEOS-5 system. The motivation of this study is based on the dynamic thinning distance method developed in our all-sky framework to use of denser data in cloudy and precipitating regions due to relatively small spatial correlations of observation errors. To investigate the benefits of all-sky microwave radiance on hurricane forecasts, several hurricane cases selected between 2016-2017 are examined. The dynamic thinning distance method is utilized in our all-sky approach to understand the sources and mechanisms to explain the benefits of all-sky microwave radiance data from various microwave radiance sensors like Advanced Microwave Sounder Unit (AMSU-A), Microwave Humidity Sounder (MHS), and GMI on GEOS-5 analyses and forecasts of various hurricanes.

Circular Array of Magnetic Sensors for Current Measurement: Analysis for Error Caused by Position of Conductor.

PubMed

Yu, Hao; Qian, Zheng; Liu, Huayi; Qu, Jiaqi

2018-02-14

This paper analyzes the measurement error, caused by the position of the current-carrying conductor, of a circular array of magnetic sensors for current measurement. The circular array of magnetic sensors is an effective approach for AC or DC non-contact measurement, as it is low-cost, light-weight, has a large linear range, wide bandwidth, and low noise. Especially, it has been claimed that such structure has excellent reduction ability for errors caused by the position of the current-carrying conductor, crosstalk current interference, shape of the conduction cross-section, and the Earth's magnetic field. However, the positions of the current-carrying conductor-including un-centeredness and un-perpendicularity-have not been analyzed in detail until now. In this paper, for the purpose of having minimum measurement error, a theoretical analysis has been proposed based on vector inner and exterior product. In the presented mathematical model of relative error, the un-center offset distance, the un-perpendicular angle, the radius of the circle, and the number of magnetic sensors are expressed in one equation. The comparison of the relative error caused by the position of the current-carrying conductor between four and eight sensors is conducted. Tunnel magnetoresistance (TMR) sensors are used in the experimental prototype to verify the mathematical model. The analysis results can be the reference to design the details of the circular array of magnetic sensors for current measurement in practical situations.

Gust prediction via artificial hair sensor array and neural network

NASA Astrophysics Data System (ADS)

Pankonien, Alexander M.; Thapa Magar, Kaman S.; Beblo, Richard V.; Reich, Gregory W.

2017-04-01

Gust Load Alleviation (GLA) is an important aspect of flight dynamics and control that reduces structural loadings and enhances ride quality. In conventional GLA systems, the structural response to aerodynamic excitation informs the control scheme. A phase lag, imposed by inertia, between the excitation and the measurement inherently limits the effectiveness of these systems. Hence, direct measurement of the aerodynamic loading can eliminate this lag, providing valuable information for effective GLA system design. Distributed arrays of Artificial Hair Sensors (AHS) are ideal for surface flow measurements that can be used to predict other necessary parameters such as aerodynamic forces, moments, and turbulence. In previous work, the spatially distributed surface flow velocities obtained from an array of artificial hair sensors using a Single-State (or feedforward) Neural Network were found to be effective in estimating the steady aerodynamic parameters such as air speed, angle of attack, lift and moment coefficient. This paper extends the investigation of the same configuration to unsteady force and moment estimation, which is important for active GLA control design. Implementing a Recurrent Neural Network that includes previous-timestep sensor information, the hair sensor array is shown to be capable of capturing gust disturbances with a wide range of periods, reducing predictive error in lift and moment by 68% and 52% respectively. The L2 norms of the first layer of the weight matrices were compared showing a 23% emphasis on prior versus current information. The Recurrent architecture also improves robustness, exhibiting only a 30% increase in predictive error when undertrained as compared to a 170% increase by the Single-State NN. This diverse, localized information can thus be directly implemented into a control scheme that alleviates the gusts without waiting for a structural response or requiring user-intensive sensor calibration.

Compensation for positioning error of industrial robot for flexible vision measuring system

NASA Astrophysics Data System (ADS)

Guo, Lei; Liang, Yajun; Song, Jincheng; Sun, Zengyu; Zhu, Jigui

2013-01-01

Positioning error of robot is a main factor of accuracy of flexible coordinate measuring system which consists of universal industrial robot and visual sensor. Present compensation methods for positioning error based on kinematic model of robot have a significant limitation that it isn't effective in the whole measuring space. A new compensation method for positioning error of robot based on vision measuring technique is presented. One approach is setting global control points in measured field and attaching an orientation camera to vision sensor. Then global control points are measured by orientation camera to calculate the transformation relation from the current position of sensor system to global coordinate system and positioning error of robot is compensated. Another approach is setting control points on vision sensor and two large field cameras behind the sensor. Then the three dimensional coordinates of control points are measured and the pose and position of sensor is calculated real-timely. Experiment result shows the RMS of spatial positioning is 3.422mm by single camera and 0.031mm by dual cameras. Conclusion is arithmetic of single camera method needs to be improved for higher accuracy and accuracy of dual cameras method is applicable.

Robust Adaptive Beamforming with Sensor Position Errors Using Weighted Subspace Fitting-Based Covariance Matrix Reconstruction.

PubMed

Chen, Peng; Yang, Yixin; Wang, Yong; Ma, Yuanliang

2018-05-08

When sensor position errors exist, the performance of recently proposed interference-plus-noise covariance matrix (INCM)-based adaptive beamformers may be severely degraded. In this paper, we propose a weighted subspace fitting-based INCM reconstruction algorithm to overcome sensor displacement for linear arrays. By estimating the rough signal directions, we construct a novel possible mismatched steering vector (SV) set. We analyze the proximity of the signal subspace from the sample covariance matrix (SCM) and the space spanned by the possible mismatched SV set. After solving an iterative optimization problem, we reconstruct the INCM using the estimated sensor position errors. Then we estimate the SV of the desired signal by solving an optimization problem with the reconstructed INCM. The main advantage of the proposed algorithm is its robustness against SV mismatches dominated by unknown sensor position errors. Numerical examples show that even if the position errors are up to half of the assumed sensor spacing, the output signal-to-interference-plus-noise ratio is only reduced by 4 dB. Beam patterns plotted using experiment data show that the interference suppression capability of the proposed beamformer outperforms other tested beamformers.

Exception handling for sensor fusion

NASA Astrophysics Data System (ADS)

Chavez, G. T.; Murphy, Robin R.

1993-08-01

This paper presents a control scheme for handling sensing failures (sensor malfunctions, significant degradations in performance due to changes in the environment, and errant expectations) in sensor fusion for autonomous mobile robots. The advantages of the exception handling mechanism are that it emphasizes a fast response to sensing failures, is able to use only a partial causal model of sensing failure, and leads to a graceful degradation of sensing if the sensing failure cannot be compensated for. The exception handling mechanism consists of two modules: error classification and error recovery. The error classification module in the exception handler attempts to classify the type and source(s) of the error using a modified generate-and-test procedure. If the source of the error is isolated, the error recovery module examines its cache of recovery schemes, which either repair or replace the current sensing configuration. If the failure is due to an error in expectation or cannot be identified, the planner is alerted. Experiments using actual sensor data collected by the CSM Mobile Robotics/Machine Perception Laboratory's Denning mobile robot demonstrate the operation of the exception handling mechanism.

Local Observability Analysis of Star Sensor Installation Errors in a SINS/CNS Integration System for Near-Earth Flight Vehicles.

PubMed

Yang, Yanqiang; Zhang, Chunxi; Lu, Jiazhen

2017-01-16

Strapdown inertial navigation system/celestial navigation system (SINS/CNS) integrated navigation is a fully autonomous and high precision method, which has been widely used to improve the hitting accuracy and quick reaction capability of near-Earth flight vehicles. The installation errors between SINS and star sensors have been one of the main factors that restrict the actual accuracy of SINS/CNS. In this paper, an integration algorithm based on the star vector observations is derived considering the star sensor installation error. Then, the star sensor installation error is accurately estimated based on Kalman Filtering (KF). Meanwhile, a local observability analysis is performed on the rank of observability matrix obtained via linearization observation equation, and the observable conditions are presented and validated. The number of star vectors should be greater than or equal to 2, and the times of posture adjustment also should be greater than or equal to 2. Simulations indicate that the star sensor installation error could be readily observable based on the maneuvering condition; moreover, the attitude errors of SINS are less than 7 arc-seconds. This analysis method and conclusion are useful in the ballistic trajectory design of near-Earth flight vehicles.

An LPV Adaptive Observer for Updating a Map Applied to an MAF Sensor in a Diesel Engine.

PubMed

Liu, Zhiyuan; Wang, Changhui

2015-10-23

In this paper, a new method for mass air flow (MAF) sensor error compensation and an online updating error map (or lookup table) due to installation and aging in a diesel engine is developed. Since the MAF sensor error is dependent on the engine operating point, the error model is represented as a two-dimensional (2D) map with two inputs, fuel mass injection quantity and engine speed. Meanwhile, the 2D map representing the MAF sensor error is described as a piecewise bilinear interpolation model, which can be written as a dot product between the regression vector and parameter vector using a membership function. With the combination of the 2D map regression model and the diesel engine air path system, an LPV adaptive observer with low computational load is designed to estimate states and parameters jointly. The convergence of the proposed algorithm is proven under the conditions of persistent excitation and given inequalities. The observer is validated against the simulation data from engine software enDYNA provided by Tesis. The results demonstrate that the operating point-dependent error of the MAF sensor can be approximated acceptably by the 2D map from the proposed method.

Deep Kalman Filter: Simultaneous Multi-Sensor Integration and Modelling; A GNSS/IMU Case Study

PubMed Central

Hosseinyalamdary, Siavash

2018-01-01

Bayes filters, such as the Kalman and particle filters, have been used in sensor fusion to integrate two sources of information and obtain the best estimate of unknowns. The efficient integration of multiple sensors requires deep knowledge of their error sources. Some sensors, such as Inertial Measurement Unit (IMU), have complicated error sources. Therefore, IMU error modelling and the efficient integration of IMU and Global Navigation Satellite System (GNSS) observations has remained a challenge. In this paper, we developed deep Kalman filter to model and remove IMU errors and, consequently, improve the accuracy of IMU positioning. To achieve this, we added a modelling step to the prediction and update steps of the Kalman filter, so that the IMU error model is learned during integration. The results showed our deep Kalman filter outperformed the conventional Kalman filter and reached a higher level of accuracy. PMID:29695119

Deep Kalman Filter: Simultaneous Multi-Sensor Integration and Modelling; A GNSS/IMU Case Study.

PubMed

Hosseinyalamdary, Siavash

2018-04-24

Bayes filters, such as the Kalman and particle filters, have been used in sensor fusion to integrate two sources of information and obtain the best estimate of unknowns. The efficient integration of multiple sensors requires deep knowledge of their error sources. Some sensors, such as Inertial Measurement Unit (IMU), have complicated error sources. Therefore, IMU error modelling and the efficient integration of IMU and Global Navigation Satellite System (GNSS) observations has remained a challenge. In this paper, we developed deep Kalman filter to model and remove IMU errors and, consequently, improve the accuracy of IMU positioning. To achieve this, we added a modelling step to the prediction and update steps of the Kalman filter, so that the IMU error model is learned during integration. The results showed our deep Kalman filter outperformed the conventional Kalman filter and reached a higher level of accuracy.

A Method to Simultaneously Detect the Current Sensor Fault and Estimate the State of Energy for Batteries in Electric Vehicles

PubMed Central

Xu, Jun; Wang, Jing; Li, Shiying; Cao, Binggang

2016-01-01

Recently, State of energy (SOE) has become one of the most fundamental parameters for battery management systems in electric vehicles. However, current information is critical in SOE estimation and current sensor is usually utilized to obtain the latest current information. However, if the current sensor fails, the SOE estimation may be confronted with large error. Therefore, this paper attempts to make the following contributions: Current sensor fault detection and SOE estimation method is realized simultaneously. Through using the proportional integral observer (PIO) based method, the current sensor fault could be accurately estimated. By taking advantage of the accurate estimated current sensor fault, the influence caused by the current sensor fault can be eliminated and compensated. As a result, the results of the SOE estimation will be influenced little by the fault. In addition, the simulation and experimental workbench is established to verify the proposed method. The results indicate that the current sensor fault can be estimated accurately. Simultaneously, the SOE can also be estimated accurately and the estimation error is influenced little by the fault. The maximum SOE estimation error is less than 2%, even though the large current error caused by the current sensor fault still exists. PMID:27548183

A Method to Simultaneously Detect the Current Sensor Fault and Estimate the State of Energy for Batteries in Electric Vehicles.

PubMed

Xu, Jun; Wang, Jing; Li, Shiying; Cao, Binggang

2016-08-19

Recently, State of energy (SOE) has become one of the most fundamental parameters for battery management systems in electric vehicles. However, current information is critical in SOE estimation and current sensor is usually utilized to obtain the latest current information. However, if the current sensor fails, the SOE estimation may be confronted with large error. Therefore, this paper attempts to make the following contributions: Current sensor fault detection and SOE estimation method is realized simultaneously. Through using the proportional integral observer (PIO) based method, the current sensor fault could be accurately estimated. By taking advantage of the accurate estimated current sensor fault, the influence caused by the current sensor fault can be eliminated and compensated. As a result, the results of the SOE estimation will be influenced little by the fault. In addition, the simulation and experimental workbench is established to verify the proposed method. The results indicate that the current sensor fault can be estimated accurately. Simultaneously, the SOE can also be estimated accurately and the estimation error is influenced little by the fault. The maximum SOE estimation error is less than 2%, even though the large current error caused by the current sensor fault still exists.

Use of the shape memory polymer polystyrene in the creation of thin film stretchable sensors for wearable applications

NASA Astrophysics Data System (ADS)

Van Volkinburg, Kyle R.; Nguyen, Thao; Pegan, Jonathan D.; Khine, Michelle; Washington, Gregory N.

2016-04-01

The shape memory polymer polystyrene (PS) has been used to create complex hierarchical wrinkling in the fabrication of stretchable thin film bimetallic sensors ideal for wearable based gesture monitoring applications. The film has been bonded to the elastomer polydimethylsiloxane (PDMS) and operates as a strain gauge under the general notion of geometric piezoresistivity. The film was subject to tensile, cyclic, and step loading conditions in order to characterize its dynamic behavior. To measure the joint angle of the metacarpophalangeal (MCP) joint on the right index finger, the sensor was adhered to a fitted golf glove above said joint and a motion study was conducted. At maximum joint angle the sensor experienced roughly 23.5% strain. From the study it was found that two simple curves, one while the finger was in flexion and the other while the finger was in extension, were able to predict the joint angle from measured voltage with an average error of 2.99 degrees.

Fluctuating pressures measured beneath a high-temperature, turbulent boundary layer on a flat plate at Mach number of 5

NASA Technical Reports Server (NTRS)

Parrott, Tony L.; Jones, Michael G.; Albertson, Cindy W.

1989-01-01

Fluctuating pressures were measured beneath a Mach 5, turbulent boundary layer on a flat plate with an array of piezoresistive sensors. The data were obtained with a digital signal acquisition system during a test run of 4 seconds. Data sampling rate was such that frequency analysis up to 62.5 kHz could be performed. To assess in situ frequency response of the sensors, a specially designed waveguide calibration system was employed to measure transfer functions of all sensors and related instrumentation. Pressure time histories were approximated well by a Gaussian prohibiting distribution. Pressure spectra were very repeatable over the array span of 76 mm. Total rms pressures ranged from 0.0017 to 0.0046 of the freestream dynamic pressure. Streamwise, space-time correlations exhibited expected decaying behavior of a turbulence generated pressure field. Average convection speed was 0.87 of freestream velocity. The trendless behavior with sensor separation indicated possible systematic errors.

Study of an automatic trajectory following control system

NASA Technical Reports Server (NTRS)

Vanlandingham, H. F.; Moose, R. L.; Zwicke, P. E.; Lucas, W. H.; Brinkley, J. D.

1983-01-01

It is shown that the estimator part of the Modified Partitioned Adaptive Controller, (MPAC) developed for nonlinear aircraft dynamics of a small jet transport can adapt to sensor failures. In addition, an investigation is made into the potential usefulness of the configuration detection technique used in the MPAC and the failure detection filter is developed that determines how a noise plant output is associated with a line or plane characteristic of a failure. It is shown by computer simulation that the estimator part and the configuration detection part of the MPAC can readily adapt to actuator and sensor failures and that the failure detection filter technique cannot detect actuator or sensor failures accurately for this type of system because of the plant modeling errors. In addition, it is shown that the decision technique, developed for the failure detection filter, can accurately determine that the plant output is related to the characteristic line or plane in the presence of sensor noise.

Automated vehicle guidance using discrete reference markers. [road surface steering techniques

NASA Technical Reports Server (NTRS)

Johnston, A. R.; Assefi, T.; Lai, J. Y.

1979-01-01

Techniques for providing steering control for an automated vehicle using discrete reference markers fixed to the road surface are investigated analytically. Either optical or magnetic approaches can be used for the sensor, which generates a measurement of the lateral offset of the vehicle path at each marker to form the basic data for steering control. Possible mechanizations of sensor and controller are outlined. Techniques for handling certain anomalous conditions, such as a missing marker, or loss of acquisition, and special maneuvers, such as u-turns and switching, are briefly discussed. A general analysis of the vehicle dynamics and the discrete control system is presented using the state variable formulation. Noise in both the sensor measurement and in the steering servo are accounted for. An optimal controller is simulated on a general purpose computer, and the resulting plots of vehicle path are presented. Parameters representing a small multipassenger tram were selected, and the simulation runs show response to an erroneous sensor measurement and acquisition following large initial path errors.

A human pilot study of the fluorescence affinity sensor for continuous glucose monitoring in diabetes.

PubMed

Dutt-Ballerstadt, Ralph; Evans, Colton; Pillai, Arun P; Orzeck, Eric; Drabek, Rafal; Gowda, Ashok; McNichols, Roger

2012-03-01

We report results of a pilot clinical study of a subcutaneous fluorescence affinity sensor (FAS) for continuous glucose monitoring conducted in people with type 1 and type 2 diabetes. The device was assessed based on performance, safety, and comfort level under acute conditions (4 h). A second-generation FAS (BioTex Inc., Houston, TX) was subcutaneously implanted in the abdomens of 12 people with diabetes, and its acute performance to excursions in blood glucose was monitored over 4 h. After 30-60 min the subjects, who all had fasting blood glucose levels of less than 200 mg/dl, received a glucose bolus of 75 g/liter dextrose by oral administration. Capillary blood glucose samples were obtained from the finger tip. The FAS data were retrospectively evaluated by linear least squares regression analysis and by the Clarke error grid method. Comfort levels during insertion, operation, and sensor removal were scored by the subjects using an analog pain scale. After retrospective calibration of 17 sensors implanted in 12 subjects, error grid analysis showed 97% of the paired values in zones A and B and 1.5% in zones C and D, respectively. The mean absolute relative error between sensor signal and capillary blood glucose was 13% [±15% standard deviation (SD), 100-350 mg/dl] with an average correlation coefficient of 0.84 (±0.24 SD). The actual average "warm-up" time for the FAS readings, at which highest correlation with glucose readings was determined, was 65 (±32 SD) min. Mean time lag was 4 (±5 SD) min during the initial operational hours. Pain levels during insertion and operation were modest. The in vivo performance of the FAS demonstrates feasibility of the fluorescence affinity technology to determine blood glucose excursions accurately and safely under acute dynamic conditions in humans with type 1 and type 2 diabetes. Specific engineering challenges to sensor and instrumentation robustness remain. Further studies will be required to validate its promising performance over longer implantation duration (5-7 days) in people with diabetes. © 2012 Diabetes Technology Society.

Monitoring stage fright outside the laboratory: an example in a professional musician using wearable sensors.

PubMed

Kusserow, Martin; Candia, Victor; Amft, Oliver; Hildebrandt, Horst; Folkers, Gerd; Tröster, Gerhard

2012-03-01

We implemented and tested a wearable sensor system to measure patterns of stress responses in a professional musician under public performance conditions. Using this sensor system, we monitored the cellist's heart activity, the motion of multiple body parts, and their gradual changes during three repeated performances of a skill-demanding piece in front of a professional audience. From the cellist and her teachers, we collected stage fright self-reports and performance ratings that were related to our sensor data analysis results. Concomitant to changes in body motion and heart rate, the cellist perceived a reduction in stage fright. Performance quality was objectively improved, as technical playing errors decreased throughout repeated renditions. In particular, from performance 1 to 3, the wearable sensors measured a significant increase in the cellist's bowing motion dynamics of approximately 6% and a decrease in heart rate. Bowing motion showed a marginal correlation to the observed heart rate patterns during playing. The wearable system did not interfere with the cellist's performance, thereby allowing investigation of stress responses during natural public performances.

Design and Development of a Three-Component Force Sensor for Milling Process Monitoring

PubMed Central

Li, Yingxue; Zhao, Yulong; Fei, Jiyou; Qin, Yafei; Zhao, You; Cai, Anjiang; Gao, Song

2017-01-01

A strain-type three-component table dynamometer is presented in this paper, which reduces output errors produced by cutting forces imposed on the different milling positions of a workpiece. A sensor structure with eight parallel elastic beams is proposed, and sensitive regions and Wheastone measuring circuits are also designed in consideration of eliminating the influences of the eccentric forces. To evaluate the sensor decoupling performance, both of the static calibration and dynamic milling test were implemented in different positions of the workpiece. Static experiment results indicate that the maximal deviation between the measured forces and the standard inputs is 4.58%. Milling tests demonstrate that with same machining parameters, the differences of the measured forces between different milling positions derived by the developed sensor are no larger than 6.29%. In addition, the natural frequencies of the dynamometer are kept higher than 2585.5 Hz. All the measuring results show that as a strain-type dynamometer, the developed force sensor has an improved eccentric decoupling accuracy with natural frequencies not much decreased, which owns application potential in milling process monitoring. PMID:28441354

The Application of Social Characteristic and L1 Optimization in the Error Correction for Network Coding in Wireless Sensor Networks

PubMed Central

Zhang, Guangzhi; Cai, Shaobin; Xiong, Naixue

2018-01-01

One of the remarkable challenges about Wireless Sensor Networks (WSN) is how to transfer the collected data efficiently due to energy limitation of sensor nodes. Network coding will increase network throughput of WSN dramatically due to the broadcast nature of WSN. However, the network coding usually propagates a single original error over the whole network. Due to the special property of error propagation in network coding, most of error correction methods cannot correct more than C/2 corrupted errors where C is the max flow min cut of the network. To maximize the effectiveness of network coding applied in WSN, a new error-correcting mechanism to confront the propagated error is urgently needed. Based on the social network characteristic inherent in WSN and L1 optimization, we propose a novel scheme which successfully corrects more than C/2 corrupted errors. What is more, even if the error occurs on all the links of the network, our scheme also can correct errors successfully. With introducing a secret channel and a specially designed matrix which can trap some errors, we improve John and Yi’s model so that it can correct the propagated errors in network coding which usually pollute exactly 100% of the received messages. Taking advantage of the social characteristic inherent in WSN, we propose a new distributed approach that establishes reputation-based trust among sensor nodes in order to identify the informative upstream sensor nodes. With referred theory of social networks, the informative relay nodes are selected and marked with high trust value. The two methods of L1 optimization and utilizing social characteristic coordinate with each other, and can correct the propagated error whose fraction is even exactly 100% in WSN where network coding is performed. The effectiveness of the error correction scheme is validated through simulation experiments. PMID:29401668

The Application of Social Characteristic and L1 Optimization in the Error Correction for Network Coding in Wireless Sensor Networks.

PubMed

Zhang, Guangzhi; Cai, Shaobin; Xiong, Naixue

2018-02-03

One of the remarkable challenges about Wireless Sensor Networks (WSN) is how to transfer the collected data efficiently due to energy limitation of sensor nodes. Network coding will increase network throughput of WSN dramatically due to the broadcast nature of WSN. However, the network coding usually propagates a single original error over the whole network. Due to the special property of error propagation in network coding, most of error correction methods cannot correct more than C /2 corrupted errors where C is the max flow min cut of the network. To maximize the effectiveness of network coding applied in WSN, a new error-correcting mechanism to confront the propagated error is urgently needed. Based on the social network characteristic inherent in WSN and L1 optimization, we propose a novel scheme which successfully corrects more than C /2 corrupted errors. What is more, even if the error occurs on all the links of the network, our scheme also can correct errors successfully. With introducing a secret channel and a specially designed matrix which can trap some errors, we improve John and Yi's model so that it can correct the propagated errors in network coding which usually pollute exactly 100% of the received messages. Taking advantage of the social characteristic inherent in WSN, we propose a new distributed approach that establishes reputation-based trust among sensor nodes in order to identify the informative upstream sensor nodes. With referred theory of social networks, the informative relay nodes are selected and marked with high trust value. The two methods of L1 optimization and utilizing social characteristic coordinate with each other, and can correct the propagated error whose fraction is even exactly 100% in WSN where network coding is performed. The effectiveness of the error correction scheme is validated through simulation experiments.

Digital Architecture for a Trace Gas Sensor Platform

NASA Technical Reports Server (NTRS)

Gonzales, Paula; Casias, Miguel; Vakhtin, Andrei; Pilgrim, Jeffrey

2012-01-01

A digital architecture has been implemented for a trace gas sensor platform, as a companion to standard analog control electronics, which accommodates optical absorption whose fractional absorbance equivalent would result in excess error if assumed to be linear. In cases where the absorption (1-transmission) is not equivalent to the fractional absorbance within a few percent error, it is necessary to accommodate the actual measured absorption while reporting the measured concentration of a target analyte with reasonable accuracy. This requires incorporation of programmable intelligence into the sensor platform so that flexible interpretation of the acquired data may be accomplished. Several different digital component architectures were tested and implemented. Commercial off-the-shelf digital electronics including data acquisition cards (DAQs), complex programmable logic devices (CPLDs), field-programmable gate arrays (FPGAs), and microcontrollers have been used to achieve the desired outcome. The most completely integrated architecture achieved during the project used the CPLD along with a microcontroller. The CPLD provides the initial digital demodulation of the raw sensor signal, and then communicates over a parallel communications interface with a microcontroller. The microcontroller analyzes the digital signal from the CPLD, and applies a non-linear correction obtained through extensive data analysis at the various relevant EVA operating pressures. The microcontroller then presents the quantitatively accurate carbon dioxide partial pressure regardless of optical density. This technique could extend the linear dynamic range of typical absorption spectrometers, particularly those whose low end noise equivalent absorbance is below one-part-in-100,000. In the EVA application, it allows introduction of a path-length-enhancing architecture whose optical interference effects are well understood and quantified without sacrificing the dynamic range that allows quantitative detection at the higher carbon dioxide partial pressures. The digital components are compact and allow reasonably complete integration with separately developed analog control electronics without sacrificing size, mass, or power draw.

A two-step A/D conversion and column self-calibration technique for low noise CMOS image sensors.

PubMed

Bae, Jaeyoung; Kim, Daeyun; Ham, Seokheon; Chae, Youngcheol; Song, Minkyu

2014-07-04

In this paper, a 120 frames per second (fps) low noise CMOS Image Sensor (CIS) based on a Two-Step Single Slope ADC (TS SS ADC) and column self-calibration technique is proposed. The TS SS ADC is suitable for high speed video systems because its conversion speed is much faster (by more than 10 times) than that of the Single Slope ADC (SS ADC). However, there exist some mismatching errors between the coarse block and the fine block due to the 2-step operation of the TS SS ADC. In general, this makes it difficult to implement the TS SS ADC beyond a 10-bit resolution. In order to improve such errors, a new 4-input comparator is discussed and a high resolution TS SS ADC is proposed. Further, a feedback circuit that enables column self-calibration to reduce the Fixed Pattern Noise (FPN) is also described. The proposed chip has been fabricated with 0.13 μm Samsung CIS technology and the chip satisfies the VGA resolution. The pixel is based on the 4-TR Active Pixel Sensor (APS). The high frame rate of 120 fps is achieved at the VGA resolution. The measured FPN is 0.38 LSB, and measured dynamic range is about 64.6 dB.

1999 Flight Mechanics Symposium

NASA Technical Reports Server (NTRS)

Lynch, John P. (Editor)

1999-01-01

This conference publication includes papers and abstracts presented at the Flight Mechanics Symposium held on May 18-20, 1999. Sponsored by the Guidance, Navigation and Control Center of Goddard Space Flight Center, this symposium featured technical papers on a wide range of issues related to orbit-attitude prediction, determination, and control; attitude sensor calibration; attitude determination error analysis; attitude dynamics; and orbit decay and maneuver strategy. Government, industry, and the academic community participated in the preparation and presentation of these papers.

Design and simulation of sensor networks for tracking Wifi users in outdoor urban environments

NASA Astrophysics Data System (ADS)

Thron, Christopher; Tran, Khoi; Smith, Douglas; Benincasa, Daniel

2017-05-01

We present a proof-of-concept investigation into the use of sensor networks for tracking of WiFi users in outdoor urban environments. Sensors are fixed, and are capable of measuring signal power from users' WiFi devices. We derive a maximum likelihood estimate for user location based on instantaneous sensor power measurements. The algorithm takes into account the effects of power control, and is self-calibrating in that the signal power model used by the location algorithm is adjusted and improved as part of the operation of the network. Simulation results to verify the system's performance are presented. The simulation scenario is based on a 1.5 km2 area of lower Manhattan, The self-calibration mechanism was verified for initial rms (root mean square) errors of up to 12 dB in the channel power estimates: rms errors were reduced by over 60% in 300 track-hours, in systems with limited power control. Under typical operating conditions with (without) power control, location rms errors are about 8.5 (5) meters with 90% accuracy within 9 (13) meters, for both pedestrian and vehicular users. The distance error distributions for smaller distances (<30 m) are well-approximated by an exponential distribution, while the distributions for large distance errors have fat tails. The issue of optimal sensor placement in the sensor network is also addressed. We specify a linear programming algorithm for determining sensor placement for networks with reduced number of sensors. In our test case, the algorithm produces a network with 18.5% fewer sensors with comparable accuracy estimation performance. Finally, we discuss future research directions for improving the accuracy and capabilities of sensor network systems in urban environments.

Validation of the Five-Phase Method for Simulating Complex Fenestration Systems with Radiance against Field Measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Geisler-Moroder, David; Lee, Eleanor S.; Ward, Gregory J.

2016-08-29

The Five-Phase Method (5-pm) for simulating complex fenestration systems with Radiance is validated against field measurements. The capability of the method to predict workplane illuminances, vertical sensor illuminances, and glare indices derived from captured and rendered high dynamic range (HDR) images is investigated. To be able to accurately represent the direct sun part of the daylight not only in sensor point simulations, but also in renderings of interior scenes, the 5-pm calculation procedure was extended. The validation shows that the 5-pm is superior to the Three-Phase Method for predicting horizontal and vertical illuminance sensor values as well as glare indicesmore » derived from rendered images. Even with input data from global and diffuse horizontal irradiance measurements only, daylight glare probability (DGP) values can be predicted within 10% error of measured values for most situations.« less

Real-time Bayesian anomaly detection in streaming environmental data

NASA Astrophysics Data System (ADS)

Hill, David J.; Minsker, Barbara S.; Amir, Eyal

2009-04-01

With large volumes of data arriving in near real time from environmental sensors, there is a need for automated detection of anomalous data caused by sensor or transmission errors or by infrequent system behaviors. This study develops and evaluates three automated anomaly detection methods using dynamic Bayesian networks (DBNs), which perform fast, incremental evaluation of data as they become available, scale to large quantities of data, and require no a priori information regarding process variables or types of anomalies that may be encountered. This study investigates these methods' abilities to identify anomalies in eight meteorological data streams from Corpus Christi, Texas. The results indicate that DBN-based detectors, using either robust Kalman filtering or Rao-Blackwellized particle filtering, outperform a DBN-based detector using Kalman filtering, with the former having false positive/negative rates of less than 2%. These methods were successful at identifying data anomalies caused by two real events: a sensor failure and a large storm.

Trajectory prediction for ballistic missiles based on boost-phase LOS measurements

NASA Astrophysics Data System (ADS)

Yeddanapudi, Murali; Bar-Shalom, Yaakov

1997-10-01

This paper addresses the problem of the estimation of the trajectory of a tactical ballistic missile using line of sight (LOS) measurements from one or more passive sensors (typically satellites). The major difficulties of this problem include: the estimation of the unknown time of launch, incorporation of (inaccurate) target thrust profiles to model the target dynamics during the boost phase and an overall ill-conditioning of the estimation problem due to poor observability of the target motion via the LOS measurements. We present a robust estimation procedure based on the Levenberg-Marquardt algorithm that provides both the target state estimate and error covariance taking into consideration the complications mentioned above. An important consideration in the defense against tactical ballistic missiles is the determination of the target position and error covariance at the acquisition range of a surveillance radar in the vicinity of the impact point. We present a systematic procedure to propagate the target state and covariance to a nominal time, when it is within the detection range of a surveillance radar to obtain a cueing volume. Mont Carlo simulation studies on typical single and two sensor scenarios indicate that the proposed algorithms are accurate in terms of the estimates and the estimator calculated covariances are consistent with the errors.

Estimation of attitude sensor timetag biases

NASA Technical Reports Server (NTRS)

Sedlak, J.

1995-01-01

This paper presents an extended Kalman filter for estimating attitude sensor timing errors. Spacecraft attitude is determined by finding the mean rotation from a set of reference vectors in inertial space to the corresponding observed vectors in the body frame. Any timing errors in the observations can lead to attitude errors if either the spacecraft is rotating or the reference vectors themselves vary with time. The state vector here consists of the attitude quaternion, timetag biases, and, optionally, gyro drift rate biases. The filter models the timetags as random walk processes: their expectation values propagate as constants and white noise contributes to their covariance. Thus, this filter is applicable to cases where the true timing errors are constant or slowly varying. The observability of the state vector is studied first through an examination of the algebraic observability condition and then through several examples with simulated star tracker timing errors. The examples use both simulated and actual flight data from the Extreme Ultraviolet Explorer (EUVE). The flight data come from times when EUVE had a constant rotation rate, while the simulated data feature large angle attitude maneuvers. The tests include cases with timetag errors on one or two sensors, both constant and time-varying, and with and without gyro bias errors. Due to EUVE's sensor geometry, the observability of the state vector is severely limited when the spacecraft rotation rate is constant. In the absence of attitude maneuvers, the state elements are highly correlated, and the state estimate is unreliable. The estimates are particularly sensitive to filter mistuning in this case. The EUVE geometry, though, is a degenerate case having coplanar sensors and rotation vector. Observability is much improved and the filter performs well when the rate is either varying or noncoplanar with the sensors, as during a slew. Even with bad geometry and constant rates, if gyro biases are independently known, the timetag error for a single sensor can be accurately estimated as long as its boresight is not too close to the spacecraft rotation axis.

The Development and Test of a Sensor for Measurement of the Working Level of Gas–Liquid Two-Phase Flow in a Coalbed Methane Wellbore Annulus

PubMed Central

Wu, Chuan; Ding, Huafeng; Han, Lei

2018-01-01

Coalbed methane (CBM) is one kind of clean-burning gas and has been valued as a new form of energy that will be used widely in the near future. When producing CBM, the working level within a CBM wellbore annulus needs to be monitored to dynamically adjust the gas drainage and extraction processes. However, the existing method of measuring the working level does not meet the needs of accurate adjustment, so we designed a new sensor for this purpose. The principle of our sensor is a liquid pressure formula, i.e., the sensor monitors the two-phase flow patterns and obtains the mean density of the two-phase flow according to the pattern recognition result in the first step, and then combines the pressure data of the working level to calculate the working level using the liquid pressure formula. The sensor was tested in both the lab and on site, and the tests showed that the sensor’s error was ±8% and that the sensor could function well in practical conditions and remain stable in the long term. PMID:29443871

Virtual sensors for robust on-line monitoring (OLM) and Diagnostics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tipireddy, Ramakrishna; Lerchen, Megan E.; Ramuhalli, Pradeep

Unscheduled shutdown of nuclear power facilities for recalibration and replacement of faulty sensors can be expensive and disruptive to grid management. In this work, we present virtual (software) sensors that can replace a faulty physical sensor for a short duration thus allowing recalibration to be safely deferred to a later time. The virtual sensor model uses a Gaussian process model to process input data from redundant and other nearby sensors. Predicted data includes uncertainty bounds including spatial association uncertainty and measurement noise and error. Using data from an instrumented cooling water flow loop testbed, the virtual sensor model has predictedmore » correct sensor measurements and the associated error corresponding to a faulty sensor.« less

A novel optical fiber displacement sensor of wider measurement range based on neural network

NASA Astrophysics Data System (ADS)

Guo, Yuan; Dai, Xue Feng; Wang, Yu Tian

2006-02-01

By studying on the output characteristics of random type optical fiber sensor and semicircular type optical fiber sensor, the ratio of the two output signals was used as the output signal of the whole system. Then the measurement range was enlarged, the linearity was improved, and the errors of reflective and absorbent changing of target surface are automatically compensated. Meantime, an optical fiber sensor model of correcting static error based on BP artificial neural network(ANN) is set up. So the intrinsic errors such as effects of fluctuations in the light, circuit excursion, the intensity losses in the fiber lines and the additional losses in the receiving fiber caused by bends are eliminated. By discussing in theory and experiment, the error of nonlinear is 2.9%, the measuring range reaches to 5-6mm and the relative accuracy is 2%.And this sensor has such characteristics as no electromagnetic interference, simple construction, high sensitivity, good accuracy and stability. Also the multi-point sensor system can be used to on-line and non-touch monitor in working locales.

Analytical and finite element performance evaluation of embedded piezoelectric sensors in polyethylene

NASA Astrophysics Data System (ADS)

Safaei, Mohsen; Anton, Steven R.

2017-04-01

A common application of piezoelectric transducers is to obtain operational data from working structures and dynamic components. Collected data can then be used to evaluate dynamic characterization of the system, perform structural health monitoring, or implement various other assessments. In some applications, piezoelectric transducers are bonded inside the host structure to satisfy system requirements; for example, piezoelectric transducers can be embedded inside the biopolymers of total joint replacements to evaluate the functionality of the artificial joint. The interactions between the piezoelectric device (inhomogeneity) and the surrounding polymer matrix determine the mechanical behavior of the matrix and the electromechanical behavior of the sensor. In this work, an analytical approach is employed to evaluate the electromechanical performance of 2-D plane strain piezoelectric elements of both circular and rectangular-shape inhomogeneities. These piezoelectric elements are embedded inside medical grade ultra-high molecular weight (UHMW) polyethylene, a material commonly used for bearing surfaces of joint replacements, such as total knee replacements (TKRs). Using the famous Eshelby inhomogeneity solution, the stress and electric field inside the circular (elliptical) inhomogeneity is obtained by decoupling the solution into purely elastic and dielectric systems of equations. For rectangular (non-elliptical) inhomogeneities, an approximation method based on the boundary integral function is utilized and the same decoupling method is employed. In order to validate the analytical result, a finite element analysis is performed for both the circular and rectangular inhomogeneities and the error for each case is calculated. For elliptical geometry, the error is less than 1% for stress and electric fields inside and outside the piezoelectric inhomogeneity, whereas, the error for non-elliptical geometry is obtained as 11% and 7% for stress and electric field inside the inhomogeneity, respectively.

Estimation of distributed Fermat-point location for wireless sensor networking.

PubMed

Huang, Po-Hsian; Chen, Jiann-Liang; Larosa, Yanuarius Teofilus; Chiang, Tsui-Lien

2011-01-01

This work presents a localization scheme for use in wireless sensor networks (WSNs) that is based on a proposed connectivity-based RF localization strategy called the distributed Fermat-point location estimation algorithm (DFPLE). DFPLE applies triangle area of location estimation formed by intersections of three neighboring beacon nodes. The Fermat point is determined as the shortest path from three vertices of the triangle. The area of estimated location then refined using Fermat point to achieve minimum error in estimating sensor nodes location. DFPLE solves problems of large errors and poor performance encountered by localization schemes that are based on a bounding box algorithm. Performance analysis of a 200-node development environment reveals that, when the number of sensor nodes is below 150, the mean error decreases rapidly as the node density increases, and when the number of sensor nodes exceeds 170, the mean error remains below 1% as the node density increases. Second, when the number of beacon nodes is less than 60, normal nodes lack sufficient beacon nodes to enable their locations to be estimated. However, the mean error changes slightly as the number of beacon nodes increases above 60. Simulation results revealed that the proposed algorithm for estimating sensor positions is more accurate than existing algorithms, and improves upon conventional bounding box strategies.

Cross-calibration of MODIS with ETM+ and ALI sensors for long-term monitoring of land surface processes

USGS Publications Warehouse

Meyer, D.; Chander, G.

2006-01-01

Increasingly, data from multiple sensors are used to gain a more complete understanding of land surface processes at a variety of scales. Although higher-level products (e.g., vegetation cover, albedo, surface temperature) derived from different sensors can be validated independently, the degree to which these sensors and their products can be compared to one another is vastly improved if their relative spectroradiometric responses are known. Most often, sensors are directly calibrated to diffuse solar irradiation or vicariously to ground targets. However, space-based targets are not traceable to metrological standards, and vicarious calibrations are expensive and provide a poor sampling of a sensor's full dynamic range. Crosscalibration of two sensors can augment these methods if certain conditions can be met: (1) the spectral responses are similar, (2) the observations are reasonably concurrent (similar atmospheric & solar illumination conditions), (3) errors due to misregistrations of inhomogeneous surfaces can be minimized (including scale differences), and (4) the viewing geometry is similar (or, some reasonable knowledge of surface bi-directional reflectance distribution functions is available). This study explores the impacts of cross-calibrating sensors when such conditions are met to some degree but not perfectly. In order to constrain the range of conditions at some level, the analysis is limited to sensors where cross-calibration studies have been conducted (Enhanced Thematic Mapper Plus (ETM+) on Landsat-7 (L7), Advance Land Imager (ALI) and Hyperion on Earth Observer-1 (EO-1)) and including systems having somewhat dissimilar geometry, spatial resolution & spectral response characteristics but are still part of the so-called "A.M. constellation" (Moderate Resolution Imaging Spectrometer (MODIS) aboard the Terra platform). Measures for spectral response differences and methods for cross calibrating such sensors are provided in this study. These instruments are cross calibrated using the Railroad Valley playa in Nevada. Best fit linear coefficients (slope and offset) are provided for ALI-to-MODIS and ETM+-to-MODIS cross calibrations, and root-mean-squared errors (RMSEs) and correlation coefficients are provided to quantify the uncertainty in these relationships. In theory, the linear fits and uncertainties can be used to compare radiance and reflectance products derived from each instrument.

Cross-calibration of A.M. constellation sensors for long term monitoring of land surface processes

USGS Publications Warehouse

Meyer, D.; Chander, G.

2006-01-01

Data from multiple sensors must be used together to gain a more complete understanding of land surface processes at a variety of scales. Although higher-level products derived from different sensors (e.g., vegetation cover, albedo, surface temperature) can be validated independently, the degree to which these sensors and their products can be compared to one another is vastly improved if their relative spectro-radiometric responses are known. Most often, sensors are directly calibrated to diffuse solar irradiation or vicariously to ground targets. However, space-based targets are not traceable to metrological standards, and vicarious calibrations are expensive and provide a poor sampling of a sensor's full dynamic range. Cross-calibration of two sensors can augment these methods if certain conditions can be met: (1) the spectral responses are similar, (2) the observations are reasonably concurrent (similar atmospheric & solar illumination conditions), (3) errors due to misregistrations of inhomogeneous surfaces can be minimized (including scale differences), and (4) the viewing geometry is similar (or, some reasonable knowledge of surface bi-directional reflectance distribution functions is available). This study extends on a previous study of Terra/MODIS and Landsat/ETM+ cross calibration by including the Terra/ASTER and EO-1/ALI sensors, exploring the impacts of cross-calibrating sensors when conditions described above are met to some degree but not perfectly. Measures for spectral response differences and methods for cross calibrating such sensors are provided in this study. These instruments are cross calibrated using the Railroad Valley playa in Nevada. Best fit linear coefficients (slope and offset) are provided for ALI-to-MODIS and ETM+-to-MODIS cross calibrations, and root-mean-squared errors (RMSEs) and correlation coefficients are provided to quantify the uncertainty in these relationships. Due to problems with direct calibration of ASTER data, linear fits were developed between ASTER and ETM+ to assess the impacts of spectral bandpass differences between the two systems. In theory, the linear fits and uncertainties can be used to compare radiance and reflectance products derived from each instrument.

An LPV Adaptive Observer for Updating a Map Applied to an MAF Sensor in a Diesel Engine

PubMed Central

Liu, Zhiyuan; Wang, Changhui

2015-01-01

In this paper, a new method for mass air flow (MAF) sensor error compensation and an online updating error map (or lookup table) due to installation and aging in a diesel engine is developed. Since the MAF sensor error is dependent on the engine operating point, the error model is represented as a two-dimensional (2D) map with two inputs, fuel mass injection quantity and engine speed. Meanwhile, the 2D map representing the MAF sensor error is described as a piecewise bilinear interpolation model, which can be written as a dot product between the regression vector and parameter vector using a membership function. With the combination of the 2D map regression model and the diesel engine air path system, an LPV adaptive observer with low computational load is designed to estimate states and parameters jointly. The convergence of the proposed algorithm is proven under the conditions of persistent excitation and given inequalities. The observer is validated against the simulation data from engine software enDYNA provided by Tesis. The results demonstrate that the operating point-dependent error of the MAF sensor can be approximated acceptably by the 2D map from the proposed method. PMID:26512675

Local Observability Analysis of Star Sensor Installation Errors in a SINS/CNS Integration System for Near-Earth Flight Vehicles

PubMed Central

Yang, Yanqiang; Zhang, Chunxi; Lu, Jiazhen

2017-01-01

Strapdown inertial navigation system/celestial navigation system (SINS/CNS) integrated navigation is a fully autonomous and high precision method, which has been widely used to improve the hitting accuracy and quick reaction capability of near-Earth flight vehicles. The installation errors between SINS and star sensors have been one of the main factors that restrict the actual accuracy of SINS/CNS. In this paper, an integration algorithm based on the star vector observations is derived considering the star sensor installation error. Then, the star sensor installation error is accurately estimated based on Kalman Filtering (KF). Meanwhile, a local observability analysis is performed on the rank of observability matrix obtained via linearization observation equation, and the observable conditions are presented and validated. The number of star vectors should be greater than or equal to 2, and the times of posture adjustment also should be greater than or equal to 2. Simulations indicate that the star sensor installation error could be readily observable based on the maneuvering condition; moreover, the attitude errors of SINS are less than 7 arc-seconds. This analysis method and conclusion are useful in the ballistic trajectory design of near-Earth flight vehicles. PMID:28275211

Use of Earth's magnetic field for mitigating gyroscope errors regardless of magnetic perturbation.

PubMed

Afzal, Muhammad Haris; Renaudin, Valérie; Lachapelle, Gérard

2011-01-01

Most portable systems like smart-phones are equipped with low cost consumer grade sensors, making them useful as Pedestrian Navigation Systems (PNS). Measurements of these sensors are severely contaminated by errors caused due to instrumentation and environmental issues rendering the unaided navigation solution with these sensors of limited use. The overall navigation error budget associated with pedestrian navigation can be categorized into position/displacement errors and attitude/orientation errors. Most of the research is conducted for tackling and reducing the displacement errors, which either utilize Pedestrian Dead Reckoning (PDR) or special constraints like Zero velocity UPdaTes (ZUPT) and Zero Angular Rate Updates (ZARU). This article targets the orientation/attitude errors encountered in pedestrian navigation and develops a novel sensor fusion technique to utilize the Earth's magnetic field, even perturbed, for attitude and rate gyroscope error estimation in pedestrian navigation environments where it is assumed that Global Navigation Satellite System (GNSS) navigation is denied. As the Earth's magnetic field undergoes severe degradations in pedestrian navigation environments, a novel Quasi-Static magnetic Field (QSF) based attitude and angular rate error estimation technique is developed to effectively use magnetic measurements in highly perturbed environments. The QSF scheme is then used for generating the desired measurements for the proposed Extended Kalman Filter (EKF) based attitude estimator. Results indicate that the QSF measurements are capable of effectively estimating attitude and gyroscope errors, reducing the overall navigation error budget by over 80% in urban canyon environment.

Use of Earth’s Magnetic Field for Mitigating Gyroscope Errors Regardless of Magnetic Perturbation

PubMed Central

Afzal, Muhammad Haris; Renaudin, Valérie; Lachapelle, Gérard

2011-01-01

Most portable systems like smart-phones are equipped with low cost consumer grade sensors, making them useful as Pedestrian Navigation Systems (PNS). Measurements of these sensors are severely contaminated by errors caused due to instrumentation and environmental issues rendering the unaided navigation solution with these sensors of limited use. The overall navigation error budget associated with pedestrian navigation can be categorized into position/displacement errors and attitude/orientation errors. Most of the research is conducted for tackling and reducing the displacement errors, which either utilize Pedestrian Dead Reckoning (PDR) or special constraints like Zero velocity UPdaTes (ZUPT) and Zero Angular Rate Updates (ZARU). This article targets the orientation/attitude errors encountered in pedestrian navigation and develops a novel sensor fusion technique to utilize the Earth’s magnetic field, even perturbed, for attitude and rate gyroscope error estimation in pedestrian navigation environments where it is assumed that Global Navigation Satellite System (GNSS) navigation is denied. As the Earth’s magnetic field undergoes severe degradations in pedestrian navigation environments, a novel Quasi-Static magnetic Field (QSF) based attitude and angular rate error estimation technique is developed to effectively use magnetic measurements in highly perturbed environments. The QSF scheme is then used for generating the desired measurements for the proposed Extended Kalman Filter (EKF) based attitude estimator. Results indicate that the QSF measurements are capable of effectively estimating attitude and gyroscope errors, reducing the overall navigation error budget by over 80% in urban canyon environment. PMID:22247672

In Vivo Evaluation of Wearable Head Impact Sensors.

PubMed

Wu, Lyndia C; Nangia, Vaibhav; Bui, Kevin; Hammoor, Bradley; Kurt, Mehmet; Hernandez, Fidel; Kuo, Calvin; Camarillo, David B

2016-04-01

Inertial sensors are commonly used to measure human head motion. Some sensors have been tested with dummy or cadaver experiments with mixed results, and methods to evaluate sensors in vivo are lacking. Here we present an in vivo method using high speed video to test teeth-mounted (mouthguard), soft tissue-mounted (skin patch), and headgear-mounted (skull cap) sensors during 6-13 g sagittal soccer head impacts. Sensor coupling to the skull was quantified by displacement from an ear-canal reference. Mouthguard displacements were within video measurement error (<1 mm), while the skin patch and skull cap displaced up to 4 and 13 mm from the ear-canal reference, respectively. We used the mouthguard, which had the least displacement from skull, as the reference to assess 6-degree-of-freedom skin patch and skull cap measurements. Linear and rotational acceleration magnitudes were over-predicted by both the skin patch (with 120% NRMS error for a(mag), 290% for α(mag)) and the skull cap (320% NRMS error for a(mag), 500% for α(mag)). Such over-predictions were largely due to out-of-plane motion. To model sensor error, we found that in-plane skin patch linear acceleration in the anterior-posterior direction could be modeled by an underdamped viscoelastic system. In summary, the mouthguard showed tighter skull coupling than the other sensor mounting approaches. Furthermore, the in vivo methods presented are valuable for investigating skull acceleration sensor technologies.

Detecting Signatures of GRACE Sensor Errors in Range-Rate Residuals

NASA Astrophysics Data System (ADS)

Goswami, S.; Flury, J.

2016-12-01

In order to reach the accuracy of the GRACE baseline, predicted earlier from the design simulations, efforts are ongoing since a decade. GRACE error budget is highly dominated by noise from sensors, dealiasing models and modeling errors. GRACE range-rate residuals contain these errors. Thus, their analysis provides an insight to understand the individual contribution to the error budget. Hence, we analyze the range-rate residuals with focus on contribution of sensor errors due to mis-pointing and bad ranging performance in GRACE solutions. For the analysis of pointing errors, we consider two different reprocessed attitude datasets with differences in pointing performance. Then range-rate residuals are computed from these two datasetsrespectively and analysed. We further compare the system noise of four K-and Ka- band frequencies of the two spacecrafts, with range-rate residuals. Strong signatures of mis-pointing errors can be seen in the range-rate residuals. Also, correlation between range frequency noise and range-rate residuals are seen.

Tilt Error in Cryospheric Surface Radiation Measurements at High Latitudes: A Model Study

NASA Astrophysics Data System (ADS)

Bogren, W.; Kylling, A.; Burkhart, J. F.

2015-12-01

We have evaluated the magnitude and makeup of error in cryospheric radiation observations due to small sensor misalignment in in-situ measurements of solar irradiance. This error is examined through simulation of diffuse and direct irradiance arriving at a detector with a cosine-response foreoptic. Emphasis is placed on assessing total error over the solar shortwave spectrum from 250nm to 4500nm, as well as supporting investigation over other relevant shortwave spectral ranges. The total measurement error introduced by sensor tilt is dominated by the direct component. For a typical high latitude albedo measurement with a solar zenith angle of 60◦, a sensor tilted by 1, 3, and 5◦ can respectively introduce up to 2.6, 7.7, and 12.8% error into the measured irradiance and similar errors in the derived albedo. Depending on the daily range of solar azimuth and zenith angles, significant measurement error can persist also in integrated daily irradiance and albedo.

Low Frequency Error Analysis and Calibration for High-Resolution Optical Satellite's Uncontrolled Geometric Positioning

NASA Astrophysics Data System (ADS)

Wang, Mi; Fang, Chengcheng; Yang, Bo; Cheng, Yufeng

2016-06-01

The low frequency error is a key factor which has affected uncontrolled geometry processing accuracy of the high-resolution optical image. To guarantee the geometric quality of imagery, this paper presents an on-orbit calibration method for the low frequency error based on geometric calibration field. Firstly, we introduce the overall flow of low frequency error on-orbit analysis and calibration, which includes optical axis angle variation detection of star sensor, relative calibration among star sensors, multi-star sensor information fusion, low frequency error model construction and verification. Secondly, we use optical axis angle change detection method to analyze the law of low frequency error variation. Thirdly, we respectively use the method of relative calibration and information fusion among star sensors to realize the datum unity and high precision attitude output. Finally, we realize the low frequency error model construction and optimal estimation of model parameters based on DEM/DOM of geometric calibration field. To evaluate the performance of the proposed calibration method, a certain type satellite's real data is used. Test results demonstrate that the calibration model in this paper can well describe the law of the low frequency error variation. The uncontrolled geometric positioning accuracy of the high-resolution optical image in the WGS-84 Coordinate Systems is obviously improved after the step-wise calibration.

Safety assurance of non-deterministic flight controllers in aircraft applications

NASA Astrophysics Data System (ADS)

Noriega, Alfonso

Loss of control is a serious problem in aviation that primarily affects General Aviation. Technological advancements can help mitigate the problem, but the FAA certification process makes certain solutions economically unfeasible. This investigation presents the design of a generic adaptive autopilot that could potentially lead to a single certification for use in several makes and models of aircraft. The autopilot consists of a conventional controller connected in series with a robust direct adaptive model reference controller. In this architecture, the conventional controller is tuned once to provide outer-loop guidance and navigation to a reference model. The adaptive controller makes unknown aircraft behave like the reference model, allowing the conventional controller to successfully provide navigation without the need for retuning. A strong theoretical foundation is presented as an argument for the safety and stability of the controller. The stability proof of direct adaptive controllers require that the plant being controlled has no unstable transmission zeros and has a nonzero high frequency gain. Because most conventional aircraft do not readily meet these requirements, a process known as sensor blending was used. Sensor blending consists of using a linear combination of the plant's outputs that has no unstable transmission zeros and has a nonzero high frequency gain to drive the adaptive controller. Although this method does not present a problem for regulators, it can lead to a steady state error in tracking applications. The sensor blending theory was expanded to take advantage of the system's dynamics to allow for zero steady state error tracking. This method does not need knowledge of the specific system's dynamics, but instead uses the structure of the A and B matrices to perform the blending for the general case. The generic adaptive autopilot was tested in two high-fidelity nonlinear simulators of two typical General Aviation aircraft. The results show that the autopilot was able to adapt appropriately to the different aircraft and was able to perform three-dimensional navigation and an ILS approach, without any modification to the controller. The autopilot was tested in moderate atmospheric turbulence, using consumer-grade sensors and actuators currently available in General Aviation aircraft. The generic adaptive autopilot was shown to be robust to atmospheric turbulence and sensor and actuator random noise. In both aircraft simulators, the autopilot adapted successfully to changes in airspeed, altitude, and configuration. This investigation proves the feasibility of a generic autopilot using direct adaptive controller. The autopilot does not need a priori information of the specific aircraft's dynamics to maintain its safety and stability arguments. Real-time parameter estimation of the aircraft dynamics are not needed. Recommendations for future work are provided.

The Accuracy Benefit of Multiple Amperometric Glucose Sensors in People With Type 1 Diabetes

PubMed Central

Castle, Jessica R.; Pitts, Amy; Hanavan, Kathryn; Muhly, Rhonda; El Youssef, Joseph; Hughes-Karvetski, Colleen; Kovatchev, Boris; Ward, W. Kenneth

2012-01-01

OBJECTIVE To improve glucose sensor accuracy in subjects with type 1 diabetes by using multiple sensors and to assess whether the benefit of redundancy is affected by intersensor distance. RESEARCH DESIGN AND METHODS Nineteen adults with type 1 diabetes wore four Dexcom SEVEN PLUS subcutaneous glucose sensors during two 9-h studies. One pair of sensors was worn on each side of the abdomen, with each sensor pair placed at a predetermined distance apart and 20 cm away from the opposite pair. Arterialized venous blood glucose levels were measured every 15 min, and sensor glucose values were recorded every 5 min. Sensors were calibrated once at the beginning of the study. RESULTS The use of four sensors significantly reduced very large errors compared with one sensor (0.4 vs. 2.6% of errors ≥50% from reference glucose, P < 0.001) and also improved overall accuracy (mean absolute relative difference, 11.6 vs. 14.8%, P < 0.001). Using only two sensors also significantly improved very large errors and accuracy. Intersensor distance did not affect the function of sensor pairs. CONCLUSIONS Sensor accuracy is significantly improved with the use of multiple sensors compared with the use of a single sensor. The benefit of redundancy is present even when sensors are positioned very closely together (7 mm). These findings are relevant to the design of an artificial pancreas device. PMID:22357189

The accuracy benefit of multiple amperometric glucose sensors in people with type 1 diabetes.

PubMed

Castle, Jessica R; Pitts, Amy; Hanavan, Kathryn; Muhly, Rhonda; El Youssef, Joseph; Hughes-Karvetski, Colleen; Kovatchev, Boris; Ward, W Kenneth

2012-04-01

To improve glucose sensor accuracy in subjects with type 1 diabetes by using multiple sensors and to assess whether the benefit of redundancy is affected by intersensor distance. Nineteen adults with type 1 diabetes wore four Dexcom SEVEN PLUS subcutaneous glucose sensors during two 9-h studies. One pair of sensors was worn on each side of the abdomen, with each sensor pair placed at a predetermined distance apart and 20 cm away from the opposite pair. Arterialized venous blood glucose levels were measured every 15 min, and sensor glucose values were recorded every 5 min. Sensors were calibrated once at the beginning of the study. The use of four sensors significantly reduced very large errors compared with one sensor (0.4 vs. 2.6% of errors ≥50% from reference glucose, P < 0.001) and also improved overall accuracy (mean absolute relative difference, 11.6 vs. 14.8%, P < 0.001). Using only two sensors also significantly improved very large errors and accuracy. Intersensor distance did not affect the function of sensor pairs. Sensor accuracy is significantly improved with the use of multiple sensors compared with the use of a single sensor. The benefit of redundancy is present even when sensors are positioned very closely together (7 mm). These findings are relevant to the design of an artificial pancreas device.

A gamma ray observatory ground attitude error analysis study using the generalized calibration system

NASA Technical Reports Server (NTRS)

Ketchum, E.

1988-01-01

The Goddard Space Flight Center (GSFC) Flight Dynamics Division (FDD) will be responsible for performing ground attitude determination for Gamma Ray Observatory (GRO) support. The study reported in this paper provides the FDD and the GRO project with ground attitude determination error information and illustrates several uses of the Generalized Calibration System (GCS). GCS, an institutional software tool in the FDD, automates the computation of the expected attitude determination uncertainty that a spacecraft will encounter during its mission. The GRO project is particularly interested in the uncertainty in the attitude determination using Sun sensors and a magnetometer when both star trackers are inoperable. In order to examine the expected attitude errors for GRO, a systematic approach was developed including various parametric studies. The approach identifies pertinent parameters and combines them to form a matrix of test runs in GCS. This matrix formed the basis for this study.

VEHIOT: Design and Evaluation of an IoT Architecture Based on Low-Cost Devices to Be Embedded in Production Vehicles.

PubMed

Redondo, Jonatan Pajares; González, Lisardo Prieto; Guzman, Javier García; Boada, Beatriz L; Díaz, Vicente

2018-02-06

Nowadays, the current vehicles are incorporating control systems in order to improve their stability and handling. These control systems need to know the vehicle dynamics through the variables (lateral acceleration, roll rate, roll angle, sideslip angle, etc.) that are obtained or estimated from sensors. For this goal, it is necessary to mount on vehicles not only low-cost sensors, but also low-cost embedded systems, which allow acquiring data from sensors and executing the developed algorithms to estimate and to control with novel higher speed computing. All these devices have to be integrated in an adequate architecture with enough performance in terms of accuracy, reliability and processing time. In this article, an architecture to carry out the estimation and control of vehicle dynamics has been developed. This architecture was designed considering the basic principles of IoT and integrates low-cost sensors and embedded hardware for orchestrating the experiments. A comparison of two different low-cost systems in terms of accuracy, acquisition time and reliability has been done. Both devices have been compared with the VBOX device from Racelogic, which has been used as the ground truth. The comparison has been made from tests carried out in a real vehicle. The lateral acceleration and roll rate have been analyzed in order to quantify the error of these devices.

VEHIOT: Design and Evaluation of an IoT Architecture Based on Low-Cost Devices to Be Embedded in Production Vehicles

PubMed Central

Díaz, Vicente

2018-01-01

Nowadays, the current vehicles are incorporating control systems in order to improve their stability and handling. These control systems need to know the vehicle dynamics through the variables (lateral acceleration, roll rate, roll angle, sideslip angle, etc.) that are obtained or estimated from sensors. For this goal, it is necessary to mount on vehicles not only low-cost sensors, but also low-cost embedded systems, which allow acquiring data from sensors and executing the developed algorithms to estimate and to control with novel higher speed computing. All these devices have to be integrated in an adequate architecture with enough performance in terms of accuracy, reliability and processing time. In this article, an architecture to carry out the estimation and control of vehicle dynamics has been developed. This architecture was designed considering the basic principles of IoT and integrates low-cost sensors and embedded hardware for orchestrating the experiments. A comparison of two different low-cost systems in terms of accuracy, acquisition time and reliability has been done. Both devices have been compared with the VBOX device from Racelogic, which has been used as the ground truth. The comparison has been made from tests carried out in a real vehicle. The lateral acceleration and roll rate have been analyzed in order to quantify the error of these devices. PMID:29415507

Error Analysis of Magnetohydrodynamic Angular Rate Sensor Combing with Coriolis Effect at Low Frequency.

PubMed

Ji, Yue; Xu, Mengjie; Li, Xingfei; Wu, Tengfei; Tuo, Weixiao; Wu, Jun; Dong, Jiuzhi

2018-06-13

The magnetohydrodynamic (MHD) angular rate sensor (ARS) with low noise level in ultra-wide bandwidth is developed in lasing and imaging applications, especially the line-of-sight (LOS) system. A modified MHD ARS combined with the Coriolis effect was studied in this paper to expand the sensor’s bandwidth at low frequency (<1 Hz), which is essential for precision LOS pointing and wide-bandwidth LOS jitter suppression. The model and the simulation method were constructed and a comprehensive solving method based on the magnetic and electric interaction methods was proposed. The numerical results on the Coriolis effect and the frequency response of the modified MHD ARS were detailed. In addition, according to the experimental results of the designed sensor consistent with the simulation results, an error analysis of model errors was discussed. Our study provides an error analysis method of MHD ARS combined with the Coriolis effect and offers a framework for future studies to minimize the error.

Study of a Solar Sensor for use in Space Vehicle Orientation Control Systems

NASA Technical Reports Server (NTRS)

Spencer, Paul R.

1961-01-01

The solar sensor described herein may be used for a variety of space operations requiring solar orientation. The use of silicon solar cells as the sensing elements provides the sensor with sufficient capability to withstand the hazards of a space environment. A method of arranging the cells in a sensor consists simply of mounting them at a large angle to the base. The use of an opaque shield placed between the cells and perpendicular to the base enhances the small-angle sensitivity while adding slightly to the bulk of the sensor. The difference in illumination of these cells as the result of an oblique incidence of the light rays from the reference source causes an electrical error signal which, when used in a battery-bridge circuit, requires a minimum of electrical processing for use in a space-vehicle orientation control system. An error which could occur after prolonged operation of the sensor is that resulting from asymmetrical aging of opposite cells. This could be periodically corrected with a balance potentiometer. A more routine error in the sensor is that produced by reflected earth radiation. This error may be eliminated over a large portion of the operation time by restricting the field of view and, consequently, the capture capability. A more sophisticated method of eliminating this error is to use separate sensors, for capture and fine pointing, along with a switching device. An experimental model has been constructed and tested to yield an output sensitivity of 1.2 millivolts per second of arc with a load resistance of 1,000 ohms and a reference light source of approximately 1,200 foot-candles delivered at the sensor.

Automatic Multi-sensor Data Quality Checking and Event Detection for Environmental Sensing

NASA Astrophysics Data System (ADS)

LIU, Q.; Zhang, Y.; Zhao, Y.; Gao, D.; Gallaher, D. W.; Lv, Q.; Shang, L.

2017-12-01

With the advances in sensing technologies, large-scale environmental sensing infrastructures are pervasively deployed to continuously collect data for various research and application fields, such as air quality study and weather condition monitoring. In such infrastructures, many sensor nodes are distributed in a specific area and each individual sensor node is capable of measuring several parameters (e.g., humidity, temperature, and pressure), providing massive data for natural event detection and analysis. However, due to the dynamics of the ambient environment, sensor data can be contaminated by errors or noise. Thus, data quality is still a primary concern for scientists before drawing any reliable scientific conclusions. To help researchers identify potential data quality issues and detect meaningful natural events, this work proposes a novel algorithm to automatically identify and rank anomalous time windows from multiple sensor data streams. More specifically, (1) the algorithm adaptively learns the characteristics of normal evolving time series and (2) models the spatial-temporal relationship among multiple sensor nodes to infer the anomaly likelihood of a time series window for a particular parameter in a sensor node. Case studies using different data sets are presented and the experimental results demonstrate that the proposed algorithm can effectively identify anomalous time windows, which may resulted from data quality issues and natural events.

Evaluation of a load cell model for dynamic calibration of the rotor systems research aircraft

NASA Technical Reports Server (NTRS)

Duval, R. W.; Bahrami, H.; Wellman, B.

1985-01-01

The Rotor Systems Research Aircraft uses load cells to isolate the rotor/transmission system from the fuselage. An analytical model of the relationship between applied rotor loads and the resulting load cell measurements is derived by applying a force-and-moment balance to the isolated rotor/transmission system. The model is then used to estimate the applied loads from measured load cell data, as obtained from a ground-based shake test. Using nominal design values for the parameters, the estimation errors, for the case of lateral forcing, were shown to be on the order of the sensor measurement noise in all but the roll axis. An unmodeled external load appears to be the source of the error in this axis.

Modeling Analysis of a Six-axis Force/Tactile Sensor for Robot Fingers and a Method for Decreasing Error

NASA Astrophysics Data System (ADS)

Luo, Minghua; Shimizu, Etsuro; Zhang, Feifei; Ito, Masanori

This paper describes a six-axis force/tactile sensor for robot fingers. A mathematical model of this sensor is proposed. By this model, the grasping force and its moments, and touching position of robot finger for holding an object can be calculated. A new sensor is fabricated based on this model, where the elastic sensing unit of the sensor is made of a brazen plate. A new compensating method for decreasing error is proposed. Furthermore, the performance of this sensor is examined. The test results present approximate relationship between theoretical input and output of the sensor. It is obvious that the performance of the new sensor is better than the sensor with no compensation.

Neuro-Analogical Gate Tuning of Trajectory Data Fusion for a Mecanum-Wheeled Special Needs Chair

PubMed Central

ElSaharty, M. A.; zakzouk, Ezz Eldin

2017-01-01

Trajectory tracking of mobile wheeled chairs using internal shaft encoder and inertia measurement unit(IMU), exhibits several complications and accumulated errors in the tracking process due to wheel slippage, offset drift and integration approximations. These errors can be realized when comparing localization results from such sensors with a camera tracking system. In long trajectory tracking, such errors can accumulate and result in significant deviations which make data from these sensors unreliable for tracking. Meanwhile the utilization of an external camera tracking system is not always a feasible solution depending on the implementation environment. This paper presents a novel sensor fusion method that combines the measurements of internal sensors to accurately predict the location of the wheeled chair in an environment. The method introduces a new analogical OR gate structured with tuned parameters using multi-layer feedforward neural network denoted as “Neuro-Analogical Gate” (NAG). The resulting system minimize any deviation error caused by the sensors, thus accurately tracking the wheeled chair location without the requirement of an external camera tracking system. The fusion methodology has been tested with a prototype Mecanum wheel-based chair, and significant improvement over tracking response, error and performance has been observed. PMID:28045973

Tilt error in cryospheric surface radiation measurements at high latitudes: a model study

NASA Astrophysics Data System (ADS)

Bogren, Wiley Steven; Faulkner Burkhart, John; Kylling, Arve

2016-03-01

We have evaluated the magnitude and makeup of error in cryospheric radiation observations due to small sensor misalignment in in situ measurements of solar irradiance. This error is examined through simulation of diffuse and direct irradiance arriving at a detector with a cosine-response fore optic. Emphasis is placed on assessing total error over the solar shortwave spectrum from 250 to 4500 nm, as well as supporting investigation over other relevant shortwave spectral ranges. The total measurement error introduced by sensor tilt is dominated by the direct component. For a typical high-latitude albedo measurement with a solar zenith angle of 60°, a sensor tilted by 1, 3, and 5° can, respectively introduce up to 2.7, 8.1, and 13.5 % error into the measured irradiance and similar errors in the derived albedo. Depending on the daily range of solar azimuth and zenith angles, significant measurement error can persist also in integrated daily irradiance and albedo. Simulations including a cloud layer demonstrate decreasing tilt error with increasing cloud optical depth.

A task control architecture for autonomous robots

NASA Technical Reports Server (NTRS)

Simmons, Reid; Mitchell, Tom

1990-01-01

An architecture is presented for controlling robots that have multiple tasks, operate in dynamic domains, and require a fair degree of autonomy. The architecture is built on several layers of functionality, including a distributed communication layer, a behavior layer for querying sensors, expanding goals, and executing commands, and a task level for managing the temporal aspects of planning and achieving goals, coordinating tasks, allocating resources, monitoring, and recovering from errors. Application to a legged planetary rover and an indoor mobile manipulator is described.

Estimation of Human Foot Motion During Normal Walking Using Inertial and Magnetic Sensor Measurements

DTIC Science & Technology

2012-07-01

and foot dynamics,” IEEE Trans. Biomed. Eng., vol. 54, no. 5, pp. 895–902, May 2007. [25] R. G. Brown and P. Y. C. Hwang , Introduction to Random Signals...the direction of displacement or position. In [18], Sabatini described a quaternion-based extended Kalman filter for determining the orientation of a...position. In [19], Foxlin used a foot-mounted IMMU from Inter- Sense incorporating the ZVU and an extended Kalman filter to achieve error performance

A Method for Testing the Dynamic Accuracy of Micro-Electro-Mechanical Systems (MEMS) Magnetic, Angular Rate, and Gravity (MARG) Sensors for Inertial Navigation Systems (INS) and Human Motion Tracking Applications

DTIC Science & Technology

2010-06-01

32 2. Low-Cost Framework........................................................................33 3. Low Magnetic Field ...that have a significant impact on the magnetic field measured by a MARG, which could potentially add errors that are due entirely to the test...minimize the impact on the local magnetic field , and the apparatus was made as rigidly as possible using 2 x 4s to minimize any out of plane motions that

Error analysis in a stereo vision-based pedestrian detection sensor for collision avoidance applications.

PubMed

Llorca, David F; Sotelo, Miguel A; Parra, Ignacio; Ocaña, Manuel; Bergasa, Luis M

2010-01-01

This paper presents an analytical study of the depth estimation error of a stereo vision-based pedestrian detection sensor for automotive applications such as pedestrian collision avoidance and/or mitigation. The sensor comprises two synchronized and calibrated low-cost cameras. Pedestrians are detected by combining a 3D clustering method with Support Vector Machine-based (SVM) classification. The influence of the sensor parameters in the stereo quantization errors is analyzed in detail providing a point of reference for choosing the sensor setup according to the application requirements. The sensor is then validated in real experiments. Collision avoidance maneuvers by steering are carried out by manual driving. A real time kinematic differential global positioning system (RTK-DGPS) is used to provide ground truth data corresponding to both the pedestrian and the host vehicle locations. The performed field test provided encouraging results and proved the validity of the proposed sensor for being used in the automotive sector towards applications such as autonomous pedestrian collision avoidance.

Error Analysis in a Stereo Vision-Based Pedestrian Detection Sensor for Collision Avoidance Applications

PubMed Central

Llorca, David F.; Sotelo, Miguel A.; Parra, Ignacio; Ocaña, Manuel; Bergasa, Luis M.

2010-01-01

This paper presents an analytical study of the depth estimation error of a stereo vision-based pedestrian detection sensor for automotive applications such as pedestrian collision avoidance and/or mitigation. The sensor comprises two synchronized and calibrated low-cost cameras. Pedestrians are detected by combining a 3D clustering method with Support Vector Machine-based (SVM) classification. The influence of the sensor parameters in the stereo quantization errors is analyzed in detail providing a point of reference for choosing the sensor setup according to the application requirements. The sensor is then validated in real experiments. Collision avoidance maneuvers by steering are carried out by manual driving. A real time kinematic differential global positioning system (RTK-DGPS) is used to provide ground truth data corresponding to both the pedestrian and the host vehicle locations. The performed field test provided encouraging results and proved the validity of the proposed sensor for being used in the automotive sector towards applications such as autonomous pedestrian collision avoidance. PMID:22319323

Influence of Errors in Tactile Sensors on Some High Level Parameters Used for Manipulation with Robotic Hands.

PubMed

Sánchez-Durán, José A; Hidalgo-López, José A; Castellanos-Ramos, Julián; Oballe-Peinado, Óscar; Vidal-Verdú, Fernando

2015-08-19

Tactile sensors suffer from many types of interference and errors like crosstalk, non-linearity, drift or hysteresis, therefore calibration should be carried out to compensate for these deviations. However, this procedure is difficult in sensors mounted on artificial hands for robots or prosthetics for instance, where the sensor usually bends to cover a curved surface. Moreover, the calibration procedure should be repeated often because the correction parameters are easily altered by time and surrounding conditions. Furthermore, this intensive and complex calibration could be less determinant, or at least simpler. This is because manipulation algorithms do not commonly use the whole data set from the tactile image, but only a few parameters such as the moments of the tactile image. These parameters could be changed less by common errors and interferences, or at least their variations could be in the order of those caused by accepted limitations, like reduced spatial resolution. This paper shows results from experiments to support this idea. The experiments are carried out with a high performance commercial sensor as well as with a low-cost error-prone sensor built with a common procedure in robotics.

An Enhanced MEMS Error Modeling Approach Based on Nu-Support Vector Regression

PubMed Central

Bhatt, Deepak; Aggarwal, Priyanka; Bhattacharya, Prabir; Devabhaktuni, Vijay

2012-01-01

Micro Electro Mechanical System (MEMS)-based inertial sensors have made possible the development of a civilian land vehicle navigation system by offering a low-cost solution. However, the accurate modeling of the MEMS sensor errors is one of the most challenging tasks in the design of low-cost navigation systems. These sensors exhibit significant errors like biases, drift, noises; which are negligible for higher grade units. Different conventional techniques utilizing the Gauss Markov model and neural network method have been previously utilized to model the errors. However, Gauss Markov model works unsatisfactorily in the case of MEMS units due to the presence of high inherent sensor errors. On the other hand, modeling the random drift utilizing Neural Network (NN) is time consuming, thereby affecting its real-time implementation. We overcome these existing drawbacks by developing an enhanced Support Vector Machine (SVM) based error model. Unlike NN, SVMs do not suffer from local minimisation or over-fitting problems and delivers a reliable global solution. Experimental results proved that the proposed SVM approach reduced the noise standard deviation by 10–35% for gyroscopes and 61–76% for accelerometers. Further, positional error drifts under static conditions improved by 41% and 80% in comparison to NN and GM approaches. PMID:23012552

Research on MEMS sensor in hydraulic system flow detection

NASA Astrophysics Data System (ADS)

Zhang, Hongpeng; Zhang, Yindong; Liu, Dong; Ji, Yulong; Jiang, Jihai; Sun, Yuqing

2011-05-01

With the development of mechatronics technology and fault diagnosis theory, people regard flow information much more than before. Cheap, fast and accurate flow sensors are urgently needed by hydraulic industry. So MEMS sensor, which is small, low cost, well performed and easy to integrate, will surely play an important role in this field. Based on the new method of flow measurement which was put forward by our research group, this paper completed the measurement of flow rate in hydraulic system by setting up the mathematical model, using numerical simulation method and doing physical experiment. Based on viscous fluid flow equations we deduced differential pressure-velocity model of this new sensor and did optimization on parameters. Then, we designed and manufactured the throttle and studied the velocity and pressure field inside the sensor by FLUENT. Also in simulation we get the differential pressure-velocity curve .The model machine was simulated too to direct experiment. In the static experiments we calibrated the MEMS sensing element and built some sample sensors. Then in a hydraulic testing system we compared the sensor signal with a turbine meter. It presented good linearity and could meet general hydraulic system use. Based on the CFD curves, we analyzed the error reasons and made some suggestion to improve. In the dynamic test, we confirmed this sensor can realize high frequency flow detection by a 7 piston-pump.

Research on MEMS sensor in hydraulic system flow detection

NASA Astrophysics Data System (ADS)

Zhang, Hongpeng; Zhang, Yindong; Liu, Dong; Ji, Yulong; Jiang, Jihai; Sun, Yuqing

2010-12-01

With the development of mechatronics technology and fault diagnosis theory, people regard flow information much more than before. Cheap, fast and accurate flow sensors are urgently needed by hydraulic industry. So MEMS sensor, which is small, low cost, well performed and easy to integrate, will surely play an important role in this field. Based on the new method of flow measurement which was put forward by our research group, this paper completed the measurement of flow rate in hydraulic system by setting up the mathematical model, using numerical simulation method and doing physical experiment. Based on viscous fluid flow equations we deduced differential pressure-velocity model of this new sensor and did optimization on parameters. Then, we designed and manufactured the throttle and studied the velocity and pressure field inside the sensor by FLUENT. Also in simulation we get the differential pressure-velocity curve .The model machine was simulated too to direct experiment. In the static experiments we calibrated the MEMS sensing element and built some sample sensors. Then in a hydraulic testing system we compared the sensor signal with a turbine meter. It presented good linearity and could meet general hydraulic system use. Based on the CFD curves, we analyzed the error reasons and made some suggestion to improve. In the dynamic test, we confirmed this sensor can realize high frequency flow detection by a 7 piston-pump.

Amperometric Glucose Sensors: Sources of Error and Potential Benefit of Redundancy

PubMed Central

Castle, Jessica R.; Kenneth Ward, W.

2010-01-01

Amperometric glucose sensors have advanced the care of patients with diabetes and are being studied to control insulin delivery in the research setting. However, at times, currently available sensors demonstrate suboptimal accuracy, which can result from calibration error, sensor drift, or lag. Inaccuracy can be particularly problematic in a closed-loop glycemic control system. In such a system, the use of two sensors allows selection of the more accurate sensor as the input to the controller. In our studies in subjects with type 1 diabetes, the accuracy of the better of two sensors significantly exceeded the accuracy of a single, randomly selected sensor. If an array with three or more sensors were available, it would likely allow even better accuracy with the use of voting. PMID:20167187

Suitability of Smartphone Inertial Sensors for Real-Time Biofeedback Applications.

PubMed

Kos, Anton; Tomažič, Sašo; Umek, Anton

2016-02-27

This article studies the suitability of smartphones with built-in inertial sensors for biofeedback applications. Biofeedback systems use various sensors to measure body functions and parameters. These sensor data are analyzed, and the results are communicated back to the user, who then tries to act on the feedback signals. Smartphone inertial sensors can be used to capture body movements in biomechanical biofeedback systems. These sensors exhibit various inaccuracies that induce significant angular and positional errors. We studied deterministic and random errors of smartphone accelerometers and gyroscopes, primarily focusing on their biases. Based on extensive measurements, we determined accelerometer and gyroscope noise models and bias variation ranges. Then, we compiled a table of predicted positional and angular errors under various biofeedback system operation conditions. We suggest several bias compensation options that are suitable for various examples of use in real-time biofeedback applications. Measurements within the developed experimental biofeedback application show that under certain conditions, even uncompensated sensors can be used for real-time biofeedback. For general use, especially for more demanding biofeedback applications, sensor biases should be compensated. We are convinced that real-time biofeedback systems based on smartphone inertial sensors are applicable to many similar examples in sports, healthcare, and other areas.

Suitability of Smartphone Inertial Sensors for Real-Time Biofeedback Applications

PubMed Central

Kos, Anton; Tomažič, Sašo; Umek, Anton

2016-01-01

This article studies the suitability of smartphones with built-in inertial sensors for biofeedback applications. Biofeedback systems use various sensors to measure body functions and parameters. These sensor data are analyzed, and the results are communicated back to the user, who then tries to act on the feedback signals. Smartphone inertial sensors can be used to capture body movements in biomechanical biofeedback systems. These sensors exhibit various inaccuracies that induce significant angular and positional errors. We studied deterministic and random errors of smartphone accelerometers and gyroscopes, primarily focusing on their biases. Based on extensive measurements, we determined accelerometer and gyroscope noise models and bias variation ranges. Then, we compiled a table of predicted positional and angular errors under various biofeedback system operation conditions. We suggest several bias compensation options that are suitable for various examples of use in real-time biofeedback applications. Measurements within the developed experimental biofeedback application show that under certain conditions, even uncompensated sensors can be used for real-time biofeedback. For general use, especially for more demanding biofeedback applications, sensor biases should be compensated. We are convinced that real-time biofeedback systems based on smartphone inertial sensors are applicable to many similar examples in sports, healthcare, and other areas. PMID:26927125

A Formal Approach to the Selection by Minimum Error and Pattern Method for Sensor Data Loss Reduction in Unstable Wireless Sensor Network Communications

PubMed Central

Kim, Changhwa; Shin, DongHyun

2017-01-01

There are wireless networks in which typically communications are unsafe. Most terrestrial wireless sensor networks belong to this category of networks. Another example of an unsafe communication network is an underwater acoustic sensor network (UWASN). In UWASNs in particular, communication failures occur frequently and the failure durations can range from seconds up to a few hours, days, or even weeks. These communication failures can cause data losses significant enough to seriously damage human life or property, depending on their application areas. In this paper, we propose a framework to reduce sensor data loss during communication failures and we present a formal approach to the Selection by Minimum Error and Pattern (SMEP) method that plays the most important role for the reduction in sensor data loss under the proposed framework. The SMEP method is compared with other methods to validate its effectiveness through experiments using real-field sensor data sets. Moreover, based on our experimental results and performance comparisons, the SMEP method has been validated to be better than others in terms of the average sensor data value error rate caused by sensor data loss. PMID:28498312

A Formal Approach to the Selection by Minimum Error and Pattern Method for Sensor Data Loss Reduction in Unstable Wireless Sensor Network Communications.

PubMed

Kim, Changhwa; Shin, DongHyun

2017-05-12

There are wireless networks in which typically communications are unsafe. Most terrestrial wireless sensor networks belong to this category of networks. Another example of an unsafe communication network is an underwater acoustic sensor network (UWASN). In UWASNs in particular, communication failures occur frequently and the failure durations can range from seconds up to a few hours, days, or even weeks. These communication failures can cause data losses significant enough to seriously damage human life or property, depending on their application areas. In this paper, we propose a framework to reduce sensor data loss during communication failures and we present a formal approach to the Selection by Minimum Error and Pattern (SMEP) method that plays the most important role for the reduction in sensor data loss under the proposed framework. The SMEP method is compared with other methods to validate its effectiveness through experiments using real-field sensor data sets. Moreover, based on our experimental results and performance comparisons, the SMEP method has been validated to be better than others in terms of the average sensor data value error rate caused by sensor data loss.

Design and Fabrication of a MEMS Flow Sensor and Its Application in Precise Liquid Dispensing

PubMed Central

Liu, Yaxin; Chen, Liguo; Sun, Lining

2009-01-01

A high speed MEMS flow sensor to enhance the reliability and accuracy of a liquid dispensing system is proposed. Benefitting from the sensor information feedback, the system can self-adjust the open time of the solenoid valve to accurately dispense desired volumes of reagent without any pre-calibration. First, an integrated high-speed liquid flow sensor based on the measurement of the pressure difference across a flow channel is presented. Dimensions of the micro-flow channel and two pressure sensors have been appropriately designed to meet the static and dynamic requirements of the liquid dispensing system. Experiments results show that the full scale (FS) flow measurement ranges up to 80 μL/s, with a nonlinearity better than 0.51% FS. Secondly, a novel closed-loop control strategy is proposed to calculate the valve open time in each dispensing cycle, which makes the system immune to liquid viscosity, pressure fluctuation, and other sources of error. Finally, dispensing results show that the system can achieve better dispensing performance, and the coefficient of variance (CV) for liquid dispensing is below 3% at 1 μL and below 4% at 100 nL. PMID:22408517

Design and Fabrication of a MEMS Flow Sensor and Its Application in Precise Liquid Dispensing.

PubMed

Liu, Yaxin; Chen, Liguo; Sun, Lining

2009-01-01

A high speed MEMS flow sensor to enhance the reliability and accuracy of a liquid dispensing system is proposed. Benefitting from the sensor information feedback, the system can self-adjust the open time of the solenoid valve to accurately dispense desired volumes of reagent without any pre-calibration. First, an integrated high-speed liquid flow sensor based on the measurement of the pressure difference across a flow channel is presented. Dimensions of the micro-flow channel and two pressure sensors have been appropriately designed to meet the static and dynamic requirements of the liquid dispensing system. Experiments results show that the full scale (FS) flow measurement ranges up to 80 μL/s, with a nonlinearity better than 0.51% FS. Secondly, a novel closed-loop control strategy is proposed to calculate the valve open time in each dispensing cycle, which makes the system immune to liquid viscosity, pressure fluctuation, and other sources of error. Finally, dispensing results show that the system can achieve better dispensing performance, and the coefficient of variance (CV) for liquid dispensing is below 3% at 1 μL and below 4% at 100 nL.

An improved genetic algorithm for increasing the addressing accuracy of encoding fiber Bragg grating sensor network

NASA Astrophysics Data System (ADS)

Liu, Huanlin; Wang, Chujun; Chen, Yong

2018-01-01

Large-capacity encoding fiber Bragg grating (FBG) sensor network is widely used in modern long-term health monitoring system. Encoding FBG sensors have greatly improved the capacity of distributed FBG sensor network. However, the error of addressing increases correspondingly with the enlarging of capacity. To address the issue, an improved algorithm called genetic tracking algorithm (GTA) is proposed in the paper. In the GTA, for improving the success rate of matching and reducing the large number of redundant matching operations generated by sequential matching, the individuals are designed based on the feasible matching. Then, two kinds of self-crossover ways and a dynamic variation during mutation process are designed to increase the diversity of individuals and to avoid falling into local optimum. Meanwhile, an assistant decision is proposed to handle the issue that the GTA cannot solve when the variation of sensor information is highly overlapped. The simulation results indicate that the proposed GTA has higher accuracy compared with the traditional tracking algorithm and the enhanced tracking algorithm. In order to address the problems of spectrum fragmentation and low sharing degree of spectrum resources in survivable.

Where and when should sensors move? Sampling using the expected value of information.

PubMed

de Bruin, Sytze; Ballari, Daniela; Bregt, Arnold K

2012-11-26

In case of an environmental accident, initially available data are often insufficient for properly managing the situation. In this paper, new sensor observations are iteratively added to an initial sample by maximising the global expected value of information of the points for decision making. This is equivalent to minimizing the aggregated expected misclassification costs over the study area. The method considers measurement error and different costs for class omissions and false class commissions. Constraints imposed by a mobile sensor web are accounted for using cost distances to decide which sensor should move to the next sample location. The method is demonstrated using synthetic examples of static and dynamic phenomena. This allowed computation of the true misclassification costs and comparison with other sampling approaches. The probability of local contamination levels being above a given critical threshold were computed by indicator kriging. In the case of multiple sensors being relocated simultaneously, a genetic algorithm was used to find sets of suitable new measurement locations. Otherwise, all grid nodes were searched exhaustively, which is computationally demanding. In terms of true misclassification costs, the method outperformed random sampling and sampling based on minimisation of the kriging variance.

Where and When Should Sensors Move? Sampling Using the Expected Value of Information

PubMed Central

de Bruin, Sytze; Ballari, Daniela; Bregt, Arnold K.

2012-01-01

In case of an environmental accident, initially available data are often insufficient for properly managing the situation. In this paper, new sensor observations are iteratively added to an initial sample by maximising the global expected value of information of the points for decision making. This is equivalent to minimizing the aggregated expected misclassification costs over the study area. The method considers measurement error and different costs for class omissions and false class commissions. Constraints imposed by a mobile sensor web are accounted for using cost distances to decide which sensor should move to the next sample location. The method is demonstrated using synthetic examples of static and dynamic phenomena. This allowed computation of the true misclassification costs and comparison with other sampling approaches. The probability of local contamination levels being above a given critical threshold were computed by indicator kriging. In the case of multiple sensors being relocated simultaneously, a genetic algorithm was used to find sets of suitable new measurement locations. Otherwise, all grid nodes were searched exhaustively, which is computationally demanding. In terms of true misclassification costs, the method outperformed random sampling and sampling based on minimisation of the kriging variance. PMID:23443379

Two-Time Scale Virtual Sensor Design for Vibration Observation of a Translational Flexible-Link Manipulator Based on Singular Perturbation and Differential Games

PubMed Central

Ju, Jinyong; Li, Wei; Wang, Yuqiao; Fan, Mengbao; Yang, Xuefeng

2016-01-01

Effective feedback control requires all state variable information of the system. However, in the translational flexible-link manipulator (TFM) system, it is unrealistic to measure the vibration signals and their time derivative of any points of the TFM by infinite sensors. With the rigid-flexible coupling between the global motion of the rigid base and the elastic vibration of the flexible-link manipulator considered, a two-time scale virtual sensor, which includes the speed observer and the vibration observer, is designed to achieve the estimation for the vibration signals and their time derivative of the TFM, as well as the speed observer and the vibration observer are separately designed for the slow and fast subsystems, which are decomposed from the dynamic model of the TFM by the singular perturbation. Additionally, based on the linear-quadratic differential games, the observer gains of the two-time scale virtual sensor are optimized, which aims to minimize the estimation error while keeping the observer stable. Finally, the numerical calculation and experiment verify the efficiency of the designed two-time scale virtual sensor. PMID:27801840

Designing non-Hermitian dynamics for conservative state evolution on the Bloch sphere

NASA Astrophysics Data System (ADS)

Yu, Sunkyu; Piao, Xianji; Park, Namkyoo

2018-03-01

An evolution on the Bloch sphere is the fundamental state transition, including optical polarization controls and qubit operations. Conventional evolution of a polarization state or qubit is implemented within a closed system that automatically satisfies energy conservation from the Hermitian formalism. Although particular forms of static non-Hermitian Hamiltonians, such as parity-time-symmetric Hamiltonians, allow conservative states in an open system, the criteria for the energy conservation in a dynamical open system have not been fully explored. Here, we derive the condition of conservative state evolution in open-system dynamics and its inverse design method, by developing the non-Hermitian modification of the Larmor precession equation. We show that the geometrically designed locus on the Bloch sphere can be realized by different forms of dynamics, leading to the isolocus family of non-Hermitian dynamics. This increased degree of freedom allows the complementary phenomena of error-robust and highly sensitive evolutions on the Bloch sphere, which could be applicable to stable polarizers, quantum gates, and optimized sensors in dynamical open systems.

Fourier optics analysis of grating sensors with tilt errors.

PubMed

Ferhanoglu, Onur; Toy, M Fatih; Urey, Hakan

2011-06-15

Dynamic diffraction gratings can be microfabricated with precision and offer extremely sensitive displacement measurements and light intensity modulation. The effect of pure translation of the moving part of the grating on diffracted order intensities is well known. This study focuses on the parameters that limit the intensity and the contrast of the interference. The effects of grating duty cycle, mirror reflectivities, sensor tilt and detector size are investigated using Fourier optics theory and Gaussian beam optics. Analytical findings reveal that fringe visibility becomes <0.3 when the optical path variation exceeds half the wavelength within the grating interferometer. The fringe visibility can be compensated by monitoring the interfering portion of the diffracted order light only through detector size reduction in the expense of optical power. Experiments were conducted with a grating interferometer that resulted in an eightfold increase in fringe visibility with reduced detector size, which is in agreement with theory. Findings show that diffraction grating readout principle is not limited to translating sensors but also can be used for sensors with tilt or other deflection modes.

On the frequency response of a Wenglor particle-counting system for aeolian transport measurements

NASA Astrophysics Data System (ADS)

Bauer, Bernard O.; Davidson-Arnott, Robin G. D.; Hilton, Michael J.; Fraser, Douglas

2018-06-01

A commonly deployed particle-counting system for aeolian saltation flux, consisting of a Wenglor fork sensor and an Onset Hobo Pulse Input Adapter linked to an Onset Hobo Energy Logger Pro data logger, was tested for frequency response. The Wenglor fork sensor is an optical gate device that has very fast switching capacity that can accommodate the time of flight of saltating sand particles through the sensing volume with the exception of very fine sand or silt and very quickly moving particles. The Pulse Input Adapter, in contrast, imposes limitations on the frequency response of the system. The manufacturer of the pulse adapter specifies an upper limit of 120 Hz, although bench tests with an electronic pulse generator indicate that the frequency response of the Pulse Input Adapter, in isolation, is excellent up to 3000 Hz, with only small error (less than 1.6%) due to under-counting during data transfer intervals. A mechanical test of the integrated system (fork sensor, pulse input adapter, and data logger) demonstrates excellent performance up to about 700 Hz (less than 2% error), but significant under-counting above 1000 Hz for unknown reasons. This specific particle-counting system therefore has a frequency response that is well suited for investigation of the dynamics of aeolian saltation as typically encountered in most field conditions on coastal beaches with the exception of extreme wind events and very small particle sizes.

A Dual-Linear Kalman Filter for Real-Time Orientation Determination System Using Low-Cost MEMS Sensors.

PubMed

Zhang, Shengzhi; Yu, Shuai; Liu, Chaojun; Yuan, Xuebing; Liu, Sheng

2016-02-20

To provide a long-time reliable orientation, sensor fusion technologies are widely used to integrate available inertial sensors for the low-cost orientation estimation. In this paper, a novel dual-linear Kalman filter was designed for a multi-sensor system integrating MEMS gyros, an accelerometer, and a magnetometer. The proposed filter precludes the impacts of magnetic disturbances on the pitch and roll which the heading is subjected to. The filter can achieve robust orientation estimation for different statistical models of the sensors. The root mean square errors (RMSE) of the estimated attitude angles are reduced by 30.6% under magnetic disturbances. Owing to the reduction of system complexity achieved by smaller matrix operations, the mean total time consumption is reduced by 23.8%. Meanwhile, the separated filter offers greater flexibility for the system configuration, as it is possible to switch on or off the second stage filter to include or exclude the magnetometer compensation for the heading. Online experiments were performed on the homemade miniature orientation determination system (MODS) with the turntable. The average RMSE of estimated orientation are less than 0.4° and 1° during the static and low-dynamic tests, respectively. More realistic tests on two-wheel self-balancing vehicle driving and indoor pedestrian walking were carried out to evaluate the performance of the designed MODS when high accelerations and angular rates were introduced. Test results demonstrate that the MODS is applicable for the orientation estimation under various dynamic conditions. This paper provides a feasible alternative for low-cost orientation determination.

A Dual-Linear Kalman Filter for Real-Time Orientation Determination System Using Low-Cost MEMS Sensors

PubMed Central

Zhang, Shengzhi; Yu, Shuai; Liu, Chaojun; Yuan, Xuebing; Liu, Sheng

2016-01-01

To provide a long-time reliable orientation, sensor fusion technologies are widely used to integrate available inertial sensors for the low-cost orientation estimation. In this paper, a novel dual-linear Kalman filter was designed for a multi-sensor system integrating MEMS gyros, an accelerometer, and a magnetometer. The proposed filter precludes the impacts of magnetic disturbances on the pitch and roll which the heading is subjected to. The filter can achieve robust orientation estimation for different statistical models of the sensors. The root mean square errors (RMSE) of the estimated attitude angles are reduced by 30.6% under magnetic disturbances. Owing to the reduction of system complexity achieved by smaller matrix operations, the mean total time consumption is reduced by 23.8%. Meanwhile, the separated filter offers greater flexibility for the system configuration, as it is possible to switch on or off the second stage filter to include or exclude the magnetometer compensation for the heading. Online experiments were performed on the homemade miniature orientation determination system (MODS) with the turntable. The average RMSE of estimated orientation are less than 0.4° and 1° during the static and low-dynamic tests, respectively. More realistic tests on two-wheel self-balancing vehicle driving and indoor pedestrian walking were carried out to evaluate the performance of the designed MODS when high accelerations and angular rates were introduced. Test results demonstrate that the MODS is applicable for the orientation estimation under various dynamic conditions. This paper provides a feasible alternative for low-cost orientation determination. PMID:26907294

Error Modelling for Multi-Sensor Measurements in Infrastructure-Free Indoor Navigation

PubMed Central

Ruotsalainen, Laura; Kirkko-Jaakkola, Martti; Rantanen, Jesperi; Mäkelä, Maija

2018-01-01

The long-term objective of our research is to develop a method for infrastructure-free simultaneous localization and mapping (SLAM) and context recognition for tactical situational awareness. Localization will be realized by propagating motion measurements obtained using a monocular camera, a foot-mounted Inertial Measurement Unit (IMU), sonar, and a barometer. Due to the size and weight requirements set by tactical applications, Micro-Electro-Mechanical (MEMS) sensors will be used. However, MEMS sensors suffer from biases and drift errors that may substantially decrease the position accuracy. Therefore, sophisticated error modelling and implementation of integration algorithms are key for providing a viable result. Algorithms used for multi-sensor fusion have traditionally been different versions of Kalman filters. However, Kalman filters are based on the assumptions that the state propagation and measurement models are linear with additive Gaussian noise. Neither of the assumptions is correct for tactical applications, especially for dismounted soldiers, or rescue personnel. Therefore, error modelling and implementation of advanced fusion algorithms are essential for providing a viable result. Our approach is to use particle filtering (PF), which is a sophisticated option for integrating measurements emerging from pedestrian motion having non-Gaussian error characteristics. This paper discusses the statistical modelling of the measurement errors from inertial sensors and vision based heading and translation measurements to include the correct error probability density functions (pdf) in the particle filter implementation. Then, model fitting is used to verify the pdfs of the measurement errors. Based on the deduced error models of the measurements, particle filtering method is developed to fuse all this information, where the weights of each particle are computed based on the specific models derived. The performance of the developed method is tested via two experiments, one at a university’s premises and another in realistic tactical conditions. The results show significant improvement on the horizontal localization when the measurement errors are carefully modelled and their inclusion into the particle filtering implementation correctly realized. PMID:29443918

A Novel Angular Acceleration Sensor Based on the Electromagnetic Induction Principle and Investigation of Its Calibration Tests

PubMed Central

Zhao, Hao; Feng, Hao

2013-01-01

An angular acceleration sensor can be used for the dynamic analysis of human and joint motions. In this paper, an angular acceleration sensor with novel structure based on the principle of electromagnetic induction is designed. The method involves the construction of a constant magnetic field by the excitation windings of sensor, and the cup-shaped rotor that cut the magnetic field. The output windings of the sensor generate an electromotive force, which is directly proportional to the angular acceleration through the electromagnetic coupling when the rotor has rotational angular acceleration. The mechanical structure and the magnetic working circuit of the sensor are described. The output properties and the mathematical model including the transfer function and state-space model of the sensor are established. The asymptotical stability of the sensor when it is working is verified by the Lyapunov Theorem. An angular acceleration calibration device based on the torsional pendulum principle is designed. The method involves the coaxial connection of the angular acceleration sensor, torsion pendulum and a high-precision angle sensor, and then an initial external force is applied to the torsion pendulum to produce a periodic damping angle oscillation. The angular acceleration sensor and the angle sensor will generate two corresponding electrical signals. The sensitivity coefficient of the angular acceleration sensor can be obtained after processing these two-channel signals. The experiment results show that the sensitivity coefficient of the sensor is about 17.29 mv/Krad·s2. Finally, the errors existing in the practical applications of the sensor are discussed and the corresponding improvement measures are proposed to provide effective technical support for the practical promotion of the novel sensor. PMID:23941911

Accounting for sampling variability, injury under-reporting, and sensor error in concussion injury risk curves.

PubMed

Elliott, Michael R; Margulies, Susan S; Maltese, Matthew R; Arbogast, Kristy B

2015-09-18

There has been recent dramatic increase in the use of sensors affixed to the heads or helmets of athletes to measure the biomechanics of head impacts that lead to concussion. The relationship between injury and linear or rotational head acceleration measured by such sensors can be quantified with an injury risk curve. The utility of the injury risk curve relies on the accuracy of both the clinical diagnosis and the biomechanical measure. The focus of our analysis was to demonstrate the influence of three sources of error on the shape and interpretation of concussion injury risk curves: sampling variability associated with a rare event, concussion under-reporting, and sensor measurement error. We utilized Bayesian statistical methods to generate synthetic data from previously published concussion injury risk curves developed using data from helmet-based sensors on collegiate football players and assessed the effect of the three sources of error on the risk relationship. Accounting for sampling variability adds uncertainty or width to the injury risk curve. Assuming a variety of rates of unreported concussions in the non-concussed group, we found that accounting for under-reporting lowers the rotational acceleration required for a given concussion risk. Lastly, after accounting for sensor error, we find strengthened relationships between rotational acceleration and injury risk, further lowering the magnitude of rotational acceleration needed for a given risk of concussion. As more accurate sensors are designed and more sensitive and specific clinical diagnostic tools are introduced, our analysis provides guidance for the future development of comprehensive concussion risk curves. Copyright © 2015 Elsevier Ltd. All rights reserved.

Analysis and Calibration of Sources of Electronic Error in PSD Sensor Response.

PubMed

Rodríguez-Navarro, David; Lázaro-Galilea, José Luis; Bravo-Muñoz, Ignacio; Gardel-Vicente, Alfredo; Tsirigotis, Georgios

2016-04-29

In order to obtain very precise measurements of the position of agents located at a considerable distance using a sensor system based on position sensitive detectors (PSD), it is necessary to analyze and mitigate the factors that generate substantial errors in the system's response. These sources of error can be divided into electronic and geometric factors. The former stem from the nature and construction of the PSD as well as the performance, tolerances and electronic response of the system, while the latter are related to the sensor's optical system. Here, we focus solely on the electrical effects, since the study, analysis and correction of these are a prerequisite for subsequently addressing geometric errors. A simple calibration method is proposed, which considers PSD response, component tolerances, temperature variations, signal frequency used, signal to noise ratio (SNR), suboptimal operational amplifier parameters, and analog to digital converter (ADC) quantitation SNRQ, etc. Following an analysis of these effects and calibration of the sensor, it was possible to correct the errors, thus rendering the effects negligible, as reported in the results section.

Statistical Sensor Fusion of a 9-DOF Mems Imu for Indoor Navigation

NASA Astrophysics Data System (ADS)

Chow, J. C. K.

2017-09-01

Sensor fusion of a MEMS IMU with a magnetometer is a popular system design, because such 9-DoF (degrees of freedom) systems are capable of achieving drift-free 3D orientation tracking. However, these systems are often vulnerable to ambient magnetic distortions and lack useful position information; in the absence of external position aiding (e.g. satellite/ultra-wideband positioning systems) the dead-reckoned position accuracy from a 9-DoF MEMS IMU deteriorates rapidly due to unmodelled errors. Positioning information is valuable in many satellite-denied geomatics applications (e.g. indoor navigation, location-based services, etc.). This paper proposes an improved 9-DoF IMU indoor pose tracking method using batch optimization. By adopting a robust in-situ user self-calibration approach to model the systematic errors of the accelerometer, gyroscope, and magnetometer simultaneously in a tightly-coupled post-processed least-squares framework, the accuracy of the estimated trajectory from a 9-DoF MEMS IMU can be improved. Through a combination of relative magnetic measurement updates and a robust weight function, the method is able to tolerate a high level of magnetic distortions. The proposed auto-calibration method was tested in-use under various heterogeneous magnetic field conditions to mimic a person walking with the sensor in their pocket, a person checking their phone, and a person walking with a smartwatch. In these experiments, the presented algorithm improved the in-situ dead-reckoning orientation accuracy by 79.8-89.5 % and the dead-reckoned positioning accuracy by 72.9-92.8 %, thus reducing the relative positioning error from metre-level to decimetre-level after ten seconds of integration, without making assumptions about the user's dynamics.

Real-time catheter tracking for high-dose-rate prostate brachytherapy using an electromagnetic 3D-guidance device: A preliminary performance study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou Jun; Sebastian, Evelyn; Mangona, Victor

2013-02-15

Purpose: In order to increase the accuracy and speed of catheter reconstruction in a high-dose-rate (HDR) prostate implant procedure, an automatic tracking system has been developed using an electromagnetic (EM) device (trakSTAR, Ascension Technology, VT). The performance of the system, including the accuracy and noise level with various tracking parameters and conditions, were investigated. Methods: A direct current (dc) EM transmitter (midrange model) and a sensor with diameter of 1.3 mm (Model 130) were used in the trakSTAR system for tracking catheter position during HDR prostate brachytherapy. Localization accuracy was assessed under both static and dynamic analyses conditions. For themore » static analysis, a calibration phantom was used to investigate error dependency on operating room (OR) table height (bottom vs midposition vs top), sensor position (distal tip of catheter vs connector end of catheter), direction [left-right (LR) vs anterior-posterior (AP) vs superior-inferior (SI)], sampling frequency (40 vs 80 vs 120 Hz), and interference from OR equipment (present vs absent). The mean and standard deviation of the localization offset in each direction and the corresponding error vectors were calculated. For dynamic analysis, the paths of five straight catheters were tracked to study the effects of directions, sampling frequency, and interference of EM field. Statistical analysis was conducted to compare the results in different configurations. Results: When interference was present in the static analysis, the error vectors were significantly higher at the top table position (3.3 {+-} 1.3 vs 1.8 {+-} 0.9 mm at bottom and 1.7 {+-} 1.0 mm at middle, p < 0.001), at catheter end position (3.1 {+-} 1.1 vs 1.4 {+-} 0.7 mm at the tip position, p < 0.001), and at 40 Hz sampling frequency (2.6 {+-} 1.1 vs 2.4 {+-} 1.5 mm at 80 Hz and 1.8 {+-} 1.1 at 160 Hz, p < 0.001). So did the mean offset errors in the LR direction (-1.7 {+-} 1.4 vs 0.4 {+-} 0.5 mm in AP and 0.8 {+-} 0.8 mm in SI directions, p < 0.001). The error vectors were significantly higher with surrounding interference (2.2 {+-} 1.3 mm) vs without interference (1.0 {+-} 0.7 mm, p < 0.001). An accuracy of 1.6 {+-} 0.2 mm can be reached when using optimum configuration (160 Hz at middle table position). When interference was present in the dynamic tracking, the mean tracking errors in LR direction (1.4 {+-} 0.5 mm) was significantly higher than that in AP direction (0.3 {+-} 0.2 mm, p < 0.001). So did the mean vector errors at 40 Hz (2.1 {+-} 0.2 mm vs 1.3 {+-} 0.2 mm at 80 Hz and 0.9 {+-} 0.2 mm at 160 Hz, p < 0.05). However, when interference was absent, they were comparable in the both directions and at all sampling frequencies. An accuracy of 0.9 {+-} 0.2 mm was obtained for the dynamic tracking when using optimum configuration. Conclusions: The performance of an EM tracking system depends highly on the system configuration and surrounding environment. The accuracy of EM tracking for catheter reconstruction in a prostate HDR brachytherapy procedure can be improved by reducing interference from surrounding equipment, decreasing distance from transmitter to tracking area, and choosing appropriated sampling frequency. A calibration scheme is needed to further reduce the tracking error when the interference is high.« less

On the Probability of Error and Stochastic Resonance in Discrete Memoryless Channels

DTIC Science & Technology

2013-12-01

Information - Driven Doppler Shift Estimation and Compensation Methods for Underwater Wireless Sensor Networks ”, which is to analyze and develop... underwater wireless sensor networks . We formulated an analytic relationship that relates the average probability of error to the systems parameters, the...thesis, we studied the performance of Discrete Memoryless Channels (DMC), arising in the context of cooperative underwater wireless sensor networks

Low Power Shoe Integrated Intelligent Wireless Gait Measurement System

NASA Astrophysics Data System (ADS)

Wahab, Y.; Mazalan, M.; Bakar, N. A.; Anuar, A. F.; Zainol, M. Z.; Hamzah, F.

2014-04-01

Gait analysis measurement is a method to assess and identify gait events and the measurements of dynamic, motion and pressure parameters involving the lowest part of the body. This significant analysis is widely used in sports, rehabilitation as well as other health diagnostic towards improving the quality of life. This paper presents a new system empowered by Inertia Measurement Unit (IMU), ultrasonic sensors, piezoceramic sensors array, XBee wireless modules and Arduino processing unit. This research focuses on the design and development of a low power ultra-portable shoe integrated wireless intelligent gait measurement using MEMS and recent microelectronic devices for foot clearance, orientation, error correction, gait events and pressure measurement system. It is developed to be cheap, low power, wireless, real time and suitable for real life in-door and out-door environment.

A Cost-Effective Geodetic Strainmeter Based on Dual Coaxial Cable Bragg Gratings

PubMed Central

Fu, Jihua; Wang, Xu; Wei, Tao; Wei, Meng; Shen, Yang

2017-01-01

Observations of surface deformation are essential for understanding a wide range of geophysical problems, including earthquakes, volcanoes, landslides, and glaciers. Current geodetic technologies, such as global positioning system (GPS), interferometric synthetic aperture radar (InSAR), borehole and laser strainmeters, are costly and limited in their temporal or spatial resolutions. Here we present a new type of strainmeters based on the coaxial cable Bragg grating (CCBG) sensing technology that provides cost-effective strain measurements. Two CCBGs are introduced into the geodetic strainmeter: one serves as a sensor to measure the strain applied on it, and the other acts as a reference to detect environmental noises. By integrating the sensor and reference signals in a mixer, the environmental noises are minimized and a lower mixed frequency is obtained. The lower mixed frequency allows for measurements to be taken with a portable spectrum analyzer, rather than an expensive spectrum analyzer or a vector network analyzer (VNA). Analysis of laboratory experiments shows that the strain can be measured by the CCBG sensor, and the portable spectrum analyzer can make measurements with the accuracy similar to the expensive spectrum analyzer, whose relative error to the spectrum analyzer R3272 is less than ±0.4%. The outputs of the geodetic strainmeter show a linear relationship with the strains that the CCBG sensor experienced. The measured sensitivity of the geodetic strainmeter is about −0.082 kHz/με; it can cover a large dynamic measuring range up to 2%, and its nonlinear errors can be less than 5.3%. PMID:28417925

A Cost-Effective Geodetic Strainmeter Based on Dual Coaxial Cable Bragg Gratings.

PubMed

Fu, Jihua; Wang, Xu; Wei, Tao; Wei, Meng; Shen, Yang

2017-04-12

Observations of surface deformation are essential for understanding a wide range of geophysical problems, including earthquakes, volcanoes, landslides, and glaciers. Current geodetic technologies, such as global positioning system (GPS), interferometric synthetic aperture radar (InSAR), borehole and laser strainmeters, are costly and limited in their temporal or spatial resolutions. Here we present a new type of strainmeters based on the coaxial cable Bragg grating (CCBG) sensing technology that provides cost-effective strain measurements. Two CCBGs are introduced into the geodetic strainmeter: one serves as a sensor to measure the strain applied on it, and the other acts as a reference to detect environmental noises. By integrating the sensor and reference signals in a mixer, the environmental noises are minimized and a lower mixed frequency is obtained. The lower mixed frequency allows for measurements to be taken with a portable spectrum analyzer, rather than an expensive spectrum analyzer or a vector network analyzer (VNA). Analysis of laboratory experiments shows that the strain can be measured by the CCBG sensor, and the portable spectrum analyzer can make measurements with the accuracy similar to the expensive spectrum analyzer, whose relative error to the spectrum analyzer R3272 is less than ±0.4%. The outputs of the geodetic strainmeter show a linear relationship with the strains that the CCBG sensor experienced. The measured sensitivity of the geodetic strainmeter is about -0.082 kHz/με; it can cover a large dynamic measuring range up to 2%, and its nonlinear errors can be less than 5.3%.

Error compensation for thermally induced errors on a machine tool

DOE Office of Scientific and Technical Information (OSTI.GOV)

Krulewich, D.A.

1996-11-08

Heat flow from internal and external sources and the environment create machine deformations, resulting in positioning errors between the tool and workpiece. There is no industrially accepted method for thermal error compensation. A simple model has been selected that linearly relates discrete temperature measurements to the deflection. The biggest problem is how to locate the temperature sensors and to determine the number of required temperature sensors. This research develops a method to determine the number and location of temperature measurements.

Horizon sensor errors calculated by computer models compared with errors measured in orbit

NASA Technical Reports Server (NTRS)

Ward, K. A.; Hogan, R.; Andary, J.

1982-01-01

Using a computer program to model the earth's horizon and to duplicate the signal processing procedure employed by the ESA (Earth Sensor Assembly), errors due to radiance variation have been computed for a particular time of the year. Errors actually occurring in flight at the same time of year are inferred from integrated rate gyro data for a satellite of the TIROS series of NASA weather satellites (NOAA-A). The predicted performance is compared with actual flight history.

Numerical analysis of the blade tip-timing signal of a fiber bundle sensor probe

NASA Astrophysics Data System (ADS)

Guo, Haotian; Duan, Fajie; Cheng, Zhonghai

2015-03-01

Blade tip-timing is the most effective method for online blade vibration measurement of large rotating machines like turbine engines. Fiber bundle sensors are utilized in tip-timing system to measure the arrival time of the blade. The model of the tip-timing signal of the fiber bundle sensor is established. Experiments are conducted and the results are in concordance with the model established. The rising speed of the tip-timing signal is analyzed. To minimize the tip-timing error, the effects of the clearance change between the sensor and the blade and the deflection of the tip surface are analyzed. Simulation results indicate that the variable gain amplifier, which amplifies the signals to a similar level, can eliminate the measurement error caused by the variation of the clearance between the sensor and blade. Increasing the clearance between the sensor and blade can reduce the measurement error introduced by deflection of the tip surface.

A Systematic Approach to Sensor Selection for Aircraft Engine Health Estimation

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Garg, Sanjay

2009-01-01

A systematic approach for selecting an optimal suite of sensors for on-board aircraft gas turbine engine health estimation is presented. The methodology optimally chooses the engine sensor suite and the model tuning parameter vector to minimize the Kalman filter mean squared estimation error in the engine s health parameters or other unmeasured engine outputs. This technique specifically addresses the underdetermined estimation problem where there are more unknown system health parameters representing degradation than available sensor measurements. This paper presents the theoretical estimation error equations, and describes the optimization approach that is applied to select the sensors and model tuning parameters to minimize these errors. Two different model tuning parameter vector selection approaches are evaluated: the conventional approach of selecting a subset of health parameters to serve as the tuning parameters, and an alternative approach that selects tuning parameters as a linear combination of all health parameters. Results from the application of the technique to an aircraft engine simulation are presented, and compared to those from an alternative sensor selection strategy.

Instrumented urethral catheter and its ex vivo validation in a sheep urethra

NASA Astrophysics Data System (ADS)

Ahmadi, Mahdi; Rajamani, Rajesh; Timm, Gerald; Sezen, Serdar

2017-03-01

This paper designs and fabricates an instrumented catheter for instantaneous measurement of distributed urethral pressure profiles. Since the catheter enables a new type of urological measurement, a process for accurate ex vivo validation of the catheter is developed. A flexible sensor strip is first fabricated with nine pressure sensors and integrated electronic pads for an associated sensor IC chip. The flexible sensor strip and associated IC chip are assembled on a 7 Fr Foley catheter. A sheep bladder and urethra are extracted and used in an ex vivo set up for verification of the developed instrumented catheter. The bladder-urethra are suspended in a test rig and pressure cuffs placed to apply known static and dynamic pressures around the urethra. A significant challenge in the performance of the sensor system is the presence of parasitics that introduce large bias and drift errors in the capacitive sensor signals. An algorithm based on use of reference parasitic transducers is used to compensate for the parasitics. Extensive experimental results verify that the developed compensation method works effectively. Results on pressure variation profiles circumferentially around the urethra and longitudinally along the urethra are presented. The developed instrumented catheter will be useful in improved urodynamics to more accurately diagnose the source of urinary incontinence in patients.

Monitoring gait in multiple sclerosis with novel wearable motion sensors.

PubMed

Moon, Yaejin; McGinnis, Ryan S; Seagers, Kirsten; Motl, Robert W; Sheth, Nirav; Wright, John A; Ghaffari, Roozbeh; Sosnoff, Jacob J

2017-01-01

Mobility impairment is common in people with multiple sclerosis (PwMS) and there is a need to assess mobility in remote settings. Here, we apply a novel wireless, skin-mounted, and conformal inertial sensor (BioStampRC, MC10 Inc.) to examine gait characteristics of PwMS under controlled conditions. We determine the accuracy and precision of BioStampRC in measuring gait kinematics by comparing to contemporary research-grade measurement devices. A total of 45 PwMS, who presented with diverse walking impairment (Mild MS = 15, Moderate MS = 15, Severe MS = 15), and 15 healthy control subjects participated in the study. Participants completed a series of clinical walking tests. During the tests participants were instrumented with BioStampRC and MTx (Xsens, Inc.) sensors on their shanks, as well as an activity monitor GT3X (Actigraph, Inc.) on their non-dominant hip. Shank angular velocity was simultaneously measured with the inertial sensors. Step number and temporal gait parameters were calculated from the data recorded by each sensor. Visual inspection and the MTx served as the reference standards for computing the step number and temporal parameters, respectively. Accuracy (error) and precision (variance of error) was assessed based on absolute and relative metrics. Temporal parameters were compared across groups using ANOVA. Mean accuracy±precision for the BioStampRC was 2±2 steps error for step number, 6±9ms error for stride time and 6±7ms error for step time (0.6-2.6% relative error). Swing time had the least accuracy±precision (25±19ms error, 5±4% relative error) among the parameters. GT3X had the least accuracy±precision (8±14% relative error) in step number estimate among the devices. Both MTx and BioStampRC detected significantly distinct gait characteristics between PwMS with different disability levels (p<0.01). BioStampRC sensors accurately and precisely measure gait parameters in PwMS across diverse walking impairment levels and detected differences in gait characteristics by disability level in PwMS. This technology has the potential to provide granular monitoring of gait both inside and outside the clinic.

Analysis and correction for measurement error of edge sensors caused by deformation of guide flexure applied in the Thirty Meter Telescope SSA.

PubMed

Cao, Haifeng; Zhang, Jingxu; Yang, Fei; An, Qichang; Zhao, Hongchao; Guo, Peng

2018-05-01

The Thirty Meter Telescope (TMT) project will design and build a 30-m-diameter telescope for research in astronomy in visible and infrared wavelengths. The primary mirror of TMT is made up of 492 hexagonal mirror segments under active control. The highly segmented primary mirror will utilize edge sensors to align and stabilize the relative piston, tip, and tilt degrees of segments. The support system assembly (SSA) of the segmented mirror utilizes a guide flexure to decouple the axial support and lateral support, while its deformation will cause measurement error of the edge sensor. We have analyzed the theoretical relationship between the segment movement and the measurement value of the edge sensor. Further, we have proposed an error correction method with a matrix. The correction process and the simulation results of the edge sensor will be described in this paper.

Exploring the "what if?" in geology through a RESTful open-source framework for cloud-based simulation and analysis

NASA Astrophysics Data System (ADS)

Klump, Jens; Robertson, Jess

2016-04-01

The spatial and temporal extent of geological phenomena makes experiments in geology difficult to conduct, if not entirely impossible and collection of data is laborious and expensive - so expensive that most of the time we cannot test a hypothesis. The aim, in many cases, is to gather enough data to build a predictive geological model. Even in a mine, where data are abundant, a model remains incomplete because the information at the level of a blasting block is two orders of magnitude larger than the sample from a drill core, and we have to take measurement errors into account. So, what confidence can we have in a model based on sparse data, uncertainties and measurement error? Our framework consist of two layers: (a) a ground-truth layer that contains geological models, which can be statistically based on historical operations data, and (b) a network of RESTful synthetic sensor microservices which can query the ground-truth for underlying properties and produce a simulated measurement to a control layer, which could be a database or LIMS, a machine learner or a companies' existing data infrastructure. Ground truth data are generated by an implicit geological model which serves as a host for nested models of geological processes as smaller scales. Our two layers are implemented using Flask and Gunicorn, which are open source Python web application framework and server, the PyData stack (numpy, scipy etc) and Rabbit MQ (an open-source queuing library). Sensor data is encoded using a JSON-LD version of the SensorML and Observations and Measurements standards. Containerisation of the synthetic sensors using Docker and CoreOS allows rapid and scalable deployment of large numbers of sensors, as well as sensor discovery to form a self-organized dynamic network of sensors. Real-time simulation of data sources can be used to investigate crucial questions such as the potential information gain from future sensing capabilities, or from new sampling strategies, or the combination of both, and it enables us to test many "what if?" questions, both in geology and in data engineering. What would we be able to see if we could obtain data at higher resolution? How would real-time data analysis change sampling strategies? Does our data infrastructure handle many new real-time data streams? What feature engineering can be deducted for machine learning approaches? By providing a 'data sandbox' able to scale to realistic geological scenarios we hope to start answering some of these questions. Faults happen in real world networks. Future work will investigate the effect of failure on dynamic sensor networks and the impact on the predictive capability of machine learning algorithms.

Experimental study on an FBG strain sensor

NASA Astrophysics Data System (ADS)

Liu, Hong-lin; Zhu, Zheng-wei; Zheng, Yong; Liu, Bang; Xiao, Feng

2018-01-01

Landslides and other geological disasters occur frequently and often cause high financial and humanitarian cost. The real-time, early-warning monitoring of landslides has important significance in reducing casualties and property losses. In this paper, by taking the high initial precision and high sensitivity advantage of FBG, an FBG strain sensor is designed combining FBGs with inclinometer. The sensor was regarded as a cantilever beam with one end fixed. According to the anisotropic material properties of the inclinometer, a theoretical formula between the FBG wavelength and the deflection of the sensor was established using the elastic mechanics principle. Accuracy of the formula established had been verified through laboratory calibration testing and model slope monitoring experiments. The displacement of landslide could be calculated by the established theoretical formula using the changing values of FBG central wavelength obtained by the demodulation instrument remotely. Results showed that the maximum error at different heights was 9.09%; the average of the maximum error was 6.35%, and its corresponding variance was 2.12; the minimum error was 4.18%; the average of the minimum error was 5.99%, and its corresponding variance was 0.50. The maximum error of the theoretical and the measured displacement decrease gradually, and the variance of the error also decreases gradually. This indicates that the theoretical results are more and more reliable. It also shows that the sensor and the theoretical formula established in this paper can be used for remote, real-time, high precision and early warning monitoring of the slope.

Bias estimation for moving optical sensor measurements with targets of opportunity

NASA Astrophysics Data System (ADS)

Belfadel, Djedjiga; Osborne, Richard W.; Bar-Shalom, Yaakov

2014-06-01

Integration of space based sensors into a Ballistic Missile Defense System (BMDS) allows for detection and tracking of threats over a larger area than ground based sensors [1]. This paper examines the effect of sensor bias error on the tracking quality of a Space Tracking and Surveillance System (STSS) for the highly non-linear problem of tracking a ballistic missile. The STSS constellation consists of two or more satellites (on known trajectories) for tracking ballistic targets. Each satellite is equipped with an IR sensor that provides azimuth and elevation to the target. The tracking problem is made more difficult due to a constant or slowly varying bias error present in each sensor's line of sight measurements. It is important to correct for these bias errors so that the multiple sensor measurements and/or tracks can be referenced as accurately as possible to a common tracking coordinate system. The measurements provided by these sensors are assumed time-coincident (synchronous) and perfectly associated. The line of sight (LOS) measurements from the sensors can be fused into measurements which are the Cartesian target position, i.e., linear in the target state. We evaluate the Cramér-Rao Lower Bound (CRLB) on the covariance of the bias estimates, which serves as a quantification of the available information about the biases. Statistical tests on the results of simulations show that this method is statistically efficient, even for small sample sizes (as few as two sensors and six points on the (unknown) trajectory of a single target of opportunity). We also show that the RMS position error is significantly improved with bias estimation compared with the target position estimation using the original biased measurements.

Identification and compensation of the temperature influences in a miniature three-axial accelerometer based on the least squares method

NASA Astrophysics Data System (ADS)

Grigorie, Teodor Lucian; Corcau, Ileana Jenica; Tudosie, Alexandru Nicolae

2017-06-01

The paper presents a way to obtain an intelligent miniaturized three-axial accelerometric sensor, based on the on-line estimation and compensation of the sensor errors generated by the environmental temperature variation. Taking into account that this error's value is a strongly nonlinear complex function of the values of environmental temperature and of the acceleration exciting the sensor, its correction may not be done off-line and it requires the presence of an additional temperature sensor. The proposed identification methodology for the error model is based on the least square method which process off-line the numerical values obtained from the accelerometer experimental testing for different values of acceleration applied to its axes of sensitivity and for different values of operating temperature. A final analysis of the error level after the compensation highlights the best variant for the matrix in the error model. In the sections of the paper are shown the results of the experimental testing of the accelerometer on all the three sensitivity axes, the identification of the error models on each axis by using the least square method, and the validation of the obtained models with experimental values. For all of the three detection channels was obtained a reduction by almost two orders of magnitude of the acceleration absolute maximum error due to environmental temperature variation.

Bias-field equalizer for bubble memories

NASA Technical Reports Server (NTRS)

Keefe, G. E.

1977-01-01

Magnetoresistive Perm-alloy sensor monitors bias field required to maintain bubble memory. Sensor provides error signal that, in turn, corrects magnitude of bias field. Error signal from sensor can be used to control magnitude of bias field in either auxiliary set of bias-field coils around permanent magnet field, or current in small coils used to remagnetize permanent magnet by infrequent, short, high-current pulse or short sequence of pulses.

A fiber Bragg grating sensor system for estimating the large deflection of a lightweight flexible beam

NASA Astrophysics Data System (ADS)

Peng, Te; Yang, Yangyang; Ma, Lina; Yang, Huayong

2016-10-01

A sensor system based on fiber Bragg grating (FBG) is presented which is to estimate the deflection of a lightweight flexible beam, including the tip position and the tip rotation angle. In this paper, the classical problem of the deflection of a lightweight flexible beam of linear elastic material is analysed. We present the differential equation governing the behavior of a physical system and show that this equation although straightforward in appearance, is in fact rather difficult to solve due to the presence of a non-linear term. We used epoxy glue to attach the FBG sensors to specific locations upper and lower surface of the beam in order to measure local strain measurements. A quasi-distributed FBG static strain sensor network is designed and established. The estimation results from FBG sensors are also compared to reference displacements from the ANSYS simulation results and the experimental results obtained in the laboratory in the static case. The errors of the estimation by FBG sensors are analysed for further error-correction and option-design. When the load weight is 20g, the precision is the highest, the position errors ex and ex are 0.19%, 0.14% respectively, the rotation error eθ, is 1.23%.

Influence of model errors in optimal sensor placement

NASA Astrophysics Data System (ADS)

Vincenzi, Loris; Simonini, Laura

2017-02-01

The paper investigates the role of model errors and parametric uncertainties in optimal or near optimal sensor placements for structural health monitoring (SHM) and modal testing. The near optimal set of measurement locations is obtained by the Information Entropy theory; the results of placement process considerably depend on the so-called covariance matrix of prediction error as well as on the definition of the correlation function. A constant and an exponential correlation function depending on the distance between sensors are firstly assumed; then a proposal depending on both distance and modal vectors is presented. With reference to a simple case-study, the effect of model uncertainties on results is described and the reliability and the robustness of the proposed correlation function in the case of model errors are tested with reference to 2D and 3D benchmark case studies. A measure of the quality of the obtained sensor configuration is considered through the use of independent assessment criteria. In conclusion, the results obtained by applying the proposed procedure on a real 5-spans steel footbridge are described. The proposed method also allows to better estimate higher modes when the number of sensors is greater than the number of modes of interest. In addition, the results show a smaller variation in the sensor position when uncertainties occur.

Adaptive and iterative methods for simulations of nanopores with the PNP-Stokes equations

NASA Astrophysics Data System (ADS)

Mitscha-Baude, Gregor; Buttinger-Kreuzhuber, Andreas; Tulzer, Gerhard; Heitzinger, Clemens

2017-06-01

We present a 3D finite element solver for the nonlinear Poisson-Nernst-Planck (PNP) equations for electrodiffusion, coupled to the Stokes system of fluid dynamics. The model serves as a building block for the simulation of macromolecule dynamics inside nanopore sensors. The source code is released online at http://github.com/mitschabaude/nanopores. We add to existing numerical approaches by deploying goal-oriented adaptive mesh refinement. To reduce the computation overhead of mesh adaptivity, our error estimator uses the much cheaper Poisson-Boltzmann equation as a simplified model, which is justified on heuristic grounds but shown to work well in practice. To address the nonlinearity in the full PNP-Stokes system, three different linearization schemes are proposed and investigated, with two segregated iterative approaches both outperforming a naive application of Newton's method. Numerical experiments are reported on a real-world nanopore sensor geometry. We also investigate two different models for the interaction of target molecules with the nanopore sensor through the PNP-Stokes equations. In one model, the molecule is of finite size and is explicitly built into the geometry; while in the other, the molecule is located at a single point and only modeled implicitly - after solution of the system - which is computationally favorable. We compare the resulting force profiles of the electric and velocity fields acting on the molecule, and conclude that the point-size model fails to capture important physical effects such as the dependence of charge selectivity of the sensor on the molecule radius.

Fiber optic vibration sensor using bifurcated plastic optical fiber

NASA Astrophysics Data System (ADS)

Abdullah, M.; Bidin, N.; Yasin, M.

2016-11-01

An extrinsic fiber optic vibration sensor is demonstrated for a fiber optic displacement sensor based on a bundled multimode fiber to measure a vibration frequency ranging from 100 until 3000 Hz. The front slope has a sensitivity of 0.1938mV/mm and linearity of 99.7% within a measurement range between 0.15-3.00 mm. By placing the diaphragm of the concave load-speaker within the linear range from the probe, the frequency of the vibration can be measured with error percentage of less than 1.54%. The graph of input against output frequency for low, medium and high frequency range show very high linearity up to 99%. Slope for low, medium, and high frequency range are calculated as 1.0026, 0.9934, and 1.0007 respectively. Simplicity, long term stability, low power consumption, wide dynamic and frequency ranges, noise reduction, ruggedness, linearity and light weight make it promising alternative to other well-establish methods for vibration frequency measurement.

CMOS Rad-Hard Front-End Electronics for Precise Sensors Measurements

NASA Astrophysics Data System (ADS)

Sordo-Ibáñez, Samuel; Piñero-García, Blanca; Muñoz-Díaz, Manuel; Ragel-Morales, Antonio; Ceballos-Cáceres, Joaquín; Carranza-González, Luis; Espejo-Meana, Servando; Arias-Drake, Alberto; Ramos-Martos, Juan; Mora-Gutiérrez, José Miguel; Lagos-Florido, Miguel Angel

2016-08-01

This paper reports a single-chip solution for the implementation of radiation-tolerant CMOS front-end electronics (FEE) for applications requiring the acquisition of base-band sensor signals. The FEE has been designed in a 0.35μm CMOS process, and implements a set of parallel conversion channels with high levels of configurability to adapt the resolution, conversion rate, as well as the dynamic input range for the required application. Each conversion channel has been designed with a fully-differential implementation of a configurable-gain instrumentation amplifier, followed by an also configurable dual-slope ADC (DS ADC) up to 16 bits. The ASIC also incorporates precise thermal monitoring, sensor conditioning and error detection functionalities to ensure proper operation in extreme environments. Experimental results confirm that the proposed topologies, in conjunction with the applied radiation-hardening techniques, are reliable enough to be used without loss in the performance in environments with an extended temperature range (between -25 and 125 °C) and a total dose beyond 300 krad.

Fast Bayesian approach for modal identification using free vibration data, Part I - Most probable value

NASA Astrophysics Data System (ADS)

Zhang, Feng-Liang; Ni, Yan-Chun; Au, Siu-Kui; Lam, Heung-Fai

2016-03-01

The identification of modal properties from field testing of civil engineering structures is becoming economically viable, thanks to the advent of modern sensor and data acquisition technology. Its demand is driven by innovative structural designs and increased performance requirements of dynamic-prone structures that call for a close cross-checking or monitoring of their dynamic properties and responses. Existing instrumentation capabilities and modal identification techniques allow structures to be tested under free vibration, forced vibration (known input) or ambient vibration (unknown broadband loading). These tests can be considered complementary rather than competing as they are based on different modeling assumptions in the identification model and have different implications on costs and benefits. Uncertainty arises naturally in the dynamic testing of structures due to measurement noise, sensor alignment error, modeling error, etc. This is especially relevant in field vibration tests because the test condition in the field environment can hardly be controlled. In this work, a Bayesian statistical approach is developed for modal identification using the free vibration response of structures. A frequency domain formulation is proposed that makes statistical inference based on the Fast Fourier Transform (FFT) of the data in a selected frequency band. This significantly simplifies the identification model because only the modes dominating the frequency band need to be included. It also legitimately ignores the information in the excluded frequency bands that are either irrelevant or difficult to model, thereby significantly reducing modeling error risk. The posterior probability density function (PDF) of the modal parameters is derived rigorously from modeling assumptions and Bayesian probability logic. Computational difficulties associated with calculating the posterior statistics, including the most probable value (MPV) and the posterior covariance matrix, are addressed. Fast computational algorithms for determining the MPV are proposed so that the method can be practically implemented. In the companion paper (Part II), analytical formulae are derived for the posterior covariance matrix so that it can be evaluated without resorting to finite difference method. The proposed method is verified using synthetic data. It is also applied to modal identification of full-scale field structures.

A multi-parameter optical fiber sensor with interrogation and discrimination capabilities

NASA Astrophysics Data System (ADS)

Zhan, Yage; Wu, Hua; Yang, Qinyu; Pei, Jincheng; Yang, Xichun

2009-11-01

A multi-parameter and multi-function, but low-cost, optical fiber grating sensor with self-interrogation and self-discrimination capabilities is presented theoretically and experimentally. The sensor bases on three fiber Bragg gratings (FBG) and one fiber long period grating (LPG). Strain, vibration, pressure, ordinary temperature (-10 to 100 °C) and high temperature (100-800 °C) can be measured by the sensor. When high temperature (100-800 °C) is measured, the LPG is used as a high temperture sensor head and FBG 1 is used as an interrogation element. Alternatively, when one of the other four measurands is measured, FBG 1 (or FBG 2) is used as a sensor head and LPG is used as an interrogation element. When two of the other four measurands are measured simultaneously, FBG 1 and FBG 2 are used as sensor heads and LPG is used as a shared interrogation element. FBG 3 is used as a reference element to eliminate the errors resulted from light source fluctuation and the cross-sensitivity between measurand and environmental temperature. The measurands can be interrogated according to the signals of the photodiodes (PDs), which are related to the relative wavelength shift of the LPG and the FBGs. Experimental results agree well with theoretical analyses. The interrogation scheme is immune to light source fluctuation and the cross-sensitivity between measurands and enviromental temperature, and also the dynamic range is large.

Integration of airborne LiDAR data and voxel-based ray tracing to determine high-resolution solar radiation dynamics at the forest floor: implications for improving stand-scale distributed snowmelt models

NASA Astrophysics Data System (ADS)

Musselman, K. N.; Molotch, N. P.; Margulis, S. A.

2012-12-01

Forest architecture dictates sub-canopy solar irradiance and the resulting patterns can vary seasonally and over short spatial distances. These radiation dynamics are thought to have significant implications on snowmelt processes, regional hydrology, and remote sensing signatures. The variability calls into question many assumptions inherent in traditional canopy models (e.g. Beer's Law) when applied at high resolution (i.e. 1 m). We present a method of estimating solar canopy transmissivity using airborne LiDAR data. The canopy structure is represented in 3-D voxel space (i.e. a cubic discretization of a 3-D domain analogous to a pixel representation of a 2-D space). The solar direct beam canopy transmissivity (DBT) is estimated with a ray-tracing algorithm and the diffuse component is estimated from LiDAR-derived effective LAI. Results from one year at five-minute temporal and 1 m spatial resolutions are presented from Sequoia National Park. Compared to estimates from 28 hemispherical photos, the ray-tracing model estimated daily mean DBT with a 10% average error, while the errors from a Beer's-type DBT estimate exceeded 20%. Compared to the ray-tracing estimates, the Beer's-type transmissivity method was unable to resolve complex spatial patterns resulting from canopy gaps, individual tree canopies and boles, and steep variable terrain. The snowmelt model SNOWPACK was applied at locations of ultrasonic snow depth sensors. Two scenarios were tested; 1) a nominal case where canopy model parameters were obtained from hemispherical photographs, and 2) an explicit scenario where the model was modified to accept LiDAR-derived time-variant DBT. The bulk canopy treatment was generally unable to simulate the sub-canopy snowmelt dynamics observed at the depth sensor locations. The explicit treatment reduced error in the snow disappearance date by one week and both positive and negative melt-season SWE biases were reduced. The results highlight the utility of LiDAR canopy measurements and physically based snowmelt models to simulate spatially distributed stand- and slope-scale snowmelt dynamics at resolutions necessary to capture the inherent underlying variability.iDAR-derived solar direct beam canopy transmissivity computed as the daily average for March 1st and May 1st.

Testbed Demonstration of Low Order Wavefront Sensing and Control Technology for WFIRST Coronagraph

NASA Astrophysics Data System (ADS)

Shi, Fang; Balasubramanian, K.; Cady, E.; Kern, B.; Lam, R.; Mandic, M.; Patterson, K.; Poberezhskiy, I.; Shields, J.; Seo, J.; Tang, H.; Truong, T.; Wilson, D.

2017-01-01

NASA’s WFIRST-AFTA Coronagraph will be capable of directly imaging and spectrally characterizing giant exoplanets similar to Neptune and Jupiter, and possibly even super-Earths, around nearby stars. To maintain the required coronagraph performance in a realistic space environment, a Low Order Wavefront Sensing and Control (LOWFS/C) subsystem is necessary. The LOWFS/C will use the rejected stellar light to sense and suppress the telescope pointing drift and jitter as well as low order wavefront errors due to the changes in thermal loading of the telescope and the rest of the observatory. The LOWFS/C uses a Zernike phase contrast wavefront sensor with the phase shifting disk combined with the stellar light rejecting occulting mask, a key concept to minimize the non-common path error. Developed as a part of the Dynamic High Contrast Imaging Testbed (DHCIT), the LOWFS/C subsystem also consists of an Optical Telescope Assembly Simulator (OTA-S) to generate the realistic line-of-sight (LoS) drift and jitter as well as low order wavefront error from WFIRST-AFTA telescope’s vibration and thermal drift. The entire LOWFS/C subsystem have been integrated, calibrated, and tested in the Dynamic High Contrast Imaging Testbed. In this presentation we will show the results of LOWFS/C performance during the dynamic coronagraph tests in which we have demonstrated that LOWFS/C is able to maintain the coronagraph contrast with the presence of WFIRST like line-of-sight drift and jitter as well as low order wavefront drifts.

Virtual sensors for active noise control in acoustic-structural coupled enclosures using structural sensing: part II--Optimization of structural sensor placement.

PubMed

Halim, Dunant; Cheng, Li; Su, Zhongqing

2011-04-01

The work proposed an optimization approach for structural sensor placement to improve the performance of vibro-acoustic virtual sensor for active noise control applications. The vibro-acoustic virtual sensor was designed to estimate the interior sound pressure of an acoustic-structural coupled enclosure using structural sensors. A spectral-spatial performance metric was proposed, which was used to quantify the averaged structural sensor output energy of a vibro-acoustic system excited by a spatially varying point source. It was shown that (i) the overall virtual sensing error energy was contributed additively by the modal virtual sensing error and the measurement noise energy; (ii) each of the modal virtual sensing error system was contributed by both the modal observability levels for the structural sensing and the target acoustic virtual sensing; and further (iii) the strength of each modal observability level was influenced by the modal coupling and resonance frequencies of the associated uncoupled structural/cavity modes. An optimal design of structural sensor placement was proposed to achieve sufficiently high modal observability levels for certain important panel- and cavity-controlled modes. Numerical analysis on a panel-cavity system demonstrated the importance of structural sensor placement on virtual sensing and active noise control performance, particularly for cavity-controlled modes.

Thermal Error Test and Intelligent Modeling Research on the Spindle of High Speed CNC Machine Tools

NASA Astrophysics Data System (ADS)

Luo, Zhonghui; Peng, Bin; Xiao, Qijun; Bai, Lu

2018-03-01

Thermal error is the main factor affecting the accuracy of precision machining. Through experiments, this paper studies the thermal error test and intelligent modeling for the spindle of vertical high speed CNC machine tools in respect of current research focuses on thermal error of machine tool. Several testing devices for thermal error are designed, of which 7 temperature sensors are used to measure the temperature of machine tool spindle system and 2 displacement sensors are used to detect the thermal error displacement. A thermal error compensation model, which has a good ability in inversion prediction, is established by applying the principal component analysis technology, optimizing the temperature measuring points, extracting the characteristic values closely associated with the thermal error displacement, and using the artificial neural network technology.

Assessing the quality of humidity measurements from global operational radiosonde sensors

NASA Astrophysics Data System (ADS)

Moradi, Isaac; Soden, Brian; Ferraro, Ralph; Arkin, Phillip; Vömel, Holger

2013-07-01

The quality of humidity measurements from global operational radiosonde sensors in upper, middle, and lower troposphere for the period 2000-2011 were investigated using satellite observations from three microwave water vapor channels operating at 183.31±1, 183.31±3, and 183.31±7 GHz. The radiosonde data were partitioned based on sensor type into 19 classes. The satellite brightness temperatures (Tb) were simulated using radiosonde profiles and a radiative transfer model, then the radiosonde simulated Tb's were compared with the observed Tb's from the satellites. The surface affected Tb's were excluded from the comparison due to the lack of reliable surface emissivity data at the microwave frequencies. Daytime and nighttime data were examined separately to see the possible effect of daytime radiation bias on the sonde data. The error characteristics among different radiosondes vary significantly, which largely reflects the differences in sensor type. These differences are more evident in the mid-upper troposphere than in the lower troposphere, mainly because some of the sensors stop responding to tropospheric humidity somewhere in the upper or even in the middle troposphere. In the upper troposphere, most sensors have a dry bias but Russian sensors and a few other sensors including GZZ2, VZB2, and RS80H have a wet bias. In middle troposphere, Russian sensors still have a wet bias but all other sensors have a dry bias. All sensors, including Russian sensors, have a dry bias in lower troposphere. The systematic and random errors generally decrease from upper to lower troposphere. Sensors from China, India, Russia, and the U.S. have a large random error in upper troposphere, which indicates that these sensors are not suitable for upper tropospheric studies as they fail to respond to humidity changes in the upper and even middle troposphere. Overall, Vaisala sensors perform better than other sensors throughout the troposphere exhibiting the smallest systematic and random errors. Because of the large differences between different radiosonde humidity sensors, it is important for long-term trend studies to only use data measured using a single type of sensor at any given station. If multiple sensor types are used then it is necessary to consider the bias between sensor types and its possible dependence on humidity and temperature.

Solar maximum mission fine pointing sun sensor dawn and dusk errors flight data and model analysis

NASA Technical Reports Server (NTRS)

Kulp, D. R.

1988-01-01

SMM flight system control errors occurring at spacecraft dawn and dusk are analyzed. The errors are associated with the fine pointing sun sensor (FPSS), which is a primary component of the SMM attitude control system. It is shown that the source of the FPSS dawn/dusk distortion is the incomplete masking of sunlight reflected off the earth by the optical baffle covering the FPSS sensor heads onboard the SMM during periods of orbit dawn and dusk. For the most part, the modeled behavior of the FPSS under dawn and dusk lighting conditions matches the observed behavior in the SMM flight data.

Estimating pixel variances in the scenes of staring sensors

DOEpatents

Simonson, Katherine M [Cedar Crest, NM; Ma, Tian J [Albuquerque, NM

2012-01-24

A technique for detecting changes in a scene perceived by a staring sensor is disclosed. The technique includes acquiring a reference image frame and a current image frame of a scene with the staring sensor. A raw difference frame is generated based upon differences between the reference image frame and the current image frame. Pixel error estimates are generated for each pixel in the raw difference frame based at least in part upon spatial error estimates related to spatial intensity gradients in the scene. The pixel error estimates are used to mitigate effects of camera jitter in the scene between the current image frame and the reference image frame.

A Novel Low-Cost, Large Curvature Bend Sensor Based on a Bowden-Cable

PubMed Central

Jeong, Useok; Cho, Kyu-Jin

2016-01-01

Bend sensors have been developed based on conductive ink, optical fiber, and electronic textiles. Each type has advantages and disadvantages in terms of performance, ease of use, and cost. This study proposes a new and low-cost bend sensor that can measure a wide range of accumulated bend angles with large curvatures. This bend sensor utilizes a Bowden-cable, which consists of a coil sheath and an inner wire. Displacement changes of the Bowden-cable’s inner wire, when the shape of the sheath changes, have been considered to be a position error in previous studies. However, this study takes advantage of this position error to detect the bend angle of the sheath. The bend angle of the sensor can be calculated from the displacement measurement of the sensing wire using a Hall-effect sensor or a potentiometer. Simulations and experiments have shown that the accumulated bend angle of the sensor is linearly related to the sensor signal, with an R-square value up to 0.9969 and a root mean square error of 2% of the full sensing range. The proposed sensor is not affected by a bend curvature of up to 80.0 m−1, unlike previous bend sensors. The proposed sensor is expected to be useful for various applications, including motion capture devices, wearable robots, surgical devices, or generally any device that requires an affordable and low-cost bend sensor. PMID:27347959

Advancing reference emission levels in subnational and national REDD+ initiatives: a CLASlite approach

PubMed Central

Asner, Gregory P; Joseph, Shijo

2015-01-01

Conservation and monitoring of tropical forests requires accurate information on their extent and change dynamics. Cloud cover, sensor errors and technical barriers associated with satellite remote sensing data continue to prevent many national and sub-national REDD+ initiatives from developing their reference deforestation and forest degradation emission levels. Here we present a framework for large-scale historical forest cover change analysis using free multispectral satellite imagery in an extremely cloudy tropical forest region. The CLASlite approach provided highly automated mapping of tropical forest cover, deforestation and degradation from Landsat satellite imagery. Critically, the fractional cover of forest photosynthetic vegetation, non-photosynthetic vegetation, and bare substrates calculated by CLASlite provided scene-invariant quantities for forest cover, allowing for systematic mosaicking of incomplete satellite data coverage. A synthesized satellite-based data set of forest cover was thereby created, reducing image incompleteness caused by clouds, shadows or sensor errors. This approach can readily be implemented by single operators with highly constrained budgets. We test this framework on tropical forests of the Colombian Pacific Coast (Chocó) – one of the cloudiest regions on Earth, with successful comparison to the Colombian government’s deforestation map and a global deforestation map. PMID:25678933

Sound-field reproduction in-room using optimal control techniques: simulations in the frequency domain.

PubMed

Gauthier, Philippe-Aubert; Berry, Alain; Woszczyk, Wieslaw

2005-02-01

This paper describes the simulations and results obtained when applying optimal control to progressive sound-field reproduction (mainly for audio applications) over an area using multiple monopole loudspeakers. The model simulates a reproduction system that operates either in free field or in a closed space approaching a typical listening room, and is based on optimal control in the frequency domain. This rather simple approach is chosen for the purpose of physical investigation, especially in terms of sensing microphones and reproduction loudspeakers configurations. Other issues of interest concern the comparison with wave-field synthesis and the control mechanisms. The results suggest that in-room reproduction of sound field using active control can be achieved with a residual normalized squared error significantly lower than open-loop wave-field synthesis in the same situation. Active reproduction techniques have the advantage of automatically compensating for the room's natural dynamics. For the considered cases, the simulations show that optimal control results are not sensitive (in terms of reproduction error) to wall absorption in the reproduction room. A special surrounding configuration of sensors is introduced for a sensor-free listening area in free field.

An Indoor Continuous Positioning Algorithm on the Move by Fusing Sensors and Wi-Fi on Smartphones.

PubMed

Li, Huaiyu; Chen, Xiuwan; Jing, Guifei; Wang, Yuan; Cao, Yanfeng; Li, Fei; Zhang, Xinlong; Xiao, Han

2015-12-11

Wi-Fi indoor positioning algorithms experience large positioning error and low stability when continuously positioning terminals that are on the move. This paper proposes a novel indoor continuous positioning algorithm that is on the move, fusing sensors and Wi-Fi on smartphones. The main innovative points include an improved Wi-Fi positioning algorithm and a novel positioning fusion algorithm named the Trust Chain Positioning Fusion (TCPF) algorithm. The improved Wi-Fi positioning algorithm was designed based on the properties of Wi-Fi signals on the move, which are found in a novel "quasi-dynamic" Wi-Fi signal experiment. The TCPF algorithm is proposed to realize the "process-level" fusion of Wi-Fi and Pedestrians Dead Reckoning (PDR) positioning, including three parts: trusted point determination, trust state and positioning fusion algorithm. An experiment is carried out for verification in a typical indoor environment, and the average positioning error on the move is 1.36 m, a decrease of 28.8% compared to an existing algorithm. The results show that the proposed algorithm can effectively reduce the influence caused by the unstable Wi-Fi signals, and improve the accuracy and stability of indoor continuous positioning on the move.

High accuracy navigation information estimation for inertial system using the multi-model EKF fusing adams explicit formula applied to underwater gliders.

PubMed

Huang, Haoqian; Chen, Xiyuan; Zhang, Bo; Wang, Jian

2017-01-01

The underwater navigation system, mainly consisting of MEMS inertial sensors, is a key technology for the wide application of underwater gliders and plays an important role in achieving high accuracy navigation and positioning for a long time of period. However, the navigation errors will accumulate over time because of the inherent errors of inertial sensors, especially for MEMS grade IMU (Inertial Measurement Unit) generally used in gliders. The dead reckoning module is added to compensate the errors. In the complicated underwater environment, the performance of MEMS sensors is degraded sharply and the errors will become much larger. It is difficult to establish the accurate and fixed error model for the inertial sensor. Therefore, it is very hard to improve the accuracy of navigation information calculated by sensors. In order to solve the problem mentioned, the more suitable filter which integrates the multi-model method with an EKF approach can be designed according to different error models to give the optimal estimation for the state. The key parameters of error models can be used to determine the corresponding filter. The Adams explicit formula which has an advantage of high precision prediction is simultaneously fused into the above filter to achieve the much more improvement in attitudes estimation accuracy. The proposed algorithm has been proved through theory analyses and has been tested by both vehicle experiments and lake trials. Results show that the proposed method has better accuracy and effectiveness in terms of attitudes estimation compared with other methods mentioned in the paper for inertial navigation applied to underwater gliders. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Modeling for Military Operational Medicine Scientific and Technical Objectives

DTIC Science & Technology

2005-09-01

measurements and less error in interpreting the measurements since the sensor units are placed directly under armor ; and (3) new material that matches the...more accurate measurements and less error in interpreting the measurements, since the sensor units are placed directly under armor ; and (3) new

Study of Current Measurement Method Based on Circular Magnetic Field Sensing Array

PubMed Central

Li, Zhenhua; Zhang, Siqiu; Wu, Zhengtian; Tao, Yuan

2018-01-01

Classic core-based instrument transformers are more prone to magnetic saturation. This affects the measurement accuracy of such transformers and limits their applications in measuring large direct current (DC). Moreover, protection and control systems may exhibit malfunctions due to such measurement errors. This paper presents a more accurate method for current measurement based on a circular magnetic field sensing array. The proposed measurement approach utilizes multiple hall sensors that are evenly distributed on a circle. The average value of all hall sensors is regarded as the final measurement. The calculation model is established in the case of magnetic field interference of the parallel wire, and the simulation results show that the error decreases significantly when the number of hall sensors n is greater than 8. The measurement error is less than 0.06% when the wire spacing is greater than 2.5 times the radius of the sensor array. A simulation study on the off-center primary conductor is conducted, and a kind of hall sensor compensation method is adopted to improve the accuracy. The simulation and test results indicate that the measurement error of the system is less than 0.1%. PMID:29734742

Study of Current Measurement Method Based on Circular Magnetic Field Sensing Array.

PubMed

Li, Zhenhua; Zhang, Siqiu; Wu, Zhengtian; Abu-Siada, Ahmed; Tao, Yuan

2018-05-05

Classic core-based instrument transformers are more prone to magnetic saturation. This affects the measurement accuracy of such transformers and limits their applications in measuring large direct current (DC). Moreover, protection and control systems may exhibit malfunctions due to such measurement errors. This paper presents a more accurate method for current measurement based on a circular magnetic field sensing array. The proposed measurement approach utilizes multiple hall sensors that are evenly distributed on a circle. The average value of all hall sensors is regarded as the final measurement. The calculation model is established in the case of magnetic field interference of the parallel wire, and the simulation results show that the error decreases significantly when the number of hall sensors n is greater than 8. The measurement error is less than 0.06% when the wire spacing is greater than 2.5 times the radius of the sensor array. A simulation study on the off-center primary conductor is conducted, and a kind of hall sensor compensation method is adopted to improve the accuracy. The simulation and test results indicate that the measurement error of the system is less than 0.1%.

Evaluation of FNS control systems: software development and sensor characterization.

PubMed

Riess, J; Abbas, J J

1997-01-01

Functional Neuromuscular Stimulation (FNS) systems activate paralyzed limbs by electrically stimulating motor neurons. These systems have been used to restore functions such as standing and stepping in people with thoracic level spinal cord injury. Research in our laboratory is directed at the design and evaluation of the control algorithms for generating posture and movement. This paper describes software developed for implementing FNS control systems and the characterization of a sensor system used to implement and evaluate controllers in the laboratory. In order to assess FNS control algorithms, we have developed a versatile software package using Lab VIEW (National Instruments, Corp). This package provides the ability to interface with sensor systems via serial port or A/D board, implement data processing and real-time control algorithms, and interface with neuromuscular stimulation devices. In our laboratory, we use the Flock of Birds (Ascension Technology Corp.) motion tracking sensor system to monitor limb segment position and orientation (6 degrees of freedom). Errors in the sensor system have been characterized and nonlinear polynomial models have been developed to account for these errors. With this compensation, the error in the distance measurement is reduced by 90 % so that the maximum error is less than 1 cm.

A Survey on Multimedia-Based Cross-Layer Optimization in Visual Sensor Networks

PubMed Central

Costa, Daniel G.; Guedes, Luiz Affonso

2011-01-01

Visual sensor networks (VSNs) comprised of battery-operated electronic devices endowed with low-resolution cameras have expanded the applicability of a series of monitoring applications. Those types of sensors are interconnected by ad hoc error-prone wireless links, imposing stringent restrictions on available bandwidth, end-to-end delay and packet error rates. In such context, multimedia coding is required for data compression and error-resilience, also ensuring energy preservation over the path(s) toward the sink and improving the end-to-end perceptual quality of the received media. Cross-layer optimization may enhance the expected efficiency of VSNs applications, disrupting the conventional information flow of the protocol layers. When the inner characteristics of the multimedia coding techniques are exploited by cross-layer protocols and architectures, higher efficiency may be obtained in visual sensor networks. This paper surveys recent research on multimedia-based cross-layer optimization, presenting the proposed strategies and mechanisms for transmission rate adjustment, congestion control, multipath selection, energy preservation and error recovery. We note that many multimedia-based cross-layer optimization solutions have been proposed in recent years, each one bringing a wealth of contributions to visual sensor networks. PMID:22163908

Kalman Filter for Mass Property and Thrust Identification (MMS)

NASA Technical Reports Server (NTRS)

Queen, Steven

2015-01-01

The Magnetospheric Multiscale (MMS) mission consists of four identically instrumented, spin-stabilized observatories, elliptically orbiting the Earth in a tetrahedron formation. For the operational success of the mission, on-board systems must be able to deliver high-precision orbital adjustment maneuvers. On MMS, this is accomplished using feedback from on-board star sensors in tandem with accelerometers whose measurements are dynamically corrected for errors associated with a spinning platform. In order to determine the required corrections to the measured acceleration, precise estimates of attitude, rate, and mass-properties is necessary. To this end, both an on-board and ground-based Multiplicative Extended Kalman Filter (MEKF) were formulated and implemented in order to estimate the dynamic and quasi-static properties of the spacecraft.

In vivo evaluation of wearable head impact sensors

PubMed Central

Wu, Lyndia C.; Nangia, Vaibhav; Bui, Kevin; Hammoor, Bradley; Kurt, Mehmet; Hernandez, Fidel; Kuo, Calvin; Camarillo, David B.

2015-01-01

Inertial sensors are commonly used to measure human head motion.(R1–3) Some sensors have been tested with dummy or cadaver experiments with mixed results, and methods to evaluate sensors in vivo are lacking. Here we present an in vivo(R3–10) method using high speed video to test teeth-mounted (mouthguard), soft tissue-mounted (skin patch), and headgear-mounted (skull cap) sensors during 6–13g(R1–20) sagittal soccer head impacts. Sensor coupling to the skull (R1–3) was quantified by displacement from an ear-canal reference. Mouthguard displacements were within video measurement error (<1mm), while the skin patch and skull cap displaced up to 4mm and 13mm from the ear-canal reference, respectively. We used the mouthguard, which had the least displacement from skull (R1–5), as the reference to assess 6-degree-of-freedom skin patch and skull cap measurements. Linear and rotational acceleration magnitudes were over-predicted by both the skin patch (with 120% NRMS error for amag, 290% for αmag(R1–6)) and the skull cap (320% NRMS error for amag, 500% for αmag(R1–6)). Such over-predictions were largely due to out-of-plane motion. To model sensor error, we found that in-plane skin patch acceleration peaks in the anterior-posterior direction could be modeled by an underdamped viscoelastic system. In summary, the mouthguard showed tighter skull coupling than the other sensor mounting approaches(R1–7). Furthermore, the in vivo methods presented are valuable for investigating skull acceleration sensor technologies. PMID:26289941

Localization Methods for a Mobile Robot in Urban Environments

DTIC Science & Technology

2004-10-04

Columbia University, Department of Computer Science, 2001. [30] R. Brown and P. Hwang , Introduction to random signals and applied Kalman filtering, 3rd...sensor. An extended Kalman filter integrates the sensor data and keeps track of the uncertainty associated with it. The second method is based on...errors+ compass/GPS errors corrected odometry pose odometry error estimates zk zk h(x)~ h(x)~ Kalman Filter zk Fig. 4. A diagram of the extended

DOE Office of Scientific and Technical Information (OSTI.GOV)

Duchaineau, M.; Wolinsky, M.; Sigeti, D.E.

Terrain visualization is a difficult problem for applications requiring accurate images of large datasets at high frame rates, such as flight simulation and ground-based aircraft testing using synthetic sensor stimulation. On current graphics hardware, the problem is to maintain dynamic, view-dependent triangle meshes and texture maps that produce good images at the required frame rate. We present an algorithm for constructing triangle meshes that optimizes flexible view-dependent error metrics, produces guaranteed error bounds, achieves specified triangle counts directly, and uses frame-to-frame coherence to operate at high frame rates for thousands of triangles per frame. Our method, dubbed Real-time Optimally Adaptingmore » Meshes (ROAM), uses two priority queues to drive split and merge operations that maintain continuous triangulations built from pre-processed bintree triangles. We introduce two additional performance optimizations: incremental triangle stripping and priority-computation deferral lists. ROAM execution time is proportionate to the number of triangle changes per frame, which is typically a few percent of the output mesh size, hence ROAM performance is insensitive to the resolution and extent of the input terrain. Dynamic terrain and simple vertex morphing are supported.« less

Multiple Two-Way Time Message Exchange (TTME) Time Synchronization for Bridge Monitoring Wireless Sensor Networks

PubMed Central

Shi, Fanrong; Tuo, Xianguo; Yang, Simon X.; Li, Huailiang; Shi, Rui

2017-01-01

Wireless sensor networks (WSNs) have been widely used to collect valuable information in Structural Health Monitoring (SHM) of bridges, using various sensors, such as temperature, vibration and strain sensors. Since multiple sensors are distributed on the bridge, accurate time synchronization is very important for multi-sensor data fusion and information processing. Based on shape of the bridge, a spanning tree is employed to build linear topology WSNs and achieve time synchronization in this paper. Two-way time message exchange (TTME) and maximum likelihood estimation (MLE) are employed for clock offset estimation. Multiple TTMEs are proposed to obtain a subset of TTME observations. The time out restriction and retry mechanism are employed to avoid the estimation errors that are caused by continuous clock offset and software latencies. The simulation results show that the proposed algorithm could avoid the estimation errors caused by clock drift and minimize the estimation error due to the large random variable delay jitter. The proposed algorithm is an accurate and low complexity time synchronization algorithm for bridge health monitoring. PMID:28471418

Multiple Two-Way Time Message Exchange (TTME) Time Synchronization for Bridge Monitoring Wireless Sensor Networks.

PubMed

Shi, Fanrong; Tuo, Xianguo; Yang, Simon X; Li, Huailiang; Shi, Rui

2017-05-04

Wireless sensor networks (WSNs) have been widely used to collect valuable information in Structural Health Monitoring (SHM) of bridges, using various sensors, such as temperature, vibration and strain sensors. Since multiple sensors are distributed on the bridge, accurate time synchronization is very important for multi-sensor data fusion and information processing. Based on shape of the bridge, a spanning tree is employed to build linear topology WSNs and achieve time synchronization in this paper. Two-way time message exchange (TTME) and maximum likelihood estimation (MLE) are employed for clock offset estimation. Multiple TTMEs are proposed to obtain a subset of TTME observations. The time out restriction and retry mechanism are employed to avoid the estimation errors that are caused by continuous clock offset and software latencies. The simulation results show that the proposed algorithm could avoid the estimation errors caused by clock drift and minimize the estimation error due to the large random variable delay jitter. The proposed algorithm is an accurate and low complexity time synchronization algorithm for bridge health monitoring.

Calibration and temperature correction of heat dissipation matric potential sensors

USGS Publications Warehouse

Flint, A.L.; Campbell, G.S.; Ellett, K.M.; Calissendorff, C.

2002-01-01

This paper describes how heat dissipation sensors, used to measure soil water matric potential, were analyzed to develop a normalized calibration equation and a temperature correction method. Inference of soil matric potential depends on a correlation between the variable thermal conductance of the sensor's porous ceramic and matric poten-tial. Although this correlation varies among sensors, we demonstrate a normalizing procedure that produces a single calibration relationship. Using sensors from three sources and different calibration methods, the normalized calibration resulted in a mean absolute error of 23% over a matric potential range of -0.01 to -35 MPa. Because the thermal conductivity of variably saturated porous media is temperature dependent, a temperature correction is required for application of heat dissipation sensors in field soils. A temperature correction procedure is outlined that reduces temperature dependent errors by 10 times, which reduces the matric potential measurement errors by more than 30%. The temperature dependence is well described by a thermal conductivity model that allows for the correction of measurements at any temperature to measurements at the calibration temperature.

Space based optical staring sensor LOS determination and calibration using GCPs observation

NASA Astrophysics Data System (ADS)

Chen, Jun; An, Wei; Deng, Xinpu; Yang, Jungang; Sha, Zhichao

2016-10-01

Line of sight (LOS) attitude determination and calibration is the key prerequisite of tracking and location of targets in space based infrared (IR) surveillance systems (SBIRS) and the LOS determination and calibration of staring sensor is one of the difficulties. This paper provides a novel methodology for removing staring sensor bias through the use of Ground Control Points (GCPs) detected in the background field of the sensor. Based on researching the imaging model and characteristics of the staring sensor of SBIRS geostationary earth orbit part (GEO), the real time LOS attitude determination and calibration algorithm using landmark control point is proposed. The influential factors (including the thermal distortions error, assemble error, and so on) of staring sensor LOS attitude error are equivalent to bias angle of LOS attitude. By establishing the observation equation of GCPs and the state transition equation of bias angle, and using an extend Kalman filter (EKF), the real time estimation of bias angle and the high precision sensor LOS attitude determination and calibration are achieved. The simulation results show that the precision and timeliness of the proposed algorithm meet the request of target tracking and location process in space based infrared surveillance system.

Particle-based optical pressure sensors for 3D pressure mapping.

PubMed

Banerjee, Niladri; Xie, Yan; Chalaseni, Sandeep; Mastrangelo, Carlos H

2015-10-01

This paper presents particle-based optical pressure sensors for in-flow pressure sensing, especially for microfluidic environments. Three generations of pressure sensitive particles have been developed- flat planar particles, particles with integrated retroreflectors and spherical microballoon particles. The first two versions suffer from pressure measurement dependence on particles orientation in 3D space and angle of interrogation. The third generation of microspherical particles with spherical symmetry solves these problems making particle-based manometry in microfluidic environment a viable and efficient methodology. Static and dynamic pressure measurements have been performed in liquid medium for long periods of time in a pressure range of atmospheric to 40 psi. Spherical particles with radius of 12 μm and balloon-wall thickness of 0.5 μm are effective for more than 5 h in this pressure range with an error of less than 5%.

Continuous glucose monitoring in subcutaneous tissue using factory-calibrated sensors: a pilot study.

PubMed

Hoss, Udo; Jeddi, Iman; Schulz, Mark; Budiman, Erwin; Bhogal, Claire; McGarraugh, Geoffrey

2010-08-01

Commercial continuous subcutaneous glucose monitors require in vivo calibration using capillary blood glucose tests. Feasibility of factory calibration, i.e., sensor batch characterization in vitro with no further need for in vivo calibration, requires a predictable and stable in vivo sensor sensitivity and limited inter- and intra-subject variation of the ratio of interstitial to blood glucose concentration. Twelve volunteers wore two FreeStyle Navigator (Abbott Diabetes Care, Alameda, CA) continuous glucose monitoring systems for 5 days in parallel for two consecutive sensor wears (four sensors per subject, 48 sensors total). Sensors from a prototype sensor lot with a low variability in glucose sensitivity were used for the study. Median sensor sensitivity values based on capillary blood glucose were calculated per sensor and compared for inter- and intra-subject variation. Mean absolute relative difference (MARD) calculation and error grid analysis were performed using a single calibration factor for all sensors to simulate factory calibration and compared to standard fingerstick calibration. Sensor sensitivity variation in vitro was 4.6%, which increased to 8.3% in vivo (P < 0.0001). Analysis of variance revealed no significant inter-subject differences in sensor sensitivity (P = 0.134). Applying a single universal calibration factor retrospectively to all sensors resulted in a MARD of 10.4% and 88.1% of values in Clarke Error Grid Zone A, compared to a MARD of 10.9% and 86% of values in Error Grid Zone A for fingerstick calibration. Factory calibration of sensors for continuous subcutaneous glucose monitoring is feasible with similar accuracy to standard fingerstick calibration. Additional data are required to confirm this result in subjects with diabetes.

A minimalist approach to bias estimation for passive sensor measurements with targets of opportunity

NASA Astrophysics Data System (ADS)

Belfadel, Djedjiga; Osborne, Richard W.; Bar-Shalom, Yaakov

2013-09-01

In order to carry out data fusion, registration error correction is crucial in multisensor systems. This requires estimation of the sensor measurement biases. It is important to correct for these bias errors so that the multiple sensor measurements and/or tracks can be referenced as accurately as possible to a common tracking coordinate system. This paper provides a solution for bias estimation for the minimum number of passive sensors (two), when only targets of opportunity are available. The sensor measurements are assumed time-coincident (synchronous) and perfectly associated. Since these sensors provide only line of sight (LOS) measurements, the formation of a single composite Cartesian measurement obtained from fusing the LOS measurements from different sensors is needed to avoid the need for nonlinear filtering. We evaluate the Cramer-Rao Lower Bound (CRLB) on the covariance of the bias estimate, i.e., the quantification of the available information about the biases. Statistical tests on the results of simulations show that this method is statistically efficient, even for small sample sizes (as few as two sensors and six points on the trajectory of a single target of opportunity). We also show that the RMS position error is significantly improved with bias estimation compared with the target position estimation using the original biased measurements.

Postlaunch calibration of spacecraft attitude instruments

NASA Technical Reports Server (NTRS)

Davis, W.; Hashmall, J.; Garrick, J.; Harman, R.

1993-01-01

The accuracy of both onboard and ground attitude determination can be significantly enhanced by calibrating spacecraft attitude instruments (sensors) after launch. Although attitude sensors are accurately calibrated before launch, the stresses of launch and the space environment inevitably cause changes in sensor parameters. During the mission, these parameters may continue to drift requiring repeated on-orbit calibrations. The goal of attitude sensor calibration is to reduce the systematic errors in the measurement models. There are two stages at which systematic errors may enter. The first occurs in the conversion of sensor output into an observation vector in the sensor frame. The second occurs in the transformation of the vector from the sensor frame to the spacecraft attitude reference frame. This paper presents postlaunch alignment and transfer function calibration of the attitude sensors for the Compton Gamma Ray Observatory (GRO), the Upper Atmosphere Research Satellite (UARS), and the Extreme Ultraviolet Explorer (EUVE).

Monitoring gait in multiple sclerosis with novel wearable motion sensors

PubMed Central

McGinnis, Ryan S.; Seagers, Kirsten; Motl, Robert W.; Sheth, Nirav; Wright, John A.; Ghaffari, Roozbeh; Sosnoff, Jacob J.

2017-01-01

Background Mobility impairment is common in people with multiple sclerosis (PwMS) and there is a need to assess mobility in remote settings. Here, we apply a novel wireless, skin-mounted, and conformal inertial sensor (BioStampRC, MC10 Inc.) to examine gait characteristics of PwMS under controlled conditions. We determine the accuracy and precision of BioStampRC in measuring gait kinematics by comparing to contemporary research-grade measurement devices. Methods A total of 45 PwMS, who presented with diverse walking impairment (Mild MS = 15, Moderate MS = 15, Severe MS = 15), and 15 healthy control subjects participated in the study. Participants completed a series of clinical walking tests. During the tests participants were instrumented with BioStampRC and MTx (Xsens, Inc.) sensors on their shanks, as well as an activity monitor GT3X (Actigraph, Inc.) on their non-dominant hip. Shank angular velocity was simultaneously measured with the inertial sensors. Step number and temporal gait parameters were calculated from the data recorded by each sensor. Visual inspection and the MTx served as the reference standards for computing the step number and temporal parameters, respectively. Accuracy (error) and precision (variance of error) was assessed based on absolute and relative metrics. Temporal parameters were compared across groups using ANOVA. Results Mean accuracy±precision for the BioStampRC was 2±2 steps error for step number, 6±9ms error for stride time and 6±7ms error for step time (0.6–2.6% relative error). Swing time had the least accuracy±precision (25±19ms error, 5±4% relative error) among the parameters. GT3X had the least accuracy±precision (8±14% relative error) in step number estimate among the devices. Both MTx and BioStampRC detected significantly distinct gait characteristics between PwMS with different disability levels (p<0.01). Conclusion BioStampRC sensors accurately and precisely measure gait parameters in PwMS across diverse walking impairment levels and detected differences in gait characteristics by disability level in PwMS. This technology has the potential to provide granular monitoring of gait both inside and outside the clinic. PMID:28178288

Unscented predictive variable structure filter for satellite attitude estimation with model errors when using low precision sensors

NASA Astrophysics Data System (ADS)

Cao, Lu; Li, Hengnian

2016-10-01

For the satellite attitude estimation problem, the serious model errors always exist and hider the estimation performance of the Attitude Determination and Control System (ACDS), especially for a small satellite with low precision sensors. To deal with this problem, a new algorithm for the attitude estimation, referred to as the unscented predictive variable structure filter (UPVSF) is presented. This strategy is proposed based on the variable structure control concept and unscented transform (UT) sampling method. It can be implemented in real time with an ability to estimate the model errors on-line, in order to improve the state estimation precision. In addition, the model errors in this filter are not restricted only to the Gaussian noises; therefore, it has the advantages to deal with the various kinds of model errors or noises. It is anticipated that the UT sampling strategy can further enhance the robustness and accuracy of the novel UPVSF. Numerical simulations show that the proposed UPVSF is more effective and robustness in dealing with the model errors and low precision sensors compared with the traditional unscented Kalman filter (UKF).

Design of fiber optic based respiratory sensor for newborn incubator application

NASA Astrophysics Data System (ADS)

Dhia, Arika; Devara, Kresna; Abuzairi, Tomy; Poespawati, N. R.; Purnamaningsih, Retno W.

2018-02-01

This paper reports the design of respiratory sensor using fiber optic for newborn incubator application. The sensor works based on light intensity losses difference obtained due to thorax movement during respiration. The output of the sensor launched to support electronic circuits to be processed in Arduino Uno microcontroler such that the real-time respiratory rate (breath per minute) can be presented on LCD. Experiment results using thorax expansion of newborn simulator show that the system is able to measure respiratory rate from 10 up to 130 breaths per minute with 0.595% error and 0.2% hysteresis error.

Probing-error compensation using 5 degree of freedom force/moment sensor for coordinate measuring machine

NASA Astrophysics Data System (ADS)

Lee, Minho; Cho, Nahm-Gyoo

2013-09-01

A new probing and compensation method is proposed to improve the three-dimensional (3D) measuring accuracy of 3D shapes, including irregular surfaces. A new tactile coordinate measuring machine (CMM) probe with a five-degree of freedom (5-DOF) force/moment sensor using carbon fiber plates was developed. The proposed method efficiently removes the anisotropic sensitivity error and decreases the stylus deformation and the actual contact point estimation errors that are major error components of shape measurement using touch probes. The relationship between the measuring force and estimation accuracy of the actual contact point error and stylus deformation error are examined for practical use of the proposed method. The appropriate measuring force condition is presented for the precision measurement.

Integrated polarization-dependent sensor for autonomous navigation

NASA Astrophysics Data System (ADS)

Liu, Ze; Zhang, Ran; Wang, Zhiwen; Guan, Le; Li, Bin; Chu, Jinkui

2015-01-01

Based on the navigation strategy of insects utilizing the polarized skylight, an integrated polarization-dependent sensor for autonomous navigation is presented. The navigation sensor has the features of compact structure, high precision, strong robustness, and a simple manufacture technique. The sensor is composed by integrating a complementary-metal-oxide-semiconductor sensor with a multiorientation nanowire grid polarizer. By nanoimprint lithography, the multiorientation nanowire polarizer is fabricated in one step and the alignment error is eliminated. The statistical theory is added to the interval-division algorithm to calculate the polarization angle of the incident light. The laboratory and outdoor tests for the navigation sensor are implemented and the errors of the measured angle are ±0.02 deg and ±1.3 deg, respectively. The results show that the proposed sensor has potential for application in autonomous navigation.

Effect of retransmission and retrodiction on estimation and fusion in long-haul sensor networks

DOE PAGES

Liu, Qiang; Wang, Xin; Rao, Nageswara S. V.; ...

2016-01-01

In a long-haul sensor network, sensors are remotely deployed over a large geographical area to perform certain tasks, such as target tracking. In this work, we study the scenario where sensors take measurements of one or more dynamic targets and send state estimates of the targets to a fusion center via satellite links. The severe loss and delay inherent over the satellite channels reduce the number of estimates successfully arriving at the fusion center, thereby limiting the potential fusion gain and resulting in suboptimal accuracy performance of the fused estimates. In addition, the errors in target-sensor data association can alsomore » degrade the estimation performance. To mitigate the effect of imperfect communications on state estimation and fusion, we consider retransmission and retrodiction. The system adopts certain retransmission-based transport protocols so that lost messages can be recovered over time. Besides, retrodiction/smoothing techniques are applied so that the chances of incurring excess delay due to retransmission are greatly reduced. We analyze the extent to which retransmission and retrodiction can improve the performance of delay-sensitive target tracking tasks under variable communication loss and delay conditions. Lastly, simulation results of a ballistic target tracking application are shown in the end to demonstrate the validity of our analysis.« less

Cooperative MIMO communication at wireless sensor network: an error correcting code approach.

PubMed

Islam, Mohammad Rakibul; Han, Young Shin

2011-01-01

Cooperative communication in wireless sensor network (WSN) explores the energy efficient wireless communication schemes between multiple sensors and data gathering node (DGN) by exploiting multiple input multiple output (MIMO) and multiple input single output (MISO) configurations. In this paper, an energy efficient cooperative MIMO (C-MIMO) technique is proposed where low density parity check (LDPC) code is used as an error correcting code. The rate of LDPC code is varied by varying the length of message and parity bits. Simulation results show that the cooperative communication scheme outperforms SISO scheme in the presence of LDPC code. LDPC codes with different code rates are compared using bit error rate (BER) analysis. BER is also analyzed under different Nakagami fading scenario. Energy efficiencies are compared for different targeted probability of bit error p(b). It is observed that C-MIMO performs more efficiently when the targeted p(b) is smaller. Also the lower encoding rate for LDPC code offers better error characteristics.

Cooperative MIMO Communication at Wireless Sensor Network: An Error Correcting Code Approach

PubMed Central

Islam, Mohammad Rakibul; Han, Young Shin

2011-01-01

Cooperative communication in wireless sensor network (WSN) explores the energy efficient wireless communication schemes between multiple sensors and data gathering node (DGN) by exploiting multiple input multiple output (MIMO) and multiple input single output (MISO) configurations. In this paper, an energy efficient cooperative MIMO (C-MIMO) technique is proposed where low density parity check (LDPC) code is used as an error correcting code. The rate of LDPC code is varied by varying the length of message and parity bits. Simulation results show that the cooperative communication scheme outperforms SISO scheme in the presence of LDPC code. LDPC codes with different code rates are compared using bit error rate (BER) analysis. BER is also analyzed under different Nakagami fading scenario. Energy efficiencies are compared for different targeted probability of bit error pb. It is observed that C-MIMO performs more efficiently when the targeted pb is smaller. Also the lower encoding rate for LDPC code offers better error characteristics. PMID:22163732

Effect of Slice Error of Glass on Zero Offset of Capacitive Accelerometer

NASA Astrophysics Data System (ADS)

Hao, R.; Yu, H. J.; Zhou, W.; Peng, B.; Guo, J.

2018-03-01

Packaging process had been studied on capacitance accelerometer. The silicon-glass bonding process had been adopted on sensor chip and glass, and sensor chip and glass was adhered on ceramic substrate, the three-layer structure was curved due to the thermal mismatch, the slice error of glass lead to asymmetrical curve of sensor chip. Thus, the sensitive mass of accelerometer deviated along the sensitive direction, which was caused in zero offset drift. It was meaningful to confirm the influence of slice error of glass, the simulation results showed that the zero output drift was 12.3×10-3 m/s2 when the deviation was 40μm.

Attitude error response of structures to actuator/sensor noise

NASA Technical Reports Server (NTRS)

Balakrishnan, A. V.

1991-01-01

Explicit closed-form formulas are presented for the RMS attitude-error response to sensor and actuator noise for co-located actuators/sensors as a function of both control-gain parameters and structure parameters. The main point of departure is the use of continuum models. In particular the anisotropic Timoshenko model is used for lattice trusses typified by the NASA EPS Structure Model and the Evolutionary Model. One conclusion is that the maximum attainable improvement in the attitude error varying either structure parameters or control gains is 3 dB for the axial and torsion modes, the bending being essentially insensitive. The results are similar whether the Bernoulli model or the anisotropic Timoshenko model is used.

Robustness of Thirty Meter Telescope primary mirror control

NASA Astrophysics Data System (ADS)

Macmynowski, Douglas G.; Thompson, Peter M.; Shelton, Chris; Roberts, Lewis C., Jr.

2010-07-01

The primary mirror control system for the Thirty Meter Telescope (TMT) maintains the alignment of the 492 segments in the presence of both quasi-static (gravity and thermal) and dynamic disturbances due to unsteady wind loads. The latter results in a desired control bandwidth of 1Hz at high spatial frequencies. The achievable bandwidth is limited by robustness to (i) uncertain telescope structural dynamics (control-structure interaction) and (ii) small perturbations in the ill-conditioned influence matrix that relates segment edge sensor response to actuator commands. Both of these effects are considered herein using models of TMT. The former is explored through multivariable sensitivity analysis on a reduced-order Zernike-basis representation of the structural dynamics. The interaction matrix ("A-matrix") uncertainty has been analyzed theoretically elsewhere, and is examined here for realistic amplitude perturbations due to segment and sensor installation errors, and gravity and thermal induced segment motion. The primary influence of A-matrix uncertainty is on the control of "focusmode"; this is the least observable mode, measurable only through the edge-sensor (gap-dependent) sensitivity to the dihedral angle between segments. Accurately estimating focus-mode will require updating the A-matrix as a function of the measured gap. A-matrix uncertainty also results in a higher gain-margin requirement for focus-mode, and hence the A-matrix and CSI robustness need to be understood simultaneously. Based on the robustness analysis, the desired 1 Hz bandwidth is achievable in the presence of uncertainty for all except the lowest spatial-frequency response patterns of the primary mirror.

Attitude control system conceptual design for the GOES-N spacecraft series

NASA Technical Reports Server (NTRS)

Markley, F. L.; Bauer, F. H.; Deily, J. J.; Femiano, M. D.

1991-01-01

The attitude determination sensing and processing of the system are considered, and inertial reference units, star trackers, and beacons and landmarks are discussed as well as an extended Kalman filter and expected attitude-determination performance. The baseline controller is overviewed, and a spacecraft motion compensation (SMC) algorithm, disturbance environment, and SMC performance expectations are covered. Detailed simulation results are presented, and emphasis is placed on dynamic models, attitude estimation and control, and SMC disturbance accommmodation. It is shown that the attitude control system employing gyro/star tracker sensing and active three-axis control with reaction wheels is capable of maintaining attitude errors of 1.7 microrad or less on all axes in the absence of attitude disturbances, and that the sensor line-of-sight pointing errors can be reduced to 0.1 microrad by SMC.

On the importance of measurement error correlations in data assimilation for integrated hydrological models

NASA Astrophysics Data System (ADS)

Camporese, Matteo; Botto, Anna

2017-04-01

Data assimilation is becoming increasingly popular in hydrological and earth system modeling, as it allows us to integrate multisource observation data in modeling predictions and, in doing so, to reduce uncertainty. For this reason, data assimilation has been recently the focus of much attention also for physically-based integrated hydrological models, whereby multiple terrestrial compartments (e.g., snow cover, surface water, groundwater) are solved simultaneously, in an attempt to tackle environmental problems in a holistic approach. Recent examples include the joint assimilation of water table, soil moisture, and river discharge measurements in catchment models of coupled surface-subsurface flow using the ensemble Kalman filter (EnKF). One of the typical assumptions in these studies is that the measurement errors are uncorrelated, whereas in certain situations it is reasonable to believe that some degree of correlation occurs, due for example to the fact that a pair of sensors share the same soil type. The goal of this study is to show if and how the measurement error correlations between different observation data play a significant role on assimilation results in a real-world application of an integrated hydrological model. The model CATHY (CATchment HYdrology) is applied to reproduce the hydrological dynamics observed in an experimental hillslope. The physical model, located in the Department of Civil, Environmental and Architectural Engineering of the University of Padova (Italy), consists of a reinforced concrete box containing a soil prism with maximum height of 3.5 m, length of 6 m, and width of 2 m. The hillslope is equipped with sensors to monitor the pressure head and soil moisture responses to a series of generated rainfall events applied onto a 60 cm thick sand layer overlying a sandy clay soil. The measurement network is completed by two tipping bucket flow gages to measure the two components (subsurface and surface) of the outflow. By collecting data at a temporal resolution of 0.5 Hz (relatively high, compared to the hydrological dynamics), we can perform a comprehensive statistical analysis of the observations, including the cross-correlations between data from different sensors. We report on the impact of taking these correlations into account in a series of assimilation scenarios, where the EnKF is used to assimilate pressure head and/or soil moisture and/or subsurface outflow.

Distributed fault detection over sensor networks with Markovian switching topologies

NASA Astrophysics Data System (ADS)

Ge, Xiaohua; Han, Qing-Long

2014-05-01

This paper deals with the distributed fault detection for discrete-time Markov jump linear systems over sensor networks with Markovian switching topologies. The sensors are scatteredly deployed in the sensor field and the fault detectors are physically distributed via a communication network. The system dynamics changes and sensing topology variations are modeled by a discrete-time Markov chain with incomplete mode transition probabilities. Each of these sensor nodes firstly collects measurement outputs from its all underlying neighboring nodes, processes these data in accordance with the Markovian switching topologies, and then transmits the processed data to the remote fault detector node. Network-induced delays and accumulated data packet dropouts are incorporated in the data transmission between the sensor nodes and the distributed fault detector nodes through the communication network. To generate localized residual signals, mode-independent distributed fault detection filters are proposed. By means of the stochastic Lyapunov functional approach, the residual system performance analysis is carried out such that the overall residual system is stochastically stable and the error between each residual signal and the fault signal is made as small as possible. Furthermore, a sufficient condition on the existence of the mode-independent distributed fault detection filters is derived in the simultaneous presence of incomplete mode transition probabilities, Markovian switching topologies, network-induced delays, and accumulated data packed dropouts. Finally, a stirred-tank reactor system is given to show the effectiveness of the developed theoretical results.

Semi-physical simulation test for micro CMOS star sensor

NASA Astrophysics Data System (ADS)

Yang, Jian; Zhang, Guang-jun; Jiang, Jie; Fan, Qiao-yun

2008-03-01

A designed star sensor must be extensively tested before launching. Testing star sensor requires complicated process with much time and resources input. Even observing sky on the ground is a challenging and time-consuming job, requiring complicated and expensive equipments, suitable time and location, and prone to be interfered by weather. And moreover, not all stars distributed on the sky can be observed by this testing method. Semi-physical simulation in laboratory reduces the testing cost and helps to debug, analyze and evaluate the star sensor system while developing the model. The test system is composed of optical platform, star field simulator, star field simulator computer, star sensor and the central data processing computer. The test system simulates the starlight with high accuracy and good parallelism, and creates static or dynamic image in FOV (Field of View). The conditions of the test are close to observing real sky. With this system, the test of a micro star tracker designed by Beijing University of Aeronautics and Astronautics has been performed successfully. Some indices including full-sky autonomous star identification time, attitude update frequency and attitude precision etc. meet design requirement of the star sensor. Error source of the testing system is also analyzed. It is concluded that the testing system is cost-saving, efficient, and contributes to optimizing the embed arithmetic, shortening the development cycle and improving engineering design processes.

Mathematical models and photogrammetric exploitation of image sensing

NASA Astrophysics Data System (ADS)

Puatanachokchai, Chokchai

Mathematical models of image sensing are generally categorized into physical/geometrical sensor models and replacement sensor models. While the former is determined from image sensing geometry, the latter is based on knowledge of the physical/geometric sensor models and on using such models for its implementation. The main thrust of this research is in replacement sensor models which have three important characteristics: (1) Highly accurate ground-to-image functions; (2) Rigorous error propagation that is essentially of the same accuracy as the physical model; and, (3) Adjustability, or the ability to upgrade the replacement sensor model parameters when additional control information becomes available after the replacement sensor model has replaced the physical model. In this research, such replacement sensor models are considered as True Replacement Models or TRMs. TRMs provide a significant advantage of universality, particularly for image exploitation functions. There have been several writings about replacement sensor models, and except for the so called RSM (Replacement Sensor Model as a product described in the Manual of Photogrammetry), almost all of them pay very little or no attention to errors and their propagation. This is because, it is suspected, the few physical sensor parameters are usually replaced by many more parameters, thus presenting a potential error estimation difficulty. The third characteristic, adjustability, is perhaps the most demanding. It provides an equivalent flexibility to that of triangulation using the physical model. Primary contributions of this thesis include not only "the eigen-approach", a novel means of replacing the original sensor parameter covariance matrices at the time of estimating the TRM, but also the implementation of the hybrid approach that combines the eigen-approach with the added parameters approach used in the RSM. Using either the eigen-approach or the hybrid approach, rigorous error propagation can be performed during image exploitation. Further, adjustability can be performed when additional control information becomes available after the TRM has been implemented. The TRM is shown to apply to imagery from sensors having different geometries, including an aerial frame camera, a spaceborne linear array sensor, an airborne pushbroom sensor, and an airborne whiskbroom sensor. TRM results show essentially negligible differences as compared to those from rigorous physical sensor models, both for geopositioning from single and overlapping images. Simulated as well as real image data are used to address all three characteristics of the TRM.

On-Line Temperature Estimation for Noisy Thermal Sensors Using a Smoothing Filter-Based Kalman Predictor

PubMed Central

Li, Zhi; Wei, Henglu; Zhou, Wei; Duan, Zhemin

2018-01-01

Dynamic thermal management (DTM) mechanisms utilize embedded thermal sensors to collect fine-grained temperature information for monitoring the real-time thermal behavior of multi-core processors. However, embedded thermal sensors are very susceptible to a variety of sources of noise, including environmental uncertainty and process variation. This causes the discrepancies between actual temperatures and those observed by on-chip thermal sensors, which seriously affect the efficiency of DTM. In this paper, a smoothing filter-based Kalman prediction technique is proposed to accurately estimate the temperatures from noisy sensor readings. For the multi-sensor estimation scenario, the spatial correlations among different sensor locations are exploited. On this basis, a multi-sensor synergistic calibration algorithm (known as MSSCA) is proposed to improve the simultaneous prediction accuracy of multiple sensors. Moreover, an infrared imaging-based temperature measurement technique is also proposed to capture the thermal traces of an advanced micro devices (AMD) quad-core processor in real time. The acquired real temperature data are used to evaluate our prediction performance. Simulation shows that the proposed synergistic calibration scheme can reduce the root-mean-square error (RMSE) by 1.2 ∘C and increase the signal-to-noise ratio (SNR) by 15.8 dB (with a very small average runtime overhead) compared with assuming the thermal sensor readings to be ideal. Additionally, the average false alarm rate (FAR) of the corrected sensor temperature readings can be reduced by 28.6%. These results clearly demonstrate that if our approach is used to perform temperature estimation, the response mechanisms of DTM can be triggered to adjust the voltages, frequencies, and cooling fan speeds at more appropriate times. PMID:29393862

On-Line Temperature Estimation for Noisy Thermal Sensors Using a Smoothing Filter-Based Kalman Predictor.

PubMed

Li, Xin; Ou, Xingtao; Li, Zhi; Wei, Henglu; Zhou, Wei; Duan, Zhemin

2018-02-02

Dynamic thermal management (DTM) mechanisms utilize embedded thermal sensors to collect fine-grained temperature information for monitoring the real-time thermal behavior of multi-core processors. However, embedded thermal sensors are very susceptible to a variety of sources of noise, including environmental uncertainty and process variation. This causes the discrepancies between actual temperatures and those observed by on-chip thermal sensors, which seriously affect the efficiency of DTM. In this paper, a smoothing filter-based Kalman prediction technique is proposed to accurately estimate the temperatures from noisy sensor readings. For the multi-sensor estimation scenario, the spatial correlations among different sensor locations are exploited. On this basis, a multi-sensor synergistic calibration algorithm (known as MSSCA) is proposed to improve the simultaneous prediction accuracy of multiple sensors. Moreover, an infrared imaging-based temperature measurement technique is also proposed to capture the thermal traces of an advanced micro devices (AMD) quad-core processor in real time. The acquired real temperature data are used to evaluate our prediction performance. Simulation shows that the proposed synergistic calibration scheme can reduce the root-mean-square error (RMSE) by 1.2 ∘ C and increase the signal-to-noise ratio (SNR) by 15.8 dB (with a very small average runtime overhead) compared with assuming the thermal sensor readings to be ideal. Additionally, the average false alarm rate (FAR) of the corrected sensor temperature readings can be reduced by 28.6%. These results clearly demonstrate that if our approach is used to perform temperature estimation, the response mechanisms of DTM can be triggered to adjust the voltages, frequencies, and cooling fan speeds at more appropriate times.

Measurement of centering error for probe of swing arm profilometer using a spectral confocal sensor

NASA Astrophysics Data System (ADS)

Chen, Lin; Jing, Hongwei; Wei, Zhongwei; Cao, Xuedong

2015-02-01

A spectral confocal sensor was used to measure the centering error for probe of swing arm profilometer (SAP). The feasibility of this technology was proved through simulation and experiment. The final measurement results was also analyzed to evaluate the advantages and disadvantages of this technology.

Capacitive wearable tactile sensor based on smart textile substrate with carbon black /silicone rubber composite dielectric

NASA Astrophysics Data System (ADS)

Guo, Xiaohui; Huang, Ying; Cai, Xia; Liu, Caixia; Liu, Ping

2016-04-01

To achieve the wearable comfort of electronic skin (e-skin), a capacitive sensor printed on a flexible textile substrate with a carbon black (CB)/silicone rubber (SR) composite dielectric was demonstrated in this paper. Organo-silicone conductive silver adhesive serves as a flexible electrodes/shielding layer. The structure design, sensing mechanism and the influence of the conductive filler content and temperature variations on the sensor performance were investigated. The proposed device can effectively enhance the flexibility and comfort of wearing the device asthe sensing element has achieved a sensitivity of 0.02536%/KPa, a hysteresis error of 5.6%, and a dynamic response time of ~89 ms at the range of 0-700 KPa. The drift induced by temperature variations has been calibrated by presenting the temperature compensation model. The research on the time-space distribution of plantar pressure information and the experiment of the manipulator soft-grasping were implemented with the introduced device, and the experimental results indicate that the capacitive flexible textile tactile sensor has good stability and tactile perception capacity. This study provides a good candidate for wearable artificial skin.

Multi Sensor Fusion Framework for Indoor-Outdoor Localization of Limited Resource Mobile Robots

PubMed Central

Marín, Leonardo; Vallés, Marina; Soriano, Ángel; Valera, Ángel; Albertos, Pedro

2013-01-01

This paper presents a sensor fusion framework that improves the localization of mobile robots with limited computational resources. It employs an event based Kalman Filter to combine the measurements of a global sensor and an inertial measurement unit (IMU) on an event based schedule, using fewer resources (execution time and bandwidth) but with similar performance when compared to the traditional methods. The event is defined to reflect the necessity of the global information, when the estimation error covariance exceeds a predefined limit. The proposed experimental platforms are based on the LEGO Mindstorm NXT, and consist of a differential wheel mobile robot navigating indoors with a zenithal camera as global sensor, and an Ackermann steering mobile robot navigating outdoors with a SBG Systems GPS accessed through an IGEP board that also serves as datalogger. The IMU in both robots is built using the NXT motor encoders along with one gyroscope, one compass and two accelerometers from Hitecnic, placed according to a particle based dynamic model of the robots. The tests performed reflect the correct performance and low execution time of the proposed framework. The robustness and stability is observed during a long walk test in both indoors and outdoors environments. PMID:24152933

Multi sensor fusion framework for indoor-outdoor localization of limited resource mobile robots.

PubMed

Marín, Leonardo; Vallés, Marina; Soriano, Ángel; Valera, Ángel; Albertos, Pedro

2013-10-21

This paper presents a sensor fusion framework that improves the localization of mobile robots with limited computational resources. It employs an event based Kalman Filter to combine the measurements of a global sensor and an inertial measurement unit (IMU) on an event based schedule, using fewer resources (execution time and bandwidth) but with similar performance when compared to the traditional methods. The event is defined to reflect the necessity of the global information, when the estimation error covariance exceeds a predefined limit. The proposed experimental platforms are based on the LEGO Mindstorm NXT, and consist of a differential wheel mobile robot navigating indoors with a zenithal camera as global sensor, and an Ackermann steering mobile robot navigating outdoors with a SBG Systems GPS accessed through an IGEP board that also serves as datalogger. The IMU in both robots is built using the NXT motor encoders along with one gyroscope, one compass and two accelerometers from Hitecnic, placed according to a particle based dynamic model of the robots. The tests performed reflect the correct performance and low execution time of the proposed framework. The robustness and stability is observed during a long walk test in both indoors and outdoors environments.

Virtual Sensor for Kinematic Estimation of Flexible Links in Parallel Robots

PubMed Central

Cabanes, Itziar; Mancisidor, Aitziber; Pinto, Charles

2017-01-01

The control of flexible link parallel manipulators is still an open area of research, endpoint trajectory tracking being one of the main challenges in this type of robot. The flexibility and deformations of the limbs make the estimation of the Tool Centre Point (TCP) position a challenging one. Authors have proposed different approaches to estimate this deformation and deduce the location of the TCP. However, most of these approaches require expensive measurement systems or the use of high computational cost integration methods. This work presents a novel approach based on a virtual sensor which can not only precisely estimate the deformation of the flexible links in control applications (less than 2% error), but also its derivatives (less than 6% error in velocity and 13% error in acceleration) according to simulation results. The validity of the proposed Virtual Sensor is tested in a Delta Robot, where the position of the TCP is estimated based on the Virtual Sensor measurements with less than a 0.03% of error in comparison with the flexible approach developed in ADAMS Multibody Software. PMID:28832510

Research on the Conductivity-Based Detection Principles of Bubbles in Two-Phase Flows and the Design of a Bubble Sensor for CBM Wells.

PubMed

Wu, Chuan; Wen, Guojun; Han, Lei; Wu, Xiaoming

2016-09-17

The parameters of gas-liquid two-phase flow bubbles in field coalbed methane (CBM) wells are of great significance for analyzing coalbed methane output, judging faults in CBM wells, and developing gas drainage and extraction processes, which stimulates an urgent need for detecting bubble parameters for CBM wells in the field. However, existing bubble detectors cannot meet the requirements of the working environments of CBM wells. Therefore, this paper reports findings on the principles of measuring the flow pattern, velocity, and volume of two-phase flow bubbles based on conductivity, from which a new bubble sensor was designed. The structural parameters and other parameters of the sensor were then computed, the "water film phenomenon" produced by the sensor was analyzed, and the appropriate materials for making the sensor were tested and selected. After the sensor was successfully devised, laboratory tests and field tests were performed, and the test results indicated that the sensor was highly reliable and could detect the flow patterns of two-phase flows, as well as the quantities, velocities, and volumes of bubbles. With a velocity measurement error of ±5% and a volume measurement error of ±7%, the sensor can meet the requirements of field use. Finally, the characteristics and deficiencies of the bubble sensor are summarized based on an analysis of the measurement errors and a comparison of existing bubble-measuring devices and the designed sensor.

Research on the Conductivity-Based Detection Principles of Bubbles in Two-Phase Flows and the Design of a Bubble Sensor for CBM Wells

PubMed Central

Wu, Chuan; Wen, Guojun; Han, Lei; Wu, Xiaoming

2016-01-01

The parameters of gas-liquid two-phase flow bubbles in field coalbed methane (CBM) wells are of great significance for analyzing coalbed methane output, judging faults in CBM wells, and developing gas drainage and extraction processes, which stimulates an urgent need for detecting bubble parameters for CBM wells in the field. However, existing bubble detectors cannot meet the requirements of the working environments of CBM wells. Therefore, this paper reports findings on the principles of measuring the flow pattern, velocity, and volume of two-phase flow bubbles based on conductivity, from which a new bubble sensor was designed. The structural parameters and other parameters of the sensor were then computed, the “water film phenomenon” produced by the sensor was analyzed, and the appropriate materials for making the sensor were tested and selected. After the sensor was successfully devised, laboratory tests and field tests were performed, and the test results indicated that the sensor was highly reliable and could detect the flow patterns of two-phase flows, as well as the quantities, velocities, and volumes of bubbles. With a velocity measurement error of ±5% and a volume measurement error of ±7%, the sensor can meet the requirements of field use. Finally, the characteristics and deficiencies of the bubble sensor are summarized based on an analysis of the measurement errors and a comparison of existing bubble-measuring devices and the designed sensor. PMID:27649206

A high accuracy magnetic heading system composed of fluxgate magnetometers and a microcomputer

NASA Astrophysics Data System (ADS)

Liu, Sheng-Wu; Zhang, Zhao-Nian; Hung, James C.

The authors present a magnetic heading system consisting of two fluxgate magnetometers and a single-chip microcomputer. The system, when compared to gyro compasses, is smaller in size, lighter in weight, simpler in construction, quicker in reaction time, free from drift, and more reliable. Using a microcomputer in the system, heading error due to compass deviation, sensor offsets, scale factor uncertainty, and sensor tilts can be compensated with the help of an error model. The laboratory test of a typical system showed that the accuracy of the system was improved from more than 8 deg error without error compensation to less than 0.3 deg error with compensation.

A flexible wearable sensor for knee flexion assessment during gait.

PubMed

Papi, Enrica; Bo, Yen Nee; McGregor, Alison H

2018-05-01

Gait analysis plays an important role in the diagnosis and management of patients with movement disorders but it is usually performed within a laboratory. Recently interest has shifted towards the possibility of conducting gait assessments in everyday environments thus facilitating long-term monitoring. This is possible by using wearable technologies rather than laboratory based equipment. This study aims to validate a novel wearable sensor system's ability to measure peak knee sagittal angles during gait. The proposed system comprises a flexible conductive polymer unit interfaced with a wireless acquisition node attached over the knee on a pair of leggings. Sixteen healthy volunteers participated to two gait assessments on separate occasions. Data was simultaneously collected from the novel sensor and a gold standard 10 camera motion capture system. The relationship between sensor signal and reference knee flexion angles was defined for each subject to allow the transformation of sensor voltage outputs to angular measures (degrees). The knee peak flexion angle from the sensor and reference system were compared by means of root mean square error (RMSE), absolute error, Bland-Altman plots and intra-class correlation coefficients (ICCs) to assess test-retest reliability. Comparisons of knee peak flexion angles calculated from the sensor and gold standard yielded an absolute error of 0.35(±2.9°) and RMSE of 1.2(±0.4)°. Good agreement was found between the two systems with the majority of data lying within the limits of agreement. The sensor demonstrated high test-retest reliability (ICCs>0.8). These results show the ability of the sensor to monitor knee peak sagittal angles with small margins of error and in agreement with the gold standard system. The sensor has potential to be used in clinical settings as a discreet, unobtrusive wearable device allowing for long-term gait analysis. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

A Measuring System for Well Logging Attitude and a Method of Sensor Calibration

PubMed Central

Ren, Yong; Wang, Yangdong; Wang, Mijian; Wu, Sheng; Wei, Biao

2014-01-01

This paper proposes an approach for measuring the azimuth angle and tilt angle of underground drilling tools with a MEMS three-axis accelerometer and a three-axis fluxgate sensor. A mathematical model of well logging attitude angle is deduced based on combining space coordinate transformations and algebraic equations. In addition, a system implementation plan of the inclinometer is given in this paper, which features low cost, small volume and integration. Aiming at the sensor and assembly errors, this paper analyses the sources of errors, and establishes two mathematical models of errors and calculates related parameters to achieve sensor calibration. The results show that this scheme can obtain a stable and high precision azimuth angle and tilt angle of drilling tools, with the deviation of the former less than ±1.4° and the deviation of the latter less than ±0.1°. PMID:24859028

Calibration and compensation method of three-axis geomagnetic sensor based on pre-processing total least square iteration

NASA Astrophysics Data System (ADS)

Zhou, Y.; Zhang, X.; Xiao, W.

2018-04-01

As the geomagnetic sensor is susceptible to interference, a pre-processing total least square iteration method is proposed for calibration compensation. Firstly, the error model of the geomagnetic sensor is analyzed and the correction model is proposed, then the characteristics of the model are analyzed and converted into nine parameters. The geomagnetic data is processed by Hilbert transform (HHT) to improve the signal-to-noise ratio, and the nine parameters are calculated by using the combination of Newton iteration method and the least squares estimation method. The sifter algorithm is used to filter the initial value of the iteration to ensure that the initial error is as small as possible. The experimental results show that this method does not need additional equipment and devices, can continuously update the calibration parameters, and better than the two-step estimation method, it can compensate geomagnetic sensor error well.

A measuring system for well logging attitude and a method of sensor calibration.

PubMed

Ren, Yong; Wang, Yangdong; Wang, Mijian; Wu, Sheng; Wei, Biao

2014-05-23

This paper proposes an approach for measuring the azimuth angle and tilt angle of underground drilling tools with a MEMS three-axis accelerometer and a three-axis fluxgate sensor. A mathematical model of well logging attitude angle is deduced based on combining space coordinate transformations and algebraic equations. In addition, a system implementation plan of the inclinometer is given in this paper, which features low cost, small volume and integration. Aiming at the sensor and assembly errors, this paper analyses the sources of errors, and establishes two mathematical models of errors and calculates related parameters to achieve sensor calibration. The results show that this scheme can obtain a stable and high precision azimuth angle and tilt angle of drilling tools, with the deviation of the former less than ±1.4° and the deviation of the latter less than ±0.1°.

Two-Dimensional Micro-/Nanoradian Angle Generator with High Resolution and Repeatability Based on Piezo-Driven Double-Axis Flexure Hinge and Three Capacitive Sensors.

PubMed

Tan, Xinran; Zhu, Fan; Wang, Chao; Yu, Yang; Shi, Jian; Qi, Xue; Yuan, Feng; Tan, Jiubin

2017-11-19

This study presents a two-dimensional micro-/nanoradian angle generator (2D-MNAG) that achieves high angular displacement resolution and repeatability using a piezo-driven flexure hinge for two-dimensional deflections and three capacitive sensors for output angle monitoring and feedback control. The principal error of the capacitive sensor for precision microangle measurement is analyzed and compensated for; so as to achieve a high angle output resolution of 10 nrad (0.002 arcsec) and positioning repeatability of 120 nrad (0.024 arcsec) over a large angular range of ±4363 μrad (±900 arcsec) for the 2D-MNAG. The impact of each error component, together with the synthetic error of the 2D-MNAG after principal error compensation are determined using Monte Carlo simulation for further improvement of the 2D-MNAG.

Two-Dimensional Micro-/Nanoradian Angle Generator with High Resolution and Repeatability Based on Piezo-Driven Double-Axis Flexure Hinge and Three Capacitive Sensors

PubMed Central

Tan, Xinran; Zhu, Fan; Wang, Chao; Yu, Yang; Shi, Jian; Qi, Xue; Yuan, Feng; Tan, Jiubin

2017-01-01

This study presents a two-dimensional micro-/nanoradian angle generator (2D-MNAG) that achieves high angular displacement resolution and repeatability using a piezo-driven flexure hinge for two-dimensional deflections and three capacitive sensors for output angle monitoring and feedback control. The principal error of the capacitive sensor for precision microangle measurement is analyzed and compensated for; so as to achieve a high angle output resolution of 10 nrad (0.002 arcsec) and positioning repeatability of 120 nrad (0.024 arcsec) over a large angular range of ±4363 μrad (±900 arcsec) for the 2D-MNAG. The impact of each error component, together with the synthetic error of the 2D-MNAG after principal error compensation are determined using Monte Carlo simulation for further improvement of the 2D-MNAG. PMID:29156595

A numerical study of some potential sources of error in side-by-side seismometer evaluations

USGS Publications Warehouse

Holcomb, L. Gary

1990-01-01

This report presents the results of a series of computer simulations of potential errors in test data, which might be obtained when conducting side-by-side comparisons of seismometers. These results can be used as guides in estimating potential sources and magnitudes of errors one might expect when analyzing real test data. First, the derivation of a direct method for calculating the noise levels of two sensors in a side-by-side evaluation is repeated and extended slightly herein. This bulk of this derivation was presented previously (see Holcomb 1989); it is repeated here for easy reference.This method is applied to the analysis of a simulated test of two sensors in a side-by-side test in which the outputs of both sensors consist of white noise spectra with known signal-tonoise ratios (SNR's). This report extends this analysis to high SNR's to determine the limitations of the direct method for calculating the noise levels at signal-to-noise levels which are much higher than presented previously (see Holcomb 1989). Next, the method is used to analyze a simulated test of two sensors in a side-by-side test in which the outputs of both sensors consist of bandshaped noise spectra with known signal-tonoise ratios. This is a much more realistic representation of real world data because the earth's background spectrum is certainly not flat.Finally, the results of the analysis of simulated white and bandshaped side-by-side test data are used to assist in interpreting the analysis of the effects of simulated azimuthal misalignment in side-by-side sensor evaluations. A thorough understanding of azimuthal misalignment errors is important because of the physical impossibility of perfectly aligning two sensors in a real world situation. The analysis herein indicates that alignment errors place lower limits on the levels of system noise which can be resolved in a side-by-side measurement It also indicates that alignment errors are the source of the fact that real data noise spectra tend to follow the earth's background spectra in shape.

Surface-roughness considerations for atmospheric correction of ocean color sensors. II: Error in the retrieved water-leaving radiance.

PubMed

Gordon, H R; Wang, M

1992-07-20

In the algorithm for the atmospheric correction of coastal zone color scanner (CZCS) imagery, it is assumed that the sea surface is flat. Simulations are carried out to assess the error incurred when the CZCS-type algorithm is applied to a realistic ocean in which the surface is roughened by the wind. In situations where there is no direct Sun glitter (either a large solar zenith angle or the sensor tilted away from the specular image of the Sun), the following conclusions appear justified: (1) the error induced by ignoring the surface roughness is less, similar1 CZCS digital count for wind speeds up to approximately 17 m/s, and therefore can be ignored for this sensor; (2) the roughness-induced error is much more strongly dependent on the wind speed than on the wave shadowing, suggesting that surface effects can be adequately dealt with without precise knowledge of the shadowing; and (3) the error induced by ignoring the Rayleigh-aerosol interaction is usually larger than that caused by ignoring the surface roughness, suggesting that in refining algorithms for future sensors more effort should be placed on dealing with the Rayleigh-aerosol interaction than on the roughness of the sea surface.

Performance Evaluation and Requirements Assessment for Gravity Gradient Referenced Navigation

PubMed Central

Lee, Jisun; Kwon, Jay Hyoun; Yu, Myeongjong

2015-01-01

In this study, simulation tests for gravity gradient referenced navigation (GGRN) are conducted to verify the effects of various factors such as database (DB) and sensor errors, flight altitude, DB resolution, initial errors, and measurement update rates on the navigation performance. Based on the simulation results, requirements for GGRN are established for position determination with certain target accuracies. It is found that DB and sensor errors and flight altitude have strong effects on the navigation performance. In particular, a DB and sensor with accuracies of 0.1 E and 0.01 E, respectively, are required to determine the position more accurately than or at a level similar to the navigation performance of terrain referenced navigation (TRN). In most cases, the horizontal position error of GGRN is less than 100 m. However, the navigation performance of GGRN is similar to or worse than that of a pure inertial navigation system when the DB and sensor errors are 3 E or 5 E each and the flight altitude is 3000 m. Considering that the accuracy of currently available gradiometers is about 3 E or 5 E, GGRN does not show much advantage over TRN at present. However, GGRN is expected to exhibit much better performance in the near future when accurate DBs and gravity gradiometer are available. PMID:26184212

Afocal optical flow sensor for reducing vertical height sensitivity in indoor robot localization and navigation.

PubMed

Yi, Dong-Hoon; Lee, Tae-Jae; Cho, Dong-Il Dan

2015-05-13

This paper introduces a novel afocal optical flow sensor (OFS) system for odometry estimation in indoor robotic navigation. The OFS used in computer optical mouse has been adopted for mobile robots because it is not affected by wheel slippage. Vertical height variance is thought to be a dominant factor in systematic error when estimating moving distances in mobile robots driving on uneven surfaces. We propose an approach to mitigate this error by using an afocal (infinite effective focal length) system. We conducted experiments in a linear guide on carpet and three other materials with varying sensor heights from 30 to 50 mm and a moving distance of 80 cm. The same experiments were repeated 10 times. For the proposed afocal OFS module, a 1 mm change in sensor height induces a 0.1% systematic error; for comparison, the error for a conventional fixed-focal-length OFS module is 14.7%. Finally, the proposed afocal OFS module was installed on a mobile robot and tested 10 times on a carpet for distances of 1 m. The average distance estimation error and standard deviation are 0.02% and 17.6%, respectively, whereas those for a conventional OFS module are 4.09% and 25.7%, respectively.

SSC Geopositional Assessment of the Advanced Wide Field Sensor

NASA Technical Reports Server (NTRS)

Ross, Kenton

2006-01-01

The geopositional accuracy of the standard geocorrected product from the Advanced Wide Field Sensor (AWiFS) was evaluated using digital orthophoto quarter quadrangles and other reference sources of similar accuracy. Images were analyzed from summer 2004 through spring 2005. Forty to fifty check points were collected manually per scene and analyzed to determine overall circular error, estimates of horizontal bias, and other systematic errors. Measured errors were somewhat higher than the specifications for the data, but they were consistent with the analysis of the distributing vendor.

Design, analysis, and fabrication of a piezoelectric force plate

NASA Astrophysics Data System (ADS)

Hoummadi, Elias; Safaei, Mohsen; Anton, Steven R.

2017-04-01

Force plates are used to detect static and dynamic reaction forces due to presence of stationary or moving objects as well as the location of applied forces. The application of force plates in various biomechanical fields, such as gait analysis, has been widely suggested and investigated in the past. Several sensor technologies like piezoelectrics, capacitance gauges, and piezoresistive sensors are utilized to develop force plates with special characteristics. Among the technologies employed in force plate designs, piezoelectrics present the ability of providing a self-powered sensory system. Recently, it has been suggested to implement piezoelectric transducers as sensors in the tibial bearing of total knee replacement (TKR) implants in order to transform the knee bearing into a force plate with the ability to detect force and contact point location for in vivo knee load analysis. Considering this application, a simplified design of a force plate instrumented with six piezoelectric transducers is presented in this study. The force plate is modeled using a finite element (FE) model to investigate the sensing performance of the system. In order to validate the simulation, a prototype force plate is fabricated and tested under the same loading condition applied on the FE model. The results are presented in terms of measured location and amplitude of applied force measured by the piezoelectric transducers. For the FE simulation, the deviation of the measured location of the applied force from the actual location is obtained as 0.62 mm in the x-direction and 0.13 mm in the y-direction, and the error in the amplitude of the measured force is 0.03% of the applied force. On the other hand, the deviation in the measured location of the force from the experimental test is 0.53 mm in the x-direction and 0.1 mm in the y-direction, while the error in force is 3.6% of the applied force. The small quantities of error in both sensed location and amplitude of applied force obtained from the FE simulation and experimental test results demonstrates the potential of the proposed design to be utilized as the sensor in the knee bearing of TKR implants.

Experiments on active isolation using distributed PVDF error sensors

NASA Technical Reports Server (NTRS)

Lefebvre, S.; Guigou, C.; Fuller, C. R.

1992-01-01

A control system based on a two-channel narrow-band LMS algorithm is used to isolate periodic vibration at low frequencies on a structure composed of a rigid top plate mounted on a flexible receiving plate. The control performance of distributed PVDF error sensors and accelerometer point sensors is compared. For both sensors, high levels of global reduction, up to 32 dB, have been obtained. It is found that, by driving the PVDF strip output voltage to zero, the controller may force the structure to vibrate so that the integration of the strain under the length of the PVDF strip is zero. This ability of the PVDF sensors to act as spatial filters is especially relevant in active control of sound radiation. It is concluded that the PVDF sensors are flexible, nonfragile, and inexpensive and can be used as strain sensors for active control applications of vibration isolation and sound radiation.

Error decomposition and estimation of inherent optical properties.

PubMed

Salama, Mhd Suhyb; Stein, Alfred

2009-09-10

We describe a methodology to quantify and separate the errors of inherent optical properties (IOPs) derived from ocean-color model inversion. Their total error is decomposed into three different sources, namely, model approximations and inversion, sensor noise, and atmospheric correction. Prior information on plausible ranges of observation, sensor noise, and inversion goodness-of-fit are employed to derive the posterior probability distribution of the IOPs. The relative contribution of each error component to the total error budget of the IOPs, all being of stochastic nature, is then quantified. The method is validated with the International Ocean Colour Coordinating Group (IOCCG) data set and the NASA bio-Optical Marine Algorithm Data set (NOMAD). The derived errors are close to the known values with correlation coefficients of 60-90% and 67-90% for IOCCG and NOMAD data sets, respectively. Model-induced errors inherent to the derived IOPs are between 10% and 57% of the total error, whereas atmospheric-induced errors are in general above 43% and up to 90% for both data sets. The proposed method is applied to synthesized and in situ measured populations of IOPs. The mean relative errors of the derived values are between 2% and 20%. A specific error table to the Medium Resolution Imaging Spectrometer (MERIS) sensor is constructed. It serves as a benchmark to evaluate the performance of the atmospheric correction method and to compute atmospheric-induced errors. Our method has a better performance and is more appropriate to estimate actual errors of ocean-color derived products than the previously suggested methods. Moreover, it is generic and can be applied to quantify the error of any derived biogeophysical parameter regardless of the used derivation.

Multiparametric methane sensor for environmental monitoring

NASA Astrophysics Data System (ADS)

Borecki, M.; Duk, M.; Kociubiński, A.; Korwin-Pawlowski, M. L.

2016-12-01

Today, methane sensors find applications mostly in safety alarm installations, gas parameters detection and air pollution classification. Such sensors and sensors elements exists for industry and home use. Under development area of methane sensors application is dedicated to ground gases monitoring. Proper monitoring of soil gases requires reliable and maintenance-free semi-constant and longtime examination at relatively low cost of equipment. The sensors for soil monitoring have to work on soil probe. Therefore, sensor is exposed to environment conditions, as a wide range of temperatures and a full scale of humidity changes, as well as rain, snow and wind, that are not specified for classical methane sensors. Development of such sensor is presented in this paper. The presented sensor construction consists of five commercial non dispersive infra-red (NDIR) methane sensing units, a set of temperature and humidity sensing units, a gas chamber equipped with a micro-fan, automated gas valves and also a microcontroller that controls the measuring procedure. The electronics part of sensor was installed into customized 3D printed housing equipped with self-developed gas valves. The main development of proposed sensor is on the side of experimental evaluation of construction reliability and results of data processing included safety procedures and function for hardware error correction. Redundant methane sensor units are used providing measurement error correction as well as improved measurement accuracy. The humidity and temperature sensors are used for internal compensation of methane measurements as well as for cutting-off the sensor from the environment when the conditions exceed allowable parameters. Results obtained during environment sensing prove that the gas concentration readings are not sensitive to gas chamber vertical or horizontal position. It is important as vertical sensor installation on soil probe is simpler that horizontal one. Data acquired during six month of environment monitoring prove that error correction of methane sensing units was essential for maintenance free sensor operation, despite used safety procedures.

Study on the special vision sensor for detecting position error in robot precise TIG welding of some key part of rocket engine

NASA Astrophysics Data System (ADS)

Zhang, Wenzeng; Chen, Nian; Wang, Bin; Cao, Yipeng

2005-01-01

Rocket engine is a hard-core part of aerospace transportation and thrusting system, whose research and development is very important in national defense, aviation and aerospace. A novel vision sensor is developed, which can be used for error detecting in arc length control and seam tracking in precise pulse TIG welding of the extending part of the rocket engine jet tube. The vision sensor has many advantages, such as imaging with high quality, compactness and multiple functions. The optics design, mechanism design and circuit design of the vision sensor have been described in detail. Utilizing the mirror imaging of Tungsten electrode in the weld pool, a novel method is proposed to detect the arc length and seam tracking error of Tungsten electrode to the center line of joint seam from a single weld image. A calculating model of the method is proposed according to the relation of the Tungsten electrode, weld pool, the mirror of Tungsten electrode in weld pool and joint seam. The new methodologies are given to detect the arc length and seam tracking error. Through analyzing the results of the experiments, a system error modifying method based on a linear function is developed to improve the detecting precise of arc length and seam tracking error. Experimental results show that the final precision of the system reaches 0.1 mm in detecting the arc length and the seam tracking error of Tungsten electrode to the center line of joint seam.

Outdoor surface temperature measurement: ground truth or lie?

NASA Astrophysics Data System (ADS)

Skauli, Torbjorn

2004-08-01

Contact surface temperature measurement in the field is essential in trials of thermal imaging systems and camouflage, as well as for scene modeling studies. The accuracy of such measurements is challenged by environmental factors such as sun and wind, which induce temperature gradients around a surface sensor and lead to incorrect temperature readings. In this work, a simple method is used to test temperature sensors under conditions representative of a surface whose temperature is determined by heat exchange with the environment. The tested sensors are different types of thermocouples and platinum thermistors typically used in field trials, as well as digital temperature sensors. The results illustrate that the actual measurement errors can be much larger than the specified accuracy of the sensors. The measurement error typically scales with the difference between surface temperature and ambient air temperature. Unless proper care is taken, systematic errors can easily reach 10% of this temperature difference, which is often unacceptable. Reasonably accurate readings are obtained using a miniature platinum thermistor. Thermocouples can perform well on bare metal surfaces if the connection to the surface is highly conductive. It is pointed out that digital temperature sensors have many advantages for field trials use.

Minimalistic optic flow sensors applied to indoor and outdoor visual guidance and odometry on a car-like robot.

PubMed

Mafrica, Stefano; Servel, Alain; Ruffier, Franck

2016-11-10

Here we present a novel bio-inspired optic flow (OF) sensor and its application to visual  guidance and odometry on a low-cost car-like robot called BioCarBot. The minimalistic OF sensor was robust to high-dynamic-range lighting conditions and to various visual patterns encountered thanks to its M 2 APIX auto-adaptive pixels and the new cross-correlation OF algorithm implemented. The low-cost car-like robot estimated its velocity and steering angle, and therefore its position and orientation, via an extended Kalman filter (EKF) using only two downward-facing OF sensors and the Ackerman steering model. Indoor and outdoor experiments were carried out in which the robot was driven in the closed-loop mode based on the velocity and steering angle estimates. The experimental results obtained show that our novel OF sensor can deliver high-frequency measurements ([Formula: see text]) in a wide OF range (1.5-[Formula: see text]) and in a 7-decade high-dynamic light level range. The OF resolution was constant and could be adjusted as required (up to [Formula: see text]), and the OF precision obtained was relatively high (standard deviation of [Formula: see text] with an average OF of [Formula: see text], under the most demanding lighting conditions). An EKF-based algorithm gave the robot's position and orientation with a relatively high accuracy (maximum errors outdoors at a very low light level: [Formula: see text] and [Formula: see text] over about [Formula: see text] and [Formula: see text]) despite the low-resolution control systems of the steering servo and the DC motor, as well as a simplified model identification and calibration. Finally, the minimalistic OF-based odometry results were compared to those obtained using measurements based on an inertial measurement unit (IMU) and a motor's speed sensor.

A small, lightweight multipollutant sensor system for ground-mobile and aerial emission sampling from open area sources

NASA Astrophysics Data System (ADS)

Zhou, Xiaochi; Aurell, Johanna; Mitchell, William; Tabor, Dennis; Gullett, Brian

2017-04-01

Characterizing highly dynamic, transient, and vertically lofted emissions from open area sources poses unique measurement challenges. This study developed and applied a multipollutant sensor and time-integrated sampler system for use on mobile applications such as vehicles, tethered balloons (aerostats) and unmanned aerial vehicles (UAVs) to determine emission factors. The system is particularly applicable to open area sources, such as forest fires, due to its light weight (3.5 kg), compact size (6.75 L), and internal power supply. The sensor system, termed ;Kolibri;, consists of sensors measuring CO2 and CO, and samplers for particulate matter (PM) and volatile organic compounds (VOCs). The Kolibri is controlled by a microcontroller which can record and transfer data in real time through a radio module. Selection of the sensors was based on laboratory testing for accuracy, response delay and recovery, cross-sensitivity, and precision. The Kolibri was compared against rack-mounted continuous emissions monitoring system (CEMs) and another mobile sampling instrument (the ;Flyer;) that has been used in over ten open area pollutant sampling events. Our results showed that the time series of CO, CO2, and PM2.5 concentrations measured by the Kolibri agreed well with those from the CEMs and the Flyer, with a laboratory-tested percentage error of 4.9%, 3%, and 5.8%, respectively. The VOC emission factors obtained using the Kolibri were consistent with existing literature values that relate concentration to modified combustion efficiency. The potential effect of rotor downwash on particle sampling was investigated in an indoor laboratory and the preliminary results suggested that its influence is minimal. Field application of the Kolibri sampling open detonation plumes indicated that the CO and CO2 sensors responded dynamically and their concentrations co-varied with emission transients. The Kolibri system can be applied to various challenging open area scenarios such as fires, lagoons, flares, and landfills.

A Kalman Filter for Mass Property and Thrust Identification of the Spin-Stabilized Magnetospheric Multiscale Formation

NASA Technical Reports Server (NTRS)

Queen, Steven Z.

2015-01-01

The Magnetospheric Multiscale (MMS) mission consists of four identically instrumented, spin-stabilized observatories, elliptically orbiting the Earth in a tetrahedron formation. For the operational success of the mission, on-board systems must be able to deliver high-precision orbital adjustment maneuvers. On MMS, this is accomplished using feedback from on-board star sensors in tandem with accelerometers whose measurements are dynamically corrected for errors associated with a spinning platform. In order to determine the required corrections to the measured acceleration, precise estimates of attitude, rate, and mass-properties are necessary. To this end, both an on-board and ground-based Multiplicative Extended Kalman Filter (MEKF) were formulated and implemented in order to estimate the dynamic and quasi-static properties of the spacecraft.

Low-Cost Ultrasonic Distance Sensor Arrays with Networked Error Correction

PubMed Central

Dai, Hongjun; Zhao, Shulin; Jia, Zhiping; Chen, Tianzhou

2013-01-01

Distance has been one of the basic factors in manufacturing and control fields, and ultrasonic distance sensors have been widely used as a low-cost measuring tool. However, the propagation of ultrasonic waves is greatly affected by environmental factors such as temperature, humidity and atmospheric pressure. In order to solve the problem of inaccurate measurement, which is significant within industry, this paper presents a novel ultrasonic distance sensor model using networked error correction (NEC) trained on experimental data. This is more accurate than other existing approaches because it uses information from indirect association with neighboring sensors, which has not been considered before. The NEC technique, focusing on optimization of the relationship of the topological structure of sensor arrays, is implemented for the compensation of erroneous measurements caused by the environment. We apply the maximum likelihood method to determine the optimal fusion data set and use a neighbor discovery algorithm to identify neighbor nodes at the top speed. Furthermore, we adopt the NEC optimization algorithm, which takes full advantage of the correlation coefficients for neighbor sensors. The experimental results demonstrate that the ranging errors of the NEC system are within 2.20%; furthermore, the mean absolute percentage error is reduced to 0.01% after three iterations of this method, which means that the proposed method performs extremely well. The optimized method of distance measurement we propose, with the capability of NEC, would bring a significant advantage for intelligent industrial automation. PMID:24013491

Optimal full motion video registration with rigorous error propagation

NASA Astrophysics Data System (ADS)

Dolloff, John; Hottel, Bryant; Doucette, Peter; Theiss, Henry; Jocher, Glenn

2014-06-01

Optimal full motion video (FMV) registration is a crucial need for the Geospatial community. It is required for subsequent and optimal geopositioning with simultaneous and reliable accuracy prediction. An overall approach being developed for such registration is presented that models relevant error sources in terms of the expected magnitude and correlation of sensor errors. The corresponding estimator is selected based on the level of accuracy of the a priori information of the sensor's trajectory and attitude (pointing) information, in order to best deal with non-linearity effects. Estimator choices include near real-time Kalman Filters and batch Weighted Least Squares. Registration solves for corrections to the sensor a priori information for each frame. It also computes and makes available a posteriori accuracy information, i.e., the expected magnitude and correlation of sensor registration errors. Both the registered sensor data and its a posteriori accuracy information are then made available to "down-stream" Multi-Image Geopositioning (MIG) processes. An object of interest is then measured on the registered frames and a multi-image optimal solution, including reliable predicted solution accuracy, is then performed for the object's 3D coordinates. This paper also describes a robust approach to registration when a priori information of sensor attitude is unavailable. It makes use of structure-from-motion principles, but does not use standard Computer Vision techniques, such as estimation of the Essential Matrix which can be very sensitive to noise. The approach used instead is a novel, robust, direct search-based technique.

POD-based constrained sensor placement and field reconstruction from noisy wind measurements: A perturbation study

DOE PAGES

Zhang, Zhongqiang; Yang, Xiu; Lin, Guang

2016-04-14

Sensor placement at the extrema of Proper Orthogonal Decomposition (POD) is efficient and leads to accurate reconstruction of the wind field from a limited number of measure- ments. In this paper we extend this approach of sensor placement and take into account measurement errors and detect possible malfunctioning sensors. We use the 48 hourly spa- tial wind field simulation data sets simulated using the Weather Research an Forecasting (WRF) model applied to the Maine Bay to evaluate the performances of our methods. Specifically, we use an exclusion disk strategy to distribute sensors when the extrema of POD modes are close.more » It turns out that this strategy can also reduce the error of recon- struction from noise measurements. Also, by a cross-validation technique, we successfully locate the malfunctioning sensors.« less

Operational Modal Analysis of Bridge Structures with Data from GNSS/Accelerometer Measurements.

PubMed

Xiong, Chunbao; Lu, Huali; Zhu, Jinsong

2017-02-23

Real-time dynamic displacement and acceleration responses of the main span section of the Tianjin Fumin Bridge in China under ambient excitation were tested using a Global Navigation Satellite System (GNSS) dynamic deformation monitoring system and an acceleration sensor vibration test system. Considering the close relationship between the GNSS multipath errors and measurement environment in combination with the noise reduction characteristics of different filtering algorithms, the researchers proposed an AFEC mixed filtering algorithm, which is an combination of autocorrelation function-based empirical mode decomposition (EMD) and Chebyshev mixed filtering to extract the real vibration displacement of the bridge structure after system error correction and filtering de-noising of signals collected by the GNSS. The proposed AFEC mixed filtering algorithm had high accuracy (1 mm) of real displacement at the elevation direction. Next, the traditional random decrement technique (used mainly for stationary random processes) was expanded to non-stationary random processes. Combining the expanded random decrement technique (RDT) and autoregressive moving average model (ARMA), the modal frequency of the bridge structural system was extracted using an expanded ARMA_RDT modal identification method, which was compared with the power spectrum analysis results of the acceleration signal and finite element analysis results. Identification results demonstrated that the proposed algorithm is applicable to analyze the dynamic displacement monitoring data of real bridge structures under ambient excitation and could identify the first five orders of the inherent frequencies of the structural system accurately. The identification error of the inherent frequency was smaller than 6%, indicating the high identification accuracy of the proposed algorithm. Furthermore, the GNSS dynamic deformation monitoring method can be used to monitor dynamic displacement and identify the modal parameters of bridge structures. The GNSS can monitor the working state of bridges effectively and accurately. Research results can provide references to evaluate the bearing capacity, safety performance, and durability of bridge structures during operation.

Operational Modal Analysis of Bridge Structures with Data from GNSS/Accelerometer Measurements

PubMed Central

Xiong, Chunbao; Lu, Huali; Zhu, Jinsong

2017-01-01

Real-time dynamic displacement and acceleration responses of the main span section of the Tianjin Fumin Bridge in China under ambient excitation were tested using a Global Navigation Satellite System (GNSS) dynamic deformation monitoring system and an acceleration sensor vibration test system. Considering the close relationship between the GNSS multipath errors and measurement environment in combination with the noise reduction characteristics of different filtering algorithms, the researchers proposed an AFEC mixed filtering algorithm, which is an combination of autocorrelation function-based empirical mode decomposition (EMD) and Chebyshev mixed filtering to extract the real vibration displacement of the bridge structure after system error correction and filtering de-noising of signals collected by the GNSS. The proposed AFEC mixed filtering algorithm had high accuracy (1 mm) of real displacement at the elevation direction. Next, the traditional random decrement technique (used mainly for stationary random processes) was expanded to non-stationary random processes. Combining the expanded random decrement technique (RDT) and autoregressive moving average model (ARMA), the modal frequency of the bridge structural system was extracted using an expanded ARMA_RDT modal identification method, which was compared with the power spectrum analysis results of the acceleration signal and finite element analysis results. Identification results demonstrated that the proposed algorithm is applicable to analyze the dynamic displacement monitoring data of real bridge structures under ambient excitation and could identify the first five orders of the inherent frequencies of the structural system accurately. The identification error of the inherent frequency was smaller than 6%, indicating the high identification accuracy of the proposed algorithm. Furthermore, the GNSS dynamic deformation monitoring method can be used to monitor dynamic displacement and identify the modal parameters of bridge structures. The GNSS can monitor the working state of bridges effectively and accurately. Research results can provide references to evaluate the bearing capacity, safety performance, and durability of bridge structures during operation. PMID:28241472

Modelling hourly dissolved oxygen concentration (DO) using dynamic evolving neural-fuzzy inference system (DENFIS)-based approach: case study of Klamath River at Miller Island Boat Ramp, OR, USA.

PubMed

Heddam, Salim

2014-01-01

In this study, we present application of an artificial intelligence (AI) technique model called dynamic evolving neural-fuzzy inference system (DENFIS) based on an evolving clustering method (ECM), for modelling dissolved oxygen concentration in a river. To demonstrate the forecasting capability of DENFIS, a one year period from 1 January 2009 to 30 December 2009, of hourly experimental water quality data collected by the United States Geological Survey (USGS Station No: 420853121505500) station at Klamath River at Miller Island Boat Ramp, OR, USA, were used for model development. Two DENFIS-based models are presented and compared. The two DENFIS systems are: (1) offline-based system named DENFIS-OF, and (2) online-based system, named DENFIS-ON. The input variables used for the two models are water pH, temperature, specific conductance, and sensor depth. The performances of the models are evaluated using root mean square errors (RMSE), mean absolute error (MAE), Willmott index of agreement (d) and correlation coefficient (CC) statistics. The lowest root mean square error and highest correlation coefficient values were obtained with the DENFIS-ON method. The results obtained with DENFIS models are compared with linear (multiple linear regression, MLR) and nonlinear (multi-layer perceptron neural networks, MLPNN) methods. This study demonstrates that DENFIS-ON investigated herein outperforms all the proposed techniques for DO modelling.

Robot Position Sensor Fault Tolerance

NASA Technical Reports Server (NTRS)

Aldridge, Hal A.

1997-01-01

Robot systems in critical applications, such as those in space and nuclear environments, must be able to operate during component failure to complete important tasks. One failure mode that has received little attention is the failure of joint position sensors. Current fault tolerant designs require the addition of directly redundant position sensors which can affect joint design. A new method is proposed that utilizes analytical redundancy to allow for continued operation during joint position sensor failure. Joint torque sensors are used with a virtual passive torque controller to make the robot joint stable without position feedback and improve position tracking performance in the presence of unknown link dynamics and end-effector loading. Two Cartesian accelerometer based methods are proposed to determine the position of the joint. The joint specific position determination method utilizes two triaxial accelerometers attached to the link driven by the joint with the failed position sensor. The joint specific method is not computationally complex and the position error is bounded. The system wide position determination method utilizes accelerometers distributed on different robot links and the end-effector to determine the position of sets of multiple joints. The system wide method requires fewer accelerometers than the joint specific method to make all joint position sensors fault tolerant but is more computationally complex and has lower convergence properties. Experiments were conducted on a laboratory manipulator. Both position determination methods were shown to track the actual position satisfactorily. A controller using the position determination methods and the virtual passive torque controller was able to servo the joints to a desired position during position sensor failure.

Enhanced Pedestrian Navigation Based on Course Angle Error Estimation Using Cascaded Kalman Filters

PubMed Central

Park, Chan Gook

2018-01-01

An enhanced pedestrian dead reckoning (PDR) based navigation algorithm, which uses two cascaded Kalman filters (TCKF) for the estimation of course angle and navigation errors, is proposed. The proposed algorithm uses a foot-mounted inertial measurement unit (IMU), waist-mounted magnetic sensors, and a zero velocity update (ZUPT) based inertial navigation technique with TCKF. The first stage filter estimates the course angle error of a human, which is closely related to the heading error of the IMU. In order to obtain the course measurements, the filter uses magnetic sensors and a position-trace based course angle. For preventing magnetic disturbance from contaminating the estimation, the magnetic sensors are attached to the waistband. Because the course angle error is mainly due to the heading error of the IMU, and the characteristic error of the heading angle is highly dependent on that of the course angle, the estimated course angle error is used as a measurement for estimating the heading error in the second stage filter. At the second stage, an inertial navigation system-extended Kalman filter-ZUPT (INS-EKF-ZUPT) method is adopted. As the heading error is estimated directly by using course-angle error measurements, the estimation accuracy for the heading and yaw gyro bias can be enhanced, compared with the ZUPT-only case, which eventually enhances the position accuracy more efficiently. The performance enhancements are verified via experiments, and the way-point position error for the proposed method is compared with those for the ZUPT-only case and with other cases that use ZUPT and various types of magnetic heading measurements. The results show that the position errors are reduced by a maximum of 90% compared with the conventional ZUPT based PDR algorithms. PMID:29690539

Software Would Largely Automate Design of Kalman Filter

NASA Technical Reports Server (NTRS)

Chuang, Jason C. H.; Negast, William J.

2005-01-01

Embedded Navigation Filter Automatic Designer (ENFAD) is a computer program being developed to automate the most difficult tasks in designing embedded software to implement a Kalman filter in a navigation system. The most difficult tasks are selection of error states of the filter and tuning of filter parameters, which are timeconsuming trial-and-error tasks that require expertise and rarely yield optimum results. An optimum selection of error states and filter parameters depends on navigation-sensor and vehicle characteristics, and on filter processing time. ENFAD would include a simulation module that would incorporate all possible error states with respect to a given set of vehicle and sensor characteristics. The first of two iterative optimization loops would vary the selection of error states until the best filter performance was achieved in Monte Carlo simulations. For a fixed selection of error states, the second loop would vary the filter parameter values until an optimal performance value was obtained. Design constraints would be satisfied in the optimization loops. Users would supply vehicle and sensor test data that would be used to refine digital models in ENFAD. Filter processing time and filter accuracy would be computed by ENFAD.

Analysis on the dynamic error for optoelectronic scanning coordinate measurement network

NASA Astrophysics Data System (ADS)

Shi, Shendong; Yang, Linghui; Lin, Jiarui; Guo, Siyang; Ren, Yongjie

2018-01-01

Large-scale dynamic three-dimension coordinate measurement technique is eagerly demanded in equipment manufacturing. Noted for advantages of high accuracy, scale expandability and multitask parallel measurement, optoelectronic scanning measurement network has got close attention. It is widely used in large components jointing, spacecraft rendezvous and docking simulation, digital shipbuilding and automated guided vehicle navigation. At present, most research about optoelectronic scanning measurement network is focused on static measurement capacity and research about dynamic accuracy is insufficient. Limited by the measurement principle, the dynamic error is non-negligible and restricts the application. The workshop measurement and positioning system is a representative which can realize dynamic measurement function in theory. In this paper we conduct deep research on dynamic error resources and divide them two parts: phase error and synchronization error. Dynamic error model is constructed. Based on the theory above, simulation about dynamic error is carried out. Dynamic error is quantized and the rule of volatility and periodicity has been found. Dynamic error characteristics are shown in detail. The research result lays foundation for further accuracy improvement.

Centroid estimation for a Shack-Hartmann wavefront sensor based on stream processing.

PubMed

Kong, Fanpeng; Polo, Manuel Cegarra; Lambert, Andrew

2017-08-10

Using center of gravity to estimate the centroid of the spot in a Shack-Hartmann wavefront sensor, the measurement corrupts with photon and detector noise. Parameters, like window size, often require careful optimization to balance the noise error, dynamic range, and linearity of the response coefficient under different photon flux. It also needs to be substituted by the correlation method for extended sources. We propose a centroid estimator based on stream processing, where the center of gravity calculation window floats with the incoming pixel from the detector. In comparison with conventional methods, we show that the proposed estimator simplifies the choice of optimized parameters, provides a unit linear coefficient response, and reduces the influence of background and noise. It is shown that the stream-based centroid estimator also works well for limited size extended sources. A hardware implementation of the proposed estimator is discussed.

Wavefront measurements of phase plates combining a point-diffraction interferometer and a Hartmann-Shack sensor.

PubMed

Bueno, Juan M; Acosta, Eva; Schwarz, Christina; Artal, Pablo

2010-01-20

A dual setup composed of a point diffraction interferometer (PDI) and a Hartmann-Shack (HS) wavefront sensor was built to compare the estimates of wavefront aberrations provided by the two different and complementary techniques when applied to different phase plates. Results show that under the same experimental and fitting conditions both techniques provide similar information concerning the wavefront aberration map. When taking into account all Zernike terms up to 6th order, the maximum difference in root-mean-square wavefront error was 0.08 microm, and this reduced up to 0.03 microm when excluding lower-order terms. The effects of the pupil size and the order of the Zernike expansion used to reconstruct the wavefront were evaluated. The combination of the two techniques can accurately measure complicated phase profiles, combining the robustness of the HS and the higher resolution and dynamic range of the PDI.

Adaptive target binarization method based on a dual-camera system

NASA Astrophysics Data System (ADS)

Lei, Jing; Zhang, Ping; Xu, Jiangtao; Gao, Zhiyuan; Gao, Jing

2018-01-01

An adaptive target binarization method based on a dual-camera system that contains two dynamic vision sensors was proposed. First, a preprocessing procedure of denoising is introduced to remove the noise events generated by the sensors. Then, the complete edge of the target is retrieved and represented by events based on an event mosaicking method. Third, the region of the target is confirmed by an event-to-event method. Finally, a postprocessing procedure of image open and close operations of morphology methods is adopted to remove the artifacts caused by event-to-event mismatching. The proposed binarization method has been extensively tested on numerous degraded images with nonuniform illumination, low contrast, noise, or light spots and successfully compared with other well-known binarization methods. The experimental results, which are based on visual and misclassification error criteria, show that the proposed method performs well and has better robustness on the binarization of degraded images.

A vehicle health monitoring system for the Space Shuttle Reaction Control System during reentry. M.S. Thesis - Massachusetts Inst. of Technology

NASA Technical Reports Server (NTRS)

Rosello, Anthony David

1995-01-01

A general two tier framework for vehicle health monitoring of Guidance Navigation and Control (GN&C) system actuators, effectors, and propulsion devices is presented. In this context, a top level monitor that estimates jet thrust is designed for the Space Shuttle Reaction Control System (RCS) during the reentry phase of flight. Issues of importance for the use of estimation technologies in vehicle health monitoring are investigated and quantified for the Shuttle RCS demonstration application. These issues include rate of convergence, robustness to unmodeled dynamics, sensor quality, sensor data rates, and information recording objectives. Closed loop simulations indicate that a Kalman filter design is sensitive to modeling error and robust estimators may reduce this sensitivity. Jet plume interaction with the aerodynamic flowfield is shown to be a significant effect adversely impacting the ability to accurately estimate thrust.

Analysis of a novel device-level SINS/ACFSS deeply integrated navigation method

NASA Astrophysics Data System (ADS)

Zhang, Hao; Qin, Shiqiao; Wang, Xingshu; Jiang, Guangwen; Tan, Wenfeng; Wu, Wei

2017-02-01

The combination of the strap-down inertial navigation system(SINS) and the celestial navigation system(CNS) is one of the popular measures to constitute the integrated navigation system. A star sensor(SS) is used as a precise attitude determination device in CNS. To solve the problem that the star image obtained by SS is motion-blurred under dynamic conditions, the attitude-correlated frames(ACF) approach is presented and the star sensor which works based on ACF approach is named ACFSS. Depending on the ACF approach, a novel device-level SINS/ACFSS deeply integrated navigation method is proposed in this paper. Feedback to the ACF process from the error of the gyro is one of the typical characters of the SINS/CNS deeply integrated navigation method. Herein, simulation results have verified its validity and efficiency in improving the accuracy of gyro and it can be proved that this method is feasible.

A High Temperature Capacitive Pressure Sensor Based on Alumina Ceramic for in Situ Measurement at 600 °C

PubMed Central

Tan, Qiulin; Li, Chen; Xiong, Jijun; Jia, Pinggang; Zhang, Wendong; Liu, Jun; Xue, Chenyang; Hong, Yingping; Ren, Zhong; Luo, Tao

2014-01-01

In response to the growing demand for in situ measurement of pressure in high-temperature environments, a high temperature capacitive pressure sensor is presented in this paper. A high-temperature ceramic material-alumina is used for the fabrication of the sensor, and the prototype sensor consists of an inductance, a variable capacitance, and a sealed cavity integrated in the alumina ceramic substrate using a thick-film integrated technology. The experimental results show that the proposed sensor has stability at 850 °C for more than 20 min. The characterization in high-temperature and pressure environments successfully demonstrated sensing capabilities for pressure from 1 to 5 bar up to 600 °C, limited by the sensor test setup. At 600 °C, the sensor achieves a linear characteristic response, and the repeatability error, hysteresis error and zero-point drift of the sensor are 8.3%, 5.05% and 1%, respectively. PMID:24487624

An Insertable Passive LC Pressure Sensor Based on an Alumina Ceramic for In Situ Pressure Sensing in High-Temperature Environments.

PubMed

Xiong, Jijun; Li, Chen; Jia, Pinggang; Chen, Xiaoyong; Zhang, Wendong; Liu, Jun; Xue, Chenyang; Tan, Qiulin

2015-08-31

Pressure measurements in high-temperature applications, including compressors, turbines, and others, have become increasingly critical. This paper proposes an implantable passive LC pressure sensor based on an alumina ceramic material for in situ pressure sensing in high-temperature environments. The inductance and capacitance elements of the sensor were designed independently and separated by a thermally insulating material, which is conducive to reducing the influence of the temperature on the inductance element and improving the quality factor of the sensor. In addition, the sensor was fabricated using thick film integrated technology from high-temperature materials that ensure stable operation of the sensor in high-temperature environments. Experimental results showed that the sensor accurately monitored pressures from 0 bar to 2 bar at temperatures up to 800 °C. The sensitivity, linearity, repeatability error, and hysteretic error of the sensor were 0.225 MHz/bar, 95.3%, 5.5%, and 6.2%, respectively.

An Insertable Passive LC Pressure Sensor Based on an Alumina Ceramic for In Situ Pressure Sensing in High-Temperature Environments

PubMed Central

Xiong, Jijun; Li, Chen; Jia, Pinggang; Chen, Xiaoyong; Zhang, Wendong; Liu, Jun; Xue, Chenyang; Tan, Qiulin

2015-01-01

Pressure measurements in high-temperature applications, including compressors, turbines, and others, have become increasingly critical. This paper proposes an implantable passive LC pressure sensor based on an alumina ceramic material for in situ pressure sensing in high-temperature environments. The inductance and capacitance elements of the sensor were designed independently and separated by a thermally insulating material, which is conducive to reducing the influence of the temperature on the inductance element and improving the quality factor of the sensor. In addition, the sensor was fabricated using thick film integrated technology from high-temperature materials that ensure stable operation of the sensor in high-temperature environments. Experimental results showed that the sensor accurately monitored pressures from 0 bar to 2 bar at temperatures up to 800 °C. The sensitivity, linearity, repeatability error, and hysteretic error of the sensor were 0.225 MHz/bar, 95.3%, 5.5%, and 6.2%, respectively. PMID:26334279

Sensor fault diagnosis of singular delayed LPV systems with inexact parameters: an uncertain system approach

NASA Astrophysics Data System (ADS)

Hassanabadi, Amir Hossein; Shafiee, Masoud; Puig, Vicenc

2018-01-01

In this paper, sensor fault diagnosis of a singular delayed linear parameter varying (LPV) system is considered. In the considered system, the model matrices are dependent on some parameters which are real-time measurable. The case of inexact parameter measurements is considered which is close to real situations. Fault diagnosis in this system is achieved via fault estimation. For this purpose, an augmented system is created by including sensor faults as additional system states. Then, an unknown input observer (UIO) is designed which estimates both the system states and the faults in the presence of measurement noise, disturbances and uncertainty induced by inexact measured parameters. Error dynamics and the original system constitute an uncertain system due to inconsistencies between real and measured values of the parameters. Then, the robust estimation of the system states and the faults are achieved with H∞ performance and formulated with a set of linear matrix inequalities (LMIs). The designed UIO is also applicable for fault diagnosis of singular delayed LPV systems with unmeasurable scheduling variables. The efficiency of the proposed approach is illustrated with an example.

Extended Kalman Doppler tracking and model determination for multi-sensor short-range radar

NASA Astrophysics Data System (ADS)

Mittermaier, Thomas J.; Siart, Uwe; Eibert, Thomas F.; Bonerz, Stefan

2016-09-01

A tracking solution for collision avoidance in industrial machine tools based on short-range millimeter-wave radar Doppler observations is presented. At the core of the tracking algorithm there is an Extended Kalman Filter (EKF) that provides dynamic estimation and localization in real-time. The underlying sensor platform consists of several homodyne continuous wave (CW) radar modules. Based on In-phase-Quadrature (IQ) processing and down-conversion, they provide only Doppler shift information about the observed target. Localization with Doppler shift estimates is a nonlinear problem that needs to be linearized before the linear KF can be applied. The accuracy of state estimation depends highly on the introduced linearization errors, the initialization and the models that represent the true physics as well as the stochastic properties. The important issue of filter consistency is addressed and an initialization procedure based on data fitting and maximum likelihood estimation is suggested. Models for both, measurement and process noise are developed. Tracking results from typical three-dimensional courses of movement at short distances in front of a multi-sensor radar platform are presented.

Improvement in error propagation in the Shack-Hartmann-type zonal wavefront sensors.

PubMed

Pathak, Biswajit; Boruah, Bosanta R

2017-12-01

Estimation of the wavefront from measured slope values is an essential step in a Shack-Hartmann-type wavefront sensor. Using an appropriate estimation algorithm, these measured slopes are converted into wavefront phase values. Hence, accuracy in wavefront estimation lies in proper interpretation of these measured slope values using the chosen estimation algorithm. There are two important sources of errors associated with the wavefront estimation process, namely, the slope measurement error and the algorithm discretization error. The former type is due to the noise in the slope measurements or to the detector centroiding error, and the latter is a consequence of solving equations of a basic estimation algorithm adopted onto a discrete geometry. These errors deserve particular attention, because they decide the preference of a specific estimation algorithm for wavefront estimation. In this paper, we investigate these two important sources of errors associated with the wavefront estimation algorithms of Shack-Hartmann-type wavefront sensors. We consider the widely used Southwell algorithm and the recently proposed Pathak-Boruah algorithm [J. Opt.16, 055403 (2014)JOOPDB0150-536X10.1088/2040-8978/16/5/055403] and perform a comparative study between the two. We find that the latter algorithm is inherently superior to the Southwell algorithm in terms of the error propagation performance. We also conduct experiments that further establish the correctness of the comparative study between the said two estimation algorithms.

A Solar Position Sensor Based on Image Vision.

PubMed

Ruelas, Adolfo; Velázquez, Nicolás; Villa-Angulo, Carlos; Acuña, Alexis; Rosales, Pedro; Suastegui, José

2017-07-29

Solar collector technologies operate with better performance when the Sun beam direction is normal to the capturing surface, and for that to happen despite the relative movement of the Sun, solar tracking systems are used, therefore, there are rules and standards that need minimum accuracy for these tracking systems to be used in solar collectors' evaluation. Obtaining accuracy is not an easy job, hence in this document the design, construction and characterization of a sensor based on a visual system that finds the relative azimuth error and height of the solar surface of interest, is presented. With these characteristics, the sensor can be used as a reference in control systems and their evaluation. The proposed sensor is based on a microcontroller with a real-time clock, inertial measurement sensors, geolocation and a vision sensor, that obtains the angle of incidence from the sunrays' direction as well as the tilt and sensor position. The sensor's characterization proved how a measurement of a focus error or a Sun position can be made, with an accuracy of 0.0426° and an uncertainty of 0.986%, which can be modified to reach an accuracy under 0.01°. The validation of this sensor was determined showing the focus error on one of the best commercial solar tracking systems, a Kipp & Zonen SOLYS 2. To conclude, the solar tracking sensor based on a vision system meets the Sun detection requirements and components that meet the accuracy conditions to be used in solar tracking systems and their evaluation or, as a tracking and orientation tool, on photovoltaic installations and solar collectors.

Energy efficient data representation and aggregation with event region detection in wireless sensor networks

NASA Astrophysics Data System (ADS)

Banerjee, Torsha

Unlike conventional networks, wireless sensor networks (WSNs) are limited in power, have much smaller memory buffers, and possess relatively slower processing speeds. These characteristics necessitate minimum transfer and storage of information in order to prolong the network lifetime. In this dissertation, we exploit the spatio-temporal nature of sensor data to approximate the current values of the sensors based on readings obtained from neighboring sensors and itself. We propose a Tree based polynomial REGression algorithm, (TREG) that addresses the problem of data compression in wireless sensor networks. Instead of aggregated data, a polynomial function (P) is computed by the regression function, TREG. The coefficients of P are then passed to achieve the following goals: (i) The sink can get attribute values in the regions devoid of sensor nodes, and (ii) Readings over any portion of the region can be obtained at one time by querying the root of the tree. As the size of the data packet from each tree node to its parent remains constant, the proposed scheme scales very well with growing network density or increased coverage area. Since physical attributes exhibit a gradual change over time, we propose an iterative scheme, UPDATE_COEFF, which obviates the need to perform the regression function repeatedly and uses approximations based on previous readings. Extensive simulations are performed on real world data to demonstrate the effectiveness of our proposed aggregation algorithm, TREG. Results reveal that for a network density of 0.0025 nodes/m2, a complete binary tree of depth 4 could provide the absolute error to be less than 6%. A data compression ratio of about 0.02 is achieved using our proposed algorithm, which is almost independent of the tree depth. In addition, our proposed updating scheme makes the aggregation process faster while maintaining the desired error bounds. We also propose a Polynomial-based scheme that addresses the problem of Event Region Detection (PERD) for WSNs. When a single event occurs, a child of the tree sends a Flagged Polynomial (FP) to its parent, if the readings approximated by it falls outside the data range defining the existing phenomenon. After the aggregation process is over, the root having the two polynomials, P and FP can be queried for FP (approximating the new event region) instead of flooding the whole network. For multiple such events, instead of computing a polynomial corresponding to each new event, areas with same data range are combined by the corresponding tree nodes and the aggregated coefficients are passed on. Results reveal that a new event can be detected by PERD while error in detection remains constant and is less than a threshold of 10%. As the node density increases, accuracy and delay for event detection are found to remain almost constant, making PERD highly scalable. Whenever an event occurs in a WSN, data is generated by closeby sensors and relaying the data to the base station (BS) make sensors closer to the BS run out of energy at a much faster rate than sensors in other parts of the network. This gives rise to an unequal distribution of residual energy in the network and makes those sensors with lower remaining energy level die at much faster rate than others. We propose a scheme for enhancing network Lifetime using mobile cluster heads (CH) in a WSN. To maintain remaining energy more evenly, some energy-rich nodes are designated as CHs which move in a controlled manner towards sensors rich in energy and data. This eliminates multihop transmission required by the static sensors and thus increases the overall lifetime of the WSN. We combine the idea of clustering and mobile CH to first form clusters of static sensor nodes. A collaborative strategy among the CHs further increases the lifetime of the network. Time taken for transmitting data to the BS is reduced further by making the CHs follow a connectivity strategy that always maintain a connected path to the BS. Spatial correlation of sensor data can be further exploited for dynamic channel selection in Cellular Communication. In such a scenario within a licensed band, wireless sensors can be deployed (each sensor tuned to a frequency of the channel at a particular time) to sense the interference power of the frequency band. In an ideal channel, interference temperature (IT) which is directly proportional to the interference power, can be assumed to vary spatially with the frequency of the sub channel. We propose a scheme for fitting the sub channel frequencies and corresponding ITs to a regression model for calculating the IT of a random sub channel for further analysis of the channel interference at the base station. Our scheme, based on the readings reported by Sensors helps in Dynamic Channel Selection (S-DCS) in extended C-band for assignment to unlicensed secondary users. S-DCS proves to be economic from energy consumption point of view and it also achieves accuracy with error bound within 6.8%. Again, users are assigned empty sub channels without actually probing them, incurring minimum delay in the process. The overall channel throughput is maximized along with fairness to individual users.

Analysis and Calibration of Sources of Electronic Error in PSD Sensor Response

PubMed Central

Rodríguez-Navarro, David; Lázaro-Galilea, José Luis; Bravo-Muñoz, Ignacio; Gardel-Vicente, Alfredo; Tsirigotis, Georgios

2016-01-01

In order to obtain very precise measurements of the position of agents located at a considerable distance using a sensor system based on position sensitive detectors (PSD), it is necessary to analyze and mitigate the factors that generate substantial errors in the system’s response. These sources of error can be divided into electronic and geometric factors. The former stem from the nature and construction of the PSD as well as the performance, tolerances and electronic response of the system, while the latter are related to the sensor’s optical system. Here, we focus solely on the electrical effects, since the study, analysis and correction of these are a prerequisite for subsequently addressing geometric errors. A simple calibration method is proposed, which considers PSD response, component tolerances, temperature variations, signal frequency used, signal to noise ratio (SNR), suboptimal operational amplifier parameters, and analog to digital converter (ADC) quantitation SNRQ, etc. Following an analysis of these effects and calibration of the sensor, it was possible to correct the errors, thus rendering the effects negligible, as reported in the results section. PMID:27136562

Effects of the Ionosphere on Passive Microwave Remote Sensing of Ocean Salinity from Space

NASA Technical Reports Server (NTRS)

LeVine, D. M.; Abaham, Saji; Hildebrand, Peter H. (Technical Monitor)

2001-01-01

Among the remote sensing applications currently being considered from space is the measurement of sea surface salinity. The salinity of the open ocean is important for understanding ocean circulation and for modeling energy exchange with the atmosphere. Passive microwave remote sensors operating near 1.4 GHz (L-band) could provide data needed to fill the gap in current coverage and to complement in situ arrays being planned to provide subsurface profiles in the future. However, the dynamic range of the salinity signal in the open ocean is relatively small and propagation effects along the path from surface to sensor must be taken into account. In particular, Faraday rotation and even attenuation/emission in the ionosphere can be important sources of error. The purpose or this work is to estimate the magnitude of these effects in the context of a future remote sensing system in space to measure salinity in L-band. Data will be presented as a function of time location and solar activity using IRI-95 to model the ionosphere. The ionosphere presents two potential sources of error for the measurement of salinity: Rotation of the polarization vector (Faraday rotation) and attenuation/emission. Estimates of the effect of these two phenomena on passive remote sensing over the oceans at L-band (1.4 GHz) are presented.

Applications of inertial-sensor high-inheritance instruments to DSN precision antenna pointing

NASA Technical Reports Server (NTRS)

Goddard, R. E.

1992-01-01

Laboratory test results of the initialization and tracking performance of an existing inertial-sensor-based instrument are given. The instrument, although not primarily designed for precision antenna pointing applications, demonstrated an on-average 10-hour tracking error of several millidegrees. The system-level instrument performance is shown by analysis to be sensor limited. Simulated instrument improvements show a tracking error of less than 1 mdeg, which would provide acceptable performance, i.e., low pointing loss, for the DSN 70-m antenna sub network, operating at Ka-band (1-cm wavelength).

Applications of inertial-sensor high-inheritance instruments to DSN precision antenna pointing

NASA Technical Reports Server (NTRS)

Goddard, R. E.

1992-01-01

Laboratory test results of the initialization and tracking performance of an existing inertial-sensor-based instrument are given. The instrument, although not primarily designed for precision antenna pointing applications, demonstrated an on-average 10-hour tracking error of several millidegrees. The system-level instrument performance is shown by analysis to be sensor limited. Simulated instrument improvements show a tracking error of less than 1 mdeg, which would provide acceptable performance, i.e., low pointing loss, for the Deep Space Network 70-m antenna subnetwork, operating at Ka-band (1-cm wavelength).

Earth radiation budget measurement from a spinning satellite: Conceptual design of detectors

NASA Technical Reports Server (NTRS)

Sromovsky, L. A.; Revercomb, H. E.; Suomi, V. E.

1975-01-01

The conceptual design, sensor characteristics, sensor performance and accuracy, and spacecraft and orbital requirements for a spinning wide-field-of-view earth energy budget detector were investigated. The scientific requirements for measurement of the earth's radiative energy budget are presented. Other topics discussed include the observing system concept, solar constant radiometer design, plane flux wide FOV sensor design, fast active cavity theory, fast active cavity design and error analysis, thermopile detectors as an alternative, pre-flight and in-flight calibration plane, system error summary, and interface requirements.

High stability integrated Tri-axial fluxgate sensor with suspended technology

NASA Astrophysics Data System (ADS)

Wang, Chen; Teng, Yuntian; Wang, Xiaomei; Fan, Xiaoyong; Wu, Qiong

2017-04-01

The relative geomagnetic record of China Geomagnetic Network of China(GNC) has been digitized, network, meanwhile achieving second data acquisition and storage during after 9th five-year and 10th five-year plan upgraded. Currently the relative record in geomagnetic observatories are generally two sets of the same type instrument with parallel observation, which could distinguish the differential between observation instrument failures and environmental interference, and ensure the continuity and integrity of the observation data. Fluxgate magnetometer has become mainstream equipment for relative geomagnetic record because of its low noise, high sensitivity, and fast response. There is a problem about data inconsistency by the same type of instrument in the same station though few years observation data analysis. The researchers have done a lot of experiments and found three main error sources:1. The instrument performances, due to the limitation of manufacturing and assembly process level it is difficult to ensure the orthogonality of the instrument; other performances of scale, zero offset and temperature coefficient; 2. horizontal error, which introduced by the initial installation process due to horizontal adjustment and pillar tilling due to long-term observations; 3.The observation environment, the temperature and humidity, power supply system. The new fluxgate magnetometer uses special nonmagnetic gimbaled (made by beryllium / bronze material) construction for suspension, so the fluxgate sensor is fixed at the suspended platform in order to automatically keep the horizontal level. The advantage of this design is to eliminate horizontal error introduced by the initial installation process due to horizontal adjustment and pillar tilling due to long-term observations. The signal processing circuit board is fixed on the top of the suspended platform with certain distance to ensure the static and dynamic magnetic field produced by circuit board no effect to the sensor, so we could get flexible instrument due to signal attenuation resulting signal transmission cable limited length.

Decentralized coordinated control of elastic web winding systems without tension sensor.

PubMed

Hou, Hailiang; Nian, Xiaohong; Chen, Jie; Xiao, Dengfeng

2018-06-26

In elastic web winding systems, precise regulation of web tension in each span is critical to ensure final product quality, and to achieve low cost by reducing the occurrence of web break or fold. Generally, web winding systems use load cells or swing rolls as tension sensors, which add cost, reduce system reliability and increase the difficulty of control. In this paper, a decentralized coordinated control scheme with tension observers is designed for a three-motor web-winding system. First, two tension observers are proposed to estimate the unwinding and winding tension. The designed observers consider the essential dynamic, radius, and inertial variation effects and only require the modest computational effort. Then, using the estimated tensions as feedback signals, a robust decentralized coordinated controller is adopted to reduce the interaction between subsystems. Asymptotic stabilities of the observer error dynamics and the closed-loop winding systems are demonstrated via Lyapunov stability theory. The observer gains and the controller gains can be obtained by solving matrix inequalities. Finally, some simulations and experiments are performed on a paper winding setup to test the performance of the designed observers and the observer-base DCC method, respectively. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Visualization of Concrete Slump Flow Using the Kinect Sensor

PubMed Central

Park, Minbeom

2018-01-01

Workability is regarded as one of the important parameters of high-performance concrete and monitoring it is essential in concrete quality management at construction sites. The conventional workability test methods are basically based on length and time measured by a ruler and a stopwatch and, as such, inevitably involves human error. In this paper, we propose a 4D slump test method based on digital measurement and data processing as a novel concrete workability test. After acquiring the dynamically changing 3D surface of fresh concrete using a 3D depth sensor during the slump flow test, the stream images are processed with the proposed 4D slump processing algorithm and the results are compressed into a single 4D slump image. This image basically represents the dynamically spreading cross-section of fresh concrete along the time axis. From the 4D slump image, it is possible to determine the slump flow diameter, slump flow time, and slump height at any location simultaneously. The proposed 4D slump test will be able to activate research related to concrete flow simulation and concrete rheology by providing spatiotemporal measurement data of concrete flow. PMID:29510510

Visualization of Concrete Slump Flow Using the Kinect Sensor.

PubMed

Kim, Jung-Hoon; Park, Minbeom

2018-03-03

Workability is regarded as one of the important parameters of high-performance concrete and monitoring it is essential in concrete quality management at construction sites. The conventional workability test methods are basically based on length and time measured by a ruler and a stopwatch and, as such, inevitably involves human error. In this paper, we propose a 4D slump test method based on digital measurement and data processing as a novel concrete workability test. After acquiring the dynamically changing 3D surface of fresh concrete using a 3D depth sensor during the slump flow test, the stream images are processed with the proposed 4D slump processing algorithm and the results are compressed into a single 4D slump image. This image basically represents the dynamically spreading cross-section of fresh concrete along the time axis. From the 4D slump image, it is possible to determine the slump flow diameter, slump flow time, and slump height at any location simultaneously. The proposed 4D slump test will be able to activate research related to concrete flow simulation and concrete rheology by providing spatiotemporal measurement data of concrete flow.

Air Temperature Error Correction Based on Solar Radiation in an Economical Meteorological Wireless Sensor Network

PubMed Central

Sun, Xingming; Yan, Shuangshuang; Wang, Baowei; Xia, Li; Liu, Qi; Zhang, Hui

2015-01-01

Air temperature (AT) is an extremely vital factor in meteorology, agriculture, military, etc., being used for the prediction of weather disasters, such as drought, flood, frost, etc. Many efforts have been made to monitor the temperature of the atmosphere, like automatic weather stations (AWS). Nevertheless, due to the high cost of specialized AT sensors, they cannot be deployed within a large spatial density. A novel method named the meteorology wireless sensor network relying on a sensing node has been proposed for the purpose of reducing the cost of AT monitoring. However, the temperature sensor on the sensing node can be easily influenced by environmental factors. Previous research has confirmed that there is a close relation between AT and solar radiation (SR). Therefore, this paper presents a method to decrease the error of sensed AT, taking SR into consideration. In this work, we analyzed all of the collected data of AT and SR in May 2014 and found the numerical correspondence between AT error (ATE) and SR. This corresponding relation was used to calculate real-time ATE according to real-time SR and to correct the error of AT in other months. PMID:26213941

Air Temperature Error Correction Based on Solar Radiation in an Economical Meteorological Wireless Sensor Network.

PubMed

Sun, Xingming; Yan, Shuangshuang; Wang, Baowei; Xia, Li; Liu, Qi; Zhang, Hui

2015-07-24

Air temperature (AT) is an extremely vital factor in meteorology, agriculture, military, etc., being used for the prediction of weather disasters, such as drought, flood, frost, etc. Many efforts have been made to monitor the temperature of the atmosphere, like automatic weather stations (AWS). Nevertheless, due to the high cost of specialized AT sensors, they cannot be deployed within a large spatial density. A novel method named the meteorology wireless sensor network relying on a sensing node has been proposed for the purpose of reducing the cost of AT monitoring. However, the temperature sensor on the sensing node can be easily influenced by environmental factors. Previous research has confirmed that there is a close relation between AT and solar radiation (SR). Therefore, this paper presents a method to decrease the error of sensed AT, taking SR into consideration. In this work, we analyzed all of the collected data of AT and SR in May 2014 and found the numerical correspondence between AT error (ATE) and SR. This corresponding relation was used to calculate real-time ATE according to real-time SR and to correct the error of AT in other months.

Satellite Sampling and Retrieval Errors in Regional Monthly Rain Estimates from TMI AMSR-E, SSM/I, AMSU-B and the TRMM PR

NASA Technical Reports Server (NTRS)

Fisher, Brad; Wolff, David B.

2010-01-01

Passive and active microwave rain sensors onboard earth-orbiting satellites estimate monthly rainfall from the instantaneous rain statistics collected during satellite overpasses. It is well known that climate-scale rain estimates from meteorological satellites incur sampling errors resulting from the process of discrete temporal sampling and statistical averaging. Sampling and retrieval errors ultimately become entangled in the estimation of the mean monthly rain rate. The sampling component of the error budget effectively introduces statistical noise into climate-scale rain estimates that obscure the error component associated with the instantaneous rain retrieval. Estimating the accuracy of the retrievals on monthly scales therefore necessitates a decomposition of the total error budget into sampling and retrieval error quantities. This paper presents results from a statistical evaluation of the sampling and retrieval errors for five different space-borne rain sensors on board nine orbiting satellites. Using an error decomposition methodology developed by one of the authors, sampling and retrieval errors were estimated at 0.25 resolution within 150 km of ground-based weather radars located at Kwajalein, Marshall Islands and Melbourne, Florida. Error and bias statistics were calculated according to the land, ocean and coast classifications of the surface terrain mask developed for the Goddard Profiling (GPROF) rain algorithm. Variations in the comparative error statistics are attributed to various factors related to differences in the swath geometry of each rain sensor, the orbital and instrument characteristics of the satellite and the regional climatology. The most significant result from this study found that each of the satellites incurred negative longterm oceanic retrieval biases of 10 to 30%.

E-ELT M5 field stabilisation unit scale 1 demonstrator design and performances evaluation

NASA Astrophysics Data System (ADS)

Casalta, J. M.; Barriga, J.; Ariño, J.; Mercader, J.; San Andrés, M.; Serra, J.; Kjelberg, I.; Hubin, N.; Jochum, L.; Vernet, E.; Dimmler, M.; Müller, M.

2010-07-01

The M5 Field stabilization Unit (M5FU) for European Extremely Large Telescope (E-ELT) is a fast correcting optical system that shall provide tip-tilt corrections for the telescope dynamic pointing errors and the effect of atmospheric tiptilt and wind disturbances. A M5FU scale 1 demonstrator (M5FU1D) is being built to assess the feasibility of the key elements (actuators, sensors, mirror, mirror interfaces) and the real-time control algorithm. The strict constraints (e.g. tip-tilt control frequency range 100Hz, 3m ellipse mirror size, mirror first Eigen frequency 300Hz, maximum tip/tilt range +/- 30 arcsec, maximum tiptilt error < 40 marcsec) have been a big challenge for developing the M5FU Conceptual Design and its scale 1 demonstrator. The paper summarises the proposed design for the final unit and demonstrator and the measured performances compared to the applicable specifications.

A dynamic measure of controllability and observability for the placement of actuators and sensors on large space structures

NASA Technical Reports Server (NTRS)

Vandervelde, W. E.; Carignan, C. R.

1982-01-01

The degree of controllability of a large space structure is found by a four step procedure: (1) finding the minimum control energy for driving the system from a given initial state to the origin in the prescribed time; (2) finding the region of initial state which can be driven to the origin with constrained control energy and time using optimal control strategy; (3) scaling the axes so that a unit displacement in every direction is equally important to control; and (4) finding the linear measurement of the weighted "volume" of the ellipsoid in the equicontrol space. For observability, the error covariance must be reduced toward zero using measurements optimally, and the criterion must be standardized by the magnitude of tolerable errors. The results obtained using these methods are applied to the vibration modes of a free-free beam.

DEADS: Depth and Energy Aware Dominating Set Based Algorithm for Cooperative Routing along with Sink Mobility in Underwater WSNs.

PubMed

Umar, Amara; Javaid, Nadeem; Ahmad, Ashfaq; Khan, Zahoor Ali; Qasim, Umar; Alrajeh, Nabil; Hayat, Amir

2015-06-18

Performance enhancement of Underwater Wireless Sensor Networks (UWSNs) in terms of throughput maximization, energy conservation and Bit Error Rate (BER) minimization is a potential research area. However, limited available bandwidth, high propagation delay, highly dynamic network topology, and high error probability leads to performance degradation in these networks. In this regard, many cooperative communication protocols have been developed that either investigate the physical layer or the Medium Access Control (MAC) layer, however, the network layer is still unexplored. More specifically, cooperative routing has not yet been jointly considered with sink mobility. Therefore, this paper aims to enhance the network reliability and efficiency via dominating set based cooperative routing and sink mobility. The proposed work is validated via simulations which show relatively improved performance of our proposed work in terms the selected performance metrics.

Development of the segment alignment maintenance system (SAMS) for the Hobby-Eberly Telescope

NASA Astrophysics Data System (ADS)

Booth, John A.; Adams, Mark T.; Ames, Gregory H.; Fowler, James R.; Montgomery, Edward E.; Rakoczy, John M.

2000-07-01

A sensing and control system for maintaining optical alignment of ninety-one 1-meter mirror segments forming the Hobby-Eberly Telescope (HET) primary mirror array is now under development. The Segment Alignment Maintenance System (SAMS) is designed to sense relative shear motion between each segment edge pair and calculated individual segment tip, tilt, and piston position errors. Error information is sent to the HET primary mirror control system, which corrects the physical position of each segment as often as once per minute. Development of SAMS is required to meet optical images quality specifications for the telescope. Segment misalignment over time is though to be due to thermal inhomogeneity within the steel mirror support truss. Challenging problems of sensor resolution, dynamic range, mechanical mounting, calibration, stability, robust algorithm development, and system integration must be overcome to achieve a successful operational solution.

Evaluation of communication in wireless underground sensor networks

NASA Astrophysics Data System (ADS)

Yu, X. Q.; Zhang, Z. L.; Han, W. T.

2017-06-01

Wireless underground sensor networks (WUSN) are an emerging area of research that promises to provide communication capabilities to buried sensors. In this paper, experimental measurements have been conducted with commodity sensor motes at the frequency of 2.4GHz and 433 MHz, respectively. Experiments are run to examine the received signal strength of correctly received packets and the packet error rate for a communication link. The tests show the potential feasibility of the WUSN with the use of powerful RF transceivers at 433MHz frequency. Moreover, we also illustrate a classification for wireless underground sensor network communication. Finally, we conclude that the effects of burial depth, inter-node distance and volumetric water content of the soil on the signal strength and packet error rate in communication of WUSN.

Extended scene Shack-Hartmann wavefront sensor algorithm: minimization of scene content dependent shift estimation errors.

PubMed

Sidick, Erkin

2013-09-10

An adaptive periodic-correlation (APC) algorithm was developed for use in extended-scene Shack-Hartmann wavefront sensors. It provides high accuracy even when the subimages in a frame captured by a Shack-Hartmann camera are not only shifted but also distorted relative to each other. Recently we found that the shift estimate error of the APC algorithm has a component that depends on the content of the extended scene. In this paper, we assess the amount of that error and propose a method to minimize it.

Extended Scene SH Wavefront Sensor Algorithm: Minimization of Scene Content Dependent Shift Estimation Errors

NASA Technical Reports Server (NTRS)

Sidick, Erkin

2012-01-01

Adaptive Periodic-Correlation (APC) algorithm was developed for use in extended-scene Shack-Hartmann wavefront sensors. It provides high-accuracy even when the sub-images in a frame captured by a Shack-Hartmann camera are not only shifted but also distorted relative to each other. Recently we found that the shift-estimate error of the APC algorithm has a component that depends on the content of extended-scene. In this paper we assess the amount of that error and propose a method to minimize it.

Effects of measurement unobservability on neural extended Kalman filter tracking

NASA Astrophysics Data System (ADS)

Stubberud, Stephen C.; Kramer, Kathleen A.

2009-05-01

An important component of tracking fusion systems is the ability to fuse various sensors into a coherent picture of the scene. When multiple sensor systems are being used in an operational setting, the types of data vary. A significant but often overlooked concern of multiple sensors is the incorporation of measurements that are unobservable. An unobservable measurement is one that may provide information about the state, but cannot recreate a full target state. A line of bearing measurement, for example, cannot provide complete position information. Often, such measurements come from passive sensors such as a passive sonar array or an electronic surveillance measure (ESM) system. Unobservable measurements will, over time, result in the measurement uncertainty to grow without bound. While some tracking implementations have triggers to protect against the detrimental effects, many maneuver tracking algorithms avoid discussing this implementation issue. One maneuver tracking technique is the neural extended Kalman filter (NEKF). The NEKF is an adaptive estimation algorithm that estimates the target track as it trains a neural network on line to reduce the error between the a priori target motion model and the actual target dynamics. The weights of neural network are trained in a similar method to the state estimation/parameter estimation Kalman filter techniques. The NEKF has been shown to improve target tracking accuracy through maneuvers and has been use to predict target behavior using the new model that consists of the a priori model and the neural network. The key to the on-line adaptation of the NEKF is the fact that the neural network is trained using the same residuals as the Kalman filter for the tracker. The neural network weights are treated as augmented states to the target track. Through the state-coupling function, the weights are coupled to the target states. Thus, if the measurements cause the states of the target track to be unobservable, then the weights of the neural network have unobservable modes as well. In recent analysis, the NEKF was shown to have a significantly larger growth in the eigenvalues of the error covariance matrix than the standard EKF tracker when the measurements were purely bearings-only. This caused detrimental effects to the ability of the NEKF to model the target dynamics. In this work, the analysis is expanded to determine the detrimental effects of bearings-only measurements of various uncertainties on the performance of the NEKF when these unobservable measurements are interlaced with completely observable measurements. This analysis provides the ability to put implementation limitations on the NEKF when bearings-only sensors are present.

Fault detection and diagnosis in a spacecraft attitude determination system

NASA Astrophysics Data System (ADS)

Pirmoradi, F. N.; Sassani, F.; de Silva, C. W.

2009-09-01

This paper presents a new scheme for fault detection and diagnosis (FDD) in spacecraft attitude determination (AD) sensors. An integrated attitude determination system, which includes measurements of rate and angular position using rate gyros and vector sensors, is developed. Measurement data from all sensors are fused by a linearized Kalman filter, which is designed based on the system kinematics, to provide attitude estimation and the values of the gyro bias. Using this information the erroneous sensor measurements are corrected, and unbounded sensor measurement errors are avoided. The resulting bias-free data are used in the FDD scheme. The FDD algorithm uses model-based state estimation, combining the information from the rotational dynamics and kinematics of a spacecraft with the sensor measurements to predict the future sensor outputs. Fault isolation is performed through extended Kalman filters (EKFs). The innovation sequences of EKFs are monitored by several statistical tests to detect the presence of a failure and to localize the failures in all AD sensors. The isolation procedure is developed in two phases. In the first phase, two EKFs are designed, which use subsets of measurements to provide state estimates and form residuals, which are used to verify the source of the fault. In the second phase of isolation, testing of multiple hypotheses is performed. The generalized likelihood ratio test is utilized to identify the faulty components. In the scheme developed in this paper a relatively small number of hypotheses is used, which results in faster isolation and highly distinguishable fault signatures. An important feature of the developed FDD scheme is that it can provide attitude estimations even if only one type of sensors is functioning properly.

Optimal multi-type sensor placement for response and excitation reconstruction

NASA Astrophysics Data System (ADS)

Zhang, C. D.; Xu, Y. L.

2016-01-01

The need to perform dynamic response reconstruction always arises as the measurement of structural response is often limited to a few locations, especially for a large civil structure. Besides, it is usually very difficult, if not impossible, to measure external excitations under the operation condition of a structure. This study presents an algorithm for optimal placement of multi-type sensors, including strain gauges, displacement transducers and accelerometers, for the best reconstruction of responses of key structural components where there are no sensors installed and the best estimation of external excitations acting on the structure at the same time. The algorithm is developed in the framework of Kalman filter with unknown excitation, in which minimum-variance unbiased estimates of the generalized state of the structure and the external excitations are obtained by virtue of limited sensor measurements. The structural responses of key locations without sensors can then be reconstructed with the estimated generalized state and excitation. The asymptotic stability feature of the filter is utilized for optimal sensor placement. The number and spatial location of the multi-type sensors are determined by adding the optimal sensor which gains the maximal reduction of the estimation error of reconstructed responses. For the given mode number in response reconstruction and the given locations of external excitations, the optimal multi-sensor placement achieved by the proposed method is independent of the type and time evolution of external excitation. A simply-supported overhanging steel beam under multiple types of excitation is numerically studied to demonstrate the feasibility and superiority of the proposed method, and the experimental work is then carried out to testify the effectiveness of the proposed method.

Electroinduction disk sensor of electric field strength

NASA Astrophysics Data System (ADS)

Biryukov, S. V.; Korolyova, M. A.

2018-01-01

Measurement of the level of electric fields exposure to the technical and biological objects for a long time is an urgent task. To solve this problem, the required electric field sensors with specified metrological characteristics. The aim of the study is the establishment of theoretical assumptions for the calculation of the flat electric field sensors. It is proved that the accuracy of the sensor does not exceed 3% in the spatial range 0

Evaluating and improving the performance of thin film force sensors within body and device interfaces.

PubMed

Likitlersuang, Jirapat; Leineweber, Matthew J; Andrysek, Jan

2017-10-01

Thin film force sensors are commonly used within biomechanical systems, and at the interface of the human body and medical and non-medical devices. However, limited information is available about their performance in such applications. The aims of this study were to evaluate and determine ways to improve the performance of thin film (FlexiForce) sensors at the body/device interface. Using a custom apparatus designed to load the sensors under simulated body/device conditions, two aspects were explored relating to sensor calibration and application. The findings revealed accuracy errors of 23.3±17.6% for force measurements at the body/device interface with conventional techniques of sensor calibration and application. Applying a thin rigid disc between the sensor and human body and calibrating the sensor using compliant surfaces was found to substantially reduce measurement errors to 2.9±2.0%. The use of alternative calibration and application procedures is recommended to gain acceptable measurement performance from thin film force sensors in body/device applications. Copyright © 2017 IPEM. Published by Elsevier Ltd. All rights reserved.

A comparison between different error modeling of MEMS applied to GPS/INS integrated systems.

PubMed

Quinchia, Alex G; Falco, Gianluca; Falletti, Emanuela; Dovis, Fabio; Ferrer, Carles

2013-07-24

Advances in the development of micro-electromechanical systems (MEMS) have made possible the fabrication of cheap and small dimension accelerometers and gyroscopes, which are being used in many applications where the global positioning system (GPS) and the inertial navigation system (INS) integration is carried out, i.e., identifying track defects, terrestrial and pedestrian navigation, unmanned aerial vehicles (UAVs), stabilization of many platforms, etc. Although these MEMS sensors are low-cost, they present different errors, which degrade the accuracy of the navigation systems in a short period of time. Therefore, a suitable modeling of these errors is necessary in order to minimize them and, consequently, improve the system performance. In this work, the most used techniques currently to analyze the stochastic errors that affect these sensors are shown and compared: we examine in detail the autocorrelation, the Allan variance (AV) and the power spectral density (PSD) techniques. Subsequently, an analysis and modeling of the inertial sensors, which combines autoregressive (AR) filters and wavelet de-noising, is also achieved. Since a low-cost INS (MEMS grade) presents error sources with short-term (high-frequency) and long-term (low-frequency) components, we introduce a method that compensates for these error terms by doing a complete analysis of Allan variance, wavelet de-nosing and the selection of the level of decomposition for a suitable combination between these techniques. Eventually, in order to assess the stochastic models obtained with these techniques, the Extended Kalman Filter (EKF) of a loosely-coupled GPS/INS integration strategy is augmented with different states. Results show a comparison between the proposed method and the traditional sensor error models under GPS signal blockages using real data collected in urban roadways.

A Comparison between Different Error Modeling of MEMS Applied to GPS/INS Integrated Systems

PubMed Central

Quinchia, Alex G.; Falco, Gianluca; Falletti, Emanuela; Dovis, Fabio; Ferrer, Carles

2013-01-01

Advances in the development of micro-electromechanical systems (MEMS) have made possible the fabrication of cheap and small dimension accelerometers and gyroscopes, which are being used in many applications where the global positioning system (GPS) and the inertial navigation system (INS) integration is carried out, i.e., identifying track defects, terrestrial and pedestrian navigation, unmanned aerial vehicles (UAVs), stabilization of many platforms, etc. Although these MEMS sensors are low-cost, they present different errors, which degrade the accuracy of the navigation systems in a short period of time. Therefore, a suitable modeling of these errors is necessary in order to minimize them and, consequently, improve the system performance. In this work, the most used techniques currently to analyze the stochastic errors that affect these sensors are shown and compared: we examine in detail the autocorrelation, the Allan variance (AV) and the power spectral density (PSD) techniques. Subsequently, an analysis and modeling of the inertial sensors, which combines autoregressive (AR) filters and wavelet de-noising, is also achieved. Since a low-cost INS (MEMS grade) presents error sources with short-term (high-frequency) and long-term (low-frequency) components, we introduce a method that compensates for these error terms by doing a complete analysis of Allan variance, wavelet de-nosing and the selection of the level of decomposition for a suitable combination between these techniques. Eventually, in order to assess the stochastic models obtained with these techniques, the Extended Kalman Filter (EKF) of a loosely-coupled GPS/INS integration strategy is augmented with different states. Results show a comparison between the proposed method and the traditional sensor error models under GPS signal blockages using real data collected in urban roadways. PMID:23887084

Further development of the dynamic gas temperature measurement system. Volume 1: Technical efforts

NASA Technical Reports Server (NTRS)

Elmore, D. L.; Robinson, W. W.; Watkins, W. B.

1986-01-01

A compensated dynamic gas temperature thermocouple measurement method was experimentally verified. Dynamic gas temperature signals from a flow passing through a chopped-wheel signal generator and an atmospheric pressure laboratory burner were measured by the dynamic temperature sensor and other fast-response sensors. Compensated data from dynamic temperature sensor thermoelements were compared with fast-response sensors. Results from the two experiments are presented as time-dependent waveforms and spectral plots. Comparisons between compensated dynamic temperature sensor spectra and a commercially available optical fiber thermometer compensated spectra were made for the atmospheric burner experiment. Increases in precision of the measurement method require optimization of several factors, and directions for further work are identified.

Virtual sensors for on-line wheel wear and part roughness measurement in the grinding process.

PubMed

Arriandiaga, Ander; Portillo, Eva; Sánchez, Jose A; Cabanes, Itziar; Pombo, Iñigo

2014-05-19

Grinding is an advanced machining process for the manufacturing of valuable complex and accurate parts for high added value sectors such as aerospace, wind generation, etc. Due to the extremely severe conditions inside grinding machines, critical process variables such as part surface finish or grinding wheel wear cannot be easily and cheaply measured on-line. In this paper a virtual sensor for on-line monitoring of those variables is presented. The sensor is based on the modelling ability of Artificial Neural Networks (ANNs) for stochastic and non-linear processes such as grinding; the selected architecture is the Layer-Recurrent neural network. The sensor makes use of the relation between the variables to be measured and power consumption in the wheel spindle, which can be easily measured. A sensor calibration methodology is presented, and the levels of error that can be expected are discussed. Validation of the new sensor is carried out by comparing the sensor's results with actual measurements carried out in an industrial grinding machine. Results show excellent estimation performance for both wheel wear and surface roughness. In the case of wheel wear, the absolute error is within the range of microns (average value 32 μm). In the case of surface finish, the absolute error is well below Ra 1 μm (average value 0.32 μm). The present approach can be easily generalized to other grinding operations.

Space-based IR tracking bias removal using background star observations

NASA Astrophysics Data System (ADS)

Clemons, T. M., III; Chang, K. C.

2009-05-01

This paper provides the results of a proposed methodology for removing sensor bias from a space-based infrared (IR) tracking system through the use of stars detected in the background field of the tracking sensor. The tracking system consists of two satellites flying in a lead-follower formation tracking a ballistic target. Each satellite is equipped with a narrow-view IR sensor that provides azimuth and elevation to the target. The tracking problem is made more difficult due to a constant, non-varying or slowly varying bias error present in each sensor's line of sight measurements. As known stars are detected during the target tracking process, the instantaneous sensor pointing error can be calculated as the difference between star detection reading and the known position of the star. The system then utilizes a separate bias filter to estimate the bias value based on these detections and correct the target line of sight measurements to improve the target state vector. The target state vector is estimated through a Linearized Kalman Filter (LKF) for the highly non-linear problem of tracking a ballistic missile. Scenarios are created using Satellite Toolkit(C) for trajectories with associated sensor observations. Mean Square Error results are given for tracking during the period when the target is in view of the satellite IR sensors. The results of this research provide a potential solution to bias correction while simultaneously tracking a target.

Mathematical Model and Calibration Experiment of a Large Measurement Range Flexible Joints 6-UPUR Six-Axis Force Sensor

PubMed Central

Zhao, Yanzhi; Zhang, Caifeng; Zhang, Dan; Shi, Zhongpan; Zhao, Tieshi

2016-01-01

Nowadays improving the accuracy and enlarging the measuring range of six-axis force sensors for wider applications in aircraft landing, rocket thrust, and spacecraft docking testing experiments has become an urgent objective. However, it is still difficult to achieve high accuracy and large measuring range with traditional parallel six-axis force sensors due to the influence of the gap and friction of the joints. Therefore, to overcome the mentioned limitations, this paper proposed a 6-Universal-Prismatic-Universal-Revolute (UPUR) joints parallel mechanism with flexible joints to develop a large measurement range six-axis force sensor. The structural characteristics of the sensor are analyzed in comparison with traditional parallel sensor based on the Stewart platform. The force transfer relation of the sensor is deduced, and the force Jacobian matrix is obtained using screw theory in two cases of the ideal state and the state of flexibility of each flexible joint is considered. The prototype and loading calibration system are designed and developed. The K value method and least squares method are used to process experimental data, and in errors of kind Ι and kind II linearity are obtained. The experimental results show that the calibration error of the K value method is more than 13.4%, and the calibration error of the least squares method is 2.67%. The experimental results prove the feasibility of the sensor and the correctness of the theoretical analysis which are expected to be adopted in practical applications. PMID:27529244

Experimental study on performance verification tests for coordinate measuring systems with optical distance sensors

NASA Astrophysics Data System (ADS)

Carmignato, Simone

2009-01-01

Optical sensors are increasingly used for dimensional and geometrical metrology. However, the lack of international standards for testing optical coordinate measuring systems is currently limiting the traceability of measurements and the easy comparison of different optical systems. This paper presents an experimental investigation on artefacts and procedures for testing coordinate measuring systems equipped with optical distance sensors. The work is aimed at contributing to the standardization of testing methods. The VDI/VDE 2617-6.2:2005 guideline, which is probably the most complete document available at the state of the art for testing systems with optical distance sensors, is examined with specific experiments. Results from the experiments are discussed, with particular reference to the tests used for determining the following characteristics: error of indication for size measurement, probing error and structural resolution. Particular attention is given to the use of artefacts alternative to gauge blocks for determining the error of indication for size measurement.

A small, lightweight multipollutant sensor system for ground ...

EPA Pesticide Factsheets

Characterizing highly dynamic, transient, and vertically lofted emissions from open area sources poses unique measurement challenges. This study developed and applied a multipollutant sensor and integrated sampler system for use on mobile applications including tethered balloons (aerostats) and unmanned aerial vehicles (UAVs). The system is particularly applicable to open area sources, such as forest fires, due to its light weight (3.5 kg), compact size (6.75 L), and internal power supply. The sensor system, termed “Kolibri”, consists of sensors measuring CO2 and CO, and samplers for particulate matter (PM) and volatile organic compounds (VOCs). The Kolibri is controlled by a microcontroller which can record and transfer data in real time through a radio module. Selection of the sensors was based on laboratory testing for accuracy, response delay and recovery, cross-sensitivity, and precision. The Kolibri was compared against rack-mounted continuous emissions monitoring system (CEMs) and another mobile sampling instrument (the “Flyer”) that has been used in over ten open area pollutant sampling events. Our results showed that the time series of CO, CO2, and PM2.5 concentrations measured by the Kolibri agreed well with those from the CEMs and the Flyer, with a laboratory-tested percentage error of 4.9%, 3%, and 5.8%, respectively. The VOC emission factors obtained using the Kolibri were consistent with existing literature values that relate concentration

Observability analysis of DVL/PS aided INS for a maneuvering AUV.

PubMed

Klein, Itzik; Diamant, Roee

2015-10-22

Recently, ocean exploration has increased considerably through the use of autonomous underwater vehicles (AUV). A key enabling technology is the precision of the AUV navigation capability. In this paper, we focus on understanding the limitation of the AUV navigation system. That is, what are the observable error-states for different maneuvering types of the AUV? Since analyzing the performance of an underwater navigation system is highly complex, to answer the above question, current approaches use simulations. This, of course, limits the conclusions to the emulated type of vehicle used and to the simulation setup. For this reason, we take a different approach and analyze the system observability for different types of vehicle dynamics by finding the set of observable and unobservable states. To that end, we apply the observability Gramian approach, previously used only for terrestrial applications. We demonstrate our analysis for an underwater inertial navigation system aided by a Doppler velocity logger or by a pressure sensor. The result is a first prediction of the performance of an AUV standing, rotating at a position and turning at a constant speed. Our conclusions of the observable and unobservable navigation error states for different dynamics are supported by extensive numerical simulation.

Observability Analysis of DVL/PS Aided INS for a Maneuvering AUV

PubMed Central

Klein, Itzik; Diamant, Roee

2015-01-01

Recently, ocean exploration has increased considerably through the use of autonomous underwater vehicles (AUV). A key enabling technology is the precision of the AUV navigation capability. In this paper, we focus on understanding the limitation of the AUV navigation system. That is, what are the observable error-states for different maneuvering types of the AUV? Since analyzing the performance of an underwater navigation system is highly complex, to answer the above question, current approaches use simulations. This, of course, limits the conclusions to the emulated type of vehicle used and to the simulation setup. For this reason, we take a different approach and analyze the system observability for different types of vehicle dynamics by finding the set of observable and unobservable states. To that end, we apply the observability Gramian approach, previously used only for terrestrial applications. We demonstrate our analysis for an underwater inertial navigation system aided by a Doppler velocity logger or by a pressure sensor. The result is a first prediction of the performance of an AUV standing, rotating at a position and turning at a constant speed. Our conclusions of the observable and unobservable navigation error states for different dynamics are supported by extensive numerical simulation. PMID:26506356

Experimental Comparison Between Mahoney and Complementary Sensor Fusion Algorithm for Attitude Determination by Raw Sensor Data of Xsens Imu on Buoy

NASA Astrophysics Data System (ADS)

Jouybari, A.; Ardalan, A. A.; Rezvani, M.-H.

2017-09-01

The accurate measurement of platform orientation plays a critical role in a range of applications including marine, aerospace, robotics, navigation, human motion analysis, and machine interaction. We used Mahoney filter, Complementary filter and Xsens Kalman filter for achieving Euler angle of a dynamic platform by integration of gyroscope, accelerometer, and magnetometer measurements. The field test has been performed in Kish Island using an IMU sensor (Xsens MTi-G-700) that installed onboard a buoy so as to provide raw data of gyroscopes, accelerometers, magnetometer measurements about 25 minutes. These raw data were used to calculate the Euler angles by Mahoney filter and Complementary filter, while the Euler angles collected by XSense IMU sensor become the reference of the Euler angle estimations. We then compared Euler angles which calculated by Mahoney Filter and Complementary Filter with reference to the Euler angles recorded by the XSense IMU sensor. The standard deviations of the differences between the Mahoney Filter, Complementary Filter Euler angles and XSense IMU sensor Euler angles were about 0.5644, 0.3872, 0.4990 degrees and 0.6349, 0.2621, 2.3778 degrees for roll, pitch, and heading, respectively, so the numerical result assert that Mahoney filter is precise for roll and heading angles determination and Complementary filter is precise only for pitch determination, it should be noted that heading angle determination by Complementary filter has more error than Mahoney filter.

A new sensor system for accurate and precise determination of sediment dynamics and position.

NASA Astrophysics Data System (ADS)

Maniatis, Georgios; Hoey, Trevor; Sventek, Joseph; Hodge, Rebecca

2014-05-01

Sediment transport processes control many significant geomorphological changes. Consequently, sediment transport dynamics are studied across a wide range of scales leading to application of a variety of conceptually different mathematical descriptions (models) and data acquisition techniques (sensing). For river sediment transport processes both Eulerian and Lagrangian formulations are used. Data are gathered using a very wide range of sensing techniques that are not always compatible with the conceptual formulation applied. We are concerned with small to medium sediment grain-scale motion in gravel-bed rivers, and other coarse-grained environments, and: a) are developing a customised environmental sensor capable of providing coherent data that reliably record the motion; and, b) provide a mathematical framework in which these data can be analysed and interpreted, this being compatible with current stochastic approaches to sediment transport theory. Here we present results from three different aspects of the above developmental process. Firstly, we present a requirement analysis for the sensor based on the state of the art of the existing technologies. We focus on the factors that enhance data coherence and representativeness, extending the common practice for optimization which is based exclusively on electronics/computing related criteria. This analysis leads to formalization of a method that permits accurate control on the physical properties of the sensor using contemporary rapid prototyping techniques [Maniatis et al. 2013]. Secondly the first results are presented from a series of entrainment experiments in a 5 x 0.8 m flume in which a prototype sensor was deployed to monitor entrainment dynamics under increasing flow conditions (0.037 m3.s-1). The sensor was enclosed in an idealized spherical case (111 mm diameter) and placed on a constructed bed of hemispheres of the same diameter. We measured 3-axial inertial acceleration (as a measure of flow stress), with sampling frequency 4 to 10Hz, for two different initial positions over a range of slopes (from 0.026 to 0.57). The results reveal forces during the pre-entrainment phase and show the effect of slope on the temporal characteristics of the process. Finally we present results from the simulations using a mathematical framework developed to integrate the inertial-dynamics data (corresponding to the above experimental procedure and sensing conceptualization) [Abeywardana et al. 2012] with the mathematical techniques used in contemporary localization applications [Zanella et al. 2012]. We specifically assess different signal filtering techniques in terms of: a) how informative they are regarding the complexity of sediment movement; and, b) how possible it is to reduce rapidly accumulating errors that occur during sensing and increase positional accuracy. References Maniatis, G.; Hoey, T.; Sventek, J. Sensor Enclosures: Example Application and Implications for Data Coherence. J. Sens. Actuator Netw. 2013, 2, 761-779. Abeywardana, D. K., A. P. Hu, and N. Kularatna. "IPT charged wireless sensor module for river sedimentation detection." Sensors Applications Symposium (SAS), 2012 IEEE. IEEE, 2012. Zannella, Fillipo, and Angelo Cenedese. "Multi-agent tracking in wireless sensor networks: implementation." WSEAS Int. Conf. on Information Technology and Computer Networks (ITCN). 2012.

Electrochemical sensors applied to pollution monitoring: Measurement error and gas ratio bias - A volcano plume case study

NASA Astrophysics Data System (ADS)

Roberts, T. J.; Saffell, J. R.; Oppenheimer, C.; Lurton, T.

2014-06-01

There is an increasing scientific interest in the use of miniature electrochemical sensors to detect and quantify atmospheric trace gases. This has led to the development of ‘Multi-Gas' systems applied to measurements of both volcanic gas emissions, and urban air pollution. However, such measurements are subject to uncertainties introduced by sensor response time, a critical issue that has received limited attention to date. Here, a detailed analysis of output from an electrochemical SO2 sensor and two H2S sensors (contrasting in their time responses and cross-sensitivities) demonstrates how instrument errors arise under the conditions of rapidly fluctuating (by dilution) gas abundances, leading to scatter and importantly bias in the reported gas ratios. In a case study at Miyakejima volcano (Japan), electrochemical sensors were deployed at both the crater-rim and downwind locations, thereby exposed to rapidly fluctuating and smoothly varying plume gas concentrations, respectively. Discrepancies in the H2S/SO2 gas mixing ratios derived from these measurements are attributed to the sensors' differing time responses to SO2 and H2S under fluctuating plume conditions, with errors magnified by the need to correct for SO2 interference in the H2S readings. Development of a sensor response model that reproduces sensor t90 behaviour (the time required to reach 90% of the final signal following a step change in gas abundance) during calibration enabled this measurement error to be simulated numerically. The sensor response times were characterised as SO2 sensor (t90 ~ 13 s), H2S sensor without interference (t90 ~ 11 s), and H2S sensor with interference (t90 ~ 20 s to H2S and ~ 32 s to SO2). We show that a method involving data integration between periods of episodic plume exposure identifiable in the sensor output yields a less biased H2S/SO2 ratio estimate than that derived from standard analysis approaches. For the Miyakejima crater-rim dataset this method yields highly correlated H2S and SO2 abundances (R2 > 0.99) and the improved crater-rim data analysis combined with downwind measurements yields H2S/SO2 = 0.11 ± 0.01. Our analysis has significant implications for the reliance that can be placed on ‘Multi-Gas'-derived gas ratios, whether for volcanological or other purposes, in the absence of consideration of the complexities of sensor response times.

Complete Tri-Axis Magnetometer Calibration with a Gyro Auxiliary

PubMed Central

Yang, Deng; You, Zheng; Li, Bin; Duan, Wenrui; Yuan, Binwen

2017-01-01

Magnetometers combined with inertial sensors are widely used for orientation estimation, and calibrations are necessary to achieve high accuracy. This paper presents a complete tri-axis magnetometer calibration algorithm with a gyro auxiliary. The magnetic distortions and sensor errors, including the misalignment error between the magnetometer and assembled platform, are compensated after calibration. With the gyro auxiliary, the magnetometer linear interpolation outputs are calculated, and the error parameters are evaluated under linear operations of magnetometer interpolation outputs. The simulation and experiment are performed to illustrate the efficiency of the algorithm. After calibration, the heading errors calculated by magnetometers are reduced to 0.5° (1σ). This calibration algorithm can also be applied to tri-axis accelerometers whose error model is similar to tri-axis magnetometers. PMID:28587115

A Solar Position Sensor Based on Image Vision

PubMed Central

Ruelas, Adolfo; Velázquez, Nicolás; Villa-Angulo, Carlos; Rosales, Pedro; Suastegui, José

2017-01-01

Solar collector technologies operate with better performance when the Sun beam direction is normal to the capturing surface, and for that to happen despite the relative movement of the Sun, solar tracking systems are used, therefore, there are rules and standards that need minimum accuracy for these tracking systems to be used in solar collectors’ evaluation. Obtaining accuracy is not an easy job, hence in this document the design, construction and characterization of a sensor based on a visual system that finds the relative azimuth error and height of the solar surface of interest, is presented. With these characteristics, the sensor can be used as a reference in control systems and their evaluation. The proposed sensor is based on a microcontroller with a real-time clock, inertial measurement sensors, geolocation and a vision sensor, that obtains the angle of incidence from the sunrays’ direction as well as the tilt and sensor position. The sensor’s characterization proved how a measurement of a focus error or a Sun position can be made, with an accuracy of 0.0426° and an uncertainty of 0.986%, which can be modified to reach an accuracy under 0.01°. The validation of this sensor was determined showing the focus error on one of the best commercial solar tracking systems, a Kipp & Zonen SOLYS 2. To conclude, the solar tracking sensor based on a vision system meets the Sun detection requirements and components that meet the accuracy conditions to be used in solar tracking systems and their evaluation or, as a tracking and orientation tool, on photovoltaic installations and solar collectors. PMID:28758935

Clinical measuring system for the form and position errors of circular workpieces using optical fiber sensors

NASA Astrophysics Data System (ADS)

Tan, Jiubin; Qiang, Xifu; Ding, Xuemei

1991-08-01

Optical sensors have two notable advantages in modern precision measurement. One is that they can be used in nondestructive measurement because the sensors need not touch the surfaces of workpieces in measuring. The other one is that they can strongly resist electromagnetic interferences, vibrations, and noises, so they are suitable to be used in machining sites. But the drift of light intensity and the changing of the reflection coefficient at different measuring positions of a workpiece may have great influence on measured results. To solve the problem, a spectroscopic differential characteristic compensating method is put forward. The method can be used effectively not only in compensating the measuring errors resulted from the drift of light intensity but also in eliminating the influence to measured results caused by the changing of the reflection coefficient. Also, the article analyzes the possibility of and the means of separating data errors of a clinical measuring system for form and position errors of circular workpieces.

Accuracy evaluation of 3D lidar data from small UAV

NASA Astrophysics Data System (ADS)

Tulldahl, H. M.; Bissmarck, Fredrik; Larsson, Hâkan; Grönwall, Christina; Tolt, Gustav

2015-10-01

A UAV (Unmanned Aerial Vehicle) with an integrated lidar can be an efficient system for collection of high-resolution and accurate three-dimensional (3D) data. In this paper we evaluate the accuracy of a system consisting of a lidar sensor on a small UAV. High geometric accuracy in the produced point cloud is a fundamental qualification for detection and recognition of objects in a single-flight dataset as well as for change detection using two or several data collections over the same scene. Our work presented here has two purposes: first to relate the point cloud accuracy to data processing parameters and second, to examine the influence on accuracy from the UAV platform parameters. In our work, the accuracy is numerically quantified as local surface smoothness on planar surfaces, and as distance and relative height accuracy using data from a terrestrial laser scanner as reference. The UAV lidar system used is the Velodyne HDL-32E lidar on a multirotor UAV with a total weight of 7 kg. For processing of data into a geographically referenced point cloud, positioning and orientation of the lidar sensor is based on inertial navigation system (INS) data combined with lidar data. The combination of INS and lidar data is achieved in a dynamic calibration process that minimizes the navigation errors in six degrees of freedom, namely the errors of the absolute position (x, y, z) and the orientation (pitch, roll, yaw) measured by GPS/INS. Our results show that low-cost and light-weight MEMS based (microelectromechanical systems) INS equipment with a dynamic calibration process can obtain significantly improved accuracy compared to processing based solely on INS data.

Machine learning enhanced optical distance sensor

NASA Astrophysics Data System (ADS)

Amin, M. Junaid; Riza, N. A.

2018-01-01

Presented for the first time is a machine learning enhanced optical distance sensor. The distance sensor is based on our previously demonstrated distance measurement technique that uses an Electronically Controlled Variable Focus Lens (ECVFL) with a laser source to illuminate a target plane with a controlled optical beam spot. This spot with varying spot sizes is viewed by an off-axis camera and the spot size data is processed to compute the distance. In particular, proposed and demonstrated in this paper is the use of a regularized polynomial regression based supervised machine learning algorithm to enhance the accuracy of the operational sensor. The algorithm uses the acquired features and corresponding labels that are the actual target distance values to train a machine learning model. The optimized training model is trained over a 1000 mm (or 1 m) experimental target distance range. Using the machine learning algorithm produces a training set and testing set distance measurement errors of <0.8 mm and <2.2 mm, respectively. The test measurement error is at least a factor of 4 improvement over our prior sensor demonstration without the use of machine learning. Applications for the proposed sensor include industrial scenario distance sensing where target material specific training models can be generated to realize low <1% measurement error distance measurements.

A simulation of GPS and differential GPS sensors

NASA Technical Reports Server (NTRS)

Rankin, James M.

1993-01-01

The Global Positioning System (GPS) is a revolutionary advance in navigation. Users can determine latitude, longitude, and altitude by receiving range information from at least four satellites. The statistical accuracy of the user's position is directly proportional to the statistical accuracy of the range measurement. Range errors are caused by clock errors, ephemeris errors, atmospheric delays, multipath errors, and receiver noise. Selective Availability, which the military uses to intentionally degrade accuracy for non-authorized users, is a major error source. The proportionality constant relating position errors to range errors is the Dilution of Precision (DOP) which is a function of the satellite geometry. Receivers separated by relatively short distances have the same satellite and atmospheric errors. Differential GPS (DGPS) removes these errors by transmitting pseudorange corrections from a fixed receiver to a mobile receiver. The corrected pseudorange at the moving receiver is now corrupted only by errors from the receiver clock, multipath, and measurement noise. This paper describes a software package that models position errors for various GPS and DGPS systems. The error model is used in the Real-Time Simulator and Cockpit Technology workstation simulations at NASA-LaRC. The GPS/DGPS sensor can simulate enroute navigation, instrument approaches, or on-airport navigation.

Improved Airborne Gravity Results Using New Relative Gravity Sensor Technology

NASA Astrophysics Data System (ADS)

Brady, N.

2013-12-01

Airborne gravity data has contributed greatly to our knowledge of subsurface geophysics particularly in rugged and otherwise inaccessible areas such as Antarctica. Reliable high quality GPS data has renewed interest in improving the accuracy of airborne gravity systems and recent improvements in the electronic control of the sensor have increased the accuracy and ability of the classic Lacoste and Romberg zero length spring gravity meters to operate in turbulent air conditions. Lacoste and Romberg type gravity meters provide increased sensitivity over other relative gravity meters by utilizing a mass attached to a horizontal beam which is balanced by a ';zero length spring'. This type of dynamic gravity sensor is capable of measuring gravity changes on the order of 0.05 milliGals in laboratory conditions but more commonly 0.7 to 1 milliGal in survey use. The sensor may have errors induced by the electronics used to read the beam position as well as noise induced by unwanted accelerations, commonly turbulence, which moves the beam away from its ideal balance position otherwise known as the reading line. The sensor relies on a measuring screw controlled by a computer which attempts to bring the beam back to the reading line position. The beam is also heavily damped so that it does not react to most unwanted high frequency accelerations. However this heavily damped system is slow to react, particularly in turns where there are very high Eotvos effects. New sensor technology utilizes magnetic damping of the beam coupled with an active feedback system which acts to effectively keep the beam locked at the reading line position. The feedback system operates over the entire range of the system so there is now no requirement for a measuring screw. The feedback system operates at very high speed so that even large turbulent events have minimal impact on data quality and very little, if any, survey line data is lost because of large beam displacement errors. Airborne testing along with results from ground based van testing and laboratory results have shown that the new sensor provides more consistent gravity data, as measured by repeated line surveys, as well as preserving the inherent sensitivity of the Lacoste and Romberg zero length spring design. The sensor also provides reliability during survey operation as there is no mechanical counter screw. Results will be presented which show the advantages of the new sensor system over the current technology in both data quality and survey productivity. Applications include high resolution geoid mapping, crustal structure investigations and resource mapping of minerals, oil and gas.

A new methodology for vibration error compensation of optical encoders.

PubMed

Lopez, Jesus; Artes, Mariano

2012-01-01

Optical encoders are sensors based on grating interference patterns. Tolerances inherent to the manufacturing process can induce errors in the position accuracy as the measurement signals stand apart from the ideal conditions. In case the encoder is working under vibrations, the oscillating movement of the scanning head is registered by the encoder system as a displacement, introducing an error into the counter to be added up to graduation, system and installation errors. Behavior improvement can be based on different techniques trying to compensate the error from measurement signals processing. In this work a new "ad hoc" methodology is presented to compensate the error of the encoder when is working under the influence of vibration. The methodology is based on fitting techniques to the Lissajous figure of the deteriorated measurement signals and the use of a look up table, giving as a result a compensation procedure in which a higher accuracy of the sensor is obtained.

Evaluation of Event-Based Algorithms for Optical Flow with Ground-Truth from Inertial Measurement Sensor

PubMed Central

Rueckauer, Bodo; Delbruck, Tobi

2016-01-01

In this study we compare nine optical flow algorithms that locally measure the flow normal to edges according to accuracy and computation cost. In contrast to conventional, frame-based motion flow algorithms, our open-source implementations compute optical flow based on address-events from a neuromorphic Dynamic Vision Sensor (DVS). For this benchmarking we created a dataset of two synthesized and three real samples recorded from a 240 × 180 pixel Dynamic and Active-pixel Vision Sensor (DAVIS). This dataset contains events from the DVS as well as conventional frames to support testing state-of-the-art frame-based methods. We introduce a new source for the ground truth: In the special case that the perceived motion stems solely from a rotation of the vision sensor around its three camera axes, the true optical flow can be estimated using gyro data from the inertial measurement unit integrated with the DAVIS camera. This provides a ground-truth to which we can compare algorithms that measure optical flow by means of motion cues. An analysis of error sources led to the use of a refractory period, more accurate numerical derivatives and a Savitzky-Golay filter to achieve significant improvements in accuracy. Our pure Java implementations of two recently published algorithms reduce computational cost by up to 29% compared to the original implementations. Two of the algorithms introduced in this paper further speed up processing by a factor of 10 compared with the original implementations, at equal or better accuracy. On a desktop PC, they run in real-time on dense natural input recorded by a DAVIS camera. PMID:27199639

A Small Range Six-Axis Accelerometer Designed with High Sensitivity DCB Elastic Element

PubMed Central

Sun, Zhibo; Liu, Jinhao; Yu, Chunzhan; Zheng, Yili

2016-01-01

This paper describes a small range six-axis accelerometer (the measurement range of the sensor is ±g) with high sensitivity DCB (Double Cantilever Beam) elastic element. This sensor is developed based on a parallel mechanism because of the reliability. The accuracy of sensors is affected by its sensitivity characteristics. To improve the sensitivity, a DCB structure is applied as the elastic element. Through dynamic analysis, the dynamic model of the accelerometer is established using the Lagrange equation, and the mass matrix and stiffness matrix are obtained by a partial derivative calculation and a conservative congruence transformation, respectively. By simplifying the structure of the accelerometer, a model of the free vibration is achieved, and the parameters of the sensor are designed based on the model. Through stiffness analysis of the DCB structure, the deflection curve of the beam is calculated. Compared with the result obtained using a finite element analysis simulation in ANSYS Workbench, the coincidence rate of the maximum deflection is 89.0% along the x-axis, 88.3% along the y-axis and 87.5% along the z-axis. Through strain analysis of the DCB elastic element, the sensitivity of the beam is obtained. According to the experimental result, the accuracy of the theoretical analysis is found to be 90.4% along the x-axis, 74.9% along the y-axis and 78.9% along the z-axis. The measurement errors of linear accelerations ax, ay and az in the experiments are 2.6%, 0.6% and 1.31%, respectively. The experiments prove that accelerometer with DCB elastic element performs great sensitive and precision characteristics. PMID:27657089

Assessment of the suitability of Durafet-based sensors for pH measurement in dynamic estuarine environments

NASA Astrophysics Data System (ADS)

Gonski, Stephen F.; Cai, Wei-Jun; Ullman, William J.; Joesoef, Andrew; Main, Christopher R.; Pettay, D. Tye; Martz, Todd R.

2018-01-01

The suitability of the Honeywell Durafet to the measurement of pH in productive, high-fouling, and highly-turbid estuarine environments was investigated at the confluence of the Murderkill Estuary and Delaware Bay (Delaware, USA). Three different flow configurations of the SeapHOx sensor equipped with a Honeywell Durafet and its integrated internal (Ag/AgCl reference electrode containing a 4.5 M KCl gel liquid junction) and external (solid-state chloride ion selective electrode, Cl-ISE) reference electrodes were deployed for four periods between April 2015 and September 2016. In this environment, the Honeywell Durafet proved capable of making high-resolution and high-frequency pH measurements on the total scale between pH 6.8 and 8.4. Natural pH fluctuations of >1 pH unit were routinely captured over a range of timescales. The sensor pH collected between May and August 2016 using the most refined SeapHOx configuration exhibited good agreement with multiple sets of independently measured reference pH values. When deployed in conjunction with rigorous discrete sampling and calibration schemes, the sensor pH had a root-mean squared error ranging between 0.011 and 0.036 pH units across a wide range of salinity relative to both pHT calculated from measured dissolved inorganic carbon and total alkalinity and pHNBS measured with a glass electrode corrected to pHT at in situ conditions. The present work demonstrates the viability of the Honeywell Durafet to the measurement of pH to within the weather-level precision defined by the Global Ocean Acidification Observing Network (GOA-ON, ≤ 0.02 pH units) as a part of future estuarine CO2 chemistry studies undertaken in dynamic environments.

Magnetic-field sensing with quantum error detection under the effect of energy relaxation

NASA Astrophysics Data System (ADS)

Matsuzaki, Yuichiro; Benjamin, Simon

2017-03-01

A solid state spin is an attractive system with which to realize an ultrasensitive magnetic field sensor. A spin superposition state will acquire a phase induced by the target field, and we can estimate the field strength from this phase. Recent studies have aimed at improving sensitivity through the use of quantum error correction (QEC) to detect and correct any bit-flip errors that may occur during the sensing period. Here we investigate the performance of a two-qubit sensor employing QEC and under the effect of energy relaxation. Surprisingly, we find that the standard QEC technique to detect and recover from an error does not improve the sensitivity compared with the single-qubit sensors. This is a consequence of the fact that the energy relaxation induces both a phase-flip and a bit-flip noise where the former noise cannot be distinguished from the relative phase induced from the target fields. However, we have found that we can improve the sensitivity if we adopt postselection to discard the state when error is detected. Even when quantum error detection is moderately noisy, and allowing for the cost of the postselection technique, we find that this two-qubit system shows an advantage in sensing over a single qubit in the same conditions.

On the Statistical Errors of RADAR Location Sensor Networks with Built-In Wi-Fi Gaussian Linear Fingerprints

PubMed Central

Zhou, Mu; Xu, Yu Bin; Ma, Lin; Tian, Shuo

2012-01-01

The expected errors of RADAR sensor networks with linear probabilistic location fingerprints inside buildings with varying Wi-Fi Gaussian strength are discussed. As far as we know, the statistical errors of equal and unequal-weighted RADAR networks have been suggested as a better way to evaluate the behavior of different system parameters and the deployment of reference points (RPs). However, up to now, there is still not enough related work on the relations between the statistical errors, system parameters, number and interval of the RPs, let alone calculating the correlated analytical expressions of concern. Therefore, in response to this compelling problem, under a simple linear distribution model, much attention will be paid to the mathematical relations of the linear expected errors, number of neighbors, number and interval of RPs, parameters in logarithmic attenuation model and variations of radio signal strength (RSS) at the test point (TP) with the purpose of constructing more practical and reliable RADAR location sensor networks (RLSNs) and also guaranteeing the accuracy requirements for the location based services in future ubiquitous context-awareness environments. Moreover, the numerical results and some real experimental evaluations of the error theories addressed in this paper will also be presented for our future extended analysis. PMID:22737027

On the statistical errors of RADAR location sensor networks with built-in Wi-Fi Gaussian linear fingerprints.

PubMed

Zhou, Mu; Xu, Yu Bin; Ma, Lin; Tian, Shuo

2012-01-01

The expected errors of RADAR sensor networks with linear probabilistic location fingerprints inside buildings with varying Wi-Fi Gaussian strength are discussed. As far as we know, the statistical errors of equal and unequal-weighted RADAR networks have been suggested as a better way to evaluate the behavior of different system parameters and the deployment of reference points (RPs). However, up to now, there is still not enough related work on the relations between the statistical errors, system parameters, number and interval of the RPs, let alone calculating the correlated analytical expressions of concern. Therefore, in response to this compelling problem, under a simple linear distribution model, much attention will be paid to the mathematical relations of the linear expected errors, number of neighbors, number and interval of RPs, parameters in logarithmic attenuation model and variations of radio signal strength (RSS) at the test point (TP) with the purpose of constructing more practical and reliable RADAR location sensor networks (RLSNs) and also guaranteeing the accuracy requirements for the location based services in future ubiquitous context-awareness environments. Moreover, the numerical results and some real experimental evaluations of the error theories addressed in this paper will also be presented for our future extended analysis.

Assessment and Calibration of Ultrasonic Measurement Errors in Estimating Weathering Index of Stone Cultural Heritage

NASA Astrophysics Data System (ADS)

Lee, Y.; Keehm, Y.

2011-12-01

Estimating the degree of weathering in stone cultural heritage, such as pagodas and statues is very important to plan conservation and restoration. The ultrasonic measurement is one of commonly-used techniques to evaluate weathering index of stone cultual properties, since it is easy to use and non-destructive. Typically we use a portable ultrasonic device, PUNDIT with exponential sensors. However, there are many factors to cause errors in measurements such as operators, sensor layouts or measurement directions. In this study, we carried out variety of measurements with different operators (male and female), different sensor layouts (direct and indirect), and sensor directions (anisotropy). For operators bias, we found that there were not significant differences by the operator's sex, while the pressure an operator exerts can create larger error in measurements. Calibrating with a standard sample for each operator is very essential in this case. For the sensor layout, we found that the indirect measurement (commonly used for cultural properties, since the direct measurement is difficult in most cases) gives lower velocity than the real one. We found that the correction coefficient is slightly different for different types of rocks: 1.50 for granite and sandstone and 1.46 for marble. From the sensor directions, we found that many rocks have slight anisotropy in their ultrasonic velocity measurement, though they are considered isotropic in macroscopic scale. Thus averaging four different directional measurement (0°, 45°, 90°, 135°) gives much less errors in measurements (the variance is 2-3 times smaller). In conclusion, we reported the error in ultrasonic meaurement of stone cultural properties by various sources quantitatively and suggested the amount of correction and procedures to calibrate the measurements. Acknowledgement: This study, which forms a part of the project, has been achieved with the support of national R&D project, which has been hosted by National Research Institute of Cultural Heritage of Cultural Heritage Administration(No. NRICH-1107-B01F).

An Effective Terrain Aided Navigation for Low-Cost Autonomous Underwater Vehicles.

PubMed

Zhou, Ling; Cheng, Xianghong; Zhu, Yixian; Dai, Chenxi; Fu, Jinbo

2017-03-25

Terrain-aided navigation is a potentially powerful solution for obtaining submerged position fixes for autonomous underwater vehicles. The application of terrain-aided navigation with high-accuracy inertial navigation systems has demonstrated meter-level navigation accuracy in sea trials. However, available sensors may be limited depending on the type of the mission. Such limitations, especially for low-grade navigation sensors, not only degrade the accuracy of traditional navigation systems, but further impact the ability to successfully employ terrain-aided navigation. To address this problem, a tightly-coupled navigation is presented to successfully estimate the critical sensor errors by incorporating raw sensor data directly into an augmented navigation system. Furthermore, three-dimensional distance errors are calculated, providing measurement updates through the particle filter for absolute and bounded position error. The development of the terrain aided navigation system is elaborated for a vehicle equipped with a non-inertial-grade strapdown inertial navigation system, a 4-beam Doppler Velocity Log range sensor and a sonar altimeter. Using experimental data for navigation performance evaluation in areas with different terrain characteristics, the experiment results further show that the proposed method can be successfully applied to the low-cost AUVs and significantly improves navigation performance.

An Effective Terrain Aided Navigation for Low-Cost Autonomous Underwater Vehicles

PubMed Central

Zhou, Ling; Cheng, Xianghong; Zhu, Yixian; Dai, Chenxi; Fu, Jinbo

2017-01-01

Terrain-aided navigation is a potentially powerful solution for obtaining submerged position fixes for autonomous underwater vehicles. The application of terrain-aided navigation with high-accuracy inertial navigation systems has demonstrated meter-level navigation accuracy in sea trials. However, available sensors may be limited depending on the type of the mission. Such limitations, especially for low-grade navigation sensors, not only degrade the accuracy of traditional navigation systems, but further impact the ability to successfully employ terrain-aided navigation. To address this problem, a tightly-coupled navigation is presented to successfully estimate the critical sensor errors by incorporating raw sensor data directly into an augmented navigation system. Furthermore, three-dimensional distance errors are calculated, providing measurement updates through the particle filter for absolute and bounded position error. The development of the terrain aided navigation system is elaborated for a vehicle equipped with a non-inertial-grade strapdown inertial navigation system, a 4-beam Doppler Velocity Log range sensor and a sonar altimeter. Using experimental data for navigation performance evaluation in areas with different terrain characteristics, the experiment results further show that the proposed method can be successfully applied to the low-cost AUVs and significantly improves navigation performance. PMID:28346346

Contact Versus Non-Contact Measurement of a Helicopter Main Rotor Composite Blade

DOE Office of Scientific and Technical Information (OSTI.GOV)

Luczak, Marcin; Dziedziech, Kajetan; Peeters, Bart

2010-05-28

The dynamic characterization of lightweight structures is particularly complex as the impact of the weight of sensors and instrumentation (cables, mounting of exciters...) can distort the results. Varying mass loading or constraint effects between partial measurements may determine several errors on the final conclusions. Frequency shifts can lead to erroneous interpretations of the dynamics parameters. Typically these errors remain limited to a few percent. Inconsistent data sets however can result in major processing errors, with all related consequences towards applications based on the consistency assumption, such as global modal parameter identification, model-based damage detection and FRF-based matrix inversion in substructuring,more » load identification and transfer path analysis [1]. This paper addresses the subject of accuracy in the context of the measurement of the dynamic properties of a particular lightweight structure. It presents a comprehensive comparative study between the use of accelerometer, laser vibrometer (scanning LDV) and PU-probe (acoustic particle velocity and pressure) measurements to measure the structural responses, with as final aim the comparison of modal model quality assessment. The object of the investigation is a composite material blade from the main rotor of a helicopter. The presented results are part of an extensive test campaign performed with application of SIMO, MIMO, random and harmonic excitation, and the use of the mentioned contact and non-contact measurement techniques. The advantages and disadvantages of the applied instrumentation are discussed. Presented are real-life measurement problems related to the different set up conditions. Finally an analysis of estimated models is made in view of assessing the applicability of the various measurement approaches for successful fault detection based on modal parameters observation as well as in uncertain non-deterministic numerical model updating.« less

Contact Versus Non-Contact Measurement of a Helicopter Main Rotor Composite Blade

NASA Astrophysics Data System (ADS)

Luczak, Marcin; Dziedziech, Kajetan; Vivolo, Marianna; Desmet, Wim; Peeters, Bart; Van der Auweraer, Herman

2010-05-01

The dynamic characterization of lightweight structures is particularly complex as the impact of the weight of sensors and instrumentation (cables, mounting of exciters…) can distort the results. Varying mass loading or constraint effects between partial measurements may determine several errors on the final conclusions. Frequency shifts can lead to erroneous interpretations of the dynamics parameters. Typically these errors remain limited to a few percent. Inconsistent data sets however can result in major processing errors, with all related consequences towards applications based on the consistency assumption, such as global modal parameter identification, model-based damage detection and FRF-based matrix inversion in substructuring, load identification and transfer path analysis [1]. This paper addresses the subject of accuracy in the context of the measurement of the dynamic properties of a particular lightweight structure. It presents a comprehensive comparative study between the use of accelerometer, laser vibrometer (scanning LDV) and PU-probe (acoustic particle velocity and pressure) measurements to measure the structural responses, with as final aim the comparison of modal model quality assessment. The object of the investigation is a composite material blade from the main rotor of a helicopter. The presented results are part of an extensive test campaign performed with application of SIMO, MIMO, random and harmonic excitation, and the use of the mentioned contact and non-contact measurement techniques. The advantages and disadvantages of the applied instrumentation are discussed. Presented are real-life measurement problems related to the different set up conditions. Finally an analysis of estimated models is made in view of assessing the applicability of the various measurement approaches for successful fault detection based on modal parameters observation as well as in uncertain non-deterministic numerical model updating.