Shape Control of Plates with Piezo Actuators and Collocated Position/Rate Sensors

NASA Technical Reports Server (NTRS)

Balakrishnan, A. V.

1994-01-01

This paper treats the control problem of shaping the surface deformation of a circular plate using embedded piezo-electric actuator and collocated rate sensors. An explicit Linear Quadratic Gaussian (LQG) optimizer stability augmentation compensator is derived as well as the optimal feed-forward control. Corresponding performance evaluation formulas are also derived.

Improving Kinematic Accuracy of Soft Wearable Data Gloves by Optimizing Sensor Locations

PubMed Central

Kim, Dong Hyun; Lee, Sang Wook; Park, Hyung-Soon

2016-01-01

Bending sensors enable compact, wearable designs when used for measuring hand configurations in data gloves. While existing data gloves can accurately measure angular displacement of the finger and distal thumb joints, accurate measurement of thumb carpometacarpal (CMC) joint movements remains challenging due to crosstalk between the multi-sensor outputs required to measure the degrees of freedom (DOF). To properly measure CMC-joint configurations, sensor locations that minimize sensor crosstalk must be identified. This paper presents a novel approach to identifying optimal sensor locations. Three-dimensional hand surface data from ten subjects was collected in multiple thumb postures with varied CMC-joint flexion and abduction angles. For each posture, scanned CMC-joint contours were used to estimate CMC-joint flexion and abduction angles by varying the positions and orientations of two bending sensors. Optimal sensor locations were estimated by the least squares method, which minimized the difference between the true CMC-joint angles and the joint angle estimates. Finally, the resultant optimal sensor locations were experimentally validated. Placing sensors at the optimal locations, CMC-joint angle measurement accuracies improved (flexion, 2.8° ± 1.9°; abduction, 1.9° ± 1.2°). The proposed method for improving the accuracy of the sensing system can be extended to other types of soft wearable measurement devices. PMID:27240364

Feed-Forward Neural Network Soft-Sensor Modeling of Flotation Process Based on Particle Swarm Optimization and Gravitational Search Algorithm

PubMed Central

Wang, Jie-Sheng; Han, Shuang

2015-01-01

For predicting the key technology indicators (concentrate grade and tailings recovery rate) of flotation process, a feed-forward neural network (FNN) based soft-sensor model optimized by the hybrid algorithm combining particle swarm optimization (PSO) algorithm and gravitational search algorithm (GSA) is proposed. Although GSA has better optimization capability, it has slow convergence velocity and is easy to fall into local optimum. So in this paper, the velocity vector and position vector of GSA are adjusted by PSO algorithm in order to improve its convergence speed and prediction accuracy. Finally, the proposed hybrid algorithm is adopted to optimize the parameters of FNN soft-sensor model. Simulation results show that the model has better generalization and prediction accuracy for the concentrate grade and tailings recovery rate to meet the online soft-sensor requirements of the real-time control in the flotation process. PMID:26583034

Development and testing of a magnetic position sensor system for automotive and avionics applications

NASA Astrophysics Data System (ADS)

Jacobs, Bryan C.; Nelson, Carl V.

2001-08-01

A magnetic sensor system has been developed to measure the 3-D location and orientation of a rigid body relative to an array of magnetic dipole transmitters. A generalized solution to the measurement problem has been formulated, allowing the transmitter and receiver parameters (position, orientation, number, etc.) to be optimized for various applications. Additionally, the method of images has been used to mitigate the impact of metallic materials in close proximity to the sensor. The resulting system allows precise tracking of high-speed motion in confined metal environments. The sensor system was recently configured and tested as an abdomen displacement sensor for an automobile crash-test dummy. The test results indicate a positional accuracy of approximately 1 mm rms during 20 m/s motions. The dynamic test results also confirmed earlier covariance model predictions, which were used to optimize the sensor geometry. A covariance analysis was performed to evaluate the applicability of this magnetic position system for tracking a pilot's head motion inside an aircraft cockpit. Realistic design parameters indicate that a robust tracking system, consisting of lightweight pickup coils mounted on a pilot's helmet, and an array of transmitter coils distributed throughout a cockpit, is feasible. Recent test and covariance results are presented.

Distributed transition-edge sensors for linearized position response in a phonon-mediated X-ray imaging spectrometer

NASA Astrophysics Data System (ADS)

Cabrera, Blas; Brink, Paul L.; Leman, Steven W.; Castle, Joseph P.; Tomada, Astrid; Young, Betty A.; Martínez-Galarce, Dennis S.; Stern, Robert A.; Deiker, Steve; Irwin, Kent D.

2004-03-01

For future solar X-ray satellite missions, we are developing a phonon-mediated macro-pixel composed of a Ge crystal absorber with four superconducting transition-edge sensors (TES) distributed on the backside. The X-rays are absorbed on the opposite side and the energy is converted into phonons, which are absorbed into the four TES sensors. By connecting together parallel elements into four channels, fractional total energy absorbed between two of the sensors provides x-position information and the other two provide y-position information. We determine the optimal distribution for the TES sub-elements to obtain linear position information while minimizing the degradation of energy resolution.

Optimal Design of the Absolute Positioning Sensor for a High-Speed Maglev Train and Research on Its Fault Diagnosis

PubMed Central

Zhang, Dapeng; Long, Zhiqiang; Xue, Song; Zhang, Junge

2012-01-01

This paper studies an absolute positioning sensor for a high-speed maglev train and its fault diagnosis method. The absolute positioning sensor is an important sensor for the high-speed maglev train to accomplish its synchronous traction. It is used to calibrate the error of the relative positioning sensor which is used to provide the magnetic phase signal. On the basis of the analysis for the principle of the absolute positioning sensor, the paper describes the design of the sending and receiving coils and realizes the hardware and the software for the sensor. In order to enhance the reliability of the sensor, a support vector machine is used to recognize the fault characters, and the signal flow method is used to locate the faulty parts. The diagnosis information not only can be sent to an upper center control computer to evaluate the reliability of the sensors, but also can realize on-line diagnosis for debugging and the quick detection when the maglev train is off-line. The absolute positioning sensor we study has been used in the actual project. PMID:23112619

An Enhanced PSO-Based Clustering Energy Optimization Algorithm for Wireless Sensor Network.

PubMed

Vimalarani, C; Subramanian, R; Sivanandam, S N

2016-01-01

Wireless Sensor Network (WSN) is a network which formed with a maximum number of sensor nodes which are positioned in an application environment to monitor the physical entities in a target area, for example, temperature monitoring environment, water level, monitoring pressure, and health care, and various military applications. Mostly sensor nodes are equipped with self-supported battery power through which they can perform adequate operations and communication among neighboring nodes. Maximizing the lifetime of the Wireless Sensor networks, energy conservation measures are essential for improving the performance of WSNs. This paper proposes an Enhanced PSO-Based Clustering Energy Optimization (EPSO-CEO) algorithm for Wireless Sensor Network in which clustering and clustering head selection are done by using Particle Swarm Optimization (PSO) algorithm with respect to minimizing the power consumption in WSN. The performance metrics are evaluated and results are compared with competitive clustering algorithm to validate the reduction in energy consumption.

Node Scheduling Strategies for Achieving Full-View Area Coverage in Camera Sensor Networks.

PubMed

Wu, Peng-Fei; Xiao, Fu; Sha, Chao; Huang, Hai-Ping; Wang, Ru-Chuan; Xiong, Nai-Xue

2017-06-06

Unlike conventional scalar sensors, camera sensors at different positions can capture a variety of views of an object. Based on this intrinsic property, a novel model called full-view coverage was proposed. We study the problem that how to select the minimum number of sensors to guarantee the full-view coverage for the given region of interest (ROI). To tackle this issue, we derive the constraint condition of the sensor positions for full-view neighborhood coverage with the minimum number of nodes around the point. Next, we prove that the full-view area coverage can be approximately guaranteed, as long as the regular hexagons decided by the virtual grid are seamlessly stitched. Then we present two solutions for camera sensor networks in two different deployment strategies. By computing the theoretically optimal length of the virtual grids, we put forward the deployment pattern algorithm (DPA) in the deterministic implementation. To reduce the redundancy in random deployment, we come up with a local neighboring-optimal selection algorithm (LNSA) for achieving the full-view coverage. Finally, extensive simulation results show the feasibility of our proposed solutions.

Node Scheduling Strategies for Achieving Full-View Area Coverage in Camera Sensor Networks

PubMed Central

Wu, Peng-Fei; Xiao, Fu; Sha, Chao; Huang, Hai-Ping; Wang, Ru-Chuan; Xiong, Nai-Xue

2017-01-01

Unlike conventional scalar sensors, camera sensors at different positions can capture a variety of views of an object. Based on this intrinsic property, a novel model called full-view coverage was proposed. We study the problem that how to select the minimum number of sensors to guarantee the full-view coverage for the given region of interest (ROI). To tackle this issue, we derive the constraint condition of the sensor positions for full-view neighborhood coverage with the minimum number of nodes around the point. Next, we prove that the full-view area coverage can be approximately guaranteed, as long as the regular hexagons decided by the virtual grid are seamlessly stitched. Then we present two solutions for camera sensor networks in two different deployment strategies. By computing the theoretically optimal length of the virtual grids, we put forward the deployment pattern algorithm (DPA) in the deterministic implementation. To reduce the redundancy in random deployment, we come up with a local neighboring-optimal selection algorithm (LNSA) for achieving the full-view coverage. Finally, extensive simulation results show the feasibility of our proposed solutions. PMID:28587304

Study on the Application of an Ultra-High-Frequency Fractal Antenna to Partial Discharge Detection in Switchgears

PubMed Central

Yao, Chenguo; Chen, Pan; Huang, Congjian; Chen, Yu; Qiao, Panpan

2013-01-01

The ultra-high-frequency (UHF) method is used to analyze the insulation condition of electric equipment by detecting the UHF electromagnetic (EM) waves excited by partial discharge (PD). As part of the UHF detection system, the UHF sensor determines the detection system performance in signal extraction and recognition. In this paper, a UHF antenna sensor with the fractal structure for PD detection in switchgears was designed by means of modeling, simulation and optimization. This sensor, with a flat-plate structure, had two resonance frequencies of 583 MHz and 732 MHz. In the laboratory, four kinds of insulation defect models were positioned in the testing switchgear for typical PD tests. The results show that the sensor could reproduce the electromagnetic waves well. Furthermore, to optimize the installation position of the inner sensor for achieving best detection performance, the precise simulation model of switchgear was developed to study the propagation characteristics of UHF signals in switchgear by finite-difference time-domain (FDTD) method. According to the results of simulation and verification test, the sensor should be positioned at the right side of bottom plate in the front cabinet. This research established the foundation for the further study on the application of UHF technique in switchgear PD online detection. PMID:24351641

Physical limitations in sensors for a drag-free deep space probe

NASA Technical Reports Server (NTRS)

Juillerat, R.

1971-01-01

The inner perturbing forces acting on sensors were analyzed, taking into account the technological limitations imposed on the proof mass position pickup and proof mass acquisition system. The resulting perturbing accelerations are evaluated as a function of the drag-free sensor parameters. Perturbations included gravitational attraction, electrical action, magnetic action, pressure effects, radiation effects, and action of the position pickup. These data can be used to study the laws of guidance, providing an optimization of the space probe as a whole.

A novel capacitive absolute positioning sensor based on time grating with nanometer resolution

NASA Astrophysics Data System (ADS)

Pu, Hongji; Liu, Hongzhong; Liu, Xiaokang; Peng, Kai; Yu, Zhicheng

2018-05-01

The present work proposes a novel capacitive absolute positioning sensor based on time grating. The sensor includes a fine incremental-displacement measurement component combined with a coarse absolute-position measurement component to obtain high-resolution absolute positioning measurements. A single row type sensor was proposed to achieve fine displacement measurement, which combines the two electrode rows of a previously proposed double-row type capacitive displacement sensor based on time grating into a single row. To achieve absolute positioning measurement, the coarse measurement component is designed as a single-row type displacement sensor employing a single spatial period over the entire measurement range. In addition, this component employs a rectangular induction electrode and four groups of orthogonal discrete excitation electrodes with half-sinusoidal envelope shapes, which were formed by alternately extending the rectangular electrodes of the fine measurement component. The fine and coarse measurement components are tightly integrated to form a compact absolute positioning sensor. A prototype sensor was manufactured using printed circuit board technology for testing and optimization of the design in conjunction with simulations. Experimental results show that the prototype sensor achieves a ±300 nm measurement accuracy with a 1 nm resolution over a displacement range of 200 mm when employing error compensation. The proposed sensor is an excellent alternative to presently available long-range absolute nanometrology sensors owing to its low cost, simple structure, and ease of manufacturing.

Platform-dependent optimization considerations for mHealth applications

NASA Astrophysics Data System (ADS)

Kaghyan, Sahak; Akopian, David; Sarukhanyan, Hakob

2015-03-01

Modern mobile devices contain integrated sensors that enable multitude of applications in such fields as mobile health (mHealth), entertainment, sports, etc. Human physical activity monitoring is one of such the emerging applications. There exists a range of challenges that relate to activity monitoring tasks, and, particularly, exploiting optimal solutions and architectures for respective mobile software application development. This work addresses mobile computations related to integrated inertial sensors for activity monitoring, such as accelerometers, gyroscopes, integrated global positioning system (GPS) and WLAN-based positioning, that can be used for activity monitoring. Some of the aspects will be discussed in this paper. Each of the sensing data sources has its own characteristics such as specific data formats, data rates, signal acquisition durations etc., and these specifications affect energy consumption. Energy consumption significantly varies as sensor data acquisition is followed by data analysis including various transformations and signal processing algorithms. This paper will address several aspects of more optimal activity monitoring implementations exploiting state-of-the-art capabilities of modern platforms.

Voltage sensor and dielectric material

DOEpatents

Yakymyshyn, Christopher Paul; Yakymyshyn, Pamela Jane; Brubaker, Michael Allen

2006-10-17

A voltage sensor is described that consists of an arrangement of impedance elements. The sensor is optimized to provide an output ratio that is substantially immune to changes in voltage, temperature variations or aging. Also disclosed is a material with a large and stable dielectric constant. The dielectric constant can be tailored to vary with position or direction in the material.

Real-time identification of indoor pollutant source positions based on neural network locator of contaminant sources and optimized sensor networks.

PubMed

Vukovic, Vladimir; Tabares-Velasco, Paulo Cesar; Srebric, Jelena

2010-09-01

A growing interest in security and occupant exposure to contaminants revealed a need for fast and reliable identification of contaminant sources during incidental situations. To determine potential contaminant source positions in outdoor environments, current state-of-the-art modeling methods use computational fluid dynamic simulations on parallel processors. In indoor environments, current tools match accidental contaminant distributions with cases from precomputed databases of possible concentration distributions. These methods require intensive computations in pre- and postprocessing. On the other hand, neural networks emerged as a tool for rapid concentration forecasting of outdoor environmental contaminants such as nitrogen oxides or sulfur dioxide. All of these modeling methods depend on the type of sensors used for real-time measurements of contaminant concentrations. A review of the existing sensor technologies revealed that no perfect sensor exists, but intensity of work in this area provides promising results in the near future. The main goal of the presented research study was to extend neural network modeling from the outdoor to the indoor identification of source positions, making this technology applicable to building indoor environments. The developed neural network Locator of Contaminant Sources was also used to optimize number and allocation of contaminant concentration sensors for real-time prediction of indoor contaminant source positions. Such prediction should take place within seconds after receiving real-time contaminant concentration sensor data. For the purpose of neural network training, a multizone program provided distributions of contaminant concentrations for known source positions throughout a test building. Trained networks had an output indicating contaminant source positions based on measured concentrations in different building zones. A validation case based on a real building layout and experimental data demonstrated the ability of this method to identify contaminant source positions. Future research intentions are focused on integration with real sensor networks and model improvements for much more complicated contamination scenarios.

Upconverting nanoparticles for optimizing scintillator based detection systems

DOEpatents

Kross, Brian; McKisson, John E; McKisson, John; Weisenberger, Andrew; Xi, Wenze; Zom, Carl

2013-09-17

An upconverting device for a scintillation detection system is provided. The detection system comprises a scintillator material, a sensor, a light transmission path between the scintillator material and the sensor, and a plurality of upconverting nanoparticles particles positioned in the light transmission path.

Complex Human Activity Recognition Using Smartphone and Wrist-Worn Motion Sensors.

PubMed

Shoaib, Muhammad; Bosch, Stephan; Incel, Ozlem Durmaz; Scholten, Hans; Havinga, Paul J M

2016-03-24

The position of on-body motion sensors plays an important role in human activity recognition. Most often, mobile phone sensors at the trouser pocket or an equivalent position are used for this purpose. However, this position is not suitable for recognizing activities that involve hand gestures, such as smoking, eating, drinking coffee and giving a talk. To recognize such activities, wrist-worn motion sensors are used. However, these two positions are mainly used in isolation. To use richer context information, we evaluate three motion sensors (accelerometer, gyroscope and linear acceleration sensor) at both wrist and pocket positions. Using three classifiers, we show that the combination of these two positions outperforms the wrist position alone, mainly at smaller segmentation windows. Another problem is that less-repetitive activities, such as smoking, eating, giving a talk and drinking coffee, cannot be recognized easily at smaller segmentation windows unlike repetitive activities, like walking, jogging and biking. For this purpose, we evaluate the effect of seven window sizes (2-30 s) on thirteen activities and show how increasing window size affects these various activities in different ways. We also propose various optimizations to further improve the recognition of these activities. For reproducibility, we make our dataset publicly available.

Split-Ring Resonator Sensor Penetration Depth Assessment Using In Vivo Microwave Reflectivity and Ultrasound Measurements for Lower Extremity Trauma Rehabilitation.

PubMed

Shah, Syaiful Redzwan Mohd; Velander, Jacob; Mathur, Parul; Perez, Mauricio D; Asan, Noor Badariah; Kurup, Dhanesh G; Blokhuis, Taco J; Augustine, Robin

2018-02-21

In recent research, microwave sensors have been used to follow up the recovery of lower extremity trauma patients. This is done mainly by monitoring the changes of dielectric properties of lower limb tissues such as skin, fat, muscle, and bone. As part of the characterization of the microwave sensor, it is crucial to assess the signal penetration in in vivo tissues. This work presents a new approach for investigating the penetration depth of planar microwave sensors based on the Split-Ring Resonator in the in vivo context of the femoral area. This approach is based on the optimization of a 3D simulation model using the platform of CST Microwave Studio and consisting of a sensor of the considered type and a multilayered material representing the femoral area. The geometry of the layered material is built based on information from ultrasound images and includes mainly the thicknesses of skin, fat, and muscle tissues. The optimization target is the measured S 11 parameters at the sensor connector and the fitting parameters are the permittivity of each layer of the material. Four positions in the femoral area (two at distal and two at thigh) in four volunteers are considered for the in vivo study. The penetration depths are finally calculated with the help of the electric field distribution in simulations of the optimized model for each one of the 16 considered positions. The numerical results show that positions at the thigh contribute the highest penetration values of up to 17.5 mm. This finding has a high significance in planning in vitro penetration depth measurements and other tests that are going to be performed in the future.

Transparent silicon strip sensors for the optical alignment of particle detector systems

NASA Astrophysics Data System (ADS)

Blum, W.; Kroha, H.; Widmann, P.

1996-02-01

Modern large-area precision tracking detectors require increasing accuracy for the alignment of their components. A novel multi-point laser alignment system has been developed for such applications. The position of detector components with respect to reference laser beams is monitored by semi-transparent optical position sensors which work on the principle of silicon strip photodiodes. Two types of custom designed transparent strip sensors, based on crystalline and on amorphous silicon as active material, have been studied. The sensors are optimized for the typical diameters of collimated laser beams of 3-5 mm over distances of 10-20 m. They provide very high position resolution, on the order of 1 μm, uniformly over a wide measurement range of several centimeters. The preparation of the sensor surfaces requires special attention in order to achieve high light transmittance and minimum distortion of the traversing laser beams. At selected wavelengths, produced by laser diodes, transmission rates above 90% have been achieved. This allows to position more than 30 sensors along one laser beam. The sensors will be equipped with custom designed integrated readout electronics.

Time Series Analysis for Spatial Node Selection in Environment Monitoring Sensor Networks

PubMed Central

Bhandari, Siddhartha; Jurdak, Raja; Kusy, Branislav

2017-01-01

Wireless sensor networks are widely used in environmental monitoring. The number of sensor nodes to be deployed will vary depending on the desired spatio-temporal resolution. Selecting an optimal number, position and sampling rate for an array of sensor nodes in environmental monitoring is a challenging question. Most of the current solutions are either theoretical or simulation-based where the problems are tackled using random field theory, computational geometry or computer simulations, limiting their specificity to a given sensor deployment. Using an empirical dataset from a mine rehabilitation monitoring sensor network, this work proposes a data-driven approach where co-integrated time series analysis is used to select the number of sensors from a short-term deployment of a larger set of potential node positions. Analyses conducted on temperature time series show 75% of sensors are co-integrated. Using only 25% of the original nodes can generate a complete dataset within a 0.5 °C average error bound. Our data-driven approach to sensor position selection is applicable for spatiotemporal monitoring of spatially correlated environmental parameters to minimize deployment cost without compromising data resolution. PMID:29271880

A sensor network based virtual beam-like structure method for fault diagnosis and monitoring of complex structures with Improved Bacterial Optimization

NASA Astrophysics Data System (ADS)

Wang, H.; Jing, X. J.

2017-02-01

This paper proposes a novel method for the fault diagnosis of complex structures based on an optimized virtual beam-like structure approach. A complex structure can be regarded as a combination of numerous virtual beam-like structures considering the vibration transmission path from vibration sources to each sensor. The structural 'virtual beam' consists of a sensor chain automatically obtained by an Improved Bacterial Optimization Algorithm (IBOA). The biologically inspired optimization method (i.e. IBOA) is proposed for solving the discrete optimization problem associated with the selection of the optimal virtual beam for fault diagnosis. This novel virtual beam-like-structure approach needs less or little prior knowledge. Neither does it require stationary response data, nor is it confined to a specific structure design. It is easy to implement within a sensor network attached to the monitored structure. The proposed fault diagnosis method has been tested on the detection of loosening screws located at varying positions in a real satellite-like model. Compared with empirical methods, the proposed virtual beam-like structure method has proved to be very effective and more reliable for fault localization.

Global Radius of Curvature Estimation and Control System for Segmented Mirrors

NASA Technical Reports Server (NTRS)

Rakoczy, John M. (Inventor)

2006-01-01

An apparatus controls positions of plural mirror segments in a segmented mirror with an edge sensor system and a controller. Current mirror segment edge sensor measurements and edge sensor reference measurements are compared with calculated edge sensor bias measurements representing a global radius of curvature. Accumulated prior actuator commands output from an edge sensor control unit are combined with an estimator matrix to form the edge sensor bias measurements. An optimal control matrix unit then accumulates the plurality of edge sensor error signals calculated by the summation unit and outputs the corresponding plurality of actuator commands. The plural mirror actuators respond to the actuator commands by moving respective positions of the mixor segments. A predetermined number of boundary conditions, corresponding to a plurality of hexagonal mirror locations, are removed to afford mathematical matrix calculation.

Heterodyne laser Doppler distance sensor with phase coding measuring stationary as well as laterally and axially moving objects

NASA Astrophysics Data System (ADS)

Pfister, T.; Günther, P.; Nöthen, M.; Czarske, J.

2010-02-01

Both in production engineering and process control, multidirectional displacements, deformations and vibrations of moving or rotating components have to be measured dynamically, contactlessly and with high precision. Optical sensors would be predestined for this task, but their measurement rate is often fundamentally limited. Furthermore, almost all conventional sensors measure only one measurand, i.e. either out-of-plane or in-plane distance or velocity. To solve this problem, we present a novel phase coded heterodyne laser Doppler distance sensor (PH-LDDS), which is able to determine out-of-plane (axial) position and in-plane (lateral) velocity of rough solid-state objects simultaneously and independently with a single sensor. Due to the applied heterodyne technique, stationary or purely axially moving objects can also be measured. In addition, it is shown theoretically as well as experimentally that this sensor offers concurrently high temporal resolution and high position resolution since its position uncertainty is in principle independent of the lateral object velocity in contrast to conventional distance sensors. This is a unique feature of the PH-LDDS enabling precise and dynamic position and shape measurements also of fast moving objects. With an optimized sensor setup, an average position resolution of 240 nm was obtained.

Inductance position sensor for pneumatic cylinder

NASA Astrophysics Data System (ADS)

Ripka, Pavel; Chirtsov, Andrey; Mirzaei, Mehran; Vyhnanek, Jan

2018-04-01

The position of the piston in pneumatic cylinder with aluminum wall can be measured by external inductance sensor without modifications of the aluminum piston and massive iron piston rod. For frequencies below 20 Hz the inductance is increasing with inserting rod due to the rod permeability. This mode has disadvantage of slow response to piston movement and also high temperature sensitivity. At the frequency of 45 Hz the inductance is position independent, as the permeability effect is compensated by the eddy current effect. At higher frequencies eddy current effects in the rod prevail, the inductance is decreasing with inserting rod. In this mode the sensitivity is smaller but the sensor response is fast and temperature stability is better. We show that FEM simulation of this sensor using measured material properties gives accurate results, which is important for the sensor optimization such as designing the winding geometry for the best linearity.

A Method for Improving the Pose Accuracy of a Robot Manipulator Based on Multi-Sensor Combined Measurement and Data Fusion

PubMed Central

Liu, Bailing; Zhang, Fumin; Qu, Xinghua

2015-01-01

An improvement method for the pose accuracy of a robot manipulator by using a multiple-sensor combination measuring system (MCMS) is presented. It is composed of a visual sensor, an angle sensor and a series robot. The visual sensor is utilized to measure the position of the manipulator in real time, and the angle sensor is rigidly attached to the manipulator to obtain its orientation. Due to the higher accuracy of the multi-sensor, two efficient data fusion approaches, the Kalman filter (KF) and multi-sensor optimal information fusion algorithm (MOIFA), are used to fuse the position and orientation of the manipulator. The simulation and experimental results show that the pose accuracy of the robot manipulator is improved dramatically by 38%∼78% with the multi-sensor data fusion. Comparing with reported pose accuracy improvement methods, the primary advantage of this method is that it does not require the complex solution of the kinematics parameter equations, increase of the motion constraints and the complicated procedures of the traditional vision-based methods. It makes the robot processing more autonomous and accurate. To improve the reliability and accuracy of the pose measurements of MCMS, the visual sensor repeatability is experimentally studied. An optimal range of 1 × 0.8 × 1 ∼ 2 × 0.8 × 1 m in the field of view (FOV) is indicated by the experimental results. PMID:25850067

Energy efficient sensor scheduling with a mobile sink node for the target tracking application.

PubMed

Maheswararajah, Suhinthan; Halgamuge, Saman; Premaratne, Malin

2009-01-01

Measurement losses adversely affect the performance of target tracking. The sensor network's life span depends on how efficiently the sensor nodes consume energy. In this paper, we focus on minimizing the total energy consumed by the sensor nodes whilst avoiding measurement losses. Since transmitting data over a long distance consumes a significant amount of energy, a mobile sink node collects the measurements and transmits them to the base station. We assume that the default transmission range of the activated sensor node is limited and it can be increased to maximum range only if the mobile sink node is out-side the default transmission range. Moreover, the active sensor node can be changed after a certain time period. The problem is to select an optimal sensor sequence which minimizes the total energy consumed by the sensor nodes. In this paper, we consider two different problems depend on the mobile sink node's path. First, we assume that the mobile sink node's position is known for the entire time horizon and use the dynamic programming technique to solve the problem. Second, the position of the sink node is varied over time according to a known Markov chain, and the problem is solved by stochastic dynamic programming. We also present sub-optimal methods to solve our problem. A numerical example is presented in order to discuss the proposed methods' performance.

Energy Efficient Sensor Scheduling with a Mobile Sink Node for the Target Tracking Application

PubMed Central

Maheswararajah, Suhinthan; Halgamuge, Saman; Premaratne, Malin

2009-01-01

Measurement losses adversely affect the performance of target tracking. The sensor network's life span depends on how efficiently the sensor nodes consume energy. In this paper, we focus on minimizing the total energy consumed by the sensor nodes whilst avoiding measurement losses. Since transmitting data over a long distance consumes a significant amount of energy, a mobile sink node collects the measurements and transmits them to the base station. We assume that the default transmission range of the activated sensor node is limited and it can be increased to maximum range only if the mobile sink node is out-side the default transmission range. Moreover, the active sensor node can be changed after a certain time period. The problem is to select an optimal sensor sequence which minimizes the total energy consumed by the sensor nodes. In this paper, we consider two different problems depend on the mobile sink node's path. First, we assume that the mobile sink node's position is known for the entire time horizon and use the dynamic programming technique to solve the problem. Second, the position of the sink node is varied over time according to a known Markov chain, and the problem is solved by stochastic dynamic programming. We also present sub-optimal methods to solve our problem. A numerical example is presented in order to discuss the proposed methods' performance PMID:22399934

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.

Scheduling policies of intelligent sensors and sensor/actuators in flexible structures

NASA Astrophysics Data System (ADS)

Demetriou, Michael A.; Potami, Raffaele

2006-03-01

In this note, we revisit the problem of actuator/sensor placement in large civil infrastructures and flexible space structures within the context of spatial robustness. The positioning of these devices becomes more important in systems employing wireless sensor and actuator networks (WSAN) for improved control performance and for rapid failure detection. The ability of the sensing and actuating devices to possess the property of spatial robustness results in reduced control energy and therefore the spatial distribution of disturbances is integrated into the location optimization measures. In our studies, the structure under consideration is a flexible plate clamped at all sides. First, we consider the case of sensor placement and the optimization scheme attempts to produce those locations that minimize the effects of the spatial distribution of disturbances on the state estimation error; thus the sensor locations produce state estimators with minimized disturbance-to-error transfer function norms. A two-stage optimization procedure is employed whereby one first considers the open loop system and the spatial distribution of disturbances is found that produces the maximal effects on the entire open loop state. Once this "worst" spatial distribution of disturbances is found, the optimization scheme subsequently finds the locations that produce state estimators with minimum transfer function norms. In the second part, we consider the collocated actuator/sensor pairs and the optimization scheme produces those locations that result in compensators with the smallest norms of the disturbance-to-state transfer functions. Going a step further, an intelligent control scheme is presented which, at each time interval, activates a subset of the actuator/sensor pairs in order provide robustness against spatiotemporally moving disturbances and minimize power consumption by keeping some sensor/actuators in sleep mode.

Complex Human Activity Recognition Using Smartphone and Wrist-Worn Motion Sensors

PubMed Central

Shoaib, Muhammad; Bosch, Stephan; Incel, Ozlem Durmaz; Scholten, Hans; Havinga, Paul J. M.

2016-01-01

The position of on-body motion sensors plays an important role in human activity recognition. Most often, mobile phone sensors at the trouser pocket or an equivalent position are used for this purpose. However, this position is not suitable for recognizing activities that involve hand gestures, such as smoking, eating, drinking coffee and giving a talk. To recognize such activities, wrist-worn motion sensors are used. However, these two positions are mainly used in isolation. To use richer context information, we evaluate three motion sensors (accelerometer, gyroscope and linear acceleration sensor) at both wrist and pocket positions. Using three classifiers, we show that the combination of these two positions outperforms the wrist position alone, mainly at smaller segmentation windows. Another problem is that less-repetitive activities, such as smoking, eating, giving a talk and drinking coffee, cannot be recognized easily at smaller segmentation windows unlike repetitive activities, like walking, jogging and biking. For this purpose, we evaluate the effect of seven window sizes (2–30 s) on thirteen activities and show how increasing window size affects these various activities in different ways. We also propose various optimizations to further improve the recognition of these activities. For reproducibility, we make our dataset publicly available. PMID:27023543

A high precision position sensor design and its signal processing algorithm for a maglev train.

PubMed

Xue, Song; Long, Zhiqiang; He, Ning; Chang, Wensen

2012-01-01

High precision positioning technology for a kind of high speed maglev train with an electromagnetic suspension (EMS) system is studied. At first, the basic structure and functions of the position sensor are introduced and some key techniques to enhance the positioning precision are designed. Then, in order to further improve the positioning signal quality and the fault-tolerant ability of the sensor, a new kind of discrete-time tracking differentiator (TD) is proposed based on nonlinear optimal control theory. This new TD has good filtering and differentiating performances and a small calculation load. It is suitable for real-time signal processing. The stability, convergence property and frequency characteristics of the TD are studied and analyzed thoroughly. The delay constant of the TD is figured out and an effective time delay compensation algorithm is proposed. Based on the TD technology, a filtering process is introduced in to improve the positioning signal waveform when the sensor is under bad working conditions, and a two-sensor switching algorithm is designed to eliminate the positioning errors caused by the joint gaps of the long stator. The effectiveness and stability of the sensor and its signal processing algorithms are proved by the experiments on a test train during a long-term test run.

A High Precision Position Sensor Design and Its Signal Processing Algorithm for a Maglev Train

PubMed Central

Xue, Song; Long, Zhiqiang; He, Ning; Chang, Wensen

2012-01-01

High precision positioning technology for a kind of high speed maglev train with an electromagnetic suspension (EMS) system is studied. At first, the basic structure and functions of the position sensor are introduced and some key techniques to enhance the positioning precision are designed. Then, in order to further improve the positioning signal quality and the fault-tolerant ability of the sensor, a new kind of discrete-time tracking differentiator (TD) is proposed based on nonlinear optimal control theory. This new TD has good filtering and differentiating performances and a small calculation load. It is suitable for real-time signal processing. The stability, convergence property and frequency characteristics of the TD are studied and analyzed thoroughly. The delay constant of the TD is figured out and an effective time delay compensation algorithm is proposed. Based on the TD technology, a filtering process is introduced in to improve the positioning signal waveform when the sensor is under bad working conditions, and a two-sensor switching algorithm is designed to eliminate the positioning errors caused by the joint gaps of the long stator. The effectiveness and stability of the sensor and its signal processing algorithms are proved by the experiments on a test train during a long-term test run. PMID:22778582

Identification of the optimal spectral region for plasmonic and nanoplasmonic sensing.

PubMed

Otte, Marinus A; Sepúlveda, Borja; Ni, Weihai; Juste, Jorge Pérez; Liz-Marzán, Luis M; Lechuga, Laura M

2010-01-26

We present a theoretical and experimental study involving the sensing characteristics of wavelength-interrogated plasmonic sensors based on surface plasmon polaritons (SPP) in planar gold films and on localized surface plasmon resonances (LSPR) of single gold nanorods. The tunability of both sensing platforms allowed us to analyze their bulk and surface sensing characteristics as a function of the plasmon resonance position. We demonstrate that a general figure of merit (FOM), which is equivalent in wavelength and energy scales, can be employed to mutually compare both sensing schemes. Most interestingly, this FOM has revealed a spectral region for which the surface sensitivity performance of both sensor types is optimized, which we attribute to the intrinsic dielectric properties of plasmonic materials. Additionally, in good agreement with theoretical predictions, we experimentally demonstrate that, although the SPP sensor offers a much better bulk sensitivity, the LSPR sensor shows an approximately 15% better performance for surface sensitivity measurements when its FOM is optimized. However, optimization of the substrate refractive index and the accessibility of the relevant molecules to the nanoparticles can lead to a total 3-fold improvement of the FOM in LSPR sensors.

A Two-Phase Coverage-Enhancing Algorithm for Hybrid Wireless Sensor Networks.

PubMed

Zhang, Qingguo; Fok, Mable P

2017-01-09

Providing field coverage is a key task in many sensor network applications. In certain scenarios, the sensor field may have coverage holes due to random initial deployment of sensors; thus, the desired level of coverage cannot be achieved. A hybrid wireless sensor network is a cost-effective solution to this problem, which is achieved by repositioning a portion of the mobile sensors in the network to meet the network coverage requirement. This paper investigates how to redeploy mobile sensor nodes to improve network coverage in hybrid wireless sensor networks. We propose a two-phase coverage-enhancing algorithm for hybrid wireless sensor networks. In phase one, we use a differential evolution algorithm to compute the candidate's target positions in the mobile sensor nodes that could potentially improve coverage. In the second phase, we use an optimization scheme on the candidate's target positions calculated from phase one to reduce the accumulated potential moving distance of mobile sensors, such that the exact mobile sensor nodes that need to be moved as well as their final target positions can be determined. Experimental results show that the proposed algorithm provided significant improvement in terms of area coverage rate, average moving distance, area coverage-distance rate and the number of moved mobile sensors, when compare with other approaches.

A Two-Phase Coverage-Enhancing Algorithm for Hybrid Wireless Sensor Networks

PubMed Central

Zhang, Qingguo; Fok, Mable P.

2017-01-01

Providing field coverage is a key task in many sensor network applications. In certain scenarios, the sensor field may have coverage holes due to random initial deployment of sensors; thus, the desired level of coverage cannot be achieved. A hybrid wireless sensor network is a cost-effective solution to this problem, which is achieved by repositioning a portion of the mobile sensors in the network to meet the network coverage requirement. This paper investigates how to redeploy mobile sensor nodes to improve network coverage in hybrid wireless sensor networks. We propose a two-phase coverage-enhancing algorithm for hybrid wireless sensor networks. In phase one, we use a differential evolution algorithm to compute the candidate’s target positions in the mobile sensor nodes that could potentially improve coverage. In the second phase, we use an optimization scheme on the candidate’s target positions calculated from phase one to reduce the accumulated potential moving distance of mobile sensors, such that the exact mobile sensor nodes that need to be moved as well as their final target positions can be determined. Experimental results show that the proposed algorithm provided significant improvement in terms of area coverage rate, average moving distance, area coverage–distance rate and the number of moved mobile sensors, when compare with other approaches. PMID:28075365

Pulmonary artery location during microgravity activity: Potential impact for chest-mounted Doppler during space travel

NASA Technical Reports Server (NTRS)

Hadley, A. T., III; Conkin, J.; Waligora, J. M.; Horrigan, D. J., Jr.

1984-01-01

Doppler, or ultrasonic, monitoring for pain manifestations of decompression sickness (the bends) is accomplished by placing a sensor on the chest over the pulmonary artery and listening for bubbles. Difficulties have arisen because the technician notes that the pulmonary artery seems to move with subject movement in a one-g field and because the sensor output is influenced by only slight degrees of sensor movement. This study used two subjects and mapped the position of the pulmonary artery in one-g, microgravity, and two-g environments using ultrasound. The results showed that the pulmonary artery is fixed in location in microgravity and not affected by subject position change. The optimal position corresponded to where the Doppler signal is best heard with the subject in a supine position in a one-g environment. The impact of this result is that a proposed multiple sensor array on the chest proposed for microgravity use may not be necessary to monitor an astronaut during extravehicular activities. Instead, a single sensor of approximately 1 inch diameter and mounted in the position described above may suffice.

Optimal sensor placement for deployable antenna module health monitoring in SSPS using genetic algorithm

NASA Astrophysics Data System (ADS)

Yang, Chen; Zhang, Xuepan; Huang, Xiaoqi; Cheng, ZhengAi; Zhang, Xinghua; Hou, Xinbin

2017-11-01

The concept of space solar power satellite (SSPS) is an advanced system for collecting solar energy in space and transmitting it wirelessly to earth. However, due to the long service life, in-orbit damage may occur in the structural system of SSPS. Therefore, sensor placement layouts for structural health monitoring should be firstly considered in this concept. In this paper, based on genetic algorithm, an optimal sensor placement method for deployable antenna module health monitoring in SSPS is proposed. According to the characteristics of the deployable antenna module, the designs of sensor placement are listed. Furthermore, based on effective independence method and effective interval index, a combined fitness function is defined to maximize linear independence in targeted modes while simultaneously avoiding redundant information at nearby positions. In addition, by considering the reliability of sensors located at deployable mechanisms, another fitness function is constituted. Moreover, the solution process of optimal sensor placement by using genetic algorithm is clearly demonstrated. At last, a numerical example about the sensor placement layout in a deployable antenna module of SSPS is presented, which by synthetically considering all the above mentioned performances. All results can illustrate the effectiveness and feasibility of the proposed sensor placement method in SSPS.

Optimized passive sonar placement to allow improved interdiction

NASA Astrophysics Data System (ADS)

Johnson, Bruce A.; Matthews, Cameron

2016-05-01

The Art Gallery Problem (AGP) is the name given to a constrained optimization problem meant to determine the maximum amount of sensor coverage while utilizing the minimum number of resources. The AGP is significant because a common issue among surveillance and interdiction systems is obtaining an understanding of the optimal position of sensors and weapons in advance of enemy combatant maneuvers. The implication that an optimal position for a sensor to observe an event or for a weapon to engage a target autonomously is usually very clear after the target has passed, but for autonomous systems the solution must at least be conjectured in advance for deployment purposes. This abstract applies the AGP as a means to solve where best to place underwater sensor nodes such that the amount of information acquired about a covered area is maximized while the number of resources used to gain that information is minimized. By phrasing the ISR/interdiction problem this way, the issue is addressed as an instance of the AGP. The AGP is a member of a set of computational problems designated as nondeterministic polynomial-time (NP)-hard. As a member of this set, the AGP shares its members' defining feature, namely that no one has proven that there exists a deterministic algorithm providing a computationally-tractable solution to the AGP within a finite amount of time. At best an algorithm meant to solve the AGP can asymptotically approach perfect coverage with minimal resource usage but providing perfect coverage would either break the minimal resource usage constraint or require an exponentially-growing amount of time. No perfectly-optimal solution yet exists to the AGP, however, approximately optimal solutions to the AGP can approach complete area or barrier coverage while simultaneously minimizing the number of sensors and weapons utilized. A minimal number of underwater sensor nodes deployed can greatly increase the Mean Time Between Operational Failure (MTBOF) and logistical footprint. The resulting coverage optimizes the likelihood of encounter given an arbitrary sensor profile and threat from a free field statistical model approach. The free field statistical model is particularly applicable to worst case scenario modeling in open ocean operational profiles where targets to do not follow a particular pattern in any of the modeled dimensions. We present an algorithmic testbed which shows how to achieve approximately optimal solutions to the AGP for a network of underwater sensor nodes with or without effector systems for engagement while operating under changing environmental circumstances. The means by which we accomplish this goal are three-fold: 1) Develop a 3D model for the sonar signal propagating through the underwater environment 2) Add rigorous physics-based modeling of environmental events which can affect sensor information acquisition 3) Provide innovative solutions to the AGP which account for the environmental circumstances affecting sensor performance.

Prediction-based Dynamic Energy Management in Wireless Sensor Networks

PubMed Central

Wang, Xue; Ma, Jun-Jie; Wang, Sheng; Bi, Dao-Wei

2007-01-01

Energy consumption is a critical constraint in wireless sensor networks. Focusing on the energy efficiency problem of wireless sensor networks, this paper proposes a method of prediction-based dynamic energy management. A particle filter was introduced to predict a target state, which was adopted to awaken wireless sensor nodes so that their sleep time was prolonged. With the distributed computing capability of nodes, an optimization approach of distributed genetic algorithm and simulated annealing was proposed to minimize the energy consumption of measurement. Considering the application of target tracking, we implemented target position prediction, node sleep scheduling and optimal sensing node selection. Moreover, a routing scheme of forwarding nodes was presented to achieve extra energy conservation. Experimental results of target tracking verified that energy-efficiency is enhanced by prediction-based dynamic energy management.

Sensor management in RADAR/IRST track fusion

NASA Astrophysics Data System (ADS)

Hu, Shi-qiang; Jing, Zhong-liang

2004-07-01

In this paper, a novel radar management strategy technique suitable for RADAR/IRST track fusion, which is based on Fisher Information Matrix (FIM) and fuzzy stochastic decision approach, is put forward. Firstly, optimal radar measurements' scheduling is obtained by the method of maximizing determinant of the Fisher information matrix of radar and IRST measurements, which is managed by the expert system. Then, suggested a "pseudo sensor" to predict the possible target position using the polynomial method based on the radar and IRST measurements, using "pseudo sensor" model to estimate the target position even if the radar is turned off. At last, based on the tracking performance and the state of target maneuver, fuzzy stochastic decision is used to adjust the optimal radar scheduling and retrieve the module parameter of "pseudo sensor". The experiment result indicates that the algorithm can not only limit Radar activity effectively but also keep the tracking accuracy of active/passive system well. And this algorithm eliminates the drawback of traditional Radar management methods that the Radar activity is fixed and not easy to control and protect.

An Optimized Handover Scheme with Movement Trend Awareness for Body Sensor Networks

PubMed Central

Sun, Wen; Zhang, Zhiqiang; Ji, Lianying; Wong, Wai-Choong

2013-01-01

When a body sensor network (BSN) that is linked to the backbone via a wireless network interface moves from one coverage zone to another, a handover is required to maintain network connectivity. This paper presents an optimized handover scheme with movement trend awareness for BSNs. The proposed scheme predicts the future position of a BSN user using the movement trend extracted from the historical position, and adjusts the handover decision accordingly. Handover initiation time is optimized when the unnecessary handover rate is estimated to meet the requirement and the outage probability is minimized. The proposed handover scheme is simulated in a BSN deployment area in a hospital environment in UK. Simulation results show that the proposed scheme reduces the outage probability by 22% as compared with the existing hysteresis-based handover scheme under the constraint of acceptable handover rate. PMID:23736852

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

Discrete Particle Swarm Optimization Routing Protocol for Wireless Sensor Networks with Multiple Mobile Sinks.

PubMed

Yang, Jin; Liu, Fagui; Cao, Jianneng; Wang, Liangming

2016-07-14

Mobile sinks can achieve load-balancing and energy-consumption balancing across the wireless sensor networks (WSNs). However, the frequent change of the paths between source nodes and the sinks caused by sink mobility introduces significant overhead in terms of energy and packet delays. To enhance network performance of WSNs with mobile sinks (MWSNs), we present an efficient routing strategy, which is formulated as an optimization problem and employs the particle swarm optimization algorithm (PSO) to build the optimal routing paths. However, the conventional PSO is insufficient to solve discrete routing optimization problems. Therefore, a novel greedy discrete particle swarm optimization with memory (GMDPSO) is put forward to address this problem. In the GMDPSO, particle's position and velocity of traditional PSO are redefined under discrete MWSNs scenario. Particle updating rule is also reconsidered based on the subnetwork topology of MWSNs. Besides, by improving the greedy forwarding routing, a greedy search strategy is designed to drive particles to find a better position quickly. Furthermore, searching history is memorized to accelerate convergence. Simulation results demonstrate that our new protocol significantly improves the robustness and adapts to rapid topological changes with multiple mobile sinks, while efficiently reducing the communication overhead and the energy consumption.

Energy optimization in mobile sensor networks

NASA Astrophysics Data System (ADS)

Yu, Shengwei

Mobile sensor networks are considered to consist of a network of mobile robots, each of which has computation, communication and sensing capabilities. Energy efficiency is a critical issue in mobile sensor networks, especially when mobility (i.e., locomotion control), routing (i.e., communications) and sensing are unique characteristics of mobile robots for energy optimization. This thesis focuses on the problem of energy optimization of mobile robotic sensor networks, and the research results can be extended to energy optimization of a network of mobile robots that monitors the environment, or a team of mobile robots that transports materials from stations to stations in a manufacturing environment. On the energy optimization of mobile robotic sensor networks, our research focuses on the investigation and development of distributed optimization algorithms to exploit the mobility of robotic sensor nodes for network lifetime maximization. In particular, the thesis studies these five problems: 1. Network-lifetime maximization by controlling positions of networked mobile sensor robots based on local information with distributed optimization algorithms; 2. Lifetime maximization of mobile sensor networks with energy harvesting modules; 3. Lifetime maximization using joint design of mobility and routing; 4. Optimal control for network energy minimization; 5. Network lifetime maximization in mobile visual sensor networks. In addressing the first problem, we consider only the mobility strategies of the robotic relay nodes in a mobile sensor network in order to maximize its network lifetime. By using variable substitutions, the original problem is converted into a convex problem, and a variant of the sub-gradient method for saddle-point computation is developed for solving this problem. An optimal solution is obtained by the method. Computer simulations show that mobility of robotic sensors can significantly prolong the lifetime of the whole robotic sensor network while consuming negligible amount of energy for mobility cost. For the second problem, the problem is extended to accommodate mobile robotic nodes with energy harvesting capability, which makes it a non-convex optimization problem. The non-convexity issue is tackled by using the existing sequential convex approximation method, based on which we propose a novel procedure of modified sequential convex approximation that has fast convergence speed. For the third problem, the proposed procedure is used to solve another challenging non-convex problem, which results in utilizing mobility and routing simultaneously in mobile robotic sensor networks to prolong the network lifetime. The results indicate that joint design of mobility and routing has an edge over other methods in prolonging network lifetime, which is also the justification for the use of mobility in mobile sensor networks for energy efficiency purpose. For the fourth problem, we include the dynamics of the robotic nodes in the problem by modeling the networked robotic system using hybrid systems theory. A novel distributed method for the networked hybrid system is used to solve the optimal moving trajectories for robotic nodes and optimal network links, which are not answered by previous approaches. Finally, the fact that mobility is more effective in prolonging network lifetime for a data-intensive network leads us to apply our methods to study mobile visual sensor networks, which are useful in many applications. We investigate the joint design of mobility, data routing, and encoding power to help improving the video quality while maximizing the network lifetime. This study leads to a better understanding of the role mobility can play in data-intensive surveillance sensor networks.

Occupant detection using support vector machines with a polynomial kernel function

NASA Astrophysics Data System (ADS)

Destefanis, Eduardo A.; Kienzle, Eberhard; Canali, Luis R.

2000-10-01

The use of air bags in the presence of bad passenger and baby seat positions in car seats can injure or kill these individuals in case of an accident when this device is inflated. A proposed solution is the use of range sensors to detect passenger and baby seat risky positions. Such sensors allow the Airbag inflation to be controlled. This work is concerned with the application of different classification schemes to a real world problem and the optimization of a sensor as a function of the classification performance. The sensor is constructed using a new technology which is called Photo-Mixer-Device (PMD). A systematic analysis of the occupant detection problem was made using real and virtual environments. The challenge is to find the best sensor geometry and to adapt a classification scheme under the current technological constraints. Passenger head position detection is also a desirable issue. A couple of classifiers have been used into a simple configuration to reach this goal. Experiences and results are described.

Linear Controller Design: Limits of Performance

DTIC Science & Technology

1991-01-01

where a sensor should be placed eg where an accelerometer is to be positioned on an aircraft or where a strain gauge is placed along a beam The...309 VIII CONTENTS 14 Special Algorithms for Convex Optimization 311 Notation and Problem Denitions...311 On Algorithms for Convex Optimization 312 CuttingPlane Algorithms

Survey on the Performance of Source Localization Algorithms.

PubMed

Fresno, José Manuel; Robles, Guillermo; Martínez-Tarifa, Juan Manuel; Stewart, Brian G

2017-11-18

The localization of emitters using an array of sensors or antennas is a prevalent issue approached in several applications. There exist different techniques for source localization, which can be classified into multilateration, received signal strength (RSS) and proximity methods. The performance of multilateration techniques relies on measured time variables: the time of flight (ToF) of the emission from the emitter to the sensor, the time differences of arrival (TDoA) of the emission between sensors and the pseudo-time of flight (pToF) of the emission to the sensors. The multilateration algorithms presented and compared in this paper can be classified as iterative and non-iterative methods. Both standard least squares (SLS) and hyperbolic least squares (HLS) are iterative and based on the Newton-Raphson technique to solve the non-linear equation system. The metaheuristic technique particle swarm optimization (PSO) used for source localisation is also studied. This optimization technique estimates the source position as the optimum of an objective function based on HLS and is also iterative in nature. Three non-iterative algorithms, namely the hyperbolic positioning algorithms (HPA), the maximum likelihood estimator (MLE) and Bancroft algorithm, are also presented. A non-iterative combined algorithm, MLE-HLS, based on MLE and HLS, is further proposed in this paper. The performance of all algorithms is analysed and compared in terms of accuracy in the localization of the position of the emitter and in terms of computational time. The analysis is also undertaken with three different sensor layouts since the positions of the sensors affect the localization; several source positions are also evaluated to make the comparison more robust. The analysis is carried out using theoretical time differences, as well as including errors due to the effect of digital sampling of the time variables. It is shown that the most balanced algorithm, yielding better results than the other algorithms in terms of accuracy and short computational time, is the combined MLE-HLS algorithm.

Survey on the Performance of Source Localization Algorithms

PubMed Central

2017-01-01

The localization of emitters using an array of sensors or antennas is a prevalent issue approached in several applications. There exist different techniques for source localization, which can be classified into multilateration, received signal strength (RSS) and proximity methods. The performance of multilateration techniques relies on measured time variables: the time of flight (ToF) of the emission from the emitter to the sensor, the time differences of arrival (TDoA) of the emission between sensors and the pseudo-time of flight (pToF) of the emission to the sensors. The multilateration algorithms presented and compared in this paper can be classified as iterative and non-iterative methods. Both standard least squares (SLS) and hyperbolic least squares (HLS) are iterative and based on the Newton–Raphson technique to solve the non-linear equation system. The metaheuristic technique particle swarm optimization (PSO) used for source localisation is also studied. This optimization technique estimates the source position as the optimum of an objective function based on HLS and is also iterative in nature. Three non-iterative algorithms, namely the hyperbolic positioning algorithms (HPA), the maximum likelihood estimator (MLE) and Bancroft algorithm, are also presented. A non-iterative combined algorithm, MLE-HLS, based on MLE and HLS, is further proposed in this paper. The performance of all algorithms is analysed and compared in terms of accuracy in the localization of the position of the emitter and in terms of computational time. The analysis is also undertaken with three different sensor layouts since the positions of the sensors affect the localization; several source positions are also evaluated to make the comparison more robust. The analysis is carried out using theoretical time differences, as well as including errors due to the effect of digital sampling of the time variables. It is shown that the most balanced algorithm, yielding better results than the other algorithms in terms of accuracy and short computational time, is the combined MLE-HLS algorithm. PMID:29156565

Optimal locations and orientations of piezoelectric transducers on cylindrical shell based on gramians of contributed and undesired Rayleigh-Ritz modes using genetic algorithm

NASA Astrophysics Data System (ADS)

Biglar, Mojtaba; Mirdamadi, Hamid Reza; Danesh, Mohammad

2014-02-01

In this study, the active vibration control and configurational optimization of a cylindrical shell are analyzed by using piezoelectric transducers. The piezoelectric patches are attached to the surface of the cylindrical shell. The Rayleigh-Ritz method is used for deriving dynamic modeling of cylindrical shell and piezoelectric sensors and actuators based on the Donnel-Mushtari shell theory. The major goal of this study is to find the optimal locations and orientations of piezoelectric sensors and actuators on the cylindrical shell. The optimization procedure is designed based on desired controllability and observability of each contributed and undesired mode. Further, in order to limit spillover effects, the residual modes are taken into consideration. The optimization variables are the positions and orientations of piezoelectric patches. Genetic algorithm is utilized to evaluate the optimal configurations. In this article, for improving the maximum power and capacity of actuators for amplitude depreciation of negative velocity feedback strategy, we have proposed a new control strategy, called "Saturated Negative Velocity Feedback Rule (SNVF)". The numerical results show that the optimization procedure is effective for vibration reduction, and specifically, by locating actuators and sensors in their optimal locations and orientations, the vibrations of cylindrical shell are suppressed more quickly.

Reconstruction of the temperature field for inverse ultrasound hyperthermia calculations at a muscle/bone interface.

PubMed

Liauh, Chihng-Tsung; Shih, Tzu-Ching; Huang, Huang-Wen; Lin, Win-Li

2004-02-01

An inverse algorithm with Tikhonov regularization of order zero has been used to estimate the intensity ratios of the reflected longitudinal wave to the incident longitudinal wave and that of the refracted shear wave to the total transmitted wave into bone in calculating the absorbed power field and then to reconstruct the temperature distribution in muscle and bone regions based on a limited number of temperature measurements during simulated ultrasound hyperthermia. The effects of the number of temperature sensors are investigated, as is the amount of noise superimposed on the temperature measurements, and the effects of the optimal sensor location on the performance of the inverse algorithm. Results show that noisy input data degrades the performance of this inverse algorithm, especially when the number of temperature sensors is small. Results are also presented demonstrating an improvement in the accuracy of the temperature estimates by employing an optimal value of the regularization parameter. Based on the analysis of singular-value decomposition, the optimal sensor position in a case utilizing only one temperature sensor can be determined to make the inverse algorithm converge to the true solution.

Robust design of an inkjet-printed capacitive sensor for position tracking of a MOEMS-mirror in a Michelson interferometer setup

NASA Astrophysics Data System (ADS)

Faller, Lisa-Marie; Zangl, Hubert

2017-05-01

To guarantee high performance of Micro Optical Electro Mechanical Systems (MOEMS), precise position feedback is crucial. To overcome drawbacks of widely used optical feedback, we propose an inkjet-printed capacitive position sensor as smart packaging solution. Printing processes suffer from tolerances in excess of those from standard processes. Thus, FEM simulations covering assumed tolerances of the system are adopted. These simulations are structured following a Design Of Computer Experiments (DOCE) and are then employed to determine a optimal sensor design. Based on the simulation results, statistical models are adopted for the dynamic system. These models are to be used together with specifically designed hardware, considered to cope with challenging requirements of ≍50nm position accuracy at 10MS/s with 1000μm measurement range. Noise analysis is performed considering the influence of uncertainties to assess resolution and bandwidth capabilities.

Optical Sensor/Actuator Locations for Active Structural Acoustic Control

NASA Technical Reports Server (NTRS)

Padula, Sharon L.; Palumbo, Daniel L.; Kincaid, Rex K.

1998-01-01

Researchers at NASA Langley Research Center have extensive experience using active structural acoustic control (ASAC) for aircraft interior noise reduction. One aspect of ASAC involves the selection of optimum locations for microphone sensors and force actuators. This paper explains the importance of sensor/actuator selection, reviews optimization techniques, and summarizes experimental and numerical results. Three combinatorial optimization problems are described. Two involve the determination of the number and position of piezoelectric actuators, and the other involves the determination of the number and location of the sensors. For each case, a solution method is suggested, and typical results are examined. The first case, a simplified problem with simulated data, is used to illustrate the method. The second and third cases are more representative of the potential of the method and use measured data. The three case studies and laboratory test results establish the usefulness of the numerical methods.

Simulation of the spatial frequency-dependent sensitivities of Acoustic Emission sensors

NASA Astrophysics Data System (ADS)

Boulay, N.; Lhémery, A.; Zhang, F.

2018-05-01

Typical configurations of nondestructive testing by Acoustic Emission (NDT/AE) make use of multiple sensors positioned on the tested structure for detecting evolving flaws and possibly locating them by triangulation. Sensors positions must be optimized for ensuring global coverage sensitivity to AE events and minimizing their number. A simulator of NDT/AE is under development to provide help with designing testing configurations and with interpreting measurements. A global model performs sub-models simulating the various phenomena taking place at different spatial and temporal scales (crack growth, AE source and radiation, wave propagation in the structure, reception by sensors). In this context, accurate modelling of sensors behaviour must be developed. These sensors generally consist of a cylindrical piezoelectric element of radius approximately equal to its thickness, without damping and bonded to its case. Sensors themselves are bonded to the structure being tested. Here, a multiphysics finite element simulation tool is used to study the complex behaviour of AE sensor. The simulated behaviour is shown to accurately reproduce the high-amplitude measured contributions used in the AE practice.

Ultra compact spectrometer apparatus and method using photonic crystals

NASA Technical Reports Server (NTRS)

Ting, David Z. (Inventor); Hill, Cory J. (Inventor); Bandara, Sumith V. (Inventor); Gunapala, Sarath D. (Inventor)

2009-01-01

The present invention is directed to methods of photonic crystal formation, and to methods and apparatus for using such photonic crystals, particularly in conjunction with detector arrays. Photonic crystal parameters and detector array parameters are compared to optimize the selection and orientation of a photonic crystal shape. A photonic crystal is operatively positioned relative to a plurality of light sensors. The light sensors can be separated by a pitch distance and positioned within one half of the pitch distance of an exit surface of the photonic crystals.

Discrete Particle Swarm Optimization Routing Protocol for Wireless Sensor Networks with Multiple Mobile Sinks

PubMed Central

Yang, Jin; Liu, Fagui; Cao, Jianneng; Wang, Liangming

2016-01-01

Mobile sinks can achieve load-balancing and energy-consumption balancing across the wireless sensor networks (WSNs). However, the frequent change of the paths between source nodes and the sinks caused by sink mobility introduces significant overhead in terms of energy and packet delays. To enhance network performance of WSNs with mobile sinks (MWSNs), we present an efficient routing strategy, which is formulated as an optimization problem and employs the particle swarm optimization algorithm (PSO) to build the optimal routing paths. However, the conventional PSO is insufficient to solve discrete routing optimization problems. Therefore, a novel greedy discrete particle swarm optimization with memory (GMDPSO) is put forward to address this problem. In the GMDPSO, particle’s position and velocity of traditional PSO are redefined under discrete MWSNs scenario. Particle updating rule is also reconsidered based on the subnetwork topology of MWSNs. Besides, by improving the greedy forwarding routing, a greedy search strategy is designed to drive particles to find a better position quickly. Furthermore, searching history is memorized to accelerate convergence. Simulation results demonstrate that our new protocol significantly improves the robustness and adapts to rapid topological changes with multiple mobile sinks, while efficiently reducing the communication overhead and the energy consumption. PMID:27428971

Position-adaptive explosive detection concepts for swarming micro-UAVs

NASA Astrophysics Data System (ADS)

Selmic, Rastko R.; Mitra, Atindra

2008-04-01

We have formulated a series of position-adaptive sensor concepts for explosive detection applications using swarms of micro-UAV's. These concepts are a generalization of position-adaptive radar concepts developed for challenging conditions such as urban environments. For radar applications, this concept is developed with platforms within a UAV swarm that spatially-adapt to signal leakage points on the perimeter of complex clutter environments to collect information on embedded objects-of-interest. The concept is generalized for additional sensors applications by, for example, considering a wooden cart that contains explosives. We can formulate system-of-systems concepts for a swarm of micro-UAV's in an effort to detect whether or not a given cart contains explosives. Under this new concept, some of the members of the UAV swarm can serve as position-adaptive "transmitters" by blowing air over the cart and some of the members of the UAV swarm can serve as position-adaptive "receivers" that are equipped with chem./bio sensors that function as "electronic noses". The final objective can be defined as improving the particle count for the explosives in the air that surrounds a cart via development of intelligent position-adaptive control algorithms in order to improve the detection and false-alarm statistics. We report on recent simulation results with regard to designing optimal sensor placement for explosive or other chemical agent detection. This type of information enables the development of intelligent control algorithms for UAV swarm applications and is intended for the design of future system-of-systems with adaptive intelligence for advanced surveillance of unknown regions. Results are reported as part of a parametric investigation where it is found that the probability of contaminant detection depends on the air flow that carries contaminant particles, geometry of the surrounding space, leakage areas, and other factors. We present a concept of position-adaptive detection (i.e. based on the example in the previous paragraph) consisting of position-adaptive fluid actuators (fans) and position-adaptive sensors. Based on these results, a preliminary analysis of sensor requirements for these fluid actuators and sensors is presented for small-UAVs in a field-enabled explosive detection environment. The computational fluid dynamics (CFD) simulation software Fluent is used to simulate the air flow in the corridor model containing a box with explosive particles. It is found that such flow is turbulent with Reynolds number greater than 106. Simulation methods and results are presented which show particle velocity and concentration distribution throughout the closed box. The results indicate that the CFD-based method can be used for other sensor placement and deployment optimization problems. These techniques and results can be applied towards the development of future system-of-system UAV swarms for defense, homeland defense, and security applications.

Mobile Wireless Sensor Networks for Advanced Soil Sensing and Ecosystem Monitoring

NASA Astrophysics Data System (ADS)

Mollenhauer, Hannes; Schima, Robert; Remmler, Paul; Mollenhauer, Olaf; Hutschenreuther, Tino; Toepfer, Hannes; Dietrich, Peter; Bumberger, Jan

2015-04-01

For an adequate characterization of ecosystems it is necessary to detect individual processes with suitable monitoring strategies and methods. Due to the natural complexity of all environmental compartments, single point or temporally and spatially fixed measurements are mostly insufficient for an adequate representation. The application of mobile wireless sensor networks for soil and atmosphere sensing offers significant benefits, due to the simple adjustment of the sensor distribution, the sensor types and the sample rate (e.g. by using optimization approaches or event triggering modes) to the local test conditions. This can be essential for the monitoring of heterogeneous and dynamic environmental systems and processes. One significant advantage in the application of mobile ad-hoc wireless sensor networks is their self-organizing behavior. Thus, the network autonomously initializes and optimizes itself. Due to the localization via satellite a major reduction in installation and operation costs and time is generated. In addition, single point measurements with a sensor are significantly improved by measuring at several optimized points continuously. Since performing analog and digital signal processing and computation in the sensor nodes close to the sensors a significant reduction of the data to be transmitted can be achieved which leads to a better energy management of nodes. Furthermore, the miniaturization of the nodes and energy harvesting are current topics under investigation. First results of field measurements are given to present the potentials and limitations of this application in environmental science. In particular, collected in-situ data with numerous specific soil and atmosphere parameters per sensor node (more than 25) recorded over several days illustrates the high performance of this system for advanced soil sensing and soil-atmosphere interaction monitoring. Moreover, investigations of biotic and abiotic process interactions and optimization of sensor positioning for measuring soil moisture are scopes of this work and initial results of these issues will be presented.

Ambulatory position and orientation tracking fusing magnetic and inertial sensing.

PubMed

Roetenberg, Daniel; Slycke, Per J; Veltink, Peter H

2007-05-01

This paper presents the design and testing of a portable magnetic system combined with miniature inertial sensors for ambulatory 6 degrees of freedom (DOF) human motion tracking. The magnetic system consists of three orthogonal coils, the source, fixed to the body and 3-D magnetic sensors, fixed to remote body segments, which measure the fields generated by the source. Based on the measured signals, a processor calculates the relative positions and orientations between source and sensor. Magnetic actuation requires a substantial amount of energy which limits the update rate with a set of batteries. Moreover, the magnetic field can easily be disturbed by ferromagnetic materials or other sources. Inertial sensors can be sampled at high rates, require only little energy and do not suffer from magnetic interferences. However, accelerometers and gyroscopes can only measure changes in position and orientation and suffer from integration drift. By combing measurements from both systems in a complementary Kalman filter structure, an optimal solution for position and orientation estimates is obtained. The magnetic system provides 6 DOF measurements at a relatively low update rate while the inertial sensors track the changes position and orientation in between the magnetic updates. The implemented system is tested against a lab-bound camera tracking system for several functional body movements. The accuracy was about 5 mm for position and 3 degrees for orientation measurements. Errors were higher during movements with high velocities due to relative movement between source and sensor within one cycle of magnetic actuation.

Numerical study of ultra-low field nuclear magnetic resonance relaxometry utilizing a single axis magnetometer for signal detection.

PubMed

Vogel, Michael W; Vegh, Viktor; Reutens, David C

2013-05-01

This paper investigates optimal placement of a localized single-axis magnetometer for ultralow field (ULF) relaxometry in view of various sample shapes and sizes. The authors used finite element method for the numerical analysis to determine the sample magnetic field environment and evaluate the optimal location of the single-axis magnetometer. Given the different samples, the authors analysed the magnetic field distribution around the sample and determined the optimal orientation and possible positions of the sensor to maximize signal strength, that is, the power of the free induction decay. The authors demonstrate that a glass vial with flat bottom and 10 ml volume is the best structure to achieve the highest signal out of samples studied. This paper demonstrates the importance of taking into account the combined effects of sensor configuration and sample parameters for signal generation prior to designing and constructing ULF systems with a single-axis magnetometer. Through numerical simulations the authors were able to optimize structural parameters, such as sample shape and size, sensor orientation and location, to maximize the measured signal in ultralow field relaxometry.

Design and Optimization of Multi-Pixel Transition-Edge Sensors for X-Ray Astronomy Applications

NASA Technical Reports Server (NTRS)

Smith, Stephen J.; Adams, Joseph S.; Bandler, Simon R.; Chervenak, James A.; Datesman, Aaron Michael; Eckart, Megan E.; Ewin, Audrey J.; Finkbeiner, Fred M.; Kelley, Richard L.; Kilbourne, Caroline A.;

Adaptive Estimation and Heuristic Optimization of Nonlinear Spacecraft Attitude Dynamics

DTIC Science & Technology

2016-09-15

Algorithm GPS Global Positioning System HOUF Higher Order Unscented Filter IC initial conditions IMM Interacting Multiple Model IMU Inertial Measurement Unit ...sources ranging from inertial measurement units to star sensors are used to construct observations for attitude estimation algorithms. The sensor...parameters. A single vector measurement will provide two independent parameters, as a unit vector constraint removes a DOF making the problem underdetermined

Development of Magneto-Resistive Angular Position Sensors for Space Applications

NASA Astrophysics Data System (ADS)

Hahn, Robert; Langendorf, Sven; Seifart, Klaus; Slatter, Rolf; Olberts, Bastian; Romera, Fernando

2015-09-01

Magnetic microsystems in the form of magneto- resistive (MR) sensors are firmly established in automobiles and industrial applications. They measure path, angle, electrical current, or magnetic fields. MR technology opens up new sensor possibilities in space applications and can be an enabling technology for optimal performance, high robustness and long lifetime at reasonable costs. In a recent assessment study performed by HTS GmbH and Sensitec GmbH under ESA Contract a market survey has confirmed that space industry has a very high interest in novel, contactless position sensors based on MR technology. Now, a detailed development stage is pursued, to advance the sensor design up to Engineering Qualification Model (EQM) level and to perform qualification testing for a representative pilot space application.The paper briefly reviews the basics of magneto- resistive effects and possible sensor applications and describes the key benefits of MR angular sensors with reference to currently operational industrial and space applications. The results of the assessment study are presented and potential applications and uses of contactless magneto-resistive angular sensors for spacecraft are identified. The baseline mechanical and electrical sensor design will be discussed. An outlook on the EQM development and qualification tests is provided.

Positive position control of robotic manipulators

NASA Technical Reports Server (NTRS)

Baz, A.; Gumusel, L.

1989-01-01

The present, simple and accurate position-control algorithm, which is applicable to fast-moving and lightly damped robot arms, is based on the positive position feedback (PPF) strategy and relies solely on position sensors to monitor joint angles of robotic arms to furnish stable position control. The optimized tuned filters, in the form of a set of difference equations, manipulate position signals for robotic system performance. Attention is given to comparisons between this PPF-algorithm controller's experimentally ascertained performance characteristics and those of a conventional proportional controller.

Performance Analysis of the Ironless Inductive Position Sensor in the Large Hadron Collider Collimators Environment

PubMed Central

Danisi, Alessandro; Masi, Alessandro; Losito, Roberto

2015-01-01

The Ironless Inductive Position Sensor (I2PS) has been introduced as a valid alternative to Linear Variable Differential Transformers (LVDTs) when external magnetic fields are present. Potential applications of this linear position sensor can be found in critical systems such as nuclear plants, tokamaks, satellites and particle accelerators. This paper analyzes the performance of the I2PS in the harsh environment of the collimators of the Large Hadron Collider (LHC), where position uncertainties of less than 20 µm are demanded in the presence of nuclear radiation and external magnetic fields. The I2PS has been targeted for installation for LHC Run 2, in order to solve the magnetic interference problem which standard LVDTs are experiencing. The paper describes in detail the chain of systems which belong to the new I2PS measurement task, their impact on the sensor performance and their possible further optimization. The I2PS performance is analyzed evaluating the position uncertainty (on 30 s), the magnetic immunity and the long-term stability (on 7 days). These three indicators are assessed from data acquired during the LHC operation in 2015 and compared with those of LVDTs. PMID:26569259

Identifying typical physical activity on smartphone with varying positions and orientations.

PubMed

Miao, Fen; He, Yi; Liu, Jinlei; Li, Ye; Ayoola, Idowu

2015-04-13

Traditional activity recognition solutions are not widely applicable due to a high cost and inconvenience to use with numerous sensors. This paper aims to automatically recognize physical activity with the help of the built-in sensors of the widespread smartphone without any limitation of firm attachment to the human body. By introducing a method to judge whether the phone is in a pocket, we investigated the data collected from six positions of seven subjects, chose five signals that are insensitive to orientation for activity classification. Decision trees (J48), Naive Bayes and Sequential minimal optimization (SMO) were employed to recognize five activities: static, walking, running, walking upstairs and walking downstairs. The experimental results based on 8,097 activity data demonstrated that the J48 classifier produced the best performance with an average recognition accuracy of 89.6% during the three classifiers, and thus would serve as the optimal online classifier. The utilization of the built-in sensors of the smartphone to recognize typical physical activities without any limitation of firm attachment is feasible.

Research on a new fiber-optic axial pressure sensor of transformer winding based on fiber Bragg grating

NASA Astrophysics Data System (ADS)

Liu, Yuan; Li, Lianqing; Zhao, Lin; Wang, Jiqiang; Liu, Tongyu

2017-12-01

Based on the principle of the fiber Bragg grating, a new type of fiber-optic pressure sensor for axial force measurement of transformer winding is designed, which is designed with the structure of bending plate beam, the optimization of the packaging process, and material of the sensor. Through the calibration experiment to calibrate the sensor, the field test results of the Taikai transformer factory show that the sensitivity of the sensor is 0.133 pm/kPa and the repeatability error is 2.7% FS. The data of the fiber-optic pressure sensor in different positions maintain consistent and repeatable, which can meet the requirement of the real-time monitoring of the axial force of transformer winding.

Automated assembly of camera modules using active alignment with up to six degrees of freedom

NASA Astrophysics Data System (ADS)

Bräuniger, K.; Stickler, D.; Winters, D.; Volmer, C.; Jahn, M.; Krey, S.

2014-03-01

With the upcoming Ultra High Definition (UHD) cameras, the accurate alignment of optical systems with respect to the UHD image sensor becomes increasingly important. Even with a perfect objective lens, the image quality will deteriorate when it is poorly aligned to the sensor. For evaluating the imaging quality the Modulation Transfer Function (MTF) is used as the most accepted test. In the first part it is described how the alignment errors that lead to a low imaging quality can be measured. Collimators with crosshair at defined field positions or a test chart are used as object generators for infinite-finite or respectively finite-finite conjugation. The process how to align the image sensor accurately to the optical system will be described. The focus position, shift, tilt and rotation of the image sensor are automatically corrected to obtain an optimized MTF for all field positions including the center. The software algorithm to grab images, calculate the MTF and adjust the image sensor in six degrees of freedom within less than 30 seconds per UHD camera module is described. The resulting accuracy of the image sensor rotation is better than 2 arcmin and the accuracy position alignment in x,y,z is better 2 μm. Finally, the process of gluing and UV-curing is described and how it is managed in the integrated process.

Simulation and optimization of silicon-on-sapphire pressure sensor

NASA Astrophysics Data System (ADS)

Kulesh, N. A.; Kudyukov, E. V.; Balymov, K. G.; Beloyshov, A. A.

2017-09-01

In this paper, finite element analysis software COMSOL Multiphysics was used to simulate the performance of silicon-on-sapphire piezoresistive pressure sensor, aiming to elaborate a flexible model suitable for further optimization and customization of the currently produced pressure sensors. The base model was built around the cylindrical pressure cell made of titanium alloy having a circular diaphragm with monocrystalline sapphire layer attached. The monocrystalline piezoresistive elements were placed on top of the double-layer diaphragm and electrically connected to form the Wheatstone bridge. Verification of the model and parametric study included three main areas: geometrical parameters of the cell, position of the elements on the diaphragm, and operation at elevated temperature. Optimization of the cell geometry included variation of bossed titanium diaphragm parameters as well as rounding-off radiuses near the edges of the diaphragm. Influence of the temperature was considered separately for thermal expansion of the mechanical components and for the changes of electrical and piezoresistive properties of the piezoresistive elements. In conclusion, the simulation results were compared to the experimental data obtained for three different constructions of the commercial pressure sensors produced by SPA of Automatics named after Academician N.A. Semikhatov.

Analysis of a Segmented Annular Coplanar Capacitive Tilt Sensor with Increased Sensitivity.

PubMed

Guo, Jiahao; Hu, Pengcheng; Tan, Jiubin

2016-01-21

An investigation of a segmented annular coplanar capacitor is presented. We focus on its theoretical model, and a mathematical expression of the capacitance value is derived by solving a Laplace equation with Hankel transform. The finite element method is employed to verify the analytical result. Different control parameters are discussed, and each contribution to the capacitance value of the capacitor is obtained. On this basis, we analyze and optimize the structure parameters of a segmented coplanar capacitive tilt sensor, and three models with different positions of the electrode gap are fabricated and tested. The experimental result shows that the model (whose electrode-gap position is 10 mm from the electrode center) realizes a high sensitivity: 0.129 pF/° with a non-linearity of <0.4% FS (full scale of ± 40°). This finding offers plenty of opportunities for various measurement requirements in addition to achieving an optimized structure in practical design.

Selection of optimal sensors for predicting performance of polymer electrolyte membrane fuel cell

NASA Astrophysics Data System (ADS)

Mao, Lei; Jackson, Lisa

2016-10-01

In this paper, sensor selection algorithms are investigated based on a sensitivity analysis, and the capability of optimal sensors in predicting PEM fuel cell performance is also studied using test data. The fuel cell model is developed for generating the sensitivity matrix relating sensor measurements and fuel cell health parameters. From the sensitivity matrix, two sensor selection approaches, including the largest gap method, and exhaustive brute force searching technique, are applied to find the optimal sensors providing reliable predictions. Based on the results, a sensor selection approach considering both sensor sensitivity and noise resistance is proposed to find the optimal sensor set with minimum size. Furthermore, the performance of the optimal sensor set is studied to predict fuel cell performance using test data from a PEM fuel cell system. Results demonstrate that with optimal sensors, the performance of PEM fuel cell can be predicted with good quality.

Study on robot motion control for intelligent welding processes based on the laser tracking sensor

NASA Astrophysics Data System (ADS)

Zhang, Bin; Wang, Qian; Tang, Chen; Wang, Ju

2017-06-01

A robot motion control method is presented for intelligent welding processes of complex spatial free-form curve seams based on the laser tracking sensor. First, calculate the tip position of the welding torch according to the velocity of the torch and the seam trajectory detected by the sensor. Then, search the optimal pose of the torch under constraints using genetic algorithms. As a result, the intersection point of the weld seam and the laser plane of the sensor is within the detectable range of the sensor. Meanwhile, the angle between the axis of the welding torch and the tangent of the weld seam meets the requirements. The feasibility of the control method is proved by simulation.

Investigation of an optical sensor for small tilt angle detection of a precision linear stage

NASA Astrophysics Data System (ADS)

Saito, Yusuke; Arai, Yoshikazu; Gao, Wei

2010-05-01

This paper presents evaluation results of the characteristics of the angle sensor based on the laser autocollimation method for small tilt angle detection of a precision linear stage. The sensor consists of a laser diode (LD) as the light source, and a quadrant photodiode (QPD) as the position-sensing detector. A small plane mirror is mounted on the moving table of the stage as a target mirror for the sensor. This optical system has advantages of high sensitivity, fast response speed and the ability for two-axis angle detection. On the other hand, the sensitivity of the sensor is determined by the size of the optical spot focused on the QPD, which is a function of the diameter of the laser beam projected onto the target mirror. Because the diameter is influenced by the divergence of the laser beam, this paper focuses on the relationship between the sensor sensitivity and the moving position of the target mirror (sensor working distance) over the moving stroke of the stage. The main error components that influence the sensor sensitivity are discussed and the optimal conditions of the optical system of the sensor are analyzed. The experimental result about evaluation of the effective working distance is also presented.

Practical Considerations for Optimizing Position Sensitivity in Arrays of Position-sensitive TES's

NASA Technical Reports Server (NTRS)

Smith, Stephen J.; Bandler, Simon R.; Figueroa-Feliciano, Encetali; Iyomoto, Naoko; Kelley, Richard L.; Kilbourne, Caroline A.; Porder, Frederick S.; Sadleir, John E.

2007-01-01

We are developing Position-Sensitive Transitions-Edge Sensors (PoST's) for future X-ray astronomy missions such as NASA's Constellation-X. The PoST consists of one or more Transitions Edge Sensors (TES's) thermally connected to a large X-ray absorber, which through heat diffusion, gives rise to position dependence. The development of PoST's is motivated by the desire to achieve the largest the focal-plan coverage with the fewest number of readout channels. In order to develop a practical array, consisting of an inner pixellated core with an outer array of large absorber PoST's, we must be able to simultaneously read out all (-1800) channels in the array. This is achievable using time division multiplexing (TDM), but does set stringent slew rate requirements on the array. Typically, we must damp the pulses to reduce the slew rate of the input signal to the TDM. This is achieved by applying a low-pass analog filter with large inductance to the signal. This attenuates the high frequency components of the signal, essential for position discrimination in PoST's, relative to the white noise of the readout chain and degrades the position sensitivity. Using numerically simulated data, we investigate the position sensing ability of typical PoST designs under such high inductance conditions. We investigate signal-processing techniques for optimal determination of the event position and discuss the practical considerations for real-time implementation.

Optimal Sensor Fusion for Structural Health Monitoring of Aircraft Composite Components

DTIC Science & Technology

2011-09-01

sensor networks combine or fuse different types of sensors. Fiber Bragg Grating ( FBG ) sensors can be inserted in layers of composite structures to...consideration. This paper describes an example of optimal sensor fusion, which combines FBG sensors and PZT sensors. Optimal sensor fusion tries to find...Fiber Bragg Grating ( FBG ) sensors can be inserted in layers of composite structures to provide local damage detection, while surface mounted

Optimal Control Method of Robot End Position and Orientation Based on Dynamic Tracking Measurement

NASA Astrophysics Data System (ADS)

Liu, Dalong; Xu, Lijuan

2018-01-01

In order to improve the accuracy of robot pose positioning and control, this paper proposed a dynamic tracking measurement robot pose optimization control method based on the actual measurement of D-H parameters of the robot, the parameters is taken with feedback compensation of the robot, according to the geometrical parameters obtained by robot pose tracking measurement, improved multi sensor information fusion the extended Kalan filter method, with continuous self-optimal regression, using the geometric relationship between joint axes for kinematic parameters in the model, link model parameters obtained can timely feedback to the robot, the implementation of parameter correction and compensation, finally we can get the optimal attitude angle, realize the robot pose optimization control experiments were performed. 6R dynamic tracking control of robot joint robot with independent research and development is taken as experimental subject, the simulation results show that the control method improves robot positioning accuracy, and it has the advantages of versatility, simplicity, ease of operation and so on.

Deconvolution of continuous paleomagnetic data from pass-through magnetometer: A new algorithm to restore geomagnetic and environmental information based on realistic optimization

NASA Astrophysics Data System (ADS)

Oda, Hirokuni; Xuan, Chuang

2014-10-01

development of pass-through superconducting rock magnetometers (SRM) has greatly promoted collection of paleomagnetic data from continuous long-core samples. The output of pass-through measurement is smoothed and distorted due to convolution of magnetization with the magnetometer sensor response. Although several studies could restore high-resolution paleomagnetic signal through deconvolution of pass-through measurement, difficulties in accurately measuring the magnetometer sensor response have hindered the application of deconvolution. We acquired reliable sensor response of an SRM at the Oregon State University based on repeated measurements of a precisely fabricated magnetic point source. In addition, we present an improved deconvolution algorithm based on Akaike's Bayesian Information Criterion (ABIC) minimization, incorporating new parameters to account for errors in sample measurement position and length. The new algorithm was tested using synthetic data constructed by convolving "true" paleomagnetic signal containing an "excursion" with the sensor response. Realistic noise was added to the synthetic measurement using Monte Carlo method based on measurement noise distribution acquired from 200 repeated measurements of a u-channel sample. Deconvolution of 1000 synthetic measurements with realistic noise closely resembles the "true" magnetization, and successfully restored fine-scale magnetization variations including the "excursion." Our analyses show that inaccuracy in sample measurement position and length significantly affects deconvolution estimation, and can be resolved using the new deconvolution algorithm. Optimized deconvolution of 20 repeated measurements of a u-channel sample yielded highly consistent deconvolution results and estimates of error in sample measurement position and length, demonstrating the reliability of the new deconvolution algorithm for real pass-through measurements.

Design and Parametric Study of the Magnetic Sensor for Position Detection in Linear Motor Based on Nonlinear Parametric Model Order Reduction

PubMed Central

Paul, Sarbajit; Chang, Junghwan

2017-01-01

This paper presents a design approach for a magnetic sensor module to detect mover position using the proper orthogonal decomposition-dynamic mode decomposition (POD-DMD)-based nonlinear parametric model order reduction (PMOR). The parameterization of the sensor module is achieved by using the multipolar moment matching method. Several geometric variables of the sensor module are considered while developing the parametric study. The operation of the sensor module is based on the principle of the airgap flux density distribution detection by the Hall Effect IC. Therefore, the design objective is to achieve a peak flux density (PFD) greater than 0.1 T and total harmonic distortion (THD) less than 3%. To fulfill the constraint conditions, the specifications for the sensor module is achieved by using POD-DMD based reduced model. The POD-DMD based reduced model provides a platform to analyze the high number of design models very fast, with less computational burden. Finally, with the final specifications, the experimental prototype is designed and tested. Two different modes, 90° and 120° modes respectively are used to obtain the position information of the linear motor mover. The position information thus obtained are compared with that of the linear scale data, used as a reference signal. The position information obtained using the 120° mode has a standard deviation of 0.10 mm from the reference linear scale signal, whereas the 90° mode position signal shows a deviation of 0.23 mm from the reference. The deviation in the output arises due to the mechanical tolerances introduced into the specification during the manufacturing process. This provides a scope for coupling the reliability based design optimization in the design process as a future extension. PMID:28671580

Design and Parametric Study of the Magnetic Sensor for Position Detection in Linear Motor Based on Nonlinear Parametric model order reduction.

PubMed

Paul, Sarbajit; Chang, Junghwan

2017-07-01

This paper presents a design approach for a magnetic sensor module to detect mover position using the proper orthogonal decomposition-dynamic mode decomposition (POD-DMD)-based nonlinear parametric model order reduction (PMOR). The parameterization of the sensor module is achieved by using the multipolar moment matching method. Several geometric variables of the sensor module are considered while developing the parametric study. The operation of the sensor module is based on the principle of the airgap flux density distribution detection by the Hall Effect IC. Therefore, the design objective is to achieve a peak flux density (PFD) greater than 0.1 T and total harmonic distortion (THD) less than 3%. To fulfill the constraint conditions, the specifications for the sensor module is achieved by using POD-DMD based reduced model. The POD-DMD based reduced model provides a platform to analyze the high number of design models very fast, with less computational burden. Finally, with the final specifications, the experimental prototype is designed and tested. Two different modes, 90° and 120° modes respectively are used to obtain the position information of the linear motor mover. The position information thus obtained are compared with that of the linear scale data, used as a reference signal. The position information obtained using the 120° mode has a standard deviation of 0.10 mm from the reference linear scale signal, whereas the 90° mode position signal shows a deviation of 0.23 mm from the reference. The deviation in the output arises due to the mechanical tolerances introduced into the specification during the manufacturing process. This provides a scope for coupling the reliability based design optimization in the design process as a future extension.

Optimization-Based Sensor Fusion of GNSS and IMU Using a Moving Horizon Approach

PubMed Central

Girrbach, Fabian; Hol, Jeroen D.; Bellusci, Giovanni; Diehl, Moritz

2017-01-01

The rise of autonomous systems operating close to humans imposes new challenges in terms of robustness and precision on the estimation and control algorithms. Approaches based on nonlinear optimization, such as moving horizon estimation, have been shown to improve the accuracy of the estimated solution compared to traditional filter techniques. This paper introduces an optimization-based framework for multi-sensor fusion following a moving horizon scheme. The framework is applied to the often occurring estimation problem of motion tracking by fusing measurements of a global navigation satellite system receiver and an inertial measurement unit. The resulting algorithm is used to estimate position, velocity, and orientation of a maneuvering airplane and is evaluated against an accurate reference trajectory. A detailed study of the influence of the horizon length on the quality of the solution is presented and evaluated against filter-like and batch solutions of the problem. The versatile configuration possibilities of the framework are finally used to analyze the estimated solutions at different evaluation times exposing a nearly linear behavior of the sensor fusion problem. PMID:28534857

Optimization-Based Sensor Fusion of GNSS and IMU Using a Moving Horizon Approach.

PubMed

Girrbach, Fabian; Hol, Jeroen D; Bellusci, Giovanni; Diehl, Moritz

2017-05-19

The rise of autonomous systems operating close to humans imposes new challenges in terms of robustness and precision on the estimation and control algorithms. Approaches based on nonlinear optimization, such as moving horizon estimation, have been shown to improve the accuracy of the estimated solution compared to traditional filter techniques. This paper introduces an optimization-based framework for multi-sensor fusion following a moving horizon scheme. The framework is applied to the often occurring estimation problem of motion tracking by fusing measurements of a global navigation satellite system receiver and an inertial measurement unit. The resulting algorithm is used to estimate position, velocity, and orientation of a maneuvering airplane and is evaluated against an accurate reference trajectory. A detailed study of the influence of the horizon length on the quality of the solution is presented and evaluated against filter-like and batch solutions of the problem. The versatile configuration possibilities of the framework are finally used to analyze the estimated solutions at different evaluation times exposing a nearly linear behavior of the sensor fusion problem.

Exploiting node mobility for energy optimization in wireless sensor networks

NASA Astrophysics Data System (ADS)

El-Moukaddem, Fatme Mohammad

Wireless Sensor Networks (WSNs) have become increasingly available for data-intensive applications such as micro-climate monitoring, precision agriculture, and audio/video surveillance. A key challenge faced by data-intensive WSNs is to transmit the sheer amount of data generated within an application's lifetime to the base station despite the fact that sensor nodes have limited power supplies such as batteries or small solar panels. The availability of numerous low-cost robotic units (e.g. Robomote and Khepera) has made it possible to construct sensor networks consisting of mobile sensor nodes. It has been shown that the controlled mobility offered by mobile sensors can be exploited to improve the energy efficiency of a network. In this thesis, we propose schemes that use mobile sensor nodes to reduce the energy consumption of data-intensive WSNs. Our approaches differ from previous work in two main aspects. First, our approaches do not require complex motion planning of mobile nodes, and hence can be implemented on a number of low-cost mobile sensor platforms. Second, we integrate the energy consumption due to both mobility and wireless communications into a holistic optimization framework. We consider three problems arising from the limited energy in the sensor nodes. In the first problem, the network consists of mostly static nodes and contains only a few mobile nodes. In the second and third problems, we assume essentially that all nodes in the WSN are mobile. We first study a new problem called max-data mobile relay configuration (MMRC ) that finds the positions of a set of mobile sensors, referred to as relays, that maximize the total amount of data gathered by the network during its lifetime. We show that the MMRC problem is surprisingly complex even for a trivial network topology due to the joint consideration of the energy consumption of both wireless communication and mechanical locomotion. We present optimal MMRC algorithms and practical distributed implementations for several important network topologies and applications. Second, we consider the problem of minimizing the total energy consumption of a network. We design an iterative algorithm that improves a given configuration by relocating nodes to new positions. We show that this algorithm converges to the optimal configuration for the given transmission routes. Moreover, we propose an efficient distributed implementation that does not require explicit synchronization. Finally, we consider the problem of maximizing the lifetime of the network. We propose an approach that exploits the mobility of the nodes to balance the energy consumption throughout the network. We develop efficient algorithms for single and multiple round approaches. For all three problems, we evaluate the efficiency of our algorithms through simulations. Our simulation results based on realistic energy models obtained from existing mobile and static sensor platforms show that our approaches significantly improve the network's performance and outperform existing approaches.

Optimal accelerometer placement on a robot arm for pose estimation

NASA Astrophysics Data System (ADS)

Wijayasinghe, Indika B.; Sanford, Joseph D.; Abubakar, Shamsudeen; Saadatzi, Mohammad Nasser; Das, Sumit K.; Popa, Dan O.

2017-05-01

The performance of robots to carry out tasks depends in part on the sensor information they can utilize. Usually, robots are fitted with angle joint encoders that are used to estimate the position and orientation (or the pose) of its end-effector. However, there are numerous situations, such as in legged locomotion, mobile manipulation, or prosthetics, where such joint sensors may not be present at every, or any joint. In this paper we study the use of inertial sensors, in particular accelerometers, placed on the robot that can be used to estimate the robot pose. Studying accelerometer placement on a robot involves many parameters that affect the performance of the intended positioning task. Parameters such as the number of accelerometers, their size, geometric placement and Signal-to-Noise Ratio (SNR) are included in our study of their effects for robot pose estimation. Due to the ubiquitous availability of inexpensive accelerometers, we investigated pose estimation gains resulting from using increasingly large numbers of sensors. Monte-Carlo simulations are performed with a two-link robot arm to obtain the expected value of an estimation error metric for different accelerometer configurations, which are then compared for optimization. Results show that, with a fixed SNR model, the pose estimation error decreases with increasing number of accelerometers, whereas for a SNR model that scales inversely to the accelerometer footprint, the pose estimation error increases with the number of accelerometers. It is also shown that the optimal placement of the accelerometers depends on the method used for pose estimation. The findings suggest that an integration-based method favors placement of accelerometers at the extremities of the robot links, whereas a kinematic-constraints-based method favors a more uniformly distributed placement along the robot links.

Virtual optical interfaces for the transportation industry

NASA Astrophysics Data System (ADS)

Hejmadi, Vic; Kress, Bernard

2010-04-01

We present a novel implementation of virtual optical interfaces for the transportation industry (automotive and avionics). This new implementation includes two functionalities in a single device; projection of a virtual interface and sensing of the position of the fingers on top of the virtual interface. Both functionalities are produced by diffraction of laser light. The device we are developing include both functionalities in a compact package which has no optical elements to align since all of them are pre-aligned on a single glass wafer through optical lithography. The package contains a CMOS sensor which diffractive objective lens is optimized for the projected interface color as well as for the IR finger position sensor based on structured illumination. Two versions are proposed: a version which senses the 2d position of the hand and a version which senses the hand position in 3d.

Accurate and automatic extrinsic calibration method for blade measurement system integrated by different optical sensors

NASA Astrophysics Data System (ADS)

He, Wantao; Li, Zhongwei; Zhong, Kai; Shi, Yusheng; Zhao, Can; Cheng, Xu

2014-11-01

Fast and precise 3D inspection system is in great demand in modern manufacturing processes. At present, the available sensors have their own pros and cons, and hardly exist an omnipotent sensor to handle the complex inspection task in an accurate and effective way. The prevailing solution is integrating multiple sensors and taking advantages of their strengths. For obtaining a holistic 3D profile, the data from different sensors should be registrated into a coherent coordinate system. However, some complex shape objects own thin wall feather such as blades, the ICP registration method would become unstable. Therefore, it is very important to calibrate the extrinsic parameters of each sensor in the integrated measurement system. This paper proposed an accurate and automatic extrinsic parameter calibration method for blade measurement system integrated by different optical sensors. In this system, fringe projection sensor (FPS) and conoscopic holography sensor (CHS) is integrated into a multi-axis motion platform, and the sensors can be optimally move to any desired position at the object's surface. In order to simple the calibration process, a special calibration artifact is designed according to the characteristics of the two sensors. An automatic registration procedure based on correlation and segmentation is used to realize the artifact datasets obtaining by FPS and CHS rough alignment without any manual operation and data pro-processing, and then the Generalized Gauss-Markoff model is used to estimate the optimization transformation parameters. The experiments show the measurement result of a blade, where several sampled patches are merged into one point cloud, and it verifies the performance of the proposed method.

Affordable and personalized lighting using inverse modeling and virtual sensors

NASA Astrophysics Data System (ADS)

Basu, Chandrayee; Chen, Benjamin; Richards, Jacob; Dhinakaran, Aparna; Agogino, Alice; Martin, Rodney

2014-03-01

Wireless sensor networks (WSN) have great potential to enable personalized intelligent lighting systems while reducing building energy use by 50%-70%. As a result WSN systems are being increasingly integrated in state-ofart intelligent lighting systems. In the future these systems will enable participation of lighting loads as ancillary services. However, such systems can be expensive to install and lack the plug-and-play quality necessary for user-friendly commissioning. In this paper we present an integrated system of wireless sensor platforms and modeling software to enable affordable and user-friendly intelligent lighting. It requires ⇠ 60% fewer sensor deployments compared to current commercial systems. Reduction in sensor deployments has been achieved by optimally replacing the actual photo-sensors with real-time discrete predictive inverse models. Spatially sparse and clustered sub-hourly photo-sensor data captured by the WSN platforms are used to develop and validate a piece-wise linear regression of indoor light distribution. This deterministic data-driven model accounts for sky conditions and solar position. The optimal placement of photo-sensors is performed iteratively to achieve the best predictability of the light field desired for indoor lighting control. Using two weeks of daylight and artificial light training data acquired at the Sustainability Base at NASA Ames, the model was able to predict the light level at seven monitored workstations with 80%-95% accuracy. We estimate that 10% adoption of this intelligent wireless sensor system in commercial buildings could save 0.2-0.25 quads BTU of energy nationwide.

Influence of the middle ear anatomy on the performance of a membrane sensor in the incudostapedial joint gap.

PubMed

Koch, Martin; Seidler, Hannes; Hellmuth, Alexander; Bornitz, Matthias; Lasurashvili, Nikoloz; Zahnert, Thomas

2013-07-01

There is a great demand for implantable microphones for future generations of implantable hearing aids, especially Cochlea Implants. An implantable middle ear microphone based on a piezoelectric membrane sensor for insertion into the incudostapedial gap is investigated. The sensor is designed to measure the sound-induced forces acting on the center of the membrane. The sensor mechanically couples to the adjacent ossicles via two contact areas, the sensor membrane and the sensor housing. The sensing element is a piezoelectric single crystal bonded on a titanium membrane. The sensor allows a minimally invasive and reversible implantation without removal of ossicles and without additional sensor fixation in the tympanic cavity. This study investigates the implantable microphone sensor and its implantation concept. It intends to quantify the influence of the sensor's insertion position on the achievable microphone sensitivity. The investigation considers anatomical and pathological variations of the middle ear geometry and its space limitations. Temporal bone experiments on a laboratory model show that anatomical and pathological variations of the middle ear geometry can prevent the sensor from being placed optimally within the incudostapedial joint. Beyond scattering of transfer functions due to anatomic variations of individual middle ears there is the impact of variations in the sensor position within the ossicular chain that has a considerable effect on the transfer characteristics of the middle ear microphone. The centering of the sensor between incus and stapes, the direction of insertion (membrane to stapes or to incus) and the effect of additional contact points with surrounding anatomic structures affect the signal yield of the implanted sensor. The presence of additional contact points has a considerably impact on the sensitivity, yet the microphone sensitivity is quite robust against small changes in the positioning of the incus on the sensor. Signal losses can be avoided by adjusting the position of the sensor within the joint. The findings allow the development of an improved surgical insertion technique to ensure maximally achievable signal yield of the membrane sensor in the ISJ and provides valuable knowledge for a future design considerations including sensor miniaturization and geometry. Measurements of the implanted sensor in temporal bone specimens showed a microphone sensitivity in the order of 1 mV/Pa. This article is part of a special issue entitled "MEMRO 2012". Copyright © 2012 Elsevier B.V. All rights reserved.

Coexistence of positive and negative refractive index sensitivity in the liquid-core photonic crystal fiber based plasmonic sensor.

PubMed

Shuai, Binbin; Xia, Li; Liu, Deming

2012-11-05

We present and numerically characterize a liquid-core photonic crystal fiber based plasmonic sensor. The coupling properties and sensing performance are investigated by the finite element method. It is found that not only the plasmonic mode dispersion relation but also the fundamental mode dispersion relation is rather sensitive to the analyte refractive index (RI). The positive and negative RI sensitivity coexist in the proposed design. It features a positive RI sensitivity when the increment of the SPP mode effective index is larger than that of the fundamental mode, but the sensor shows a negative RI sensitivity once the increment of the fundamental mode gets larger. A maximum negative RI sensitivity of -5500nm/RIU (Refractive Index Unit) is achieved in the sensing range of 1.50-1.53. The effects of the structural parameters on the plasmonic excitations are also studied, with a view of tuning and optimizing the resonant spectrum.

Tunneling magnetoresistance sensor with pT level 1/f magnetic noise

NASA Astrophysics Data System (ADS)

Deak, James G.; Zhou, Zhimin; Shen, Weifeng

2017-05-01

Magnetoresistive devices are important components in a large number of commercial electronic products in a wide range of applications including industrial position sensors, automotive sensors, hard disk read heads, cell phone compasses, and solid state memories. These devices are commonly based on anisotropic magnetoresistance (AMR) and giant magnetoresistance (GMR), but over the past few years tunneling magnetoresistance (TMR) has been emerging in more applications. Here we focus on recent work that has enabled the development of TMR magnetic field sensors with 1/f noise of less than 100 pT/rtHz at 1 Hz. Of the commercially available sensors, the lowest noise devices have typically been AMR, but they generally have the largest die size. Based on this observation and modeling of experimental data size and geometry dependence, we find that there is an optimal design rule that produces minimum 1/f noise. This design rule requires maximizing the areal coverage of an on-chip flux concentrator, providing it with a minimum possible total gap width, and tightly packing the gaps with MTJ elements, which increases the effective volume and decreases the saturation field of the MTJ freelayers. When properly optimized using this rule, these sensors have noise below 60 pT/rtHz, and could possibly replace fluxgate magnetometers in some applications.

Structural damage detection-oriented multi-type sensor placement with multi-objective optimization

NASA Astrophysics Data System (ADS)

Lin, Jian-Fu; Xu, You-Lin; Law, Siu-Seong

2018-05-01

A structural damage detection-oriented multi-type sensor placement method with multi-objective optimization is developed in this study. The multi-type response covariance sensitivity-based damage detection method is first introduced. Two objective functions for optimal sensor placement are then introduced in terms of the response covariance sensitivity and the response independence. The multi-objective optimization problem is formed by using the two objective functions, and the non-dominated sorting genetic algorithm (NSGA)-II is adopted to find the solution for the optimal multi-type sensor placement to achieve the best structural damage detection. The proposed method is finally applied to a nine-bay three-dimensional frame structure. Numerical results show that the optimal multi-type sensor placement determined by the proposed method can avoid redundant sensors and provide satisfactory results for structural damage detection. The restriction on the number of each type of sensors in the optimization can reduce the searching space in the optimization to make the proposed method more effective. Moreover, how to select a most optimal sensor placement from the Pareto solutions via the utility function and the knee point method is demonstrated in the case study.

Mathematical calibration procedure of a capacitive sensor-based indexed metrology platform

NASA Astrophysics Data System (ADS)

Brau-Avila, A.; Santolaria, J.; Acero, R.; Valenzuela-Galvan, M.; Herrera-Jimenez, V. M.; Aguilar, J. J.

2017-03-01

The demand for faster and more reliable measuring tasks for the control and quality assurance of modern production systems has created new challenges for the field of coordinate metrology. Thus, the search for new solutions in coordinate metrology systems and the need for the development of existing ones still persists. One example of such a system is the portable coordinate measuring machine (PCMM), the use of which in industry has considerably increased in recent years, mostly due to its flexibility for accomplishing in-line measuring tasks as well as its reduced cost and operational advantages compared to traditional coordinate measuring machines. Nevertheless, PCMMs have a significant drawback derived from the techniques applied in the verification and optimization procedures of their kinematic parameters. These techniques are based on the capture of data with the measuring instrument from a calibrated gauge object, fixed successively in various positions so that most of the instrument measuring volume is covered, which results in time-consuming, tedious and expensive verification and optimization procedures. In this work the mathematical calibration procedure of a capacitive sensor-based indexed metrology platform (IMP) is presented. This calibration procedure is based on the readings and geometric features of six capacitive sensors and their targets with nanometer resolution. The final goal of the IMP calibration procedure is to optimize the geometric features of the capacitive sensors and their targets in order to use the optimized data in the verification procedures of PCMMs.

Inertial sensor-based smoother for gait analysis.

PubMed

Suh, Young Soo

2014-12-17

An off-line smoother algorithm is proposed to estimate foot motion using an inertial sensor unit (three-axis gyroscopes and accelerometers) attached to a shoe. The smoother gives more accurate foot motion estimation than filter-based algorithms by using all of the sensor data instead of using the current sensor data. The algorithm consists of two parts. In the first part, a Kalman filter is used to obtain initial foot motion estimation. In the second part, the error in the initial estimation is compensated using a smoother, where the problem is formulated in the quadratic optimization problem. An efficient solution of the quadratic optimization problem is given using the sparse structure. Through experiments, it is shown that the proposed algorithm can estimate foot motion more accurately than a filter-based algorithm with reasonable computation time. In particular, there is significant improvement in the foot motion estimation when the foot is moving off the floor: the z-axis position error squared sum (total time: 3.47 s) when the foot is in the air is 0.0807 m2 (Kalman filter) and 0.0020 m2 (the proposed smoother).

Analysis of a Segmented Annular Coplanar Capacitive Tilt Sensor with Increased Sensitivity

PubMed Central

Guo, Jiahao; Hu, Pengcheng; Tan, Jiubin

2016-01-01

An investigation of a segmented annular coplanar capacitor is presented. We focus on its theoretical model, and a mathematical expression of the capacitance value is derived by solving a Laplace equation with Hankel transform. The finite element method is employed to verify the analytical result. Different control parameters are discussed, and each contribution to the capacitance value of the capacitor is obtained. On this basis, we analyze and optimize the structure parameters of a segmented coplanar capacitive tilt sensor, and three models with different positions of the electrode gap are fabricated and tested. The experimental result shows that the model (whose electrode-gap position is 10 mm from the electrode center) realizes a high sensitivity: 0.129 pF/° with a non-linearity of <0.4% FS (full scale of ±40°). This finding offers plenty of opportunities for various measurement requirements in addition to achieving an optimized structure in practical design. PMID:26805844

Optimal Estimation of Glider’s Underwater Trajectory with Depth-Dependent Correction Using the Navy Coastal Ocean Model with Application to Antisubmarine Warfare

DTIC Science & Technology

2014-09-01

deployed simultaneously. For example, a fleet of gliders would be able to act as an intelligence network by gathering underwater target information ...and to verify our novel method, a glider’s real underwater trajectory information must be obtained by using additional sensors like ADCP or DVL (see...lacks of inexpensive and efficient localization sensors during its subsurface mission. Therefore, knowing its precise underwater position is a

Quantitative Damage Detection and Sparse Sensor Array Optimization of Carbon Fiber Reinforced Resin Composite Laminates for Wind Turbine Blade Structural Health Monitoring

PubMed Central

Li, Xiang; Yang, Zhibo; Chen, Xuefeng

2014-01-01

The active structural health monitoring (SHM) approach for the complex composite laminate structures of wind turbine blades (WTBs), addresses the important and complicated problem of signal noise. After illustrating the wind energy industry's development perspectives and its crucial requirement for SHM, an improved redundant second generation wavelet transform (IRSGWT) pre-processing algorithm based on neighboring coefficients is introduced for feeble signal denoising. The method can avoid the drawbacks of conventional wavelet methods that lose information in transforms and the shortcomings of redundant second generation wavelet (RSGWT) denoising that can lead to error propagation. For large scale WTB composites, how to minimize the number of sensors while ensuring accuracy is also a key issue. A sparse sensor array optimization of composites for WTB applications is proposed that can reduce the number of transducers that must be used. Compared to a full sixteen transducer array, the optimized eight transducer configuration displays better accuracy in identifying the correct position of simulated damage (mass of load) on composite laminates with anisotropic characteristics than a non-optimized array. It can help to guarantee more flexible and qualified monitoring of the areas that more frequently suffer damage. The proposed methods are verified experimentally on specimens of carbon fiber reinforced resin composite laminates. PMID:24763210

Data-driven sensor placement from coherent fluid structures

NASA Astrophysics Data System (ADS)

Manohar, Krithika; Kaiser, Eurika; Brunton, Bingni W.; Kutz, J. Nathan; Brunton, Steven L.

2017-11-01

Optimal sensor placement is a central challenge in the prediction, estimation and control of fluid flows. We reinterpret sensor placement as optimizing discrete samples of coherent fluid structures for full state reconstruction. This permits a drastic reduction in the number of sensors required for faithful reconstruction, since complex fluid interactions can often be described by a small number of coherent structures. Our work optimizes point sensors using the pivoted matrix QR factorization to sample coherent structures directly computed from flow data. We apply this sampling technique in conjunction with various data-driven modal identification methods, including the proper orthogonal decomposition (POD) and dynamic mode decomposition (DMD). In contrast to POD-based sensors, DMD demonstrably enables the optimization of sensors for prediction in systems exhibiting multiple scales of dynamics. Finally, reconstruction accuracy from pivot sensors is shown to be competitive with sensors obtained using traditional computationally prohibitive optimization methods.

Parametric study of sensor placement for vision-based relative navigation system of multiple spacecraft

NASA Astrophysics Data System (ADS)

Jeong, Junho; Kim, Seungkeun; Suk, Jinyoung

2017-12-01

In order to overcome the limited range of GPS-based techniques, vision-based relative navigation methods have recently emerged as alternative approaches for a high Earth orbit (HEO) or deep space missions. Therefore, various vision-based relative navigation systems use for proximity operations between two spacecraft. For the implementation of these systems, a sensor placement problem can occur on the exterior of spacecraft due to its limited space. To deal with the sensor placement, this paper proposes a novel methodology for a vision-based relative navigation based on multiple position sensitive diode (PSD) sensors and multiple infrared beacon modules. For the proposed method, an iterated parametric study is used based on the farthest point optimization (FPO) and a constrained extended Kalman filter (CEKF). Each algorithm is applied to set the location of the sensors and to estimate relative positions and attitudes according to each combination by the PSDs and beacons. After that, scores for the sensor placement are calculated with respect to parameters: the number of the PSDs, number of the beacons, and accuracy of relative estimates. Then, the best scoring candidate is determined for the sensor placement. Moreover, the results of the iterated estimation show that the accuracy improves dramatically, as the number of the PSDs increases from one to three.

Effect of structure variation of the aptamer-DNA duplex probe on the performance of displacement-based electrochemical aptamer sensors.

PubMed

Pang, Jie; Zhang, Ziping; Jin, Haizhu

2016-03-15

Electrochemical aptamer-based (E-AB) sensors employing electrode-immobilized, redox-tagged aptamer probes have emerged as a promising platform for the sensitive and quick detection of target analytes ranging from small molecules to proteins. Signal generation in this class of sensor is linked to change in electron transfer efficiency upon binding-induced change in flexibility/conformation of the aptamer probe. Because of this signaling mechanism, signal gains of these sensors can be improved by employing a displacement-based recognition system, which links target binding with a large-scale flexibility/conformation shift from the aptamer-DNA duplex to the single-stranded DNA or the native aptamer. Despite the relatively large number of displacement-based E-AB sensor samples, little attention has been paid to the structure variation of the aptamer-DNA duplex probe. Here we detail the effects of complementary length and position of the aptamer-DNA duplex probe on the performance of a model displacement-based E-AB sensor for ATP. We find that, greater background suppression and signal gain are observed with longer complementary length of the aptamer-DNA duplex probe. However, sensor equilibration time slows monotonically with increasing complementary length; and with too many target binding sites in aptamer sequence being occupied by the complementary DNA, the aptamer-target binding does not occur and no signal gain observed. We also demonstrate that signal gain of the displacement-based E-AB sensor is strongly dependent on the complementary position of the aptamer-DNA duplex probe, with complementary position located at the electrode-attached or redox-tagged end of the duplex probe, larger background suppression and signal increase than that of the middle position are observed. These results highlight the importance of rational structure design of the aptamer-DNA duplex probe and provide new insights into the optimization of displacement-based E-AB sensors. Copyright © 2015 Elsevier B.V. All rights reserved.

Analysis of a Smartphone-Based Architecture with Multiple Mobility Sensors for Fall Detection

PubMed Central

Santoyo-Ramón, Jose Antonio; Cano-García, Jose Manuel

2016-01-01

During the last years, many research efforts have been devoted to the definition of Fall Detection Systems (FDSs) that benefit from the inherent computing, communication and sensing capabilities of smartphones. However, employing a smartphone as the unique sensor in a FDS application entails several disadvantages as long as an accurate characterization of the patient’s mobility may force to transport this personal device on an unnatural position. This paper presents a smartphone-based architecture for the automatic detection of falls. The system incorporates a set of small sensing motes that can communicate with the smartphone to help in the fall detection decision. The deployed architecture is systematically evaluated in a testbed with experimental users in order to determine the number and positions of the sensors that optimize the effectiveness of the FDS, as well as to assess the most convenient role of the smartphone in the architecture. PMID:27930736

Analysis of a Smartphone-Based Architecture with Multiple Mobility Sensors for Fall Detection.

PubMed

Casilari, Eduardo; Santoyo-Ramón, Jose Antonio; Cano-García, Jose Manuel

2016-01-01

During the last years, many research efforts have been devoted to the definition of Fall Detection Systems (FDSs) that benefit from the inherent computing, communication and sensing capabilities of smartphones. However, employing a smartphone as the unique sensor in a FDS application entails several disadvantages as long as an accurate characterization of the patient's mobility may force to transport this personal device on an unnatural position. This paper presents a smartphone-based architecture for the automatic detection of falls. The system incorporates a set of small sensing motes that can communicate with the smartphone to help in the fall detection decision. The deployed architecture is systematically evaluated in a testbed with experimental users in order to determine the number and positions of the sensors that optimize the effectiveness of the FDS, as well as to assess the most convenient role of the smartphone in the architecture.

Theoretical Noise Analysis on a Position-sensitive Metallic Magnetic Calorimeter

NASA Technical Reports Server (NTRS)

Smith, Stephen J.

2007-01-01

We report on the theoretical noise analysis for a position-sensitive Metallic Magnetic Calorimeter (MMC), consisting of MMC read-out at both ends of a large X-ray absorber. Such devices are under consideration as alternatives to other cryogenic technologies for future X-ray astronomy missions. We use a finite-element model (FEM) to numerically calculate the signal and noise response at the detector outputs and investigate the correlations between the noise measured at each MMC coupled by the absorber. We then calculate, using the optimal filter concept, the theoretical energy and position resolution across the detector and discuss the trade-offs involved in optimizing the detector design for energy resolution, position resolution and count rate. The results show, theoretically, the position-sensitive MMC concept offers impressive spectral and spatial resolving capabilities compared to pixel arrays and similar position-sensitive cryogenic technologies using Transition Edge Sensor (TES) read-out.

Optimal Sensor Allocation for Fault Detection and Isolation

NASA Technical Reports Server (NTRS)

Azam, Mohammad; Pattipati, Krishna; Patterson-Hine, Ann

2004-01-01

Automatic fault diagnostic schemes rely on various types of sensors (e.g., temperature, pressure, vibration, etc) to measure the system parameters. Efficacy of a diagnostic scheme is largely dependent on the amount and quality of information available from these sensors. The reliability of sensors, as well as the weight, volume, power, and cost constraints, often makes it impractical to monitor a large number of system parameters. An optimized sensor allocation that maximizes the fault diagnosibility, subject to specified weight, volume, power, and cost constraints is required. Use of optimal sensor allocation strategies during the design phase can ensure better diagnostics at a reduced cost for a system incorporating a high degree of built-in testing. In this paper, we propose an approach that employs multiple fault diagnosis (MFD) and optimization techniques for optimal sensor placement for fault detection and isolation (FDI) in complex systems. Keywords: sensor allocation, multiple fault diagnosis, Lagrangian relaxation, approximate belief revision, multidimensional knapsack problem.

Implementation of Complex Signal Processing Algorithms for Position-Sensitive Microcalorimeters

NASA Technical Reports Server (NTRS)

Smith, Stephen J.

2008-01-01

We have recently reported on a theoretical digital signal-processing algorithm for improved energy and position resolution in position-sensitive, transition-edge sensor (POST) X-ray detectors [Smith et al., Nucl, lnstr and Meth. A 556 (2006) 2371. PoST's consists of one or more transition-edge sensors (TES's) on a large continuous or pixellated X-ray absorber and are under development as an alternative to arrays of single pixel TES's. PoST's provide a means to increase the field-of-view for the fewest number of read-out channels. In this contribution we extend the theoretical correlated energy position optimal filter (CEPOF) algorithm (originally developed for 2-TES continuous absorber PoST's) to investigate the practical implementation on multi-pixel single TES PoST's or Hydras. We use numerically simulated data for a nine absorber device, which includes realistic detector noise, to demonstrate an iterative scheme that enables convergence on the correct photon absorption position and energy without any a priori assumptions. The position sensitivity of the CEPOF implemented on simulated data agrees very well with the theoretically predicted resolution. We discuss practical issues such as the impact of random arrival phase of the measured data on the performance of the CEPOF. The CEPOF algorithm demonstrates that full-width-at- half-maximum energy resolution of < 8 eV coupled with position-sensitivity down to a few 100 eV should be achievable for a fully optimized device.

Robust electromagnetically guided endoscopic procedure using enhanced particle swarm optimization for multimodal information fusion.

PubMed

Luo, Xiongbiao; Wan, Ying; He, Xiangjian

2015-04-01

Electromagnetically guided endoscopic procedure, which aims at accurately and robustly localizing the endoscope, involves multimodal sensory information during interventions. However, it still remains challenging in how to integrate these information for precise and stable endoscopic guidance. To tackle such a challenge, this paper proposes a new framework on the basis of an enhanced particle swarm optimization method to effectively fuse these information for accurate and continuous endoscope localization. The authors use the particle swarm optimization method, which is one of stochastic evolutionary computation algorithms, to effectively fuse the multimodal information including preoperative information (i.e., computed tomography images) as a frame of reference, endoscopic camera videos, and positional sensor measurements (i.e., electromagnetic sensor outputs). Since the evolutionary computation method usually limits its possible premature convergence and evolutionary factors, the authors introduce the current (endoscopic camera and electromagnetic sensor's) observation to boost the particle swarm optimization and also adaptively update evolutionary parameters in accordance with spatial constraints and the current observation, resulting in advantageous performance in the enhanced algorithm. The experimental results demonstrate that the authors' proposed method provides a more accurate and robust endoscopic guidance framework than state-of-the-art methods. The average guidance accuracy of the authors' framework was about 3.0 mm and 5.6° while the previous methods show at least 3.9 mm and 7.0°. The average position and orientation smoothness of their method was 1.0 mm and 1.6°, which is significantly better than the other methods at least with (2.0 mm and 2.6°). Additionally, the average visual quality of the endoscopic guidance was improved to 0.29. A robust electromagnetically guided endoscopy framework was proposed on the basis of an enhanced particle swarm optimization method with using the current observation information and adaptive evolutionary factors. The authors proposed framework greatly reduced the guidance errors from (4.3, 7.8) to (3.0 mm, 5.6°), compared to state-of-the-art methods.

Ultra-precise micro-motion stage for optical scanning test

NASA Astrophysics Data System (ADS)

Chen, Wen; Zhang, Jianhuan; Jiang, Nan

2009-05-01

This study aims at the application of optical sensing technology in a 2D flexible hinge test stage. Optical fiber sensor which is manufactured taking advantage of the various unique properties of optical fiber, such as good electric insulation properties, resistance of electromagnetic disturbance, sparkless property and availability in flammable and explosive environment, has lots of good properties, such as high accuracy and wide dynamic range, repeatable, etc. and is applied in 2D flexible hinge stage driven by PZT. Several micro-bending structures are designed utilizing the characteristics of the flexible hinge stage. And through experiments, the optimal micro-bending tooth structure and the scope of displacement sensor trip under this optimal micro-bending tooth structure are derived. These experiments demonstrate that the application of optical fiber displacement sensor in 2D flexible hinge stage driven by PZT substantially broadens the dynamic testing range and improves the sensitivity of this apparatus. Driving accuracy and positioning stability are enhanced as well. [1,2

Acoustic Sensor Network Design for Position Estimation

DTIC Science & Technology

2009-05-01

A., Pollock, S., Netter, B., and Low, B. S. 2005. Anisogamy, expenditure of reproductive effort, and the optimality of having two sexes. Operations...Research 53, 3, 560–567. Evans, M., Hastings, N., and Peacock , B. 2000. Statistical distributions. Ed. Wiley & Sons. New York. Feeney, L. and Nilsson, M

Optimal Measurement Conditions for Spatiotemporal EEG/MEG Source Analysis.

ERIC Educational Resources Information Center

Huizenga, Hilde M.; Heslenfeld, Dirk J.; Molenaar, Peter C. M.

2002-01-01

Developed a method to determine the required number and position of sensors for human brain electromagnetic source analysis. Studied the method through a simulation study and an empirical study on visual evoked potentials in one adult male. Results indicate the method is fast and reliable and improves source precision. (SLD)

SPOT-A SENSOR PLACEMENT OPTIMIZATION TOOL FOR ...

EPA Pesticide Factsheets

journal article This paper presents SPOT, a Sensor Placement Optimization Tool. SPOT provides a toolkit that facilitates research in sensor placement optimization and enables the practical application of sensor placement solvers to real-world CWS design applications. This paper provides an overview of SPOT’s key features, and then illustrates how this tool can be flexibly applied to solve a variety of different types of sensor placement problems.

An FPGA Noise Resistant Digital Temperature Sensor with Auto Calibration

DTIC Science & Technology

2012-03-01

temperature sensor [6] . . . . . . . . . . . . . . 14 9 Two different digital temperature sensor placement algorithms: (a) Grid placement (b) Optimal...create a grid over the FPGA. While this method works reasonably well, it requires many sensors, some of which are unnecessary. The optimal placement, on...temperature sensor placement algorithms: (a) Grid placement (b) Optimal Placement [7] 16 2.4 Summary Integrated circuits’ sensitivity to temperatures has

3D sensor placement strategy using the full-range pheromone ant colony system

NASA Astrophysics Data System (ADS)

Shuo, Feng; Jingqing, Jia

2016-07-01

An optimized sensor placement strategy will be extremely beneficial to ensure the safety and cost reduction considerations of structural health monitoring (SHM) systems. The sensors must be placed such that important dynamic information is obtained and the number of sensors is minimized. The practice is to select individual sensor directions by several 1D sensor methods and the triaxial sensors are placed in these directions for monitoring. However, this may lead to non-optimal placement of many triaxial sensors. In this paper, a new method, called FRPACS, is proposed based on the ant colony system (ACS) to solve the optimal placement of triaxial sensors. The triaxial sensors are placed as single units in an optimal fashion. And then the new method is compared with other algorithms using Dalian North Bridge. The computational precision and iteration efficiency of the FRPACS has been greatly improved compared with the original ACS and EFI method.

Comparison of Artificial Immune System and Particle Swarm Optimization Techniques for Error Optimization of Machine Vision Based Tool Movements

NASA Astrophysics Data System (ADS)

Mahapatra, Prasant Kumar; Sethi, Spardha; Kumar, Amod

2015-10-01

In conventional tool positioning technique, sensors embedded in the motion stages provide the accurate tool position information. In this paper, a machine vision based system and image processing technique for motion measurement of lathe tool from two-dimensional sequential images captured using charge coupled device camera having a resolution of 250 microns has been described. An algorithm was developed to calculate the observed distance travelled by the tool from the captured images. As expected, error was observed in the value of the distance traversed by the tool calculated from these images. Optimization of errors due to machine vision system, calibration, environmental factors, etc. in lathe tool movement was carried out using two soft computing techniques, namely, artificial immune system (AIS) and particle swarm optimization (PSO). The results show better capability of AIS over PSO.

Calibration and optimization of an x-ray bendable mirror using displacement-measuring sensors.

PubMed

Vannoni, Maurizio; Martín, Idoia Freijo; Music, Valerija; Sinn, Harald

2016-07-25

We propose a method to control and to adjust in a closed-loop a bendable x-ray mirror using displacement-measuring devices. For this purpose, the usage of capacitive and interferometric sensors is investigated and compared. We installed the sensors in a bender setup and used them to continuously measure the position and shape of the mirror in the lab. The sensors are vacuum-compatible such that the same concept can also be applied in final conditions. The measurement is used to keep the calibration of the system and to create a closed-loop control compensating for external influences: in a demonstration measurement, using a 950 mm long bendable mirror, the mirror sagitta is kept stable inside a range of 10 nm Peak-To-Valley (P-V).

A Survey on Optimal Signal Processing Techniques Applied to Improve the Performance of Mechanical Sensors in Automotive Applications

PubMed Central

Hernandez, Wilmar

2007-01-01

In this paper a survey on recent applications of optimal signal processing techniques to improve the performance of mechanical sensors is made. Here, a comparison between classical filters and optimal filters for automotive sensors is made, and the current state of the art of the application of robust and optimal control and signal processing techniques to the design of the intelligent (or smart) sensors that today's cars need is presented through several experimental results that show that the fusion of intelligent sensors and optimal signal processing techniques is the clear way to go. However, the switch between the traditional methods of designing automotive sensors and the new ones cannot be done overnight because there are some open research issues that have to be solved. This paper draws attention to one of the open research issues and tries to arouse researcher's interest in the fusion of intelligent sensors and optimal signal processing techniques.

Dynamic Sensor Tasking for Space Situational Awareness via Reinforcement Learning

NASA Astrophysics Data System (ADS)

Linares, R.; Furfaro, R.

2016-09-01

This paper studies the Sensor Management (SM) problem for optical Space Object (SO) tracking. The tasking problem is formulated as a Markov Decision Process (MDP) and solved using Reinforcement Learning (RL). The RL problem is solved using the actor-critic policy gradient approach. The actor provides a policy which is random over actions and given by a parametric probability density function (pdf). The critic evaluates the policy by calculating the estimated total reward or the value function for the problem. The parameters of the policy action pdf are optimized using gradients with respect to the reward function. Both the critic and the actor are modeled using deep neural networks (multi-layer neural networks). The policy neural network takes the current state as input and outputs probabilities for each possible action. This policy is random, and can be evaluated by sampling random actions using the probabilities determined by the policy neural network's outputs. The critic approximates the total reward using a neural network. The estimated total reward is used to approximate the gradient of the policy network with respect to the network parameters. This approach is used to find the non-myopic optimal policy for tasking optical sensors to estimate SO orbits. The reward function is based on reducing the uncertainty for the overall catalog to below a user specified uncertainty threshold. This work uses a 30 km total position error for the uncertainty threshold. This work provides the RL method with a negative reward as long as any SO has a total position error above the uncertainty threshold. This penalizes policies that take longer to achieve the desired accuracy. A positive reward is provided when all SOs are below the catalog uncertainty threshold. An optimal policy is sought that takes actions to achieve the desired catalog uncertainty in minimum time. This work trains the policy in simulation by letting it task a single sensor to "learn" from its performance. The proposed approach for the SM problem is tested in simulation and good performance is found using the actor-critic policy gradient method.

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.

Wireless Sensor Network Optimization: Multi-Objective Paradigm.

PubMed

Iqbal, Muhammad; Naeem, Muhammad; Anpalagan, Alagan; Ahmed, Ashfaq; Azam, Muhammad

2015-07-20

Optimization problems relating to wireless sensor network planning, design, deployment and operation often give rise to multi-objective optimization formulations where multiple desirable objectives compete with each other and the decision maker has to select one of the tradeoff solutions. These multiple objectives may or may not conflict with each other. Keeping in view the nature of the application, the sensing scenario and input/output of the problem, the type of optimization problem changes. To address different nature of optimization problems relating to wireless sensor network design, deployment, operation, planing and placement, there exist a plethora of optimization solution types. We review and analyze different desirable objectives to show whether they conflict with each other, support each other or they are design dependent. We also present a generic multi-objective optimization problem relating to wireless sensor network which consists of input variables, required output, objectives and constraints. A list of constraints is also presented to give an overview of different constraints which are considered while formulating the optimization problems in wireless sensor networks. Keeping in view the multi facet coverage of this article relating to multi-objective optimization, this will open up new avenues of research in the area of multi-objective optimization relating to wireless sensor networks.

Analyzing the multiple-target-multiple-agent scenario using optimal assignment algorithms

NASA Astrophysics Data System (ADS)

Kwok, Kwan S.; Driessen, Brian J.; Phillips, Cynthia A.; Tovey, Craig A.

1997-09-01

This work considers the problem of maximum utilization of a set of mobile robots with limited sensor-range capabilities and limited travel distances. The robots are initially in random positions. A set of robots properly guards or covers a region if every point within the region is within the effective sensor range of at least one vehicle. We wish to move the vehicles into surveillance positions so as to guard or cover a region, while minimizing the maximum distance traveled by any vehicle. This problem can be formulated as an assignment problem, in which we must optimally decide which robot to assign to which slot of a desired matrix of grid points. The cost function is the maximum distance traveled by any robot. Assignment problems can be solved very efficiently. Solution times for one hundred robots took only seconds on a silicon graphics crimson workstation. The initial positions of all the robots can be sampled by a central base station and their newly assigned positions communicated back to the robots. Alternatively, the robots can establish their own coordinate system with the origin fixed at one of the robots and orientation determined by the compass bearing of another robot relative to this robot. This paper presents example solutions to the multiple-target-multiple-agent scenario using a matching algorithm. Two separate cases with one hundred agents in each were analyzed using this method. We have found these mobile robot problems to be a very interesting application of network optimization methods, and we expect this to be a fruitful area for future research.

Topology Optimization for Energy Management in Underwater Sensor Networks

DTIC Science & Technology

2015-02-01

1 To appear in International Journal of Control as a regular paper Topology Optimization for Energy Management in Underwater Sensor Networks ⋆ Devesh...K. Jha1 Thomas A. Wettergren2 Asok Ray1 Kushal Mukherjee3 Keywords: Underwater Sensor Network , Energy Management, Pareto Optimization, Adaptation...Optimization for Energy Management in Underwater Sensor Networks 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d

Capacitively coupled RF voltage probe having optimized flux linkage

DOEpatents

Moore, James A.; Sparks, Dennis O.

1999-02-02

An RF sensor having a novel current sensing probe and a voltage sensing probe to measure voltage and current. The current sensor is disposed in a transmission line to link all of the flux generated by the flowing current in order to obtain an accurate measurement. The voltage sensor is a flat plate which operates as a capacitive plate to sense voltage on a center conductor of the transmission line, in which the measured voltage is obtained across a resistance leg of a R-C differentiator circuit formed by the characteristic impedance of a connecting transmission line and a capacitance of the plate, which is positioned proximal to the center conductor.

Development of Position-sensitive Transition-edge Sensor X-ray Detectors

NASA Technical Reports Server (NTRS)

Smith, S. J.; Bandler, S. R.; Brekosky, R. P.; Brown, A.-D.; Chervenak, J. A.; Eckard, M. E.; Finkbeiner, F. M.; Kelley, R. L.; Kilbourne, C. A.; Porter, F. s.;

Improving geolocation and spatial accuracies with the modular integrated avionics group (MIAG)

NASA Astrophysics Data System (ADS)

Johnson, Einar; Souter, Keith

1996-05-01

The modular integrated avionics group (MIAG) is a single unit approach to combining position, inertial and baro-altitude/air data sensors to provide optimized navigation, guidance and control performance. Lear Astronics Corporation is currently working within the navigation community to upgrade existing MIAG performance with precise GPS positioning mechanization tightly integrated with inertial, baro and other sensors. Among the immediate benefits are the following: (1) accurate target location in dynamic conditions; (2) autonomous launch and recovery using airborne avionics only; (3) precise flight path guidance; and (4) improved aircraft and payload stability information. This paper will focus on the impact of using the MIAG with its multimode navigation accuracies on the UAV targeting mission. Gimbaled electro-optical sensors mounted on a UAV can be used to determine ground coordinates of a target at the center of the field of view by a series of vector rotation and scaling computations. The accuracy of the computed target coordinates is dependent on knowing the UAV position and the UAV-to-target offset computation. Astronics performed a series of simulations to evaluate the effects that the improved angular and position data available from the MIAG have on target coordinate accuracy.

Simulated and Real Sheet-of-Light 3D Object Scanning Using a-Si:H Thin Film PSD Arrays.

PubMed

Contreras, Javier; Tornero, Josep; Ferreira, Isabel; Martins, Rodrigo; Gomes, Luis; Fortunato, Elvira

2015-11-30

A MATLAB/SIMULINK software simulation model (structure and component blocks) has been constructed in order to view and analyze the potential of the PSD (Position Sensitive Detector) array concept technology before it is further expanded or developed. This simulation allows changing most of its parameters, such as the number of elements in the PSD array, the direction of vision, the viewing/scanning angle, the object rotation, translation, sample/scan/simulation time, etc. In addition, results show for the first time the possibility of scanning an object in 3D when using an a-Si:H thin film 128 PSD array sensor and hardware/software system. Moreover, this sensor technology is able to perform these scans and render 3D objects at high speeds and high resolutions when using a sheet-of-light laser within a triangulation platform. As shown by the simulation, a substantial enhancement in 3D object profile image quality and realism can be achieved by increasing the number of elements of the PSD array sensor as well as by achieving an optimal position response from the sensor since clearly the definition of the 3D object profile depends on the correct and accurate position response of each detector as well as on the size of the PSD array.

Sensor Location Problem Optimization for Traffic Network with Different Spatial Distributions of Traffic Information.

PubMed

Bao, Xu; Li, Haijian; Qin, Lingqiao; Xu, Dongwei; Ran, Bin; Rong, Jian

2016-10-27

To obtain adequate traffic information, the density of traffic sensors should be sufficiently high to cover the entire transportation network. However, deploying sensors densely over the entire network may not be realistic for practical applications due to the budgetary constraints of traffic management agencies. This paper describes several possible spatial distributions of traffic information credibility and proposes corresponding different sensor information credibility functions to describe these spatial distribution properties. A maximum benefit model and its simplified model are proposed to solve the traffic sensor location problem. The relationships between the benefit and the number of sensors are formulated with different sensor information credibility functions. Next, expanding models and algorithms in analytic results are performed. For each case, the maximum benefit, the optimal number and spacing of sensors are obtained and the analytic formulations of the optimal sensor locations are derived as well. Finally, a numerical example is proposed to verify the validity and availability of the proposed models for solving a network sensor location problem. The results show that the optimal number of sensors of segments with different model parameters in an entire freeway network can be calculated. Besides, it can also be concluded that the optimal sensor spacing is independent of end restrictions but dependent on the values of model parameters that represent the physical conditions of sensors and roads.

Sensor Location Problem Optimization for Traffic Network with Different Spatial Distributions of Traffic Information

PubMed Central

Bao, Xu; Li, Haijian; Qin, Lingqiao; Xu, Dongwei; Ran, Bin; Rong, Jian

2016-01-01

To obtain adequate traffic information, the density of traffic sensors should be sufficiently high to cover the entire transportation network. However, deploying sensors densely over the entire network may not be realistic for practical applications due to the budgetary constraints of traffic management agencies. This paper describes several possible spatial distributions of traffic information credibility and proposes corresponding different sensor information credibility functions to describe these spatial distribution properties. A maximum benefit model and its simplified model are proposed to solve the traffic sensor location problem. The relationships between the benefit and the number of sensors are formulated with different sensor information credibility functions. Next, expanding models and algorithms in analytic results are performed. For each case, the maximum benefit, the optimal number and spacing of sensors are obtained and the analytic formulations of the optimal sensor locations are derived as well. Finally, a numerical example is proposed to verify the validity and availability of the proposed models for solving a network sensor location problem. The results show that the optimal number of sensors of segments with different model parameters in an entire freeway network can be calculated. Besides, it can also be concluded that the optimal sensor spacing is independent of end restrictions but dependent on the values of model parameters that represent the physical conditions of sensors and roads. PMID:27801794

Wearable Performance Devices in Sports Medicine.

PubMed

Li, Ryan T; Kling, Scott R; Salata, Michael J; Cupp, Sean A; Sheehan, Joseph; Voos, James E

2016-01-01

Wearable performance devices and sensors are becoming more readily available to the general population and athletic teams. Advances in technology have allowed individual endurance athletes, sports teams, and physicians to monitor functional movements, workloads, and biometric markers to maximize performance and minimize injury. Movement sensors include pedometers, accelerometers/gyroscopes, and global positioning satellite (GPS) devices. Physiologic sensors include heart rate monitors, sleep monitors, temperature sensors, and integrated sensors. The purpose of this review is to familiarize health care professionals and team physicians with the various available types of wearable sensors, discuss their current utilization, and present future applications in sports medicine. Data were obtained from peer-reviewed literature through a search of the PubMed database. Included studies searched development, outcomes, and validation of wearable performance devices such as GPS, accelerometers, and physiologic monitors in sports. Clinical review. Level 4. Wearable sensors provide a method of monitoring real-time physiologic and movement parameters during training and competitive sports. These parameters can be used to detect position-specific patterns in movement, design more efficient sports-specific training programs for performance optimization, and screen for potential causes of injury. More recent advances in movement sensors have improved accuracy in detecting high-acceleration movements during competitive sports. Wearable devices are valuable instruments for the improvement of sports performance. Evidence for use of these devices in professional sports is still limited. Future developments are needed to establish training protocols using data from wearable devices. © 2015 The Author(s).

Wearable Performance Devices in Sports Medicine

PubMed Central

Li, Ryan T.; Kling, Scott R.; Salata, Michael J.; Cupp, Sean A.; Sheehan, Joseph; Voos, James E.

2016-01-01

Context: Wearable performance devices and sensors are becoming more readily available to the general population and athletic teams. Advances in technology have allowed individual endurance athletes, sports teams, and physicians to monitor functional movements, workloads, and biometric markers to maximize performance and minimize injury. Movement sensors include pedometers, accelerometers/gyroscopes, and global positioning satellite (GPS) devices. Physiologic sensors include heart rate monitors, sleep monitors, temperature sensors, and integrated sensors. The purpose of this review is to familiarize health care professionals and team physicians with the various available types of wearable sensors, discuss their current utilization, and present future applications in sports medicine. Evidence Acquisition: Data were obtained from peer-reviewed literature through a search of the PubMed database. Included studies searched development, outcomes, and validation of wearable performance devices such as GPS, accelerometers, and physiologic monitors in sports. Study Design: Clinical review. Level of Evidence: Level 4. Results: Wearable sensors provide a method of monitoring real-time physiologic and movement parameters during training and competitive sports. These parameters can be used to detect position-specific patterns in movement, design more efficient sports-specific training programs for performance optimization, and screen for potential causes of injury. More recent advances in movement sensors have improved accuracy in detecting high-acceleration movements during competitive sports. Conclusion: Wearable devices are valuable instruments for the improvement of sports performance. Evidence for use of these devices in professional sports is still limited. Future developments are needed to establish training protocols using data from wearable devices. PMID:26733594

A Bayesian Approach for Sensor Optimisation in Impact Identification

PubMed Central

Mallardo, Vincenzo; Sharif Khodaei, Zahra; Aliabadi, Ferri M. H.

2016-01-01

This paper presents a Bayesian approach for optimizing the position of sensors aimed at impact identification in composite structures under operational conditions. The uncertainty in the sensor data has been represented by statistical distributions of the recorded signals. An optimisation strategy based on the genetic algorithm is proposed to find the best sensor combination aimed at locating impacts on composite structures. A Bayesian-based objective function is adopted in the optimisation procedure as an indicator of the performance of meta-models developed for different sensor combinations to locate various impact events. To represent a real structure under operational load and to increase the reliability of the Structural Health Monitoring (SHM) system, the probability of malfunctioning sensors is included in the optimisation. The reliability and the robustness of the procedure is tested with experimental and numerical examples. Finally, the proposed optimisation algorithm is applied to a composite stiffened panel for both the uniform and non-uniform probability of impact occurrence. PMID:28774064

Wireless Sensor Network Optimization: Multi-Objective Paradigm

PubMed Central

Iqbal, Muhammad; Naeem, Muhammad; Anpalagan, Alagan; Ahmed, Ashfaq; Azam, Muhammad

2015-01-01

Optimization problems relating to wireless sensor network planning, design, deployment and operation often give rise to multi-objective optimization formulations where multiple desirable objectives compete with each other and the decision maker has to select one of the tradeoff solutions. These multiple objectives may or may not conflict with each other. Keeping in view the nature of the application, the sensing scenario and input/output of the problem, the type of optimization problem changes. To address different nature of optimization problems relating to wireless sensor network design, deployment, operation, planing and placement, there exist a plethora of optimization solution types. We review and analyze different desirable objectives to show whether they conflict with each other, support each other or they are design dependent. We also present a generic multi-objective optimization problem relating to wireless sensor network which consists of input variables, required output, objectives and constraints. A list of constraints is also presented to give an overview of different constraints which are considered while formulating the optimization problems in wireless sensor networks. Keeping in view the multi facet coverage of this article relating to multi-objective optimization, this will open up new avenues of research in the area of multi-objective optimization relating to wireless sensor networks. PMID:26205271

Ka-Band Autonomous Formation Flying Sensor

NASA Technical Reports Server (NTRS)

Tien, Jeffrey; Purcell, George, Jr.; Srinivasan, Jeffrey; Ciminera, Michael; Srinivasan, Meera; Meehan, Thomas; Young, Lawrence; Aung, MiMi; Amaro, Luis; Chong, Yong;

The optimal location of piezoelectric actuators and sensors for vibration control of plates

NASA Astrophysics Data System (ADS)

Kumar, K. Ramesh; Narayanan, S.

2007-12-01

This paper considers the optimal placement of collocated piezoelectric actuator-sensor pairs on a thin plate using a model-based linear quadratic regulator (LQR) controller. LQR performance is taken as objective for finding the optimal location of sensor-actuator pairs. The problem is formulated using the finite element method (FEM) as multi-input-multi-output (MIMO) model control. The discrete optimal sensor and actuator location problem is formulated in the framework of a zero-one optimization problem. A genetic algorithm (GA) is used to solve the zero-one optimization problem. Different classical control strategies like direct proportional feedback, constant-gain negative velocity feedback and the LQR optimal control scheme are applied to study the control effectiveness.

A Nano-Thin Film-Based Prototype QCM Sensor Array for Monitoring Human Breath and Respiratory Patterns.

PubMed

Selyanchyn, Roman; Wakamatsu, Shunichi; Hayashi, Kenshi; Lee, Seung-Woo

2015-07-31

Quartz crystal microbalance (QCM) sensor array was developed for multi-purpose human respiration assessment. The sensor system was designed to provide feedback for human respiration. Thorough optimization of measurement conditions: air flow, temperature in the QCM chamber, frequency measurement rate, and electrode position regarding to the gas flow-was performed. As shown, acquisition of respiratory parameters (rate and respiratory pattern) could be achieved even with a single electrode used in the system. The prototype system contains eight available QCM channels that can be potentially used for selective responses to certain breath chemicals. At present, the prototype machine is ready for the assessment of respiratory functions in larger populations in order to gain statistical validation. To the best of our knowledge, the developed prototype is the only respiratory assessment system based on surface modified QCM sensors.

An Extended Kalman Filter-Based Attitude Tracking Algorithm for Star Sensors

PubMed Central

Li, Jian; Wei, Xinguo; Zhang, Guangjun

2017-01-01

Efficiency and reliability are key issues when a star sensor operates in tracking mode. In the case of high attitude dynamics, the performance of existing attitude tracking algorithms degenerates rapidly. In this paper an extended Kalman filtering-based attitude tracking algorithm is presented. The star sensor is modeled as a nonlinear stochastic system with the state estimate providing the three degree-of-freedom attitude quaternion and angular velocity. The star positions in the star image are predicted and measured to estimate the optimal attitude. Furthermore, all the cataloged stars observed in the sensor field-of-view according the predicted image motion are accessed using a catalog partition table to speed up the tracking, called star mapping. Software simulation and night-sky experiment are performed to validate the efficiency and reliability of the proposed method. PMID:28825684

An Extended Kalman Filter-Based Attitude Tracking Algorithm for Star Sensors.

PubMed

Li, Jian; Wei, Xinguo; Zhang, Guangjun

2017-08-21

Efficiency and reliability are key issues when a star sensor operates in tracking mode. In the case of high attitude dynamics, the performance of existing attitude tracking algorithms degenerates rapidly. In this paper an extended Kalman filtering-based attitude tracking algorithm is presented. The star sensor is modeled as a nonlinear stochastic system with the state estimate providing the three degree-of-freedom attitude quaternion and angular velocity. The star positions in the star image are predicted and measured to estimate the optimal attitude. Furthermore, all the cataloged stars observed in the sensor field-of-view according the predicted image motion are accessed using a catalog partition table to speed up the tracking, called star mapping. Software simulation and night-sky experiment are performed to validate the efficiency and reliability of the proposed method.

Joint Optimal Placement and Energy Allocation of Underwater Sensors in a Tree Topology

DTIC Science & Technology

2014-03-10

underwater acoustic sensor nodes with respect to the capacity of the wireless links between the... underwater acoustic sensor nodes with respect to the capacity of the wireless links between the nodes. We assumed that the energy consumption of...nodes’ optimal placements. We achieve the optimal placement of the underwater acoustic sensor nodes with respect to the capacity of the wireless

Developing Fast Fluorescent Protein Voltage Sensors by Optimizing FRET Interactions

PubMed Central

Sung, Uhna; Sepehri-Rad, Masoud; Piao, Hong Hua; Jin, Lei; Hughes, Thomas; Cohen, Lawrence B.; Baker, Bradley J.

2015-01-01

FRET (Förster Resonance Energy Transfer)-based protein voltage sensors can be useful for monitoring neuronal activity in vivo because the ratio of signals between the donor and acceptor pair reduces common sources of noise such as heart beat artifacts. We improved the performance of FRET based genetically encoded Fluorescent Protein (FP) voltage sensors by optimizing the location of donor and acceptor FPs flanking the voltage sensitive domain of the Ciona intestinalis voltage sensitive phosphatase. First, we created 39 different “Nabi1” constructs by positioning the donor FP, UKG, at 8 different locations downstream of the voltage-sensing domain and the acceptor FP, mKO, at 6 positions upstream. Several of these combinations resulted in large voltage dependent signals and relatively fast kinetics. Nabi1 probes responded with signal size up to 11% ΔF/F for a 100 mV depolarization and fast response time constants both for signal activation (~2 ms) and signal decay (~3 ms). We improved expression in neuronal cells by replacing the mKO and UKG FRET pair with Clover (donor FP) and mRuby2 (acceptor FP) to create Nabi2 probes. Nabi2 probes also had large signals and relatively fast time constants in HEK293 cells. In primary neuronal culture, a Nabi2 probe was able to differentiate individual action potentials at 45 Hz. PMID:26587834

Parameter Selection and Performance Comparison of Particle Swarm Optimization in Sensor Networks Localization.

PubMed

Cui, Huanqing; Shu, Minglei; Song, Min; Wang, Yinglong

2017-03-01

Localization is a key technology in wireless sensor networks. Faced with the challenges of the sensors' memory, computational constraints, and limited energy, particle swarm optimization has been widely applied in the localization of wireless sensor networks, demonstrating better performance than other optimization methods. In particle swarm optimization-based localization algorithms, the variants and parameters should be chosen elaborately to achieve the best performance. However, there is a lack of guidance on how to choose these variants and parameters. Further, there is no comprehensive performance comparison among particle swarm optimization algorithms. The main contribution of this paper is three-fold. First, it surveys the popular particle swarm optimization variants and particle swarm optimization-based localization algorithms for wireless sensor networks. Secondly, it presents parameter selection of nine particle swarm optimization variants and six types of swarm topologies by extensive simulations. Thirdly, it comprehensively compares the performance of these algorithms. The results show that the particle swarm optimization with constriction coefficient using ring topology outperforms other variants and swarm topologies, and it performs better than the second-order cone programming algorithm.

Dynamic Hierarchical Energy-Efficient Method Based on Combinatorial Optimization for Wireless Sensor Networks.

PubMed

Chang, Yuchao; Tang, Hongying; Cheng, Yongbo; Zhao, Qin; Yuan, Baoqing Li andXiaobing

2017-07-19

Routing protocols based on topology control are significantly important for improving network longevity in wireless sensor networks (WSNs). Traditionally, some WSN routing protocols distribute uneven network traffic load to sensor nodes, which is not optimal for improving network longevity. Differently to conventional WSN routing protocols, we propose a dynamic hierarchical protocol based on combinatorial optimization (DHCO) to balance energy consumption of sensor nodes and to improve WSN longevity. For each sensor node, the DHCO algorithm obtains the optimal route by establishing a feasible routing set instead of selecting the cluster head or the next hop node. The process of obtaining the optimal route can be formulated as a combinatorial optimization problem. Specifically, the DHCO algorithm is carried out by the following procedures. It employs a hierarchy-based connection mechanism to construct a hierarchical network structure in which each sensor node is assigned to a special hierarchical subset; it utilizes the combinatorial optimization theory to establish the feasible routing set for each sensor node, and takes advantage of the maximum-minimum criterion to obtain their optimal routes to the base station. Various results of simulation experiments show effectiveness and superiority of the DHCO algorithm in comparison with state-of-the-art WSN routing algorithms, including low-energy adaptive clustering hierarchy (LEACH), hybrid energy-efficient distributed clustering (HEED), genetic protocol-based self-organizing network clustering (GASONeC), and double cost function-based routing (DCFR) algorithms.

UDECON: deconvolution optimization software for restoring high-resolution records from pass-through paleomagnetic measurements

NASA Astrophysics Data System (ADS)

Xuan, Chuang; Oda, Hirokuni

2015-11-01

The rapid accumulation of continuous paleomagnetic and rock magnetic records acquired from pass-through measurements on superconducting rock magnetometers (SRM) has greatly contributed to our understanding of the paleomagnetic field and paleo-environment. Pass-through measurements are inevitably smoothed and altered by the convolution effect of SRM sensor response, and deconvolution is needed to restore high-resolution paleomagnetic and environmental signals. Although various deconvolution algorithms have been developed, the lack of easy-to-use software has hindered the practical application of deconvolution. Here, we present standalone graphical software UDECON as a convenient tool to perform optimized deconvolution for pass-through paleomagnetic measurements using the algorithm recently developed by Oda and Xuan (Geochem Geophys Geosyst 15:3907-3924, 2014). With the preparation of a format file, UDECON can directly read pass-through paleomagnetic measurement files collected at different laboratories. After the SRM sensor response is determined and loaded to the software, optimized deconvolution can be conducted using two different approaches (i.e., "Grid search" and "Simplex method") with adjustable initial values or ranges for smoothness, corrections of sample length, and shifts in measurement position. UDECON provides a suite of tools to view conveniently and check various types of original measurement and deconvolution data. Multiple steps of measurement and/or deconvolution data can be compared simultaneously to check the consistency and to guide further deconvolution optimization. Deconvolved data together with the loaded original measurement and SRM sensor response data can be saved and reloaded for further treatment in UDECON. Users can also export the optimized deconvolution data to a text file for analysis in other software.

Priority design parameters of industrialized optical fiber sensors in civil engineering

NASA Astrophysics Data System (ADS)

Wang, Huaping; Jiang, Lizhong; Xiang, Ping

2018-03-01

Considering the mechanical effects and the different paths for transferring deformation, optical fiber sensors commonly used in civil engineering have been systematically classified. Based on the strain transfer theory, the relationship between the strain transfer coefficient and allowable testing error is established. The proposed relationship is regarded as the optimal control equation to obtain the optimal value of sensors that satisfy the requirement of measurement precision. Furthermore, specific optimization design methods and priority design parameters of the classified sensors are presented. This research indicates that (1) strain transfer theory-based optimization design method is much suitable for the sensor that depends on the interfacial shear stress to transfer the deformation; (2) the priority design parameters are bonded (sensing) length, interfacial bonded strength, elastic modulus and radius of protective layer and thickness of adhesive layer; (3) the optimization design of sensors with two anchor pieces at two ends is independent of strain transfer theory as the strain transfer coefficient can be conveniently calibrated by test, and this kind of sensors has no obvious priority design parameters. Improved calibration test is put forward to enhance the accuracy of the calibration coefficient of end-expanding sensors. By considering the practical state of sensors and the testing accuracy, comprehensive and systematic analyses on optical fiber sensors are provided from the perspective of mechanical actions, which could scientifically instruct the application design and calibration test of industrialized optical fiber sensors.

Magnetoelectric(ME) Composites and Functional Devices Based on ME Effect

NASA Astrophysics Data System (ADS)

Gao, Junqi

Magnetoelectric (ME) effect, a cross-coupling effect between magnetic and electric orders, has stimulated lots of investigations due to the potential for applications as multifunctional devices. In this thesis, I have investigated and optimized the ME effect in Metglas/piezo-fibers ME composites with a multi-push pull configuration. Moreover, I have also proposed several devices based on such composites. In this thesis, several methods for ME composites optimization have been investigated. (i) the ME coefficients can be enhanced greatly by using single crystal fibers with high piezoelectric properties; (ii) the influence of volume ratio between Metglas and piezo-fibers on ME coefficients has been studied both experimentally and theoretically. Modulating the volume ratio can increase the ME coefficient greatly; and (iii) the annealing process can change the properties of Metglas, which can enhance the ME response as well. Moreover, one differential structure for ME composites has been proposed, which can reject the external vibration noise by a factor of 10 to 20 dB. This differential structure may allow for practical applications of such sensors in real-world environments. Based on optimized ME composites, two types of AC magnetic sensor have been developed. The objective is to develop one alternative type of magnetic sensor with low noise, low cost and room-temperature operation; that makes the sensor competitive with the commercially available magnetic sensor, such as Fluxgate, GMR, SQUID, etc. Conventional passive sensors have been fully investigated, including the design of sensor working at specific frequency range, sensitivity, noise density characterization, etc. Furthermore, the extremely low frequency (< 10-3 Hz) magnetic sensor has undergone a redesign of the charge amplifier circuit. Additionally, the noise model has been established to simulate the noise density for this device which can predict the noise floor precisely. Based on theoretical noise analysis, the noise floor can be eliminated greatly. Moreover, another active magnetic senor based on nonlinear ME voltage coefficient is also developed. Such sensor is not required for external DC bias that can help the sensor for sensor arrays application. Inspired by the bio-behaviors in nature, the geomagnetic sensor is designed for sensing geomagnetic fields; it is also potentially used for positioning systems based on the geomagnetic field. In this section, some works for DC sensor optimization have been performed, including the different piezo-fibers, driving frequency and magnetic flux concentration. Meanwhile, the lock-in circuit is designed for the magnetic sensor to replace of the commercial instruments. Finally, the man-portable multi-axial geomagnetic sensor has been developed which has the highest resolution of 10 nT for DC magnetic field. Based on the geomagnetic sensor, some demonstrations have been finished, such as orientation monitor, magnetic field mapping, and geomagnetic sensing. Other devices have been also developed besides the magnetic sensor: (i) magnetic energy harvesters are developed under the resonant frequency condition. Especially, one 60 Hz magnetic harvester is designed which can harvester the magnetic energy source generated by instruments; and (ii) frequency multiplication tuned by geomagnetic field is investigated which potentially can be used for frequency multiplier or geomagnetic guidance devices.

Supervised autonomous rendezvous and docking system technology evaluation

NASA Technical Reports Server (NTRS)

Marzwell, Neville I.

1991-01-01

Technology for manned space flight is mature and has an extensive history of the use of man-in-the-loop rendezvous and docking, but there is no history of automated rendezvous and docking. Sensors exist that can operate in the space environment. The Shuttle radar can be used for ranges down to 30 meters, Japan and France are developing laser rangers, and considerable work is going on in the U.S. However, there is a need to validate a flight qualified sensor for the range of 30 meters to contact. The number of targets and illumination patterns should be minimized to reduce operation constraints with one or more sensors integrated into a robust system for autonomous operation. To achieve system redundancy, it is worthwhile to follow a parallel development of qualifying and extending the range of the 0-12 meter MSFC sensor and to simultaneously qualify the 0-30(+) meter JPL laser ranging system as an additional sensor with overlapping capabilities. Such an approach offers a redundant sensor suite for autonomous rendezvous and docking. The development should include the optimization of integrated sensory systems, packaging, mission envelopes, and computer image processing to mimic brain perception and real-time response. The benefits of the Global Positioning System in providing real-time positioning data of high accuracy must be incorporated into the design. The use of GPS-derived attitude data should be investigated further and validated.

Self-deployable mobile sensor networks for on-demand surveillance

NASA Astrophysics Data System (ADS)

Miao, Lidan; Qi, Hairong; Wang, Feiyi

2005-05-01

This paper studies two interconnected problems in mobile sensor network deployment, the optimal placement of heterogeneous mobile sensor platforms for cost-efficient and reliable coverage purposes, and the self-organizable deployment. We first develop an optimal placement algorithm based on a "mosaicked technology" such that different types of mobile sensors form a mosaicked pattern uniquely determined by the popularity of different types of sensor nodes. The initial state is assumed to be random. In order to converge to the optimal state, we investigate the swarm intelligence (SI)-based sensor movement strategy, through which the randomly deployed sensors can self-organize themselves to reach the optimal placement state. The proposed algorithm is compared with the random movement and the centralized method using performance metrics such as network coverage, convergence time, and energy consumption. Simulation results are presented to demonstrate the effectiveness of the mosaic placement and the SI-based movement.

An EGO-like optimization framework for sensor placement optimization in modal analysis

NASA Astrophysics Data System (ADS)

Morlier, Joseph; Basile, Aniello; Chiplunkar, Ankit; Charlotte, Miguel

2018-07-01

In aircraft design, ground/flight vibration tests are conducted to extract aircraft’s modal parameters (natural frequencies, damping ratios and mode shapes) also known as the modal basis. The main problem in aircraft modal identification is the large number of sensors needed, which increases operational time and costs. The goal of this paper is to minimize the number of sensors by optimizing their locations in order to reconstruct a truncated modal basis of N mode shapes with a high level of accuracy in the reconstruction. There are several methods to solve sensors placement optimization (SPO) problems, but for this case an original approach has been established based on an iterative process for mode shapes reconstruction through an adaptive Kriging metamodeling approach so called efficient global optimization (EGO)-SPO. The main idea in this publication is to solve an optimization problem where the sensors locations are variables and the objective function is defined by maximizing the trace of criteria so called AutoMAC. The results on a 2D wing demonstrate a reduction of sensors by 30% using our EGO-SPO strategy.

A market-based optimization approach to sensor and resource management

NASA Astrophysics Data System (ADS)

Schrage, Dan; Farnham, Christopher; Gonsalves, Paul G.

2006-05-01

Dynamic resource allocation for sensor management is a problem that demands solutions beyond traditional approaches to optimization. Market-based optimization applies solutions from economic theory, particularly game theory, to the resource allocation problem by creating an artificial market for sensor information and computational resources. Intelligent agents are the buyers and sellers in this market, and they represent all the elements of the sensor network, from sensors to sensor platforms to computational resources. These agents interact based on a negotiation mechanism that determines their bidding strategies. This negotiation mechanism and the agents' bidding strategies are based on game theory, and they are designed so that the aggregate result of the multi-agent negotiation process is a market in competitive equilibrium, which guarantees an optimal allocation of resources throughout the sensor network. This paper makes two contributions to the field of market-based optimization: First, we develop a market protocol to handle heterogeneous goods in a dynamic setting. Second, we develop arbitrage agents to improve the efficiency in the market in light of its dynamic nature.

Energy-aware scheduling of surveillance in wireless multimedia sensor networks.

PubMed

Wang, Xue; Wang, Sheng; Ma, Junjie; Sun, Xinyao

2010-01-01

Wireless sensor networks involve a large number of sensor nodes with limited energy supply, which impacts the behavior of their application. In wireless multimedia sensor networks, sensor nodes are equipped with audio and visual information collection modules. Multimedia contents are ubiquitously retrieved in surveillance applications. To solve the energy problems during target surveillance with wireless multimedia sensor networks, an energy-aware sensor scheduling method is proposed in this paper. Sensor nodes which acquire acoustic signals are deployed randomly in the sensing fields. Target localization is based on the signal energy feature provided by multiple sensor nodes, employing particle swarm optimization (PSO). During the target surveillance procedure, sensor nodes are adaptively grouped in a totally distributed manner. Specially, the target motion information is extracted by a forecasting algorithm, which is based on the hidden Markov model (HMM). The forecasting results are utilized to awaken sensor node in the vicinity of future target position. According to the two properties, signal energy feature and residual energy, the sensor nodes decide whether to participate in target detection separately with a fuzzy control approach. Meanwhile, the local routing scheme of data transmission towards the observer is discussed. Experimental results demonstrate the efficiency of energy-aware scheduling of surveillance in wireless multimedia sensor network, where significant energy saving is achieved by the sensor awakening approach and data transmission paths are calculated with low computational complexity.

Development of a Magneto-Resistive Angular Position Sensor for Space Mechanisms

NASA Technical Reports Server (NTRS)

Hahn, Robert; Schmidt, Tilo; Seifart, Klaus; Olberts, Bastian; Romera, Fernando

2016-01-01

Magnetic microsystems in the form of magneto-resistive (MR) sensors are firmly established in automobiles and industrial applications. They are used to measure travel, angle, electrical current, or magnetic fields. MR technology opens up new sensor possibilities in space applications and can be an enabling technology for optimal performance, high robustness and long lifetime at reasonable costs. In some science missions, the technology is already applied, however, the designs are proprietary and case specific, for instance in case of the angular sensors used for JPL/NASA's Mars rover Curiosity [1]. Since 2013 HTS GmbH and Sensitec GmbH have teamed up to develop and qualify a standardized yet flexible to use MR angular sensor for space mechanisms. Starting with a first assessment study and market survey performed under ESA contract, a very strong industry interest in novel, contactless position measurement means was found. Currently a detailed and comprehensive development program is being performed by HTS and Sensitec. The objective of this program is to advance the sensor design up to Engineering Qualification Model level and to perform qualification testing for a representative space application. The paper briefly reviews the basics of magneto-resistive effects and possible sensor applications and describes the key benefits of MR angular sensors with reference to currently operational industrial and space applications. The key applications and specification are presented and the preliminary baseline mechanical and electrical design will be discussed. An outlook on the upcoming development and test stages as well as the qualification program will be provided.

An adaptive procedure for defect identification problems in elasticity

NASA Astrophysics Data System (ADS)

Gutiérrez, Sergio; Mura, J.

2010-07-01

In the context of inverse problems in mechanics, it is well known that the most typical situation is that neither the interior nor all the boundary is available to obtain data to detect the presence of inclusions or defects. We propose here an adaptive method that uses loads and measures of displacements only on part of the surface of the body, to detect defects in the interior of an elastic body. The method is based on Small Amplitude Homogenization, that is, we work under the assumption that the contrast on the values of the Lamé elastic coefficients between the defect and the matrix is not very large. The idea is that given the data for one loading state and one location of the displacement sensors, we use an optimization method to obtain a guess for the location of the inclusion and then, using this guess, we adapt the position of the sensors and the loading zone, hoping to refine the current guess. Numerical results show that the method is quite efficient in some cases, using in those cases no more than three loading positions and three different positions of the sensors.

High temperature superconductor dc SQUID micro-susceptometer for room temperature objects

NASA Astrophysics Data System (ADS)

Faley, M. I.; Pratt, K.; Reineman, R.; Schurig, D.; Gott, S.; Atwood, C. G.; Sarwinski, R. E.; Paulson, D. N.; Starr, T. N.; Fagaly, R. L.

2004-05-01

We have developed a scanning magnetic microscope (SMM) with 25 µm resolution in spatial position for the magnetic features of room temperature objects. The microscope consists of a high-temperature superconductor (HTS) dc SQUID sensor, suspended in vacuum with a self-adjusting standoff, close spaced liquid nitrogen Dewar, X-Y scanning stage and a computer control system. The HTS SQUIDs were optimized for better spatial and field resolutions for operation at liquid nitrogen temperature. Measured inside a magnetic shield, the 10 pT Hz-1/2 typical noise of the SQUIDs is white down to frequencies of about 10 Hz, increasing up to about 20 pT Hz-1/2 at 1 Hz. The microscope is mounted on actively damped platforms, which negate vibrations from the environment as well as damping internal stepper motor noises. A high-resolution video telescope and a 1 µm precision z-axis positioning system allow a close positioning of the sample under the sensor. The ability of the sensors to operate in unshielded environmental conditions with magnetic fields up to about 15 G allowed us to perform 2D mapping of the local ac and dc susceptibility of the objects.

Monitoring in situ in real time of resin infusion for thermoset composite structures

NASA Astrophysics Data System (ADS)

Faci, A.; Wang, P.; Cochrane, C.; Koncar, V.

2017-10-01

The presented work investigates changes in electrical resistance of embedded sensory yarns as a method to monitor the resin flow front position and curing degree of resin during manufacturing of composite structures by vacuum infusion technology. The sensor concept is based on Piezo-resistive sensors integrated to the flax fabric, having almost identical propriety and dimensions as the flax threads used for the production of reinforcements. In the first time sensors have been characterized and first measures of the resin infusion have been realized in order to demonstrate the feasibility of the proposed approach. Then, the measures in real time were realized with fibrous sensors added to the flax fabric (green composites) to monitor the flow front of resin. A large amount of data recorded, filtered, examined, analysed and processed in order to understand and to optimize the infusion and polymerization process.

A Nano-Thin Film-Based Prototype QCM Sensor Array for Monitoring Human Breath and Respiratory Patterns

PubMed Central

Selyanchyn, Roman; Wakamatsu, Shunichi; Hayashi, Kenshi; Lee, Seung-Woo

2015-01-01

Quartz crystal microbalance (QCM) sensor array was developed for multi-purpose human respiration assessment. The sensor system was designed to provide feedback for human respiration. Thorough optimization of measurement conditions: air flow, temperature in the QCM chamber, frequency measurement rate, and electrode position regarding to the gas flow—was performed. As shown, acquisition of respiratory parameters (rate and respiratory pattern) could be achieved even with a single electrode used in the system. The prototype system contains eight available QCM channels that can be potentially used for selective responses to certain breath chemicals. At present, the prototype machine is ready for the assessment of respiratory functions in larger populations in order to gain statistical validation. To the best of our knowledge, the developed prototype is the only respiratory assessment system based on surface modified QCM sensors. PMID:26263994

Variational Lagrangian data assimilation in open channel networks

NASA Astrophysics Data System (ADS)

Wu, Qingfang; Tinka, Andrew; Weekly, Kevin; Beard, Jonathan; Bayen, Alexandre M.

2015-04-01

This article presents a data assimilation method in a tidal system, where data from both Lagrangian drifters and Eulerian flow sensors were fused to estimate water velocity. The system is modeled by first-order, hyperbolic partial differential equations subject to periodic forcing. The estimation problem can then be formulated as the minimization of the difference between the observed variables and model outputs, and eventually provide the velocity and water stage of the hydrodynamic system. The governing equations are linearized and discretized using an implicit discretization scheme, resulting in linear equality constraints in the optimization program. Thus, the flow estimation can be formed as an optimization problem and efficiently solved. The effectiveness of the proposed method was substantiated by a large-scale field experiment in the Sacramento-San Joaquin River Delta in California. A fleet of 100 sensors developed at the University of California, Berkeley, were deployed in Walnut Grove, CA, to collect a set of Lagrangian data, a time series of positions as the sensors moved through the water. Measurements were also taken from Eulerian sensors in the region, provided by the United States Geological Survey. It is shown that the proposed method can effectively integrate Lagrangian and Eulerian measurement data, resulting in a suited estimation of the flow variables within the hydraulic system.

The Study of Cross-layer Optimization for Wireless Rechargeable Sensor Networks Implemented in Coal Mines

PubMed Central

Ding, Xu; Shi, Lei; Han, Jianghong; Lu, Jingting

2016-01-01

Wireless sensor networks deployed in coal mines could help companies provide workers working in coal mines with more qualified working conditions. With the underground information collected by sensor nodes at hand, the underground working conditions could be evaluated more precisely. However, sensor nodes may tend to malfunction due to their limited energy supply. In this paper, we study the cross-layer optimization problem for wireless rechargeable sensor networks implemented in coal mines, of which the energy could be replenished through the newly-brewed wireless energy transfer technique. The main results of this article are two-fold: firstly, we obtain the optimal relay nodes’ placement according to the minimum overall energy consumption criterion through the Lagrange dual problem and KKT conditions; secondly, the optimal strategies for recharging locomotives and wireless sensor networks are acquired by solving a cross-layer optimization problem. The cyclic nature of these strategies is also manifested through simulations in this paper. PMID:26828500

The Study of Cross-layer Optimization for Wireless Rechargeable Sensor Networks Implemented in Coal Mines.

PubMed

Ding, Xu; Shi, Lei; Han, Jianghong; Lu, Jingting

2016-01-28

Wireless sensor networks deployed in coal mines could help companies provide workers working in coal mines with more qualified working conditions. With the underground information collected by sensor nodes at hand, the underground working conditions could be evaluated more precisely. However, sensor nodes may tend to malfunction due to their limited energy supply. In this paper, we study the cross-layer optimization problem for wireless rechargeable sensor networks implemented in coal mines, of which the energy could be replenished through the newly-brewed wireless energy transfer technique. The main results of this article are two-fold: firstly, we obtain the optimal relay nodes' placement according to the minimum overall energy consumption criterion through the Lagrange dual problem and KKT conditions; secondly, the optimal strategies for recharging locomotives and wireless sensor networks are acquired by solving a cross-layer optimization problem. The cyclic nature of these strategies is also manifested through simulations in this paper.

Dynamic Hierarchical Energy-Efficient Method Based on Combinatorial Optimization for Wireless Sensor Networks

PubMed Central

Tang, Hongying; Cheng, Yongbo; Zhao, Qin; Li, Baoqing; Yuan, Xiaobing

2017-01-01

Routing protocols based on topology control are significantly important for improving network longevity in wireless sensor networks (WSNs). Traditionally, some WSN routing protocols distribute uneven network traffic load to sensor nodes, which is not optimal for improving network longevity. Differently to conventional WSN routing protocols, we propose a dynamic hierarchical protocol based on combinatorial optimization (DHCO) to balance energy consumption of sensor nodes and to improve WSN longevity. For each sensor node, the DHCO algorithm obtains the optimal route by establishing a feasible routing set instead of selecting the cluster head or the next hop node. The process of obtaining the optimal route can be formulated as a combinatorial optimization problem. Specifically, the DHCO algorithm is carried out by the following procedures. It employs a hierarchy-based connection mechanism to construct a hierarchical network structure in which each sensor node is assigned to a special hierarchical subset; it utilizes the combinatorial optimization theory to establish the feasible routing set for each sensor node, and takes advantage of the maximum–minimum criterion to obtain their optimal routes to the base station. Various results of simulation experiments show effectiveness and superiority of the DHCO algorithm in comparison with state-of-the-art WSN routing algorithms, including low-energy adaptive clustering hierarchy (LEACH), hybrid energy-efficient distributed clustering (HEED), genetic protocol-based self-organizing network clustering (GASONeC), and double cost function-based routing (DCFR) algorithms. PMID:28753962

Bio-mimic optimization strategies in wireless sensor networks: a survey.

PubMed

Adnan, Md Akhtaruzzaman; Abdur Razzaque, Mohammd; Ahmed, Ishtiaque; Isnin, Ismail Fauzi

2013-12-24

For the past 20 years, many authors have focused their investigations on wireless sensor networks. Various issues related to wireless sensor networks such as energy minimization (optimization), compression schemes, self-organizing network algorithms, routing protocols, quality of service management, security, energy harvesting, etc., have been extensively explored. The three most important issues among these are energy efficiency, quality of service and security management. To get the best possible results in one or more of these issues in wireless sensor networks optimization is necessary. Furthermore, in number of applications (e.g., body area sensor networks, vehicular ad hoc networks) these issues might conflict and require a trade-off amongst them. Due to the high energy consumption and data processing requirements, the use of classical algorithms has historically been disregarded. In this context contemporary researchers started using bio-mimetic strategy-based optimization techniques in the field of wireless sensor networks. These techniques are diverse and involve many different optimization algorithms. As far as we know, most existing works tend to focus only on optimization of one specific issue of the three mentioned above. It is high time that these individual efforts are put into perspective and a more holistic view is taken. In this paper we take a step in that direction by presenting a survey of the literature in the area of wireless sensor network optimization concentrating especially on the three most widely used bio-mimetic algorithms, namely, particle swarm optimization, ant colony optimization and genetic algorithm. In addition, to stimulate new research and development interests in this field, open research issues, challenges and future research directions are highlighted.

Expert system for controlling plant growth in a contained environment

NASA Technical Reports Server (NTRS)

May, George A. (Inventor); Lanoue, Mark Allen (Inventor); Bethel, Matthew (Inventor); Ryan, Robert E. (Inventor)

2011-01-01

In a system for optimizing crop growth, vegetation is cultivated in a contained environment, such as a greenhouse, an underground cavern or other enclosed space. Imaging equipment is positioned within or about the contained environment, to acquire spatially distributed crop growth information, and environmental sensors are provided to acquire data regarding multiple environmental conditions that can affect crop development. Illumination within the contained environment, and the addition of essential nutrients and chemicals are in turn controlled in response to data acquired by the imaging apparatus and environmental sensors, by an "expert system" which is trained to analyze and evaluate crop conditions. The expert system controls the spatial and temporal lighting pattern within the contained area, and the timing and allocation of nutrients and chemicals to achieve optimized crop development. A user can access the "expert system" remotely, to assess activity within the growth chamber, and can override the "expert system".

Expert system for controlling plant growth in a contained environment

NASA Technical Reports Server (NTRS)

May, George A. (Inventor); Lanoue, Mark Allen (Inventor); Bethel, Matthew (Inventor); Ryan, Robert E. (Inventor)

2009-01-01

In a system for optimizing crop growth, vegetation is cultivated in a contained environment, such as a greenhouse, an underground cavern or other enclosed space. Imaging equipment is positioned within or about the contained environment, to acquire spatially distributed crop growth information, and environmental sensors are provided to acquire data regarding multiple environmental conditions that can affect crop development. Illumination within the contained environment, and the addition of essential nutrients and chemicals are in turn controlled in response to data acquired by the imaging apparatus and environmental sensors, by an ''expert system'' which is trained to analyze and evaluate crop conditions. The expert system controls the spatial and temporal lighting pattern within the contained area, and the timing and allocation of nutrients and chemicals to achieve optimized crop development. A user can access the ''expert system'' remotely, to assess activity within the growth chamber, and can override the ''expert system''.

Connectivity Restoration in Wireless Sensor Networks via Space Network Coding.

PubMed

Uwitonze, Alfred; Huang, Jiaqing; Ye, Yuanqing; Cheng, Wenqing

2017-04-20

The problem of finding the number and optimal positions of relay nodes for restoring the network connectivity in partitioned Wireless Sensor Networks (WSNs) is Non-deterministic Polynomial-time hard (NP-hard) and thus heuristic methods are preferred to solve it. This paper proposes a novel polynomial time heuristic algorithm, namely, Relay Placement using Space Network Coding (RPSNC), to solve this problem, where Space Network Coding, also called Space Information Flow (SIF), is a new research paradigm that studies network coding in Euclidean space, in which extra relay nodes can be introduced to reduce the cost of communication. Unlike contemporary schemes that are often based on Minimum Spanning Tree (MST), Euclidean Steiner Minimal Tree (ESMT) or a combination of MST with ESMT, RPSNC is a new min-cost multicast space network coding approach that combines Delaunay triangulation and non-uniform partitioning techniques for generating a number of candidate relay nodes, and then linear programming is applied for choosing the optimal relay nodes and computing their connection links with terminals. Subsequently, an equilibrium method is used to refine the locations of the optimal relay nodes, by moving them to balanced positions. RPSNC can adapt to any density distribution of relay nodes and terminals, as well as any density distribution of terminals. The performance and complexity of RPSNC are analyzed and its performance is validated through simulation experiments.

Star centroiding error compensation for intensified star sensors.

PubMed

Jiang, Jie; Xiong, Kun; Yu, Wenbo; Yan, Jinyun; Zhang, Guangjun

2016-12-26

A star sensor provides high-precision attitude information by capturing a stellar image; however, the traditional star sensor has poor dynamic performance, which is attributed to its low sensitivity. Regarding the intensified star sensor, the image intensifier is utilized to improve the sensitivity, thereby further improving the dynamic performance of the star sensor. However, the introduction of image intensifier results in star centroiding accuracy decrease, further influencing the attitude measurement precision of the star sensor. A star centroiding error compensation method for intensified star sensors is proposed in this paper to reduce the influences. First, the imaging model of the intensified detector, which includes the deformation parameter of the optical fiber panel, is established based on the orthographic projection through the analysis of errors introduced by the image intensifier. Thereafter, the position errors at the target points based on the model are obtained by using the Levenberg-Marquardt (LM) optimization method. Last, the nearest trigonometric interpolation method is presented to compensate for the arbitrary centroiding error of the image plane. Laboratory calibration result and night sky experiment result show that the compensation method effectively eliminates the error introduced by the image intensifier, thus remarkably improving the precision of the intensified star sensors.

Pure random search for ambient sensor distribution optimisation in a smart home environment.

PubMed

Poland, Michael P; Nugent, Chris D; Wang, Hui; Chen, Liming

2011-01-01

Smart homes are living spaces facilitated with technology to allow individuals to remain in their own homes for longer, rather than be institutionalised. Sensors are the fundamental physical layer with any smart home, as the data they generate is used to inform decision support systems, facilitating appropriate actuator actions. Positioning of sensors is therefore a fundamental characteristic of a smart home. Contemporary smart home sensor distribution is aligned to either a) a total coverage approach; b) a human assessment approach. These methods for sensor arrangement are not data driven strategies, are unempirical and frequently irrational. This Study hypothesised that sensor deployment directed by an optimisation method that utilises inhabitants' spatial frequency data as the search space, would produce more optimal sensor distributions vs. the current method of sensor deployment by engineers. Seven human engineers were tasked to create sensor distributions based on perceived utility for 9 deployment scenarios. A Pure Random Search (PRS) algorithm was then tasked to create matched sensor distributions. The PRS method produced superior distributions in 98.4% of test cases (n=64) against human engineer instructed deployments when the engineers had no access to the spatial frequency data, and in 92.0% of test cases (n=64) when engineers had full access to these data. These results thus confirmed the hypothesis.

The Optimization Based Dynamic and Cyclic Working Strategies for Rechargeable Wireless Sensor Networks with Multiple Base Stations and Wireless Energy Transfer Devices

PubMed Central

Ding, Xu; Han, Jianghong; Shi, Lei

2015-01-01

In this paper, the optimal working schemes for wireless sensor networks with multiple base stations and wireless energy transfer devices are proposed. The wireless energy transfer devices also work as data gatherers while charging sensor nodes. The wireless sensor network is firstly divided into sub networks according to the concept of Voronoi diagram. Then, the entire energy replenishing procedure is split into the pre-normal and normal energy replenishing stages. With the objective of maximizing the sojourn time ratio of the wireless energy transfer device, a continuous time optimization problem for the normal energy replenishing cycle is formed according to constraints with which sensor nodes and wireless energy transfer devices should comply. Later on, the continuous time optimization problem is reshaped into a discrete multi-phased optimization problem, which yields the identical optimality. After linearizing it, we obtain a linear programming problem that can be solved efficiently. The working strategies of both sensor nodes and wireless energy transfer devices in the pre-normal replenishing stage are also discussed in this paper. The intensive simulations exhibit the dynamic and cyclic working schemes for the entire energy replenishing procedure. Additionally, a way of eliminating “bottleneck” sensor nodes is also developed in this paper. PMID:25785305

The optimization based dynamic and cyclic working strategies for rechargeable wireless sensor networks with multiple base stations and wireless energy transfer devices.

PubMed

Ding, Xu; Han, Jianghong; Shi, Lei

2015-03-16

In this paper, the optimal working schemes for wireless sensor networks with multiple base stations and wireless energy transfer devices are proposed. The wireless energy transfer devices also work as data gatherers while charging sensor nodes. The wireless sensor network is firstly divided into sub networks according to the concept of Voronoi diagram. Then, the entire energy replenishing procedure is split into the pre-normal and normal energy replenishing stages. With the objective of maximizing the sojourn time ratio of the wireless energy transfer device, a continuous time optimization problem for the normal energy replenishing cycle is formed according to constraints with which sensor nodes and wireless energy transfer devices should comply. Later on, the continuous time optimization problem is reshaped into a discrete multi-phased optimization problem, which yields the identical optimality. After linearizing it, we obtain a linear programming problem that can be solved efficiently. The working strategies of both sensor nodes and wireless energy transfer devices in the pre-normal replenishing stage are also discussed in this paper. The intensive simulations exhibit the dynamic and cyclic working schemes for the entire energy replenishing procedure. Additionally, a way of eliminating "bottleneck" sensor nodes is also developed in this paper.

CPAC: Energy-Efficient Data Collection through Adaptive Selection of Compression Algorithms for Sensor Networks

PubMed Central

Lee, HyungJune; Kim, HyunSeok; Chang, Ik Joon

2014-01-01

We propose a technique to optimize the energy efficiency of data collection in sensor networks by exploiting a selective data compression. To achieve such an aim, we need to make optimal decisions regarding two aspects: (1) which sensor nodes should execute compression; and (2) which compression algorithm should be used by the selected sensor nodes. We formulate this problem into binary integer programs, which provide an energy-optimal solution under the given latency constraint. Our simulation results show that the optimization algorithm significantly reduces the overall network-wide energy consumption for data collection. In the environment having a stationary sink from stationary sensor nodes, the optimized data collection shows 47% energy savings compared to the state-of-the-art collection protocol (CTP). More importantly, we demonstrate that our optimized data collection provides the best performance in an intermittent network under high interference. In such networks, we found that the selective compression for frequent packet retransmissions saves up to 55% energy compared to the best known protocol. PMID:24721763

Information Fusion for High Level Situation Assessment and Prediction

DTIC Science & Technology

2007-03-01

procedure includes deciding a sensor set that achieves the optimal trade -off between its cost and benefit, activating the identified sensors, integrating...and effective decision can be made by dynamic inference based on selecting a subset of sensors with the optimal trade -off between their cost and...first step is achieved by designing a sensor selection criterion that represents the trade -off between the sensor benefit and sensor cost. This is then

An Artificial Neural Network Embedded Position and Orientation Determination Algorithm for Low Cost MEMS INS/GPS Integrated Sensors

PubMed Central

Chiang, Kai-Wei; Chang, Hsiu-Wen; Li, Chia-Yuan; Huang, Yun-Wen

2009-01-01

Digital mobile mapping, which integrates digital imaging with direct geo-referencing, has developed rapidly over the past fifteen years. Direct geo-referencing is the determination of the time-variable position and orientation parameters for a mobile digital imager. The most common technologies used for this purpose today are satellite positioning using Global Positioning System (GPS) and Inertial Navigation System (INS) using an Inertial Measurement Unit (IMU). They are usually integrated in such a way that the GPS receiver is the main position sensor, while the IMU is the main orientation sensor. The Kalman Filter (KF) is considered as the optimal estimation tool for real-time INS/GPS integrated kinematic position and orientation determination. An intelligent hybrid scheme consisting of an Artificial Neural Network (ANN) and KF has been proposed to overcome the limitations of KF and to improve the performance of the INS/GPS integrated system in previous studies. However, the accuracy requirements of general mobile mapping applications can’t be achieved easily, even by the use of the ANN-KF scheme. Therefore, this study proposes an intelligent position and orientation determination scheme that embeds ANN with conventional Rauch-Tung-Striebel (RTS) smoother to improve the overall accuracy of a MEMS INS/GPS integrated system in post-mission mode. By combining the Micro Electro Mechanical Systems (MEMS) INS/GPS integrated system and the intelligent ANN-RTS smoother scheme proposed in this study, a cheaper but still reasonably accurate position and orientation determination scheme can be anticipated. PMID:22574034

Choosing Sensor Configuration for a Flexible Structure Using Full Control Synthesis

NASA Technical Reports Server (NTRS)

Lind, Rick; Nalbantoglu, Volkan; Balas, Gary

1997-01-01

Optimal locations and types for feedback sensors which meet design constraints and control requirements are difficult to determine. This paper introduces an approach to choosing a sensor configuration based on Full Control synthesis. A globally optimal Full Control compensator is computed for each member of a set of sensor configurations which are feasible for the plant. The sensor configuration associated with the Full Control system achieving the best closed-loop performance is chosen for feedback measurements to an output feedback controller. A flexible structure is used as an example to demonstrate this procedure. Experimental results show sensor configurations chosen to optimize the Full Control performance are effective for output feedback controllers.

Power optimization in body sensor networks: the case of an autonomous wireless EMG sensor powered by PV-cells.

PubMed

Penders, J; Pop, V; Caballero, L; van de Molengraft, J; van Schaijk, R; Vullers, R; Van Hoof, C

2010-01-01

Recent advances in ultra-low-power circuits and energy harvesters are making self-powered body sensor nodes a reality. Power optimization at the system and application level is crucial in achieving ultra-low-power consumption for the entire system. This paper reviews system-level power optimization techniques, and illustrates their impact on the case of autonomous wireless EMG monitoring. The resulting prototype, an Autonomous wireless EMG sensor power by PV-cells, is presented.

Optimization Strategies for Sensor and Actuator Placement

NASA Technical Reports Server (NTRS)

Padula, Sharon L.; Kincaid, Rex K.

1999-01-01

This paper provides a survey of actuator and sensor placement problems from a wide range of engineering disciplines and a variety of applications. Combinatorial optimization methods are recommended as a means for identifying sets of actuators and sensors that maximize performance. Several sample applications from NASA Langley Research Center, such as active structural acoustic control, are covered in detail. Laboratory and flight tests of these applications indicate that actuator and sensor placement methods are effective and important. Lessons learned in solving these optimization problems can guide future research.

Geometrical optimization of a local ballistic magnetic sensor

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

Kanda, Yuhsuke; Hara, Masahiro; Nomura, Tatsuya

2014-04-07

We have developed a highly sensitive local magnetic sensor by using a ballistic transport property in a two-dimensional conductor. A semiclassical simulation reveals that the sensitivity increases when the geometry of the sensor and the spatial distribution of the local field are optimized. We have also experimentally demonstrated a clear observation of a magnetization process in a permalloy dot whose size is much smaller than the size of an optimized ballistic magnetic sensor fabricated from a GaAs/AlGaAs two-dimensional electron gas.

Quartz enhanced photoacoustic H{sub 2}S gas sensor based on a fiber-amplifier source and a custom tuning fork with large prong spacing

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

Wu, Hongpeng; Liu, Xiaoli; Zheng, Huadan

2015-09-14

A quartz enhanced photoacoustic spectroscopy (QEPAS) sensor, employing an erbium-doped fiber amplified laser source and a custom quartz tuning fork (QTF) with its two prongs spaced ∼800 μm apart, is reported. The sensor employs an acoustic micro-resonator (AmR) which is assembled in an “on-beam” QEPAS configuration. Both length and vertical position of the AmR are optimized in terms of signal-to-noise ratio, significantly improving the QEPAS detection sensitivity by a factor of ∼40, compared to the case of a sensor using a bare custom QTF. The fiber-amplifier-enhanced QEPAS sensor is applied to H{sub 2}S trace gas detection, reaching a sensitivity of ∼890 ppbmore » at 1 s integration time, similar to those obtained with a power-enhanced QEPAS sensor equipped with a standard QTF, but with the advantages of easy optical alignment, simple installation, and long-term stability.« less

A star recognition method based on the Adaptive Ant Colony algorithm for star sensors.

PubMed

Quan, Wei; Fang, Jiancheng

2010-01-01

A new star recognition method based on the Adaptive Ant Colony (AAC) algorithm has been developed to increase the star recognition speed and success rate for star sensors. This method draws circles, with the center of each one being a bright star point and the radius being a special angular distance, and uses the parallel processing ability of the AAC algorithm to calculate the angular distance of any pair of star points in the circle. The angular distance of two star points in the circle is solved as the path of the AAC algorithm, and the path optimization feature of the AAC is employed to search for the optimal (shortest) path in the circle. This optimal path is used to recognize the stellar map and enhance the recognition success rate and speed. The experimental results show that when the position error is about 50″, the identification success rate of this method is 98% while the Delaunay identification method is only 94%. The identification time of this method is up to 50 ms.

LinkMind: link optimization in swarming mobile sensor networks.

PubMed

Ngo, Trung Dung

2011-01-01

A swarming mobile sensor network is comprised of a swarm of wirelessly connected mobile robots equipped with various sensors. Such a network can be applied in an uncertain environment for services such as cooperative navigation and exploration, object identification and information gathering. One of the most advantageous properties of the swarming wireless sensor network is that mobile nodes can work cooperatively to organize an ad-hoc network and optimize the network link capacity to maximize the transmission of gathered data from a source to a target. This paper describes a new method of link optimization of swarming mobile sensor networks. The new method is based on combination of the artificial potential force guaranteeing connectivities of the mobile sensor nodes and the max-flow min-cut theorem of graph theory ensuring optimization of the network link capacity. The developed algorithm is demonstrated and evaluated in simulation.

LinkMind: Link Optimization in Swarming Mobile Sensor Networks

PubMed Central

Ngo, Trung Dung

2011-01-01

A swarming mobile sensor network is comprised of a swarm of wirelessly connected mobile robots equipped with various sensors. Such a network can be applied in an uncertain environment for services such as cooperative navigation and exploration, object identification and information gathering. One of the most advantageous properties of the swarming wireless sensor network is that mobile nodes can work cooperatively to organize an ad-hoc network and optimize the network link capacity to maximize the transmission of gathered data from a source to a target. This paper describes a new method of link optimization of swarming mobile sensor networks. The new method is based on combination of the artificial potential force guaranteeing connectivities of the mobile sensor nodes and the max-flow min-cut theorem of graph theory ensuring optimization of the network link capacity. The developed algorithm is demonstrated and evaluated in simulation. PMID:22164070

A self-optimizing scheme for energy balanced routing in Wireless Sensor Networks using SensorAnt.

PubMed

Shamsan Saleh, Ahmed M; Ali, Borhanuddin Mohd; Rasid, Mohd Fadlee A; Ismail, Alyani

2012-01-01

Planning of energy-efficient protocols is critical for Wireless Sensor Networks (WSNs) because of the constraints on the sensor nodes' energy. The routing protocol should be able to provide uniform power dissipation during transmission to the sink node. In this paper, we present a self-optimization scheme for WSNs which is able to utilize and optimize the sensor nodes' resources, especially the batteries, to achieve balanced energy consumption across all sensor nodes. This method is based on the Ant Colony Optimization (ACO) metaheuristic which is adopted to enhance the paths with the best quality function. The assessment of this function depends on multi-criteria metrics such as the minimum residual battery power, hop count and average energy of both route and network. This method also distributes the traffic load of sensor nodes throughout the WSN leading to reduced energy usage, extended network life time and reduced packet loss. Simulation results show that our scheme performs much better than the Energy Efficient Ant-Based Routing (EEABR) in terms of energy consumption, balancing and efficiency.

Real-time localization of mobile device by filtering method for sensor fusion

NASA Astrophysics Data System (ADS)

Fuse, Takashi; Nagara, Keita

2017-06-01

Most of the applications with mobile devices require self-localization of the devices. GPS cannot be used in indoor environment, the positions of mobile devices are estimated autonomously by using IMU. Since the self-localization is based on IMU of low accuracy, and then the self-localization in indoor environment is still challenging. The selflocalization method using images have been developed, and the accuracy of the method is increasing. This paper develops the self-localization method without GPS in indoor environment by integrating sensors, such as IMU and cameras, on mobile devices simultaneously. The proposed method consists of observations, forecasting and filtering. The position and velocity of the mobile device are defined as a state vector. In the self-localization, observations correspond to observation data from IMU and camera (observation vector), forecasting to mobile device moving model (system model) and filtering to tracking method by inertial surveying and coplanarity condition and inverse depth model (observation model). Positions of a mobile device being tracked are estimated by system model (forecasting step), which are assumed as linearly moving model. Then estimated positions are optimized referring to the new observation data based on likelihood (filtering step). The optimization at filtering step corresponds to estimation of the maximum a posterior probability. Particle filter are utilized for the calculation through forecasting and filtering steps. The proposed method is applied to data acquired by mobile devices in indoor environment. Through the experiments, the high performance of the method is confirmed.

Optimal Design of Multitype Groundwater Monitoring Networks Using Easily Accessible Tools.

PubMed

Wöhling, Thomas; Geiges, Andreas; Nowak, Wolfgang

2016-11-01

Monitoring networks are expensive to establish and to maintain. In this paper, we extend an existing data-worth estimation method from the suite of PEST utilities with a global optimization method for optimal sensor placement (called optimal design) in groundwater monitoring networks. Design optimization can include multiple simultaneous sensor locations and multiple sensor types. Both location and sensor type are treated simultaneously as decision variables. Our method combines linear uncertainty quantification and a modified genetic algorithm for discrete multilocation, multitype search. The efficiency of the global optimization is enhanced by an archive of past samples and parallel computing. We demonstrate our methodology for a groundwater monitoring network at the Steinlach experimental site, south-western Germany, which has been established to monitor river-groundwater exchange processes. The target of optimization is the best possible exploration for minimum variance in predicting the mean travel time of the hyporheic exchange. Our results demonstrate that the information gain of monitoring network designs can be explored efficiently and with easily accessible tools prior to taking new field measurements or installing additional measurement points. The proposed methods proved to be efficient and can be applied for model-based optimal design of any type of monitoring network in approximately linear systems. Our key contributions are (1) the use of easy-to-implement tools for an otherwise complex task and (2) yet to consider data-worth interdependencies in simultaneous optimization of multiple sensor locations and sensor types. © 2016, National Ground Water Association.

Optimization of Sensing and Feedback Control for Vibration/Flutter of Rotating Disk by PZT Actuators via Air Coupled Pressure

PubMed Central

Yan, Tianhong; Xu, Xinsheng; Han, Jianqiang; Lin, Rongming; Ju, Bingfeng; Li, Qing

2011-01-01

In this paper, a feedback control mechanism and its optimization for rotating disk vibration/flutter via changes of air-coupled pressure generated using piezoelectric patch actuators are studied. A thin disk rotates in an enclosure, which is equipped with a feedback control loop consisting of a micro-sensor, a signal processor, a power amplifier, and several piezoelectric (PZT) actuator patches distributed on the cover of the enclosure. The actuator patches are mounted on the inner or the outer surfaces of the enclosure to produce necessary control force required through the airflow around the disk. The control mechanism for rotating disk flutter using enclosure surfaces bonded with sensors and piezoelectric actuators is thoroughly studied through analytical simulations. The sensor output is used to determine the amount of input to the actuator for controlling the response of the disk in a closed loop configuration. The dynamic stability of the disk-enclosure system, together with the feedback control loop, is analyzed as a complex eigenvalue problem, which is solved using Galerkin’s discretization procedure. The results show that the disk flutter can be reduced effectively with proper configurations of the control gain and the phase shift through the actuations of PZT patches. The effectiveness of different feedback control methods in altering system characteristics and system response has been investigated. The control capability, in terms of control gain, phase shift, and especially the physical configuration of actuator patches, are also evaluated by calculating the complex eigenvalues and the maximum displacement produced by the actuators. To achieve a optimal control performance, sizes, positions and shapes of PZT patches used need to be optimized and such optimization has been achieved through numerical simulations. PMID:22163788

Optimization of sensing and feedback control for vibration/flutter of rotating disk by PZT actuators via air coupled pressure.

PubMed

Yan, Tianhong; Xu, Xinsheng; Han, Jianqiang; Lin, Rongming; Ju, Bingfeng; Li, Qing

2011-01-01

In this paper, a feedback control mechanism and its optimization for rotating disk vibration/flutter via changes of air-coupled pressure generated using piezoelectric patch actuators are studied. A thin disk rotates in an enclosure, which is equipped with a feedback control loop consisting of a micro-sensor, a signal processor, a power amplifier, and several piezoelectric (PZT) actuator patches distributed on the cover of the enclosure. The actuator patches are mounted on the inner or the outer surfaces of the enclosure to produce necessary control force required through the airflow around the disk. The control mechanism for rotating disk flutter using enclosure surfaces bonded with sensors and piezoelectric actuators is thoroughly studied through analytical simulations. The sensor output is used to determine the amount of input to the actuator for controlling the response of the disk in a closed loop configuration. The dynamic stability of the disk-enclosure system, together with the feedback control loop, is analyzed as a complex eigenvalue problem, which is solved using Galerkin's discretization procedure. The results show that the disk flutter can be reduced effectively with proper configurations of the control gain and the phase shift through the actuations of PZT patches. The effectiveness of different feedback control methods in altering system characteristics and system response has been investigated. The control capability, in terms of control gain, phase shift, and especially the physical configuration of actuator patches, are also evaluated by calculating the complex eigenvalues and the maximum displacement produced by the actuators. To achieve a optimal control performance, sizes, positions and shapes of PZT patches used need to be optimized and such optimization has been achieved through numerical simulations.

Bio-Mimic Optimization Strategies in Wireless Sensor Networks: A Survey

PubMed Central

Adnan, Md. Akhtaruzzaman; Razzaque, Mohammd Abdur; Ahmed, Ishtiaque; Isnin, Ismail Fauzi

2014-01-01

For the past 20 years, many authors have focused their investigations on wireless sensor networks. Various issues related to wireless sensor networks such as energy minimization (optimization), compression schemes, self-organizing network algorithms, routing protocols, quality of service management, security, energy harvesting, etc., have been extensively explored. The three most important issues among these are energy efficiency, quality of service and security management. To get the best possible results in one or more of these issues in wireless sensor networks optimization is necessary. Furthermore, in number of applications (e.g., body area sensor networks, vehicular ad hoc networks) these issues might conflict and require a trade-off amongst them. Due to the high energy consumption and data processing requirements, the use of classical algorithms has historically been disregarded. In this context contemporary researchers started using bio-mimetic strategy-based optimization techniques in the field of wireless sensor networks. These techniques are diverse and involve many different optimization algorithms. As far as we know, most existing works tend to focus only on optimization of one specific issue of the three mentioned above. It is high time that these individual efforts are put into perspective and a more holistic view is taken. In this paper we take a step in that direction by presenting a survey of the literature in the area of wireless sensor network optimization concentrating especially on the three most widely used bio-mimetic algorithms, namely, particle swarm optimization, ant colony optimization and genetic algorithm. In addition, to stimulate new research and development interests in this field, open research issues, challenges and future research directions are highlighted. PMID:24368702

Optimization of PZT ceramic IDT sensors for health monitoring of structures.

PubMed

Takpara, Rafatou; Duquennoy, Marc; Ouaftouh, Mohammadi; Courtois, Christian; Jenot, Frédéric; Rguiti, Mohamed

2017-08-01

Surface acoustic waves (SAW) are particularly suited to effectively monitoring and characterizing structural surfaces (condition of the surface, coating, thin layer, micro-cracks…) as their energy is localized on the surface, within approximately one wavelength. Conventionally, in non-destructive testing, wedge sensors are used to the generation guided waves but they are especially suited to flat surfaces and sized for a given type material (angle of refraction). Additionally, these sensors are quite expensive so it is quite difficult to leave the sensors permanently on the structure for its health monitoring. Therefore we are considering in this study, another type of ultrasonic sensors, able to generate SAW. These sensors are interdigital sensors or IDT sensors for InterDigital Transducer. This paper focuses on optimization of IDT sensors for non-destructive structural testing by using PZT ceramics. The challenge was to optimize the dimensional parameters of the IDT sensors in order to efficiently generate surface waves. Acoustic tests then confirmed these parameters. Copyright © 2017 Elsevier B.V. All rights reserved.

Sensor fusion display evaluation using information integration models in enhanced/synthetic vision applications

NASA Technical Reports Server (NTRS)

Foyle, David C.

1993-01-01

Based on existing integration models in the psychological literature, an evaluation framework is developed to assess sensor fusion displays as might be implemented in an enhanced/synthetic vision system. The proposed evaluation framework for evaluating the operator's ability to use such systems is a normative approach: The pilot's performance with the sensor fusion image is compared to models' predictions based on the pilot's performance when viewing the original component sensor images prior to fusion. This allows for the determination as to when a sensor fusion system leads to: poorer performance than one of the original sensor displays, clearly an undesirable system in which the fused sensor system causes some distortion or interference; better performance than with either single sensor system alone, but at a sub-optimal level compared to model predictions; optimal performance compared to model predictions; or, super-optimal performance, which may occur if the operator were able to use some highly diagnostic 'emergent features' in the sensor fusion display, which were unavailable in the original sensor displays.

A minimalistic and optimized conveyor belt for neutral atoms.

PubMed

Roy, Ritayan; Condylis, Paul C; Prakash, Vindhiya; Sahagun, Daniel; Hessmo, Björn

2017-10-20

Here we report of a design and the performance of an optimized micro-fabricated conveyor belt for precise and adiabatic transportation of cold atoms. A theoretical model is presented to determine optimal currents in conductors used for the transportation. We experimentally demonstrate a fast adiabatic transportation of Rubidium ( 87 Rb) cold atoms with minimal loss and heating with as few as three conveyor belt conductors. This novel design of a multilayered conveyor belt structure is fabricated in aluminium nitride (AlN) because of its outstanding thermal and electrical properties. This demonstration would pave a way for a compact and portable quantum device required for quantum information processing and sensors, where precise positioning of cold atoms is desirable.

Localization of CO2 Leakage from a Circular Hole on a Flat-Surface Structure Using a Circular Acoustic Emission Sensor Array

PubMed Central

Cui, Xiwang; Yan, Yong; Guo, Miao; Han, Xiaojuan; Hu, Yonghui

2016-01-01

Leak localization is essential for the safety and maintenance of storage vessels. This study proposes a novel circular acoustic emission sensor array to realize the continuous CO2 leak localization from a circular hole on the surface of a large storage vessel in a carbon capture and storage system. Advantages of the proposed array are analyzed and compared with the common sparse arrays. Experiments were carried out on a laboratory-scale stainless steel plate and leak signals were obtained from a circular hole in the center of this flat-surface structure. In order to reduce the influence of the ambient noise and dispersion of the acoustic wave on the localization accuracy, ensemble empirical mode decomposition is deployed to extract the useful leak signal. The time differences between the signals from the adjacent sensors in the array are calculated through correlation signal processing before estimating the corresponding distance differences between the sensors. A hyperbolic positioning algorithm is used to identify the location of the circular leak hole. Results show that the circular sensor array has very good directivity toward the circular leak hole. Furthermore, an optimized method is proposed by changing the position of the circular sensor array on the flat-surface structure or adding another circular sensor array to identify the direction of the circular leak hole. Experiential results obtained on a 100 cm × 100 cm stainless steel plate demonstrate that the full-scale error in the leak localization is within 0.6%. PMID:27869765

Roughness sensor based on a compact optoelectronic emitter-receiver modules

NASA Astrophysics Data System (ADS)

Will, Matthias; Brodersen, Olaf; Steinke, Arndt

2012-04-01

In construction and manufacturing the surface roughness and their control plays a major role. The mechanical test probes are used in many applications, because the advantage of the higher resolution of optical systems often plays no role. But in all cases the measurement systems were uses outside of fabrication processes due to the complex and expensive equipment. To overcome these we developed a roughness sensor suitable for an automated control of machined surfaces. The sensor is able to handle high throughput and parallel systems is due to the low cost available. Our solution is compact stand-alone sensors that can be simple integrated in existing systems like machine tools or transport systems. The sensor is based on a diode laser, focusing optics and a special silicon photo diode array in a stable housing. The single-mode VCSEL at 670 nm emission wavelength is focused on the surface of the sample at distance of 5mm. The light was reflected from the test surface and detected with an 8-channel photodiode array. The position of the main reflex allows an optimization of the sensor distance to the surface. During the movement of the sample with a known velocity roughness depended signals over time were recorded at 8 cannels. This allows a detection of the angular distribution of the scattered light in combination of position dependent refection. It was shown here that we be able to achieve resolution below the spot diameter (30μm FWHM). We verify the sensor capabilities for real world applications on drilled samples with typical roughness variations in micro meter range.

Systematic Sensor Selection Strategy (S4) User Guide

NASA Technical Reports Server (NTRS)

Sowers, T. Shane

2012-01-01

This paper describes a User Guide for the Systematic Sensor Selection Strategy (S4). S4 was developed to optimally select a sensor suite from a larger pool of candidate sensors based on their performance in a diagnostic system. For aerospace systems, selecting the proper sensors is important for ensuring adequate measurement coverage to satisfy operational, maintenance, performance, and system diagnostic criteria. S4 optimizes the selection of sensors based on the system fault diagnostic approach while taking conflicting objectives such as cost, weight and reliability into consideration. S4 can be described as a general architecture structured to accommodate application-specific components and requirements. It performs combinational optimization with a user defined merit or cost function to identify optimum or near-optimum sensor suite solutions. The S4 User Guide describes the sensor selection procedure and presents an example problem using an open source turbofan engine simulation to demonstrate its application.

Optimal Sensor Location Design for Reliable Fault Detection in Presence of False Alarms

PubMed Central

Yang, Fan; Xiao, Deyun; Shah, Sirish L.

2009-01-01

To improve fault detection reliability, sensor location should be designed according to an optimization criterion with constraints imposed by issues of detectability and identifiability. Reliability requires the minimization of undetectability and false alarm probability due to random factors on sensor readings, which is not only related with sensor readings but also affected by fault propagation. This paper introduces the reliability criteria expression based on the missed/false alarm probability of each sensor and system topology or connectivity derived from the directed graph. The algorithm for the optimization problem is presented as a heuristic procedure. Finally, a boiler system is illustrated using the proposed method. PMID:22291524

Analytical modeling and sensor monitoring for optimal processing of advanced textile structural composites by resin transfer molding

NASA Technical Reports Server (NTRS)

Loos, Alfred C.; Macrae, John D.; Hammond, Vincent H.; Kranbuehl, David E.; Hart, Sean M.; Hasko, Gregory H.; Markus, Alan M.

1993-01-01

A two-dimensional model of the resin transfer molding (RTM) process was developed which can be used to simulate the infiltration of resin into an anisotropic fibrous preform. Frequency dependent electromagnetic sensing (FDEMS) has been developed for in situ monitoring of the RTM process. Flow visualization tests were performed to obtain data which can be used to verify the sensor measurements and the model predictions. Results of the tests showed that FDEMS can accurately detect the position of the resin flow-front during mold filling, and that the model predicted flow-front patterns agreed well with the measured flow-front patterns.

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

Electro-optic architecture (EOA) for sensors and actuators in aircraft propulsion systems

NASA Technical Reports Server (NTRS)

Glomb, W. L., Jr.

1989-01-01

Results of a study to design an optimal architecture for electro-optical sensing and control in advanced aircraft and space systems are described. The propulsion full authority digital Electronic Engine Control (EEC) was the focus for the study. The recommended architecture is an on-engine EEC which contains electro-optic interface circuits for fiber-optic sensors on the engine. Size and weight are reduced by multiplexing arrays of functionally similar sensors on a pair of optical fibers to common electro-optical interfaces. The architecture contains common, multiplex interfaces to seven sensor groups: (1) self luminous sensors; (2) high temperatures; (3) low temperatures; (4) speeds and flows; (5) vibration; (6) pressures; and (7) mechanical positions. Nine distinct fiber-optic sensor types were found to provide these sensing functions: (1) continuous wave (CW) intensity modulators; (2) time division multiplexing (TDM) digital optic codeplates; (3) time division multiplexing (TDM) analog self-referenced sensors; (4) wavelength division multiplexing (WDM) digital optic code plates; (5) wavelength division multiplexing (WDM) analog self-referenced intensity modulators; (6) analog optical spectral shifters; (7) self-luminous bodies; (8) coherent optical interferometers; and (9) remote electrical sensors. The report includes the results of a trade study including engine sensor requirements, environment, the basic sensor types, and relevant evaluation criteria. These figures of merit for the candidate interface types were calculated from the data supplied by leading manufacturers of fiber-optic sensors.

Parameter Selection and Performance Comparison of Particle Swarm Optimization in Sensor Networks Localization

PubMed Central

Cui, Huanqing; Shu, Minglei; Song, Min; Wang, Yinglong

2017-01-01

Localization is a key technology in wireless sensor networks. Faced with the challenges of the sensors’ memory, computational constraints, and limited energy, particle swarm optimization has been widely applied in the localization of wireless sensor networks, demonstrating better performance than other optimization methods. In particle swarm optimization-based localization algorithms, the variants and parameters should be chosen elaborately to achieve the best performance. However, there is a lack of guidance on how to choose these variants and parameters. Further, there is no comprehensive performance comparison among particle swarm optimization algorithms. The main contribution of this paper is three-fold. First, it surveys the popular particle swarm optimization variants and particle swarm optimization-based localization algorithms for wireless sensor networks. Secondly, it presents parameter selection of nine particle swarm optimization variants and six types of swarm topologies by extensive simulations. Thirdly, it comprehensively compares the performance of these algorithms. The results show that the particle swarm optimization with constriction coefficient using ring topology outperforms other variants and swarm topologies, and it performs better than the second-order cone programming algorithm. PMID:28257060

Optimal placement of multiple types of communicating sensors with availability and coverage redundancy constraints

NASA Astrophysics Data System (ADS)

Vecherin, Sergey N.; Wilson, D. Keith; Pettit, Chris L.

2010-04-01

Determination of an optimal configuration (numbers, types, and locations) of a sensor network is an important practical problem. In most applications, complex signal propagation effects and inhomogeneous coverage preferences lead to an optimal solution that is highly irregular and nonintuitive. The general optimization problem can be strictly formulated as a binary linear programming problem. Due to the combinatorial nature of this problem, however, its strict solution requires significant computational resources (NP-complete class of complexity) and is unobtainable for large spatial grids of candidate sensor locations. For this reason, a greedy algorithm for approximate solution was recently introduced [S. N. Vecherin, D. K. Wilson, and C. L. Pettit, "Optimal sensor placement with terrain-based constraints and signal propagation effects," Unattended Ground, Sea, and Air Sensor Technologies and Applications XI, SPIE Proc. Vol. 7333, paper 73330S (2009)]. Here further extensions to the developed algorithm are presented to include such practical needs and constraints as sensor availability, coverage by multiple sensors, and wireless communication of the sensor information. Both communication and detection are considered in a probabilistic framework. Communication signal and signature propagation effects are taken into account when calculating probabilities of communication and detection. Comparison of approximate and strict solutions on reduced-size problems suggests that the approximate algorithm yields quick and good solutions, which thus justifies using that algorithm for full-size problems. Examples of three-dimensional outdoor sensor placement are provided using a terrain-based software analysis tool.

Localization Algorithm Based on a Spring Model (LASM) for Large Scale Wireless Sensor Networks.

PubMed

Chen, Wanming; Mei, Tao; Meng, Max Q-H; Liang, Huawei; Liu, Yumei; Li, Yangming; Li, Shuai

2008-03-15

A navigation method for a lunar rover based on large scale wireless sensornetworks is proposed. To obtain high navigation accuracy and large exploration area, highnode localization accuracy and large network scale are required. However, thecomputational and communication complexity and time consumption are greatly increasedwith the increase of the network scales. A localization algorithm based on a spring model(LASM) method is proposed to reduce the computational complexity, while maintainingthe localization accuracy in large scale sensor networks. The algorithm simulates thedynamics of physical spring system to estimate the positions of nodes. The sensor nodesare set as particles with masses and connected with neighbor nodes by virtual springs. Thevirtual springs will force the particles move to the original positions, the node positionscorrespondingly, from the randomly set positions. Therefore, a blind node position can bedetermined from the LASM algorithm by calculating the related forces with the neighbornodes. The computational and communication complexity are O(1) for each node, since thenumber of the neighbor nodes does not increase proportionally with the network scale size.Three patches are proposed to avoid local optimization, kick out bad nodes and deal withnode variation. Simulation results show that the computational and communicationcomplexity are almost constant despite of the increase of the network scale size. The time consumption has also been proven to remain almost constant since the calculation steps arealmost unrelated with the network scale size.

An Energy Balanced and Lifetime Extended Routing Protocol for Underwater Sensor Networks.

PubMed

Wang, Hao; Wang, Shilian; Zhang, Eryang; Lu, Luxi

2018-05-17

Energy limitation is an adverse problem in designing routing protocols for underwater sensor networks (UWSNs). To prolong the network lifetime with limited battery power, an energy balanced and efficient routing protocol, called energy balanced and lifetime extended routing protocol (EBLE), is proposed in this paper. The proposed EBLE not only balances traffic loads according to the residual energy, but also optimizes data transmissions by selecting low-cost paths. Two phases are operated in the EBLE data transmission process: (1) candidate forwarding set selection phase and (2) data transmission phase. In candidate forwarding set selection phase, nodes update candidate forwarding nodes by broadcasting the position and residual energy level information. The cost value of available nodes is calculated and stored in each sensor node. Then in data transmission phase, high residual energy and relatively low-cost paths are selected based on the cost function and residual energy level information. We also introduce detailed analysis of optimal energy consumption in UWSNs. Numerical simulation results on a variety of node distributions and data load distributions prove that EBLE outperforms other routing protocols (BTM, BEAR and direct transmission) in terms of network lifetime and energy efficiency.

Optimization of the Hartmann-Shack microlens array

NASA Astrophysics Data System (ADS)

de Oliveira, Otávio Gomes; de Lima Monteiro, Davies William

2011-04-01

In this work we propose to optimize the microlens-array geometry for a Hartmann-Shack wavefront sensor. The optimization makes possible that regular microlens arrays with a larger number of microlenses are replaced by arrays with fewer microlenses located at optimal sampling positions, with no increase in the reconstruction error. The goal is to propose a straightforward and widely accessible numerical method to calculate an optimized microlens array for a known aberration statistics. The optimization comprises the minimization of the wavefront reconstruction error and/or the number of necessary microlenses in the array. We numerically generate, sample and reconstruct the wavefront, and use a genetic algorithm to discover the optimal array geometry. Within an ophthalmological context, as a case study, we demonstrate that an array with only 10 suitably located microlenses can be used to produce reconstruction errors as small as those of a 36-microlens regular array. The same optimization procedure can be employed for any application where the wavefront statistics is known.

Design of a sensor network for structural health monitoring of a full-scale composite horizontal tail

NASA Astrophysics Data System (ADS)

Gao, Dongyue; Wang, Yishou; Wu, Zhanjun; Rahim, Gorgin; Bai, Shengbao

2014-05-01

The detection capability of a given structural health monitoring (SHM) system strongly depends on its sensor network placement. In order to minimize the number of sensors while maximizing the detection capability, optimal design of the PZT sensor network placement is necessary for structural health monitoring (SHM) of a full-scale composite horizontal tail. In this study, the sensor network optimization was simplified as a problem of determining the sensor array placement between stiffeners to achieve the desired the coverage rate. First, an analysis of the structural layout and load distribution of a composite horizontal tail was performed. The constraint conditions of the optimal design were presented. Then, the SHM algorithm of the composite horizontal tail under static load was proposed. Based on the given SHM algorithm, a sensor network was designed for the full-scale composite horizontal tail structure. Effective profiles of cross-stiffener paths (CRPs) and uncross-stiffener paths (URPs) were estimated by a Lamb wave propagation experiment in a multi-stiffener composite specimen. Based on the coverage rate and the redundancy requirements, a seven-sensor array-network was chosen as the optimal sensor network for each airfoil. Finally, a preliminary SHM experiment was performed on a typical composite aircraft structure component. The reliability of the SHM result for a composite horizontal tail structure under static load was validated. In the result, the red zone represented the delamination damage. The detection capability of the optimized sensor network was verified by SHM of a full-scale composite horizontal tail; all the diagnosis results were obtained in two minutes. The result showed that all the damage in the monitoring region was covered by the sensor network.

Cost-Effectiveness Analysis of Aerial Platforms and Suitable Communication Payloads

DTIC Science & Technology

2014-03-01

High altitude long endurance (HALE) platforms for tactical wireless communications and sensor use in military operations. (Master’s thesis, Naval...the ground, which can offer near limitless endurance. Additionally, running data over wired networks reduces wireless congestion. The most...system that utilizes different wind speeds and wind directions at different altitudes in an attempt to position the balloons for optimal communications

Increasing the Lifetime of Mobile WSNs via Dynamic Optimization of Sensor Node Communication Activity.

PubMed

Guimarães, Dayan Adionel; Sakai, Lucas Jun; Alberti, Antonio Marcos; de Souza, Rausley Adriano Amaral

2016-09-20

In this paper, a simple and flexible method for increasing the lifetime of fixed or mobile wireless sensor networks is proposed. Based on past residual energy information reported by the sensor nodes, the sink node or another central node dynamically optimizes the communication activity levels of the sensor nodes to save energy without sacrificing the data throughput. The activity levels are defined to represent portions of time or time-frequency slots in a frame, during which the sensor nodes are scheduled to communicate with the sink node to report sensory measurements. Besides node mobility, it is considered that sensors' batteries may be recharged via a wireless power transmission or equivalent energy harvesting scheme, bringing to the optimization problem an even more dynamic character. We report large increased lifetimes over the non-optimized network and comparable or even larger lifetime improvements with respect to an idealized greedy algorithm that uses both the real-time channel state and the residual energy information.

Developing a Fundamental Model for an Integrated GPS/INS State Estimation System with Kalman Filtering

NASA Technical Reports Server (NTRS)

Canfield, Stephen

1999-01-01

This work will demonstrate the integration of sensor and system dynamic data and their appropriate models using an optimal filter to create a robust, adaptable, easily reconfigurable state (motion) estimation system. This state estimation system will clearly show the application of fundamental modeling and filtering techniques. These techniques are presented at a general, first principles level, that can easily be adapted to specific applications. An example of such an application is demonstrated through the development of an integrated GPS/INS navigation system. This system acquires both global position data and inertial body data, to provide optimal estimates of current position and attitude states. The optimal states are estimated using a Kalman filter. The state estimation system will include appropriate error models for the measurement hardware. The results of this work will lead to the development of a "black-box" state estimation system that supplies current motion information (position and attitude states) that can be used to carry out guidance and control strategies. This black-box state estimation system is developed independent of the vehicle dynamics and therefore is directly applicable to a variety of vehicles. Issues in system modeling and application of Kalman filtering techniques are investigated and presented. These issues include linearized models of equations of state, models of the measurement sensors, and appropriate application and parameter setting (tuning) of the Kalman filter. The general model and subsequent algorithm is developed in Matlab for numerical testing. The results of this system are demonstrated through application to data from the X-33 Michael's 9A8 mission and are presented in plots and simple animations.

Research on the position estimation of human movement based on camera projection

NASA Astrophysics Data System (ADS)

Yi, Zhang; Yuan, Luo; Hu, Huosheng

2005-06-01

During the rehabilitation process of the post-stroke patients is conducted, their movements need to be localized and learned so that incorrect movement can be instantly modified or tuned. Therefore, tracking these movement becomes vital and necessary for the rehabilitative course. During human movement tracking, the position estimation of human movement is very important. In this paper, the character of the human movement system is first analyzed. Next, camera and inertial sensor are used to respectively measure the position of human movement, and the Kalman filter algorithm is proposed to fuse the two measurement to get a optimization estimation of the position. In the end, the performance of the method is analyzed.

Autonomous Sensors Powered by Energy Harvesting from von Karman Vortices in Airflow.

PubMed

Demori, Marco; Ferrari, Marco; Bonzanini, Arianna; Poesio, Pietro; Ferrari, Vittorio

2017-09-13

In this paper an energy harvesting system based on a piezoelectric converter to extract energy from airflow and use it to power battery-less sensors is presented. The converter is embedded as a part of a flexure beam that is put into vibrations by von Karman vortices detached from a bluff body placed upstream. The vortex street has been investigated by Computational Fluid Dynamics (CFD) simulations, aiming at assessing the vortex shedding frequency as a function of the flow velocity. From the simulation results the preferred positioning of the beam behind the bluff body has been derived. In the experimental characterization the electrical output from the converter has been measured for different flow velocities and beam orientations. Highest conversion effectiveness is obtained by an optimal orientation of the beam, to exploit the maximum forcing, and for flow velocities where the repetition frequency of the vortices allows to excite the beam resonant frequency at its first flexural mode. The possibility to power battery-less sensors and make them autonomous has been shown by developing an energy management and signal conditioning electronic circuit plus two sensors for measuring temperature and flow velocity and transmitting their values over a RF signal. A harvested power of about 650 μW with retransmission intervals below 2 min have been obtained for the optimal flow velocity of 4 m/s.

Autonomous Sensors Powered by Energy Harvesting from von Karman Vortices in Airflow

PubMed Central

Bonzanini, Arianna; Poesio, Pietro

2017-01-01

In this paper an energy harvesting system based on a piezoelectric converter to extract energy from airflow and use it to power battery-less sensors is presented. The converter is embedded as a part of a flexure beam that is put into vibrations by von Karman vortices detached from a bluff body placed upstream. The vortex street has been investigated by Computational Fluid Dynamics (CFD) simulations, aiming at assessing the vortex shedding frequency as a function of the flow velocity. From the simulation results the preferred positioning of the beam behind the bluff body has been derived. In the experimental characterization the electrical output from the converter has been measured for different flow velocities and beam orientations. Highest conversion effectiveness is obtained by an optimal orientation of the beam, to exploit the maximum forcing, and for flow velocities where the repetition frequency of the vortices allows to excite the beam resonant frequency at its first flexural mode. The possibility to power battery-less sensors and make them autonomous has been shown by developing an energy management and signal conditioning electronic circuit plus two sensors for measuring temperature and flow velocity and transmitting their values over a RF signal. A harvested power of about 650 μW with retransmission intervals below 2 min have been obtained for the optimal flow velocity of 4 m/s. PMID:28902139

Highly Sensitive Detection of Urinary Cadmium to Assess Personal Exposure

PubMed Central

Argun, Avni A.; Banks, Ashley; Merlen, Gwendolynne; Tempelman, Linda A.; Becker, Michael F.; Schuelke, Thomas; Dweik, Badawi

2013-01-01

A series of Boron-Doped Diamond (BDD) ultramicroelectrode arrays were fabricated and investigated for their performance as electrochemical sensors to detect trace level metals such as cadmium. The steady-state diffusion behavior of these sensors was validated using cyclic voltammetry followed by electrochemical detection of cadmium in water and in human urine to demonstrate high sensitivity (>200 μA/ppb/cm2) and low background current (<4 nA). When an array of ultramicroelectrodes was positioned with optimal spacing, these BDD sensors showed a sigmoidal diffusion behavior. They also demonstrated high accuracy with linear dose dependence for quantification of cadmium in a certified reference river water sample from the National Institute of Standards and Technology (NIST) as well as in a human urine sample spiked with 0.25–1 ppb cadmium. PMID:23561905

Probing with and into fingerprints.

PubMed

Dahiya, Ravinder S; Gori, Monica

2010-07-01

A recent report by Scheibert et al. highlights the role of fingerprints in enhancing tactile sensitivity. By scanning a surface with a biometric force sensor they demonstrate the dominance of the frequencies that fall within the optimal sensitivity range of Pacinian afferents. The sensor, in this study, has a soft cover patterned with parallel ridges-mimicking the fingerprints. However, the skin structure is quite complex. Elasticity of the skin varies with depth and the ridge like pattern is comprised of not just papillary ridges or fingerprints. Besides fingerprints there exist intermediate ridges, positioned exactly under the papillary ridges, and limiting ridges at dermis-epidermis junction. These structures are usually considered as single unit. If so, it is important to revisit and see if the role of fingerprints remains the same, should the sensor cover have both fingerprints and intermediate ridges.

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.

Teleoperation System with Hybrid Pneumatic-Piezoelectric Actuation for MRI-Guided Needle Insertion with Haptic Feedback

PubMed Central

Shang, Weijian; Su, Hao; Li, Gang; Fischer, Gregory S.

2014-01-01

This paper presents a surgical master-slave tele-operation system for percutaneous interventional procedures under continuous magnetic resonance imaging (MRI) guidance. This system consists of a piezoelectrically actuated slave robot for needle placement with integrated fiber optic force sensor utilizing Fabry-Perot interferometry (FPI) sensing principle. The sensor flexure is optimized and embedded to the slave robot for measuring needle insertion force. A novel, compact opto-mechanical FPI sensor interface is integrated into an MRI robot control system. By leveraging the complementary features of pneumatic and piezoelectric actuation, a pneumatically actuated haptic master robot is also developed to render force associated with needle placement interventions to the clinician. An aluminum load cell is implemented and calibrated to close the impedance control loop of the master robot. A force-position control algorithm is developed to control the hybrid actuated system. Teleoperated needle insertion is demonstrated under live MR imaging, where the slave robot resides in the scanner bore and the user manipulates the master beside the patient outside the bore. Force and position tracking results of the master-slave robot are demonstrated to validate the tracking performance of the integrated system. It has a position tracking error of 0.318mm and sine wave force tracking error of 2.227N. PMID:25126446

Teleoperation System with Hybrid Pneumatic-Piezoelectric Actuation for MRI-Guided Needle Insertion with Haptic Feedback.

PubMed

Shang, Weijian; Su, Hao; Li, Gang; Fischer, Gregory S

2013-01-01

This paper presents a surgical master-slave tele-operation system for percutaneous interventional procedures under continuous magnetic resonance imaging (MRI) guidance. This system consists of a piezoelectrically actuated slave robot for needle placement with integrated fiber optic force sensor utilizing Fabry-Perot interferometry (FPI) sensing principle. The sensor flexure is optimized and embedded to the slave robot for measuring needle insertion force. A novel, compact opto-mechanical FPI sensor interface is integrated into an MRI robot control system. By leveraging the complementary features of pneumatic and piezoelectric actuation, a pneumatically actuated haptic master robot is also developed to render force associated with needle placement interventions to the clinician. An aluminum load cell is implemented and calibrated to close the impedance control loop of the master robot. A force-position control algorithm is developed to control the hybrid actuated system. Teleoperated needle insertion is demonstrated under live MR imaging, where the slave robot resides in the scanner bore and the user manipulates the master beside the patient outside the bore. Force and position tracking results of the master-slave robot are demonstrated to validate the tracking performance of the integrated system. It has a position tracking error of 0.318mm and sine wave force tracking error of 2.227N.

Lab-on-a-chip sensor for measuring Zn by stripping voltammetry

NASA Astrophysics Data System (ADS)

Pei, Xing; Kang, Wenjing; Yue, Wei; Bange, Adam; Wong, Hector R.; Heineman, William R.; Papautsky, Ian

2012-03-01

This work reports on continuing development of a lab-on-a-chip sensor for electrochemical detection of heavy metal zinc in blood serum. The sensor consists of a three electrode system, including an environmentally-friendly bismuth working electrode, a Ag/AgCl reference electrode, and a gold auxiliary electrode. By optimizing the electrodeposition of bismuth film, better control of fabrication steps and improving interface between the sensor and potentiostat, repeatability and sensitivity of the lab-on-a-chip sensor has been improved. Through optimization of electrolyte and stripping voltammetry parameters, limits of detection were greatly improved. The optimized sensor was able to measure zinc in in the physiological range of 65-95 μg/dL. Ultimately, with further development and integrated sample preparation sensor system will permit rapid (min) measurements of zinc from a sub-mL sample (a few drops of blood) for bedside monitoring.

A Sensor Dynamic Measurement Error Prediction Model Based on NAPSO-SVM.

PubMed

Jiang, Minlan; Jiang, Lan; Jiang, Dingde; Li, Fei; Song, Houbing

2018-01-15

Dynamic measurement error correction is an effective way to improve sensor precision. Dynamic measurement error prediction is an important part of error correction, and support vector machine (SVM) is often used for predicting the dynamic measurement errors of sensors. Traditionally, the SVM parameters were always set manually, which cannot ensure the model's performance. In this paper, a SVM method based on an improved particle swarm optimization (NAPSO) is proposed to predict the dynamic measurement errors of sensors. Natural selection and simulated annealing are added in the PSO to raise the ability to avoid local optima. To verify the performance of NAPSO-SVM, three types of algorithms are selected to optimize the SVM's parameters: the particle swarm optimization algorithm (PSO), the improved PSO optimization algorithm (NAPSO), and the glowworm swarm optimization (GSO). The dynamic measurement error data of two sensors are applied as the test data. The root mean squared error and mean absolute percentage error are employed to evaluate the prediction models' performances. The experimental results show that among the three tested algorithms the NAPSO-SVM method has a better prediction precision and a less prediction errors, and it is an effective method for predicting the dynamic measurement errors of sensors.

Piezoresistive Composite Silicon Dioxide Nanocantilever Surface Stress Sensor: Design and Optimization.

PubMed

Mathew, Ribu; Sankar, A Ravi

2018-05-01

In this paper, we present the design and optimization of a rectangular piezoresistive composite silicon dioxide nanocantilever sensor. Unlike the conventional design approach, we perform the sensor optimization by not only considering its electro-mechanical response but also incorporating the impact of self-heating induced thermal drift in its terminal characteristics. Through extensive simulations first we comprehend and quantify the inaccuracies due to self-heating effect induced by the geometrical and intrinsic parameters of the piezoresistor. Then, by optimizing the ratio of electrical sensitivity to thermal sensitivity defined as the sensitivity ratio (υ) we improve the sensor performance and measurement reliability. Results show that to ensure υ ≥ 1, shorter and wider piezoresistors are better. In addition, it is observed that unlike the general belief that high doping concentration of piezoresistor reduces thermal sensitivity in piezoresistive sensors, to ensure υ ≥ 1 doping concentration (p) should be in the range: 1E18 cm-3 ≤ p ≤ 1E19 cm-3. Finally, we provide a set of design guidelines that will help NEMS engineers to optimize the performance of such sensors for chemical and biological sensing applications.

Unsteady flow sensing and optimal sensor placement using machine learning

NASA Astrophysics Data System (ADS)

Semaan, Richard

2016-11-01

Machine learning is used to estimate the flow state and to determine the optimal sensor placement over a two-dimensional (2D) airfoil equipped with a Coanda actuator. The analysis is based on flow field data obtained from 2D unsteady Reynolds averaged Navier-Stokes (uRANS) simulations with different jet blowing intensities and actuation frequencies, characterizing different flow separation states. This study shows how the "random forests" algorithm is utilized beyond its typical usage in fluid mechanics estimating the flow state to determine the optimal sensor placement. The results are compared against the current de-facto standard of maximum modal amplitude location and against a brute force approach that scans all possible sensor combinations. The results show that it is possible to simultaneously infer the state of flow and to determine the optimal sensor location without the need to perform proper orthogonal decomposition. Collaborative Research Center (CRC) 880, DFG.

Sentient Structures: Optimising Sensor Layouts for Direct Measurement of Discrete Variables

DTIC Science & Technology

2008-11-01

1 Sentient Structures Optimising Sensor Layouts for Direct Measurement of Discrete Variables Report to US Air Force...TITLE AND SUBTITLE Sentient Structures 5a. CONTRACT NUMBER FA48690714045 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Donald Price...optimal sensor placements is an important requirement for the development of sentient structures. An optimal sensor layout is attained when a limited

Setup and evaluation of a sensor tilting system for dimensional micro- and nanometrology

NASA Astrophysics Data System (ADS)

Schuler, Alexander; Weckenmann, Albert; Hausotte, Tino

2014-06-01

Sensors in micro- and nanometrology show their limits if the measurement objects and surfaces feature high aspect ratios, high curvature and steep surface angles. Their measurable surface angle is limited and an excess leads to measurement deviation and not detectable surface points. We demonstrate a principle to adapt the sensor's working angle during the measurement keeping the sensor in its optimal working angle. After the simulation of the principle, a hardware prototype was realized. It is based on a rotary kinematic chain with two rotary degrees of freedom, which extends the measurable surface angle to ±90° and is combined with a nanopositioning and nanomeasuring machine. By applying a calibration procedure with a quasi-tactile 3D sensor based on electrical near-field interaction the systematic position deviation of the kinematic chain is reduced. The paper shows for the first time the completed setup and integration of the prototype, the performance results of the calibration, the measurements with the prototype and the tilting principle, and finishes with the interpretation and feedback of the practical results.

Optimization of Thermal Neutron Converter in SiC Sensors for Spectral Radiation Measurements

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

Krolikowski, Igor; Cetnar, Jerzy; Issa, Fatima

2015-07-01

Optimization of the neutron converter in SiC sensors is presented. The sensors are used for spectral radiation measurements of thermal and fast neutrons and optionally gamma ray at elevated temperature in harsh radiation environment. The neutron converter, which is based on 10B, allows to detect thermal neutrons by means of neutron capture reaction. Two construction of the sensors were used to measure radiation in experiments. Sensor responses collected in experiments have been reproduced by the computer tool created by authors, it allows to validate the tool. The tool creates the response matrix function describing the characteristic of the sensors andmore » it was used for detailed analyses of the sensor responses. Obtained results help to optimize the neutron converter in order to increase thermal neutron detection. Several enhanced construction of the sensors, which includes the neutron converter based on {sup 10}B or {sup 6}Li, were proposed. (authors)« less

Bio-inspired UAV routing, source localization, and acoustic signature classification for persistent surveillance

NASA Astrophysics Data System (ADS)

Burman, Jerry; Hespanha, Joao; Madhow, Upamanyu; Pham, Tien

2011-06-01

A team consisting of Teledyne Scientific Company, the University of California at Santa Barbara and the Army Research Laboratory* is developing technologies in support of automated data exfiltration from heterogeneous battlefield sensor networks to enhance situational awareness for dismounts and command echelons. Unmanned aerial vehicles (UAV) provide an effective means to autonomously collect data from a sparse network of unattended ground sensors (UGSs) that cannot communicate with each other. UAVs are used to reduce the system reaction time by generating autonomous collection routes that are data-driven. Bio-inspired techniques for search provide a novel strategy to detect, capture and fuse data. A fast and accurate method has been developed to localize an event by fusing data from a sparse number of UGSs. This technique uses a bio-inspired algorithm based on chemotaxis or the motion of bacteria seeking nutrients in their environment. A unique acoustic event classification algorithm was also developed based on using swarm optimization. Additional studies addressed the problem of routing multiple UAVs, optimally placing sensors in the field and locating the source of gunfire at helicopters. A field test was conducted in November of 2009 at Camp Roberts, CA. The field test results showed that a system controlled by bio-inspired software algorithms can autonomously detect and locate the source of an acoustic event with very high accuracy and visually verify the event. In nine independent test runs of a UAV, the system autonomously located the position of an explosion nine times with an average accuracy of 3 meters. The time required to perform source localization using the UAV was on the order of a few minutes based on UAV flight times. In June 2011, additional field tests of the system will be performed and will include multiple acoustic events, optimal sensor placement based on acoustic phenomenology and the use of the International Technology Alliance (ITA) Sensor Network Fabric (IBM).

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.

Jamming Attack in Wireless Sensor Network: From Time to Space

NASA Astrophysics Data System (ADS)

Sun, Yanqiang; Wang, Xiaodong; Zhou, Xingming

Classical jamming attack models in the time domain have been proposed, such as constant jammer, random jammer, and reactive jammer. In this letter, we consider a new problem: given k jammers, how does the attacker minimize the pair-wise connectivity among the nodes in a Wireless Sensor Network (WSN)? We call this problem k-Jammer Deployment Problem (k-JDP). To the best of our knowledge, this is the first attempt at considering the position-critical jamming attack against wireless sensor network. We mainly make three contributions. First, we prove that the decision version of k-JDP is NP-complete even in the ideal situation where the attacker has full knowledge of the topology information of sensor network. Second, we propose a mathematical formulation based on Integer Programming (IP) model which yields an optimal solution. Third, we present a heuristic algorithm HAJDP, and compare it with the IP model. Numerical results show that our heuristic algorithm is computationally efficient.

Design of a Minimum Surface-Effect Tendon-Based Microactuator for Micromanipulation

NASA Technical Reports Server (NTRS)

Goldfarb, Michael; Lipsey, James H.

1997-01-01

A piezoelectric (PZT) stack-based actuator was developed to provide a means of actuation with dynamic characteristics appropriate for small-scale manipulation. In particular, the design incorporates a highly nonlinear, large-ratio transmission that provides approximately two orders of magnitude motion amplification from the PZT stack. In addition to motion amplification, the nonlinear transmission was designed via optimization methods to distort the highly non-uniform properties of a piezoelectric actuator so that the achievable actuation force is nearly constant throughout the actuator workspace. The package also includes sensors that independently measure actuator output force and displacement, so that a manipulator structure need not incorporate sensors nor the associated wires. Specifically, the actuator was designed to output a maximum force of at least one Newton through a stroke of at least one millimeter. For purposes of small-scale precision position and/or force control, the actuator/sensor package was designed to eliminate stick-slip friction and backlash. The overall dimensions of the actuator/sensor package are approximately 40 x 65 x 25 mm.

Management of unmanned moving sensors through human decision layers: a bi-level optimization process with calls to costly sub-processes

NASA Astrophysics Data System (ADS)

Dambreville, Frédéric

2013-10-01

While there is a variety of approaches and algorithms for optimizing the mission of an unmanned moving sensor, there are much less works which deal with the implementation of several sensors within a human organization. In this case, the management of the sensors is done through at least one human decision layer, and the sensors management as a whole arises as a bi-level optimization process. In this work, the following hypotheses are considered as realistic: Sensor handlers of first level plans their sensors by means of elaborated algorithmic tools based on accurate modelling of the environment; Higher level plans the handled sensors according to a global observation mission and on the basis of an approximated model of the environment and of the first level sub-processes. This problem is formalized very generally as the maximization of an unknown function, defined a priori by sampling a known random function (law of model error). In such case, each actual evaluation of the function increases the knowledge about the function, and subsequently the efficiency of the maximization. The issue is to optimize the sequence of value to be evaluated, in regards to the evaluation costs. There is here a fundamental link with the domain of experiment design. Jones, Schonlau and Welch proposed a general method, the Efficient Global Optimization (EGO), for solving this problem in the case of additive functional Gaussian law. In our work, a generalization of the EGO is proposed, based on a rare event simulation approach. It is applied to the aforementioned bi-level sensor planning.

Simulation of an enzyme-based glucose sensor

NASA Astrophysics Data System (ADS)

Sha, Xianzheng; Jablecki, Michael; Gough, David A.

2001-09-01

An important biosensor application is the continuous monitoring blood or tissue fluid glucose concentration in people with diabetes. Our research focuses on the development of a glucose sensor based on potentiostatic oxygen electrodes and immobilized glucose oxidase for long- term application as an implant in tissues. As the sensor signal depends on many design variables, a trial-and-error approach to sensor optimization can be time-consuming. Here, the properties of an implantable glucose sensor are optimized by a systematic computational simulation approach.

An autonomous sensor module based on a legacy CCTV camera

NASA Astrophysics Data System (ADS)

Kent, P. J.; Faulkner, D. A. A.; Marshall, G. F.

2016-10-01

A UK MoD funded programme into autonomous sensors arrays (SAPIENT) has been developing new, highly capable sensor modules together with a scalable modular architecture for control and communication. As part of this system there is a desire to also utilise existing legacy sensors. The paper reports upon the development of a SAPIENT-compliant sensor module using a legacy Close-Circuit Television (CCTV) pan-tilt-zoom (PTZ) camera. The PTZ camera sensor provides three modes of operation. In the first mode, the camera is automatically slewed to acquire imagery of a specified scene area, e.g. to provide "eyes-on" confirmation for a human operator or for forensic purposes. In the second mode, the camera is directed to monitor an area of interest, with zoom level automatically optimized for human detection at the appropriate range. Open source algorithms (using OpenCV) are used to automatically detect pedestrians; their real world positions are estimated and communicated back to the SAPIENT central fusion system. In the third mode of operation a "follow" mode is implemented where the camera maintains the detected person within the camera field-of-view without requiring an end-user to directly control the camera with a joystick.

Improved scheme for Cross-track Infrared Sounder geolocation assessment and optimization

NASA Astrophysics Data System (ADS)

Wang, Likun; Zhang, Bin; Tremblay, Denis; Han, Yong

2017-01-01

An improved scheme for Cross-track Infrared Sounder (CrIS) geolocation assessment for all scan angles (from -48.5° to 48.5°) is developed in this study. The method uses spatially collocated radiance measurements from the Visible Infrared Imaging Radiometer Suite (VIIRS) image band I5 to evaluate the geolocation performance of the CrIS Sensor Data Records (SDR) by taking advantage of its high spatial resolution (375 m at nadir) and accurate geolocation. The basic idea is to perturb CrIS line-of-sight vectors along the in-track and cross-track directions to find a position where CrIS and VIIRS data matches more closely. The perturbation angles at this best matched position are then used to evaluate the CrIS geolocation accuracy. More importantly, the new method is capable of performing postlaunch on-orbit geometric calibration by optimizing mapping angle parameters based on the assessment results and thus can be further extended to the following CrIS sensors on new satellites. Finally, the proposed method is employed to evaluate the CrIS geolocation accuracy on current Suomi National Polar-orbiting Partnership satellite. The error characteristics are revealed along the scan positions in the in-track and cross-track directions. It is found that there are relatively large errors ( 4 km) in the cross-track direction close to the end of scan positions. With newly updated mapping angles, the geolocation accuracy is greatly improved for all scan positions (less than 0.3 km). This makes CrIS and VIIRS spatially align together and thus benefits the application that needs combination of CrIS and VIIRS measurements and products.

BlueDetect: An iBeacon-Enabled Scheme for Accurate and Energy-Efficient Indoor-Outdoor Detection and Seamless Location-Based Service

PubMed Central

Zou, Han; Jiang, Hao; Luo, Yiwen; Zhu, Jianjie; Lu, Xiaoxuan; Xie, Lihua

2016-01-01

The location and contextual status (indoor or outdoor) is fundamental and critical information for upper-layer applications, such as activity recognition and location-based services (LBS) for individuals. In addition, optimizations of building management systems (BMS), such as the pre-cooling or heating process of the air-conditioning system according to the human traffic entering or exiting a building, can utilize the information, as well. The emerging mobile devices, which are equipped with various sensors, become a feasible and flexible platform to perform indoor-outdoor (IO) detection. However, power-hungry sensors, such as GPS and WiFi, should be used with caution due to the constrained battery storage on mobile device. We propose BlueDetect: an accurate, fast response and energy-efficient scheme for IO detection and seamless LBS running on the mobile device based on the emerging low-power iBeacon technology. By leveraging the on-broad Bluetooth module and our proposed algorithms, BlueDetect provides a precise IO detection service that can turn on/off on-board power-hungry sensors smartly and automatically, optimize their performances and reduce the power consumption of mobile devices simultaneously. Moreover, seamless positioning and navigation services can be realized by it, especially in a semi-outdoor environment, which cannot be achieved by GPS or an indoor positioning system (IPS) easily. We prototype BlueDetect on Android mobile devices and evaluate its performance comprehensively. The experimental results have validated the superiority of BlueDetect in terms of IO detection accuracy, localization accuracy and energy consumption. PMID:26907295

Predictive simulations and optimization of nanowire field-effect PSA sensors including screening

NASA Astrophysics Data System (ADS)

Baumgartner, Stefan; Heitzinger, Clemens; Vacic, Aleksandar; Reed, Mark A.

2013-06-01

We apply our self-consistent PDE model for the electrical response of field-effect sensors to the 3D simulation of nanowire PSA (prostate-specific antigen) sensors. The charge concentration in the biofunctionalized boundary layer at the semiconductor-electrolyte interface is calculated using the propka algorithm, and the screening of the biomolecules by the free ions in the liquid is modeled by a sensitivity factor. This comprehensive approach yields excellent agreement with experimental current-voltage characteristics without any fitting parameters. Having verified the numerical model in this manner, we study the sensitivity of nanowire PSA sensors by changing device parameters, making it possible to optimize the devices and revealing the attributes of the optimal field-effect sensor.

Optimization of wireless sensor networks based on chicken swarm optimization algorithm

NASA Astrophysics Data System (ADS)

Wang, Qingxi; Zhu, Lihua

2017-05-01

In order to reduce the energy consumption of wireless sensor network and improve the survival time of network, the clustering routing protocol of wireless sensor networks based on chicken swarm optimization algorithm was proposed. On the basis of LEACH agreement, it was improved and perfected that the points on the cluster and the selection of cluster head using the chicken group optimization algorithm, and update the location of chicken which fall into the local optimum by Levy flight, enhance population diversity, ensure the global search capability of the algorithm. The new protocol avoided the die of partial node of intensive using by making balanced use of the network nodes, improved the survival time of wireless sensor network. The simulation experiments proved that the protocol is better than LEACH protocol on energy consumption, also is better than that of clustering routing protocol based on particle swarm optimization algorithm.

Optimal sensor placement for spatial lattice structure based on genetic algorithms

NASA Astrophysics Data System (ADS)

Liu, Wei; Gao, Wei-cheng; Sun, Yi; Xu, Min-jian

2008-10-01

Optimal sensor placement technique plays a key role in structural health monitoring of spatial lattice structures. This paper considers the problem of locating sensors on a spatial lattice structure with the aim of maximizing the data information so that structural dynamic behavior can be fully characterized. Based on the criterion of optimal sensor placement for modal test, an improved genetic algorithm is introduced to find the optimal placement of sensors. The modal strain energy (MSE) and the modal assurance criterion (MAC) have been taken as the fitness function, respectively, so that three placement designs were produced. The decimal two-dimension array coding method instead of binary coding method is proposed to code the solution. Forced mutation operator is introduced when the identical genes appear via the crossover procedure. A computational simulation of a 12-bay plain truss model has been implemented to demonstrate the feasibility of the three optimal algorithms above. The obtained optimal sensor placements using the improved genetic algorithm are compared with those gained by exiting genetic algorithm using the binary coding method. Further the comparison criterion based on the mean square error between the finite element method (FEM) mode shapes and the Guyan expansion mode shapes identified by data-driven stochastic subspace identification (SSI-DATA) method are employed to demonstrate the advantage of the different fitness function. The results showed that some innovations in genetic algorithm proposed in this paper can enlarge the genes storage and improve the convergence of the algorithm. More importantly, the three optimal sensor placement methods can all provide the reliable results and identify the vibration characteristics of the 12-bay plain truss model accurately.

Swarm Optimization-Based Magnetometer Calibration for Personal Handheld Devices

PubMed Central

Ali, Abdelrahman; Siddharth, Siddharth; Syed, Zainab; El-Sheimy, Naser

2012-01-01

Inertial Navigation Systems (INS) consist of accelerometers, gyroscopes and a processor that generates position and orientation solutions by integrating the specific forces and rotation rates. In addition to the accelerometers and gyroscopes, magnetometers can be used to derive the user heading based on Earth's magnetic field. Unfortunately, the measurements of the magnetic field obtained with low cost sensors are usually corrupted by several errors, including manufacturing defects and external electro-magnetic fields. Consequently, proper calibration of the magnetometer is required to achieve high accuracy heading measurements. In this paper, a Particle Swarm Optimization (PSO)-based calibration algorithm is presented to estimate the values of the bias and scale factor of low cost magnetometers. The main advantage of this technique is the use of the artificial intelligence which does not need any error modeling or awareness of the nonlinearity. Furthermore, the proposed algorithm can help in the development of Pedestrian Navigation Devices (PNDs) when combined with inertial sensors and GPS/Wi-Fi for indoor navigation and Location Based Services (LBS) applications.

Node Self-Deployment Algorithm Based on Pigeon Swarm Optimization for Underwater Wireless Sensor Networks

PubMed Central

Yu, Shanen; Xu, Yiming; Jiang, Peng; Wu, Feng; Xu, Huan

2017-01-01

At present, free-to-move node self-deployment algorithms aim at event coverage and cannot improve network coverage under the premise of considering network connectivity, network reliability and network deployment energy consumption. Thus, this study proposes pigeon-based self-deployment algorithm (PSA) for underwater wireless sensor networks to overcome the limitations of these existing algorithms. In PSA, the sink node first finds its one-hop nodes and maximizes the network coverage in its one-hop region. The one-hop nodes subsequently divide the network into layers and cluster in each layer. Each cluster head node constructs a connected path to the sink node to guarantee network connectivity. Finally, the cluster head node regards the ratio of the movement distance of the node to the change in the coverage redundancy ratio as the target function and employs pigeon swarm optimization to determine the positions of the nodes. Simulation results show that PSA improves both network connectivity and network reliability, decreases network deployment energy consumption, and increases network coverage. PMID:28338615

Strain field reconstruction on composite spars based on the identification of equivalent load conditions

NASA Astrophysics Data System (ADS)

Airoldi, A.; Marelli, L.; Bettini, P.; Sala, G.; Apicella, A.

2017-04-01

Technologies based on optical fibers provide the possibility of installing relatively dense networks of sensors that can perform effective strain sensing functions during the operational life of structures. A contemporary trend is the increasing adoption of composite materials in aerospace constructions, which leads to structural architectures made of large monolithic elements. The paper is aimed at showing the feasibility of a detailed reconstruction of the strain field in a composite spar, which is based on the development of reference finite element models and the identification of load modes, consisting of a parameterized set of forces. The procedure is described and assessed in ideal conditions. Thereafter, a surrogate model is used to obtain realistic representation of the data acquired by the strain sensing system, so that the developed procedure is evaluated considering local effects due to the introduction of loads, significant modelling discrepancy in the development of the reference model and the presence of measurement noise. Results show that the method can obtain a robust and quite detailed reconstruction of strain fields, even at the level of local distributions, of the internal forces in the spars and of the displacements, by identifying an equivalent set of load parameters. Finally, the trade-off between the number of sensor and the accuracy, and the optimal position of the sensors for a given maximum number of sensors is evaluated by performing a multi-objective optimization, thus showing that even a relative dense network of externally applied sensors can be used to achieve good quality results.

On the Optimization of a Probabilistic Data Aggregation Framework for Energy Efficiency in Wireless Sensor Networks.

PubMed

Kafetzoglou, Stella; Aristomenopoulos, Giorgos; Papavassiliou, Symeon

2015-08-11

Among the key aspects of the Internet of Things (IoT) is the integration of heterogeneous sensors in a distributed system that performs actions on the physical world based on environmental information gathered by sensors and application-related constraints and requirements. Numerous applications of Wireless Sensor Networks (WSNs) have appeared in various fields, from environmental monitoring, to tactical fields, and healthcare at home, promising to change our quality of life and facilitating the vision of sensor network enabled smart cities. Given the enormous requirements that emerge in such a setting-both in terms of data and energy-data aggregation appears as a key element in reducing the amount of traffic in wireless sensor networks and achieving energy conservation. Probabilistic frameworks have been introduced as operational efficient and performance effective solutions for data aggregation in distributed sensor networks. In this work, we introduce an overall optimization approach that improves and complements such frameworks towards identifying the optimal probability for a node to aggregate packets as well as the optimal aggregation period that a node should wait for performing aggregation, so as to minimize the overall energy consumption, while satisfying certain imposed delay constraints. Primal dual decomposition is employed to solve the corresponding optimization problem while simulation results demonstrate the operational efficiency of the proposed approach under different traffic and topology scenarios.

Strain sensors optimal placement for vibration-based structural health monitoring. The effect of damage on the initially optimal configuration

NASA Astrophysics Data System (ADS)

Loutas, T. H.; Bourikas, A.

2017-12-01

We revisit the optimal sensor placement of engineering structures problem with an emphasis on in-plane dynamic strain measurements and to the direction of modal identification as well as vibration-based damage detection for structural health monitoring purposes. The approach utilized is based on the maximization of a norm of the Fisher Information Matrix built with numerically obtained mode shapes of the structure and at the same time prohibit the sensorization of neighbor degrees of freedom as well as those carrying similar information, in order to obtain a satisfactory coverage. A new convergence criterion of the Fisher Information Matrix (FIM) norm is proposed in order to deal with the issue of choosing an appropriate sensor redundancy threshold, a concept recently introduced but not further investigated concerning its choice. The sensor configurations obtained via a forward sequential placement algorithm are sub-optimal in terms of FIM norm values but the selected sensors are not allowed to be placed in neighbor degrees of freedom providing thus a better coverage of the structure and a subsequent better identification of the experimental mode shapes. The issue of how service induced damage affects the initially nominated as optimal sensor configuration is also investigated and reported. The numerical model of a composite sandwich panel serves as a representative aerospace structure upon which our investigations are based.

Root System Water Consumption Pattern Identification on Time Series Data

PubMed Central

Figueroa, Manuel; Pope, Christopher

2017-01-01

In agriculture, soil and meteorological sensors are used along low power networks to capture data, which allows for optimal resource usage and minimizing environmental impact. This study uses time series analysis methods for outliers’ detection and pattern recognition on soil moisture sensor data to identify irrigation and consumption patterns and to improve a soil moisture prediction and irrigation system. This study compares three new algorithms with the current detection technique in the project; the results greatly decrease the number of false positives detected. The best result is obtained by the Series Strings Comparison (SSC) algorithm averaging a precision of 0.872 on the testing sets, vastly improving the current system’s 0.348 precision. PMID:28621739

Root System Water Consumption Pattern Identification on Time Series Data.

PubMed

Figueroa, Manuel; Pope, Christopher

2017-06-16

In agriculture, soil and meteorological sensors are used along low power networks to capture data, which allows for optimal resource usage and minimizing environmental impact. This study uses time series analysis methods for outliers' detection and pattern recognition on soil moisture sensor data to identify irrigation and consumption patterns and to improve a soil moisture prediction and irrigation system. This study compares three new algorithms with the current detection technique in the project; the results greatly decrease the number of false positives detected. The best result is obtained by the Series Strings Comparison (SSC) algorithm averaging a precision of 0.872 on the testing sets, vastly improving the current system's 0.348 precision.

Analysis of Document Authentication Technique using Soft Magnetic Fibers

NASA Astrophysics Data System (ADS)

Aoki, Ayumi; Ikeda, Takashi; Yamada, Tsutomu; Takemura, Yasushi; Matsumoto, Tsutomu

An artifact-metric system using magnetic fibers can be applied for authentications of stock certificate, bill, passport, plastic cards and other documents. Security of the system is guaranteed by its feature of difficulty in copy. This authentication system is based on randomly dispersed magnetic fibers embedded in documents. In this paper, a theoretical analysis was performed in order to evaluate this system. The position of the magnetic fibers was determined by a conventional function of random number generator. By measuring output waveforms by a magnetoresistance (MR) sensor, a false match rate (FMR) could be calculated. Optimizations of the density of the magnetic fibers and the dimension of the MR sensor were achieved.

An Improved Co-evolutionary Particle Swarm Optimization for Wireless Sensor Networks with Dynamic Deployment

PubMed Central

Wang, Xue; Wang, Sheng; Ma, Jun-Jie

2007-01-01

The effectiveness of wireless sensor networks (WSNs) depends on the coverage and target detection probability provided by dynamic deployment, which is usually supported by the virtual force (VF) algorithm. However, in the VF algorithm, the virtual force exerted by stationary sensor nodes will hinder the movement of mobile sensor nodes. Particle swarm optimization (PSO) is introduced as another dynamic deployment algorithm, but in this case the computation time required is the big bottleneck. This paper proposes a dynamic deployment algorithm which is named “virtual force directed co-evolutionary particle swarm optimization” (VFCPSO), since this algorithm combines the co-evolutionary particle swarm optimization (CPSO) with the VF algorithm, whereby the CPSO uses multiple swarms to optimize different components of the solution vectors for dynamic deployment cooperatively and the velocity of each particle is updated according to not only the historical local and global optimal solutions, but also the virtual forces of sensor nodes. Simulation results demonstrate that the proposed VFCPSO is competent for dynamic deployment in WSNs and has better performance with respect to computation time and effectiveness than the VF, PSO and VFPSO algorithms.

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.

Ordered Magnetic Nanoparticle Arrays on Tunable Substrates for RF Applications

DTIC Science & Technology

2010-09-24

the author(s) and should not contrued as an official Department of the Army position, policy or decision, unless so designated by other documentation...15. “ Sensor applications and spin transport measurements in carbon nanotube composites” –J. Sanders, J. Gass, H. Srikanth, F. K. Perkins and E. S...Research highlights: 1. Magnetron sputtering, characterization and optimization of film growth parameters 2. Design and set up of a dedicated

A Node Localization Algorithm Based on Multi-Granularity Regional Division and the Lagrange Multiplier Method in Wireless Sensor Networks.

PubMed

Shang, Fengjun; Jiang, Yi; Xiong, Anping; Su, Wen; He, Li

2016-11-18

With the integrated development of the Internet, wireless sensor technology, cloud computing, and mobile Internet, there has been a lot of attention given to research about and applications of the Internet of Things. A Wireless Sensor Network (WSN) is one of the important information technologies in the Internet of Things; it integrates multi-technology to detect and gather information in a network environment by mutual cooperation, using a variety of methods to process and analyze data, implement awareness, and perform tests. This paper mainly researches the localization algorithm of sensor nodes in a wireless sensor network. Firstly, a multi-granularity region partition is proposed to divide the location region. In the range-based method, the RSSI (Received Signal Strength indicator, RSSI) is used to estimate distance. The optimal RSSI value is computed by the Gaussian fitting method. Furthermore, a Voronoi diagram is characterized by the use of dividing region. Rach anchor node is regarded as the center of each region; the whole position region is divided into several regions and the sub-region of neighboring nodes is combined into triangles while the unknown node is locked in the ultimate area. Secondly, the multi-granularity regional division and Lagrange multiplier method are used to calculate the final coordinates. Because nodes are influenced by many factors in the practical application, two kinds of positioning methods are designed. When the unknown node is inside positioning unit, we use the method of vector similarity. Moreover, we use the centroid algorithm to calculate the ultimate coordinates of unknown node. When the unknown node is outside positioning unit, we establish a Lagrange equation containing the constraint condition to calculate the first coordinates. Furthermore, we use the Taylor expansion formula to correct the coordinates of the unknown node. In addition, this localization method has been validated by establishing the real environment.

Proposed evaluation framework for assessing operator performance with multisensor displays

NASA Technical Reports Server (NTRS)

Foyle, David C.

1992-01-01

Despite aggressive work on the development of sensor fusion algorithms and techniques, no formal evaluation procedures have been proposed. Based on existing integration models in the literature, an evaluation framework is developed to assess an operator's ability to use multisensor, or sensor fusion, displays. The proposed evaluation framework for evaluating the operator's ability to use such systems is a normative approach: The operator's performance with the sensor fusion display can be compared to the models' predictions based on the operator's performance when viewing the original sensor displays prior to fusion. This allows for the determination as to when a sensor fusion system leads to: 1) poorer performance than one of the original sensor displays (clearly an undesirable system in which the fused sensor system causes some distortion or interference); 2) better performance than with either single sensor system alone, but at a sub-optimal (compared to the model predictions) level; 3) optimal performance (compared to model predictions); or, 4) super-optimal performance, which may occur if the operator were able to use some highly diagnostic 'emergent features' in the sensor fusion display, which were unavailable in the original sensor displays. An experiment demonstrating the usefulness of the proposed evaluation framework is discussed.

MASM: a market architecture for sensor management in distributed sensor networks

NASA Astrophysics Data System (ADS)

Viswanath, Avasarala; Mullen, Tracy; Hall, David; Garga, Amulya

2005-03-01

Rapid developments in sensor technology and its applications have energized research efforts towards devising a firm theoretical foundation for sensor management. Ubiquitous sensing, wide bandwidth communications and distributed processing provide both opportunities and challenges for sensor and process control and optimization. Traditional optimization techniques do not have the ability to simultaneously consider the wildly non-commensurate measures involved in sensor management in a single optimization routine. Market-oriented programming provides a valuable and principled paradigm to designing systems to solve this dynamic and distributed resource allocation problem. We have modeled the sensor management scenario as a competitive market, wherein the sensor manager holds a combinatorial auction to sell the various items produced by the sensors and the communication channels. However, standard auction mechanisms have been found not to be directly applicable to the sensor management domain. For this purpose, we have developed a specialized market architecture MASM (Market architecture for Sensor Management). In MASM, the mission manager is responsible for deciding task allocations to the consumers and their corresponding budgets and the sensor manager is responsible for resource allocation to the various consumers. In addition to having a modified combinatorial winner determination algorithm, MASM has specialized sensor network modules that address commensurability issues between consumers and producers in the sensor network domain. A preliminary multi-sensor, multi-target simulation environment has been implemented to test the performance of the proposed system. MASM outperformed the information theoretic sensor manager in meeting the mission objectives in the simulation experiments.

A Sensor Dynamic Measurement Error Prediction Model Based on NAPSO-SVM

PubMed Central

Jiang, Minlan; Jiang, Lan; Jiang, Dingde; Li, Fei

2018-01-01

Dynamic measurement error correction is an effective way to improve sensor precision. Dynamic measurement error prediction is an important part of error correction, and support vector machine (SVM) is often used for predicting the dynamic measurement errors of sensors. Traditionally, the SVM parameters were always set manually, which cannot ensure the model’s performance. In this paper, a SVM method based on an improved particle swarm optimization (NAPSO) is proposed to predict the dynamic measurement errors of sensors. Natural selection and simulated annealing are added in the PSO to raise the ability to avoid local optima. To verify the performance of NAPSO-SVM, three types of algorithms are selected to optimize the SVM’s parameters: the particle swarm optimization algorithm (PSO), the improved PSO optimization algorithm (NAPSO), and the glowworm swarm optimization (GSO). The dynamic measurement error data of two sensors are applied as the test data. The root mean squared error and mean absolute percentage error are employed to evaluate the prediction models’ performances. The experimental results show that among the three tested algorithms the NAPSO-SVM method has a better prediction precision and a less prediction errors, and it is an effective method for predicting the dynamic measurement errors of sensors. PMID:29342942

A heuristic for deriving the optimal number and placement of reconnaissance sensors

NASA Astrophysics Data System (ADS)

Nanda, S.; Weeks, J.; Archer, M.

2008-04-01

A key to mastering asymmetric warfare is the acquisition of accurate intelligence on adversaries and their assets in urban and open battlefields. To achieve this, one needs adequate numbers of tactical sensors placed in locations to optimize coverage, where optimality is realized by covering a given area of interest with the least number of sensors, or covering the largest possible subsection of an area of interest with a fixed set of sensors. Unfortunately, neither problem admits a polynomial time algorithm as a solution, and therefore, the placement of such sensors must utilize intelligent heuristics instead. In this paper, we present a scheme implemented on parallel SIMD processing architectures to yield significantly faster results, and that is highly scalable with respect to dynamic changes in the area of interest. Furthermore, the solution to the first problem immediately translates to serve as a solution to the latter if and when any sensors are rendered inoperable.

Smart garments for safety improvement of emergency/disaster operators.

PubMed

Curone, Davide; Dudnik, Gabriela; Loriga, Giannicola; Luprano, Jean; Magenes, Giovanni; Paradiso, Rita; Tognetti, Alessandro; Bonfiglio, Annalisa

2007-01-01

The main purpose of the European project ProeTEX is to develop equipment to improve safety, coordination and efficiency of emergency disaster intervention personnel like fire-fighters or civil protection rescuers. The equipment consists of a new generation of "smart" garments, integrating wearable sensors which will allow monitoring physiological parameters, position and activity of the user, as like as environmental variables of the operating field in which rescuers are working: both commercial and newly developed textile and fibre based sensors will be included. The garments will also contain an electronic box to process data collected by the sensors and a communication system enabling the transmission of data to the other rescuers and to a monitoring station. Also a "smart" victim patch will be developed: a wearable garment which will allow monitoring physiological parameters of injured civilians involved in disasters, with the aim of optimizing their survival management.

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.

An Umeclidinium membrane sensor; Two-step optimization strategy for improved responses.

PubMed

Yehia, Ali M; Monir, Hany H

2017-09-01

In the scientific context of membrane sensors and improved experimentation, we devised an experimentally designed protocol for sensor optimization. Two-step strategy was implemented for Umeclidinium bromide (UMEC) analysis which is a novel quinuclidine-based muscarinic antagonist used for maintenance treatment of symptoms accompanied with chronic obstructive pulmonary disease. In the first place, membrane components were screened for ideal ion exchanger, ionophore and plasticizer using three categorical factors at three levels in Taguchi design. Secondly, experimentally designed optimization was followed in order to tune the sensor up for finest responses. Twelve experiments were randomly carried out in a continuous factor design. Nernstian response, detection limit and selectivity were assigned as responses in these designs. The optimized membrane sensor contained tetrakis-[3,5-bis(trifluoro- methyl)phenyl] borate (0.44wt%) and calix[6]arene (0.43wt%) in 50.00% PVC plasticized with 49.13wt% 2-ni-tro-phenyl octylether. This sensor, along with an optimum concentration of inner filling solution (2×10 -4 molL -1 UMEC) and 2h of soaking time, attained the design objectives. Nernstian response approached 59.7mV/decade and detection limit decreased by about two order of magnitude (8×10 -8 mol L -1 ) through this optimization protocol. The proposed sensor was validated for UMEC determination in its linear range (3.16×10 -7 -1×10 -3 mol L -1 ) and challenged for selective discrimination of other congeners and inorganic cations. Results of INCRUSE ELLIPTA ® inhalation powder analyses obtained from the proposed sensor and manufacturer's UPLC were statistically compared. Moreover the proposed sensor was successfully used for the determination of UMEC in plasma samples. Copyright © 2017 Elsevier B.V. All rights reserved.

A open loop guidance architecture for navigationally robust on-orbit docking

NASA Technical Reports Server (NTRS)

Chern, Hung-Sheng

1995-01-01

The development of an open-hop guidance architecture is outlined for autonomous rendezvous and docking (AR&D) missions to determine whether the Global Positioning System (GPS) can be used in place of optical sensors for relative initial position determination of the chase vehicle. Feasible command trajectories for one, two, and three impulse AR&D maneuvers are determined using constrained trajectory optimization. Early AR&D command trajectory results suggest that docking accuracies are most sensitive to vertical position errors at the initial conduction of the chase vehicle. Thus, a feasible command trajectory is based on maximizing the size of the locus of initial vertical positions for which a fixed sequence of impulses will translate the chase vehicle into the target while satisfying docking accuracy requirements. Documented accuracies are used to determine whether relative GPS can achieve the vertical position error requirements of the impulsive command trajectories. Preliminary development of a thruster management system for the Cargo Transfer Vehicle (CTV) based on optimal throttle settings is presented to complete the guidance architecture. Results show that a guidance architecture based on a two impulse maneuvers generated the best performance in terms of initial position error and total velocity change for the chase vehicle.

Design and Analysis of Precise Pointing Systems

NASA Technical Reports Server (NTRS)

Kim, Young K.

2000-01-01

The mathematical models of Glovebox Integrated Microgravity Isolation Technology (g- LIMIT) dynamics/control system, which include six degrees of freedom (DOF) equations of motion, mathematical models of position sensors, accelerometers and actuators, and acceleration and position controller, were developed using MATLAB and TREETOPS simulations. Optimal control parameters of G-LIMIT control system were determined through sensitivity studies and its performance were evaluated with the TREETOPS model of G-LIMIT dynamics and control system. The functional operation and performance of the Tektronix DTM920 digital thermometer were studied and the inputs to the crew procedures and training of the DTM920 were documented.

Developments in Scanning Hall Probe Microscopy

NASA Astrophysics Data System (ADS)

Chouinard, Taras; Chu, Ricky; David, Nigel; Broun, David

2009-05-01

Low temperature scanning Hall probe microscopy is a sensitive means of imaging magnetic structures with high spatial resolution and magnetic flux sensitivity approaching that of a Superconducting Quantum Interference Device. We have developed a scanning Hall probe microscope with novel features, including highly reliable coarse positioning, in situ optimization of sensor-sample alignment and capacitive transducers for linear, long range positioning measurement. This has been motivated by the need to reposition accurately above fabricated nanostructures such as small superconducting rings. Details of the design and performance will be presented as well as recent progress towards time-resolved measurements with sub nanosecond resolution.

The Homogeneity of Optimal Sensor Placement Across Multiple Winged Insect Species

NASA Astrophysics Data System (ADS)

Jenkins, Abigail L.

Taking inspiration from biology, control algorithms can be implemented to imitate the naturally occurring control systems present in nature. This research is primarily concerned with insect flight and optimal wing sensor placement. Many winged insects with halteres are equipped with mechanoreceptors termed campaniform sensilla. Although the exact information these receptors provide to the insect's nervous system is unknown, it is thought to have the capability of measuring inertial rotation forces. During flight, when the wing bends, the information measured by the campaniform sensilla is received by the central nervous system, and provides the insect necessary data to control flight. This research compares three insect species - the hawkmoth Manduca sexta, the honeybee Apis mellifera, and the fruit fly Drosophila melanogaster. Using an observability-based sensor placement algorithm, the optimal sensor placement for these three species is determined. Simulations resolve if this optimal sensor placement corresponds to the insect's campaniform sensilla, as well as if placement is homogeneous across species.

Using RGB-D sensors and evolutionary algorithms for the optimization of workstation layouts.

PubMed

Diego-Mas, Jose Antonio; Poveda-Bautista, Rocio; Garzon-Leal, Diana

2017-11-01

RGB-D sensors can collect postural data in an automatized way. However, the application of these devices in real work environments requires overcoming problems such as lack of accuracy or body parts' occlusion. This work presents the use of RGB-D sensors and genetic algorithms for the optimization of workstation layouts. RGB-D sensors are used to capture workers' movements when they reach objects on workbenches. Collected data are then used to optimize workstation layout by means of genetic algorithms considering multiple ergonomic criteria. Results show that typical drawbacks of using RGB-D sensors for body tracking are not a problem for this application, and that the combination with intelligent algorithms can automatize the layout design process. The procedure described can be used to automatically suggest new layouts when workers or processes of production change, to adapt layouts to specific workers based on their ways to do the tasks, or to obtain layouts simultaneously optimized for several production processes. Copyright © 2017 Elsevier Ltd. All rights reserved.

Increasing the Lifetime of Mobile WSNs via Dynamic Optimization of Sensor Node Communication Activity

PubMed Central

Guimarães, Dayan Adionel; Sakai, Lucas Jun; Alberti, Antonio Marcos; de Souza, Rausley Adriano Amaral

2016-01-01

In this paper, a simple and flexible method for increasing the lifetime of fixed or mobile wireless sensor networks is proposed. Based on past residual energy information reported by the sensor nodes, the sink node or another central node dynamically optimizes the communication activity levels of the sensor nodes to save energy without sacrificing the data throughput. The activity levels are defined to represent portions of time or time-frequency slots in a frame, during which the sensor nodes are scheduled to communicate with the sink node to report sensory measurements. Besides node mobility, it is considered that sensors’ batteries may be recharged via a wireless power transmission or equivalent energy harvesting scheme, bringing to the optimization problem an even more dynamic character. We report large increased lifetimes over the non-optimized network and comparable or even larger lifetime improvements with respect to an idealized greedy algorithm that uses both the real-time channel state and the residual energy information. PMID:27657075

A Scheme to Smooth Aggregated Traffic from Sensors with Periodic Reports

PubMed Central

Oh, Sungmin; Jang, Ju Wook

2017-01-01

The possibility of smoothing aggregated traffic from sensors with varying reporting periods and frame sizes to be carried on an access link is investigated. A straightforward optimization would take O(pn) time, whereas our heuristic scheme takes O(np) time where n, p denote the number of sensors and size of periods, respectively. Our heuristic scheme performs local optimization sensor by sensor, starting with the smallest to largest periods. This is based on an observation that sensors with large offsets have more choices in offsets to avoid traffic peaks than the sensors with smaller periods. A MATLAB simulation shows that our scheme excels the known scheme by M. Grenier et al. in a similar situation (aggregating periodic traffic in a controller area network) for almost all possible permutations. The performance of our scheme is very close to the straightforward optimization, which compares all possible permutations. We expect that our scheme would greatly contribute in smoothing the traffic from an ever-increasing number of IoT sensors to the gateway, reducing the burden on the access link to the Internet. PMID:28273831

A Scheme to Smooth Aggregated Traffic from Sensors with Periodic Reports.

PubMed

Oh, Sungmin; Jang, Ju Wook

2017-03-03

The possibility of smoothing aggregated traffic from sensors with varying reporting periods and frame sizes to be carried on an access link is investigated. A straightforward optimization would take O(pn) time, whereas our heuristic scheme takes O(np) time where n, p denote the number of sensors and size of periods, respectively. Our heuristic scheme performs local optimization sensor by sensor, starting with the smallest to largest periods. This is based on an observation that sensors with large offsets have more choices in offsets to avoid traffic peaks than the sensors with smaller periods. A MATLAB simulation shows that our scheme excels the known scheme by M. Grenier et al. in a similar situation (aggregating periodic traffic in a controller area network) for almost all possible permutations. The performance of our scheme is very close to the straightforward optimization, which compares all possible permutations. We expect that our scheme would greatly contribute in smoothing the traffic from an ever-increasing number of IoT sensors to the gateway, reducing the burden on the access link to the Internet.

Spatiotemporal and geometric optimization of sensor arrays for detecting analytes fluids

DOEpatents

Lewis, Nathan S.; Freund, Michael S.; Briglin, Shawn M.; Tokumaru, Phil; Martin, Charles R.; Mitchell, David T.

2006-10-17

Sensor arrays and sensor array systems for detecting analytes in fluids. Sensors configured to generate a response upon introduction of a fluid containing one or more analytes can be located on one or more surfaces relative to one or more fluid channels in an array. Fluid channels can take the form of pores or holes in a substrate material. Fluid channels can be formed between one or more substrate plates. Sensor can be fabricated with substantially optimized sensor volumes to generate a response having a substantially maximized signal to noise ratio upon introduction of a fluid containing one or more target analytes. Methods of fabricating and using such sensor arrays and systems are also disclosed.

Spatiotemporal and geometric optimization of sensor arrays for detecting analytes in fluids

DOEpatents

Lewis, Nathan S [La Canada, CA; Freund, Michael S [Winnipeg, CA; Briglin, Shawn S [Chittenango, NY; Tokumaru, Phillip [Moorpark, CA; Martin, Charles R [Gainesville, FL; Mitchell, David [Newtown, PA

2009-09-29

Sensor arrays and sensor array systems for detecting analytes in fluids. Sensors configured to generate a response upon introduction of a fluid containing one or more analytes can be located on one or more surfaces relative to one or more fluid channels in an array. Fluid channels can take the form of pores or holes in a substrate material. Fluid channels can be formed between one or more substrate plates. Sensor can be fabricated with substantially optimized sensor volumes to generate a response having a substantially maximized signal to noise ratio upon introduction of a fluid containing one or more target analytes. Methods of fabricating and using such sensor arrays and systems are also disclosed.

AUV Underwater Positioning Algorithm Based on Interactive Assistance of SINS and LBL.

PubMed

Zhang, Tao; Chen, Liping; Li, Yao

2015-12-30

This paper studies an underwater positioning algorithm based on the interactive assistance of a strapdown inertial navigation system (SINS) and LBL, and this algorithm mainly includes an optimal correlation algorithm with aided tracking of an SINS/Doppler velocity log (DVL)/magnetic compass pilot (MCP), a three-dimensional TDOA positioning algorithm of Taylor series expansion and a multi-sensor information fusion algorithm. The final simulation results show that compared to traditional underwater positioning algorithms, this scheme can not only directly correct accumulative errors caused by a dead reckoning algorithm, but also solves the problem of ambiguous correlation peaks caused by multipath transmission of underwater acoustic signals. The proposed method can calibrate the accumulative error of the AUV position more directly and effectively, which prolongs the underwater operating duration of the AUV.

Optimal geometry for a quartz multipurpose SPM sensor.

PubMed

Stirling, Julian

2013-01-01

We propose a geometry for a piezoelectric SPM sensor that can be used for combined AFM/LFM/STM. The sensor utilises symmetry to provide a lateral mode without the need to excite torsional modes. The symmetry allows normal and lateral motion to be completely isolated, even when introducing large tips to tune the dynamic properties to optimal values.

Wireless Cooperative Networks: Self-Configuration and Optimization

DTIC Science & Technology

2011-09-09

TERMS wireless sensor networks , wireless cooperative networks, resource optimization, ultra-wideband, localization, ranging 16. SECURITY...Communications We consider two prevalent relay protocols for wireless sensor networks : decode-and-forward (DF) and amplify-and-forward (AF). To... sensor networks where each node may have its own sensing data to transmit, since they can maximally conserve energy while helping others as relays

Virtual Distances Methodology as Verification Technique for AACMMs with a Capacitive Sensor Based Indexed Metrology Platform

PubMed Central

Acero, Raquel; Santolaria, Jorge; Brau, Agustin; Pueo, Marcos

2016-01-01

This paper presents a new verification procedure for articulated arm coordinate measuring machines (AACMMs) together with a capacitive sensor-based indexed metrology platform (IMP) based on the generation of virtual reference distances. The novelty of this procedure lays on the possibility of creating virtual points, virtual gauges and virtual distances through the indexed metrology platform’s mathematical model taking as a reference the measurements of a ball bar gauge located in a fixed position of the instrument’s working volume. The measurements are carried out with the AACMM assembled on the IMP from the six rotating positions of the platform. In this way, an unlimited number and types of reference distances could be created without the need of using a physical gauge, therefore optimizing the testing time, the number of gauge positions and the space needed in the calibration and verification procedures. Four evaluation methods are presented to assess the volumetric performance of the AACMM. The results obtained proved the suitability of the virtual distances methodology as an alternative procedure for verification of AACMMs using the indexed metrology platform. PMID:27869722

Virtual Distances Methodology as Verification Technique for AACMMs with a Capacitive Sensor Based Indexed Metrology Platform.

PubMed

Acero, Raquel; Santolaria, Jorge; Brau, Agustin; Pueo, Marcos

2016-11-18

This paper presents a new verification procedure for articulated arm coordinate measuring machines (AACMMs) together with a capacitive sensor-based indexed metrology platform (IMP) based on the generation of virtual reference distances. The novelty of this procedure lays on the possibility of creating virtual points, virtual gauges and virtual distances through the indexed metrology platform's mathematical model taking as a reference the measurements of a ball bar gauge located in a fixed position of the instrument's working volume. The measurements are carried out with the AACMM assembled on the IMP from the six rotating positions of the platform. In this way, an unlimited number and types of reference distances could be created without the need of using a physical gauge, therefore optimizing the testing time, the number of gauge positions and the space needed in the calibration and verification procedures. Four evaluation methods are presented to assess the volumetric performance of the AACMM. The results obtained proved the suitability of the virtual distances methodology as an alternative procedure for verification of AACMMs using the indexed metrology platform.

NASA Tech Briefs, October 2004

NASA Technical Reports Server (NTRS)

2004-01-01

Topics include: Relative-Motion Sensors and Actuators for Two Optical Tables; Improved Position Sensor for Feedback Control of Levitation; Compact Tactile Sensors for Robot Fingers; Improved Ion-Channel Biosensors; Suspended-Patch Antenna With Inverted, EM-Coupled Feed; System Would Predictively Preempt Traffic Lights for Emergency Vehicles; Optical Position Encoders for High or Low Temperatures; Inter-Valence-Subband/Conduction-Band-Transport IR Detectors; Additional Drive Circuitry for Piezoelectric Screw Motors; Software for Use with Optoelectronic Measuring Tool; Coordinating Shared Activities; Software Reduces Radio-Interference Effects in Radar Data; Using Iron to Treat Chlorohydrocarbon-Contaminated Soil; Thermally Insulating, Kinematic Tensioned-Fiber Suspension; Back Actuators for Segmented Mirrors and Other Applications; Mechanism for Self-Reacted Friction Stir Welding; Lightweight Exoskeletons with Controllable Actuators; Miniature Robotic Submarine for Exploring Harsh Environments; Electron-Spin Filters Based on the Rashba Effect; Diffusion-Cooled Tantalum Hot-Electron Bolometer Mixers; Tunable Optical True-Time Delay Devices Would Exploit EIT; Fast Query-Optimized Kernel-Machine Classification; Indentured Parts List Maintenance and Part Assembly Capture Tool - IMPACT; An Architecture for Controlling Multiple Robots; Progress in Fabrication of Rocket Combustion Chambers by VPS; CHEM-Based Self-Deploying Spacecraft Radar Antennas; Scalable Multiprocessor for High-Speed Computing in Space; and Simple Systems for Detecting Spacecraft Meteoroid Punctures.

Optimal Power Control in Wireless Powered Sensor Networks: A Dynamic Game-Based Approach

PubMed Central

Xu, Haitao; Guo, Chao; Zhang, Long

2017-01-01

In wireless powered sensor networks (WPSN), it is essential to research uplink transmit power control in order to achieve throughput performance balancing and energy scheduling. Each sensor should have an optimal transmit power level for revenue maximization. In this paper, we discuss a dynamic game-based algorithm for optimal power control in WPSN. The main idea is to use the non-cooperative differential game to control the uplink transmit power of wireless sensors in WPSN, to extend their working hours and to meet QoS (Quality of Services) requirements. Subsequently, the Nash equilibrium solutions are obtained through Bellman dynamic programming. At the same time, an uplink power control algorithm is proposed in a distributed manner. Through numerical simulations, we demonstrate that our algorithm can obtain optimal power control and reach convergence for an infinite horizon. PMID:28282945

Statistical-Mechanics-Inspired Optimization of Sensor Field Configuration for Detection of Mobile Targets (PREPRINT)

DTIC Science & Technology

2010-11-01

pected target motion. Along this line, Wettergren [5] analyzed the performance of the track - before - detect schemes for the sensor networks. Furthermore...dressed by Baumgartner and Ferrari [11] for the reorganization of the sensor field to achieve the maximum coverage. The track - before - detect -based optimal...confirming a target. In accordance with the track - before - detect paradigm [4], a moving target is detected if the kd (typically kd = 3 or 4) sensors detect

Optimal sensor fusion for land vehicle navigation

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

Morrow, J.D.

1990-10-01

Position location is a fundamental requirement in autonomous mobile robots which record and subsequently follow x,y paths. The Dept. of Energy, Office of Safeguards and Security, Robotic Security Vehicle (RSV) program involves the development of an autonomous mobile robot for patrolling a structured exterior environment. A straight-forward method for autonomous path-following has been adopted and requires digitizing'' the desired road network by storing x,y coordinates every 2m along the roads. The position location system used to define the locations consists of a radio beacon system which triangulates position off two known transponders, and dead reckoning with compass and odometer. Thismore » paper addresses the problem of combining these two measurements to arrive at a best estimate of position. Two algorithms are proposed: the optimal'' algorithm treats the measurements as random variables and minimizes the estimate variance, while the average error'' algorithm considers the bias in dead reckoning and attempts to guarantee an average error. Data collected on the algorithms indicate that both work well in practice. 2 refs., 7 figs.« less

A Multi-Objective Partition Method for Marine Sensor Networks Based on Degree of Event Correlation.

PubMed

Huang, Dongmei; Xu, Chenyixuan; Zhao, Danfeng; Song, Wei; He, Qi

2017-09-21

Existing marine sensor networks acquire data from sea areas that are geographically divided, and store the data independently in their affiliated sea area data centers. In the case of marine events across multiple sea areas, the current network structure needs to retrieve data from multiple data centers, and thus severely affects real-time decision making. In this study, in order to provide a fast data retrieval service for a marine sensor network, we use all the marine sensors as the vertices, establish the edge based on marine events, and abstract the marine sensor network as a graph. Then, we construct a multi-objective balanced partition method to partition the abstract graph into multiple regions and store them in the cloud computing platform. This method effectively increases the correlation of the sensors and decreases the retrieval cost. On this basis, an incremental optimization strategy is designed to dynamically optimize existing partitions when new sensors are added into the network. Experimental results show that the proposed method can achieve the optimal layout for distributed storage in the process of disaster data retrieval in the China Sea area, and effectively optimize the result of partitions when new buoys are deployed, which eventually will provide efficient data access service for marine events.

Rapid Field-Usable Cyanide Sensor Development for Blood and Saliva

DTIC Science & Technology

2013-12-01

fluorescent readings were measured using an Ocean Optics USB2000+ Spectrometer. The spiked plasma gave a signal of approximately 18% of an aqueous...fluorescent readings were measured using an Ocean Optics USB2000+ Spectrometer. The optimization data can be seen in Figure 1.1.1-3. For aqueous...measured using an Ocean Optics USB2000+ Spectrometer. The identification of interferents is important to assess the possibility of false positives for

Radiation Hard Sensors for Surveillance.

DTIC Science & Technology

1988-03-11

track position measurements were noted. E. Heijne (CERN) reported on the degradation of silicon detectors for doses larger than 2x10 11 muons /cm 2...Workshop on Transmission and Emission Computerized Tomography , July 1978, Seoul, Korea Nahmias C., Kenyon D.B., Garnett E.S.: Optimization of...crystal size in emission computed tomography . IEEE Trans ,.-.e Nucl Sci NS-27: 529-532, 1980. Mullani N.A., Ficke D.C., Ter-Pogossian M.M.: Cesium Fluoride

The Joint Milli-Arcsecond Pathfinder Survey (J-MAPS) Mission: Application for Space Situational Awareness

DTIC Science & Technology

2008-09-01

One implication of this is that the instrument can physically resolve satellites at smaller separations than current and existing optical SSA assets...with the potential for 24/7 taskability and near-real time capability. By optimizing an instrument to perform position measurement rather than...sensors. The J-MAPS baseline also includes a novel filter-grating wheel, of interest in the area of non- resolved object characterization. We discuss the

Energy-Efficient Cognitive Radio Sensor Networks: Parametric and Convex Transformations

PubMed Central

Naeem, Muhammad; Illanko, Kandasamy; Karmokar, Ashok; Anpalagan, Alagan; Jaseemuddin, Muhammad

2013-01-01

Designing energy-efficient cognitive radio sensor networks is important to intelligently use battery energy and to maximize the sensor network life. In this paper, the problem of determining the power allocation that maximizes the energy-efficiency of cognitive radio-based wireless sensor networks is formed as a constrained optimization problem, where the objective function is the ratio of network throughput and the network power. The proposed constrained optimization problem belongs to a class of nonlinear fractional programming problems. Charnes-Cooper Transformation is used to transform the nonlinear fractional problem into an equivalent concave optimization problem. The structure of the power allocation policy for the transformed concave problem is found to be of a water-filling type. The problem is also transformed into a parametric form for which a ε-optimal iterative solution exists. The convergence of the iterative algorithms is proven, and numerical solutions are presented. The iterative solutions are compared with the optimal solution obtained from the transformed concave problem, and the effects of different system parameters (interference threshold level, the number of primary users and secondary sensor nodes) on the performance of the proposed algorithms are investigated. PMID:23966194

Design optimization of the sensor spatial arrangement in a direct magnetic field-based localization system for medical applications.

PubMed

Marechal, Luc; Shaohui Foong; Zhenglong Sun; Wood, Kristin L

2015-08-01

Motivated by the need for developing a neuronavigation system to improve efficacy of intracranial surgical procedures, a localization system using passive magnetic fields for real-time monitoring of the insertion process of an external ventricular drain (EVD) catheter is conceived and developed. This system operates on the principle of measuring the static magnetic field of a magnetic marker using an array of magnetic sensors. An artificial neural network (ANN) is directly used for solving the inverse problem of magnetic dipole localization for improved efficiency and precision. As the accuracy of localization system is highly dependent on the sensor spatial location, an optimization framework, based on understanding and classification of experimental sensor characteristics as well as prior knowledge of the general trajectory of the localization pathway, for design of such sensing assemblies is described and investigated in this paper. Both optimized and non-optimized sensor configurations were experimentally evaluated and results show superior performance from the optimized configuration. While the approach presented here utilizes ventriculostomy as an illustrative platform, it can be extended to other medical applications that require localization inside the body.

Model Based Optimal Sensor Network Design for Condition Monitoring in an IGCC Plant

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

Kumar, Rajeeva; Kumar, Aditya; Dai, Dan

2012-12-31

This report summarizes the achievements and final results of this program. The objective of this program is to develop a general model-based sensor network design methodology and tools to address key issues in the design of an optimal sensor network configuration: the type, location and number of sensors used in a network, for online condition monitoring. In particular, the focus in this work is to develop software tools for optimal sensor placement (OSP) and use these tools to design optimal sensor network configuration for online condition monitoring of gasifier refractory wear and radiant syngas cooler (RSC) fouling. The methodology developedmore » will be applicable to sensing system design for online condition monitoring for broad range of applications. The overall approach consists of (i) defining condition monitoring requirement in terms of OSP and mapping these requirements in mathematical terms for OSP algorithm, (ii) analyzing trade-off of alternate OSP algorithms, down selecting the most relevant ones and developing them for IGCC applications (iii) enhancing the gasifier and RSC models as required by OSP algorithms, (iv) applying the developed OSP algorithm to design the optimal sensor network required for the condition monitoring of an IGCC gasifier refractory and RSC fouling. Two key requirements for OSP for condition monitoring are desired precision for the monitoring variables (e.g. refractory wear) and reliability of the proposed sensor network in the presence of expected sensor failures. The OSP problem is naturally posed within a Kalman filtering approach as an integer programming problem where the key requirements of precision and reliability are imposed as constraints. The optimization is performed over the overall network cost. Based on extensive literature survey two formulations were identified as being relevant to OSP for condition monitoring; one based on LMI formulation and the other being standard INLP formulation. Various algorithms to solve these two formulations were developed and validated. For a given OSP problem the computation efficiency largely depends on the “size” of the problem. Initially a simplified 1-D gasifier model assuming axial and azimuthal symmetry was used to test out various OSP algorithms. Finally these algorithms were used to design the optimal sensor network for condition monitoring of IGCC gasifier refractory wear and RSC fouling. The sensors type and locations obtained as solution to the OSP problem were validated using model based sensing approach. The OSP algorithm has been developed in a modular form and has been packaged as a software tool for OSP design where a designer can explore various OSP design algorithm is a user friendly way. The OSP software tool is implemented in Matlab/Simulink© in-house. The tool also uses few optimization routines that are freely available on World Wide Web. In addition a modular Extended Kalman Filter (EKF) block has also been developed in Matlab/Simulink© which can be utilized for model based sensing of important process variables that are not directly measured through combining the online sensors with model based estimation once the hardware sensor and their locations has been finalized. The OSP algorithm details and the results of applying these algorithms to obtain optimal sensor location for condition monitoring of gasifier refractory wear and RSC fouling profile are summarized in this final report.« less

Deployment-based lifetime optimization model for homogeneous Wireless Sensor Network under retransmission.

PubMed

Li, Ruiying; Liu, Xiaoxi; Xie, Wei; Huang, Ning

2014-12-10

Sensor-deployment-based lifetime optimization is one of the most effective methods used to prolong the lifetime of Wireless Sensor Network (WSN) by reducing the distance-sensitive energy consumption. In this paper, data retransmission, a major consumption factor that is usually neglected in the previous work, is considered. For a homogeneous WSN, monitoring a circular target area with a centered base station, a sensor deployment model based on regular hexagonal grids is analyzed. To maximize the WSN lifetime, optimization models for both uniform and non-uniform deployment schemes are proposed by constraining on coverage, connectivity and success transmission rate. Based on the data transmission analysis in a data gathering cycle, the WSN lifetime in the model can be obtained through quantifying the energy consumption at each sensor location. The results of case studies show that it is meaningful to consider data retransmission in the lifetime optimization. In particular, our investigations indicate that, with the same lifetime requirement, the number of sensors needed in a non-uniform topology is much less than that in a uniform one. Finally, compared with a random scheme, simulation results further verify the advantage of our deployment model.

Maximization of the Supportable Number of Sensors in QoS-Aware Cluster-Based Underwater Acoustic Sensor Networks

PubMed Central

Nguyen, Thi-Tham; Van Le, Duc; Yoon, Seokhoon

2014-01-01

This paper proposes a practical low-complexity MAC (medium access control) scheme for quality of service (QoS)-aware and cluster-based underwater acoustic sensor networks (UASN), in which the provision of differentiated QoS is required. In such a network, underwater sensors (U-sensor) in a cluster are divided into several classes, each of which has a different QoS requirement. The major problem considered in this paper is the maximization of the number of nodes that a cluster can accommodate while still providing the required QoS for each class in terms of the PDR (packet delivery ratio). In order to address the problem, we first estimate the packet delivery probability (PDP) and use it to formulate an optimization problem to determine the optimal value of the maximum packet retransmissions for each QoS class. The custom greedy and interior-point algorithms are used to find the optimal solutions, which are verified by extensive simulations. The simulation results show that, by solving the proposed optimization problem, the supportable number of underwater sensor nodes can be maximized while satisfying the QoS requirements for each class. PMID:24608009

Maximization of the supportable number of sensors in QoS-aware cluster-based underwater acoustic sensor networks.

PubMed

Nguyen, Thi-Tham; Le, Duc Van; Yoon, Seokhoon

2014-03-07

This paper proposes a practical low-complexity MAC (medium access control) scheme for quality of service (QoS)-aware and cluster-based underwater acoustic sensor networks (UASN), in which the provision of differentiated QoS is required. In such a network, underwater sensors (U-sensor) in a cluster are divided into several classes, each of which has a different QoS requirement. The major problem considered in this paper is the maximization of the number of nodes that a cluster can accommodate while still providing the required QoS for each class in terms of the PDR (packet delivery ratio). In order to address the problem, we first estimate the packet delivery probability (PDP) and use it to formulate an optimization problem to determine the optimal value of the maximum packet retransmissions for each QoS class. The custom greedy and interior-point algorithms are used to find the optimal solutions, which are verified by extensive simulations. The simulation results show that, by solving the proposed optimization problem, the supportable number of underwater sensor nodes can be maximized while satisfying the QoS requirements for each class.

Fabrication and characterization of 3C-silicon carbide micro sensor for wireless blood pressure measurements

NASA Astrophysics Data System (ADS)

Basak, Nupur

A potentially implantable single crystal 3C-SiC pressure sensor for blood pressure measurement was designed, simulated, fabricated, characterized and optimized. This research uses a single crystal 3C-SiC, for the first time, to demonstrate its application as a blood pressure measurement sensor. The sensor, which uses the epitaxial grown 3C-SiC membrane to measure changes in pressure, is designed to be wireless, biocompatible and linear. The SiC material was chosen for its superior physical, chemical and mechanical properties; the capacitive sensor uses a 3C-SiC membrane as one of the electrodes; and, the sensor system is wireless for comfort and to allow for convenient reading of real-time pressure data (wireless communication is enabled by connecting the sensor parallel to a planar inductor). Together, the variable capacitive sensor and planar inductor create a pressure sensitive resonant circuit. The sensor system described above allows for implantation into a human patient's body, after which the planar inductor can be coupled with an external inductor to receive data for real-time blood pressure measurement. Electroplating, thick photo-resist characterization, RIE etching, oxidation, CVD, chemical mechanical polishing and wafer bonding were optimized during the process of fabricating the sensor system and, in addition to detailing the sensor system simulation and characterization; the optimized processes are detailed in the dissertation. This absolute pressure sensor is designed to function optimally within the human blood pressure range of 50-350mmHg. The layout and modeling of the sensor uses finite element analysis (FEA) software. The simulations for membrane deflection, stress analysis and electro-mechanical analysis are performed for 100 μm2 and 400μm2sensors. The membrane deflection-pressure, capacitance-pressure and resonant frequency-pressure graphs were obtained, and detailed in the dissertation, along with the planar inductor simulation for differently sized inductors. Ultimately, an optimized sensor with a size of 400μm2 was chosen because of its high sensitivity. The sensor, and the planar inductor, which is 3mm 2, is comparable to the presently researched implantable chip size. The measured inductance of the gold electroplated inductor is 0.371μH. The capacitance changes from 0.934 pF to 0.997pF with frequency shift of 248MHz to 256 MHz. The sensitivity of the sensor is found to be 0.21 fF/mmHg or 27.462 kHz/mmHg with an average non-linearity of 0.23216%.

Geometrical optimization of sensors for eddy currents nondestructive testing and evaluation

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

Thollon, F.; Burais, N.

1995-05-01

Design of Non Destructive Testing (NDT) and Non Destructive Evaluation (NDE) sensors is possible by solving Maxwell`s relations with FEM or BIM. But the large number of geometrical and electrical parameters of sensor and tested material implies many results that don`t give necessarily a well adapted sensor. The authors have used a genetic algorithm for automatic optimization. After having tested this algorithm with analytical solution of Maxwell`s relations for cladding thickness measurement, the method has been implemented in finite element package.

Strategy Developed for Selecting Optimal Sensors for Monitoring Engine Health

NASA Technical Reports Server (NTRS)

2004-01-01

Sensor indications during rocket engine operation are the primary means of assessing engine performance and health. Effective selection and location of sensors in the operating engine environment enables accurate real-time condition monitoring and rapid engine controller response to mitigate critical fault conditions. These capabilities are crucial to ensure crew safety and mission success. Effective sensor selection also facilitates postflight condition assessment, which contributes to efficient engine maintenance and reduced operating costs. Under the Next Generation Launch Technology program, the NASA Glenn Research Center, in partnership with Rocketdyne Propulsion and Power, has developed a model-based procedure for systematically selecting an optimal sensor suite for assessing rocket engine system health. This optimization process is termed the systematic sensor selection strategy. Engine health management (EHM) systems generally employ multiple diagnostic procedures including data validation, anomaly detection, fault-isolation, and information fusion. The effectiveness of each diagnostic component is affected by the quality, availability, and compatibility of sensor data. Therefore systematic sensor selection is an enabling technology for EHM. Information in three categories is required by the systematic sensor selection strategy. The first category consists of targeted engine fault information; including the description and estimated risk-reduction factor for each identified fault. Risk-reduction factors are used to define and rank the potential merit of timely fault diagnoses. The second category is composed of candidate sensor information; including type, location, and estimated variance in normal operation. The final category includes the definition of fault scenarios characteristic of each targeted engine fault. These scenarios are defined in terms of engine model hardware parameters. Values of these parameters define engine simulations that generate expected sensor values for targeted fault scenarios. Taken together, this information provides an efficient condensation of the engineering experience and engine flow physics needed for sensor selection. The systematic sensor selection strategy is composed of three primary algorithms. The core of the selection process is a genetic algorithm that iteratively improves a defined quality measure of selected sensor suites. A merit algorithm is employed to compute the quality measure for each test sensor suite presented by the selection process. The quality measure is based on the fidelity of fault detection and the level of fault source discrimination provided by the test sensor suite. An inverse engine model, whose function is to derive hardware performance parameters from sensor data, is an integral part of the merit algorithm. The final component is a statistical evaluation algorithm that characterizes the impact of interference effects, such as control-induced sensor variation and sensor noise, on the probability of fault detection and isolation for optimal and near-optimal sensor suites.

A novel application of Fiber Bragg Grating (FBG) sensors in MPGD

NASA Astrophysics Data System (ADS)

Abbaneo, D.; Abbas, M.; Abbrescia, M.; Abi Akl, M.; Aboamer, O.; Acosta, D.; Ahmad, A.; Ahmed, W.; Aleksandrov, A.; Altieri, P.; Asawatangtrakuldee, C.; Aspell, P.; Assran, Y.; Awan, I.; Bally, S.; Ban, Y.; Banerjee, S.; Barashko, V.; Barria, P.; Bencze, G.; Beni, N.; Benussi, L.; Bhopatkar, V.; Bianco, S.; Bos, J.; Bouhali, O.; Braghieri, A.; Braibant, S.; Buontempo, S.; Calabria, C.; Caponero, M.; Caputo, C.; Cassese, F.; Castaneda, A.; Cauwenbergh, S.; Cavallo, F. R.; Celik, A.; Choi, M.; Choi, S.; Christiansen, J.; Cimmino, A.; Colafranceschi, S.; Colaleo, A.; Conde Garcia, A.; Czellar, S.; Dabrowski, M. M.; De Lentdecker, G.; De Oliveira, R.; de Robertis, G.; Dildick, S.; Dorney, B.; Endroczi, G.; Errico, F.; Fenyvesi, A.; Ferrini, M.; Ferry, S.; Furic, I.; Giacomelli, P.; Gilmore, J.; Golovtsov, V.; Guiducci, L.; Guilloux, F.; Gutierrez, A.; Hadjiiska, R. M.; Hauser, J.; Hoepfner, K.; Hohlmann, M.; Hoorani, H.; Iaydjiev, P.; Jeng, Y. G.; Kamon, T.; Karchin, P.; Korytov, A.; Krutelyov, S.; Kumar, A.; Kim, H.; Lalli, A.; Lee, J.; Lenzi, T.; Litov, L.; Loddo, F.; Madorsky, A.; Maerschalk, T.; Maggi, M.; Magnani, A.; Mal, P. K.; Mandal, K.; Marchioro, A.; Marinov, A.; Majumdar, N.; Merlin, J. A.; Mitselmakher, G.; Mohanty, A. K.; Mohapatra, A.; Molnar, J.; Muhammad, S.; Mukhopadhyay, S.; Naimuddin, M.; Nuzzo, S.; Oliveri, E.; Pant, L. M.; Paolucci, P.; Park, I.; Passamonti, L.; Passeggio, G.; Pavlov, B.; Philipps, B.; Piccolo, D.; Pierluigi, D.; Postema, H.; Primavera, F.; Puig Baranac, A.; Radi, A.; Radogna, R.; Raffone, G.; Ranieri, A.; Rashevski, G.; Riccardi, C.; Rodozov, M.; Rodrigues, A.; Ropelewski, L.; RoyChowdhury, S.; Russo, A.; Ryu, G.; Ryu, M. S.; Safonov, A.; Salva, S.; Saviano, G.; Sharma, A.; Sharma, A.; Sharma, R.; Shah, A. H.; Shopova, M.; Sturdy, J.; Sultanov, G.; Swain, S. K.; Szillasi, Z.; Talvitie, J.; Tatarinov, A.; Tuuva, T.; Tytgat, M.; Valente, M.; Vai, I.; Van Stenis, M.; Venditti, R.; Verhagen, E.; Verwilligen, P.; Vitulo, P.; Volkov, S.; Vorobyev, A.; Wang, D.; Wang, M.; Yang, U.; Yang, Y.; Yonamine, R.; Zaganidis, N.; Zenoni, F.; Zhang, A.

2018-02-01

We present a novel application of Fiber Bragg Grating (FBG) sensors in the construction and characterisation of Micro Pattern Gaseous Detector (MPGD), with particular attention to the realisation of the largest triple (Gas electron Multiplier) GEM chambers so far operated, the GE1/1 chambers of the CMS experiment at LHC. The GE1/1 CMS project consists of 144 GEM chambers of about 0.5 m2 active area each, employing three GEM foils per chamber, to be installed in the forward region of the CMS endcap during the long shutdown of LHC in 2108-2019. The large active area of each GE1/1 chamber consists of GEM foils that are mechanically stretched in order to secure their flatness and the consequent uniform performance of the GE1/1 chamber across its whole active surface. So far FBGs have been used in high energy physics mainly as high precision positioning and re-positioning sensors and as low cost, easy to mount, low space consuming temperature sensors. FBGs are also commonly used for very precise strain measurements in material studies. In this work we present a novel use of FBGs as flatness and mechanical tensioning sensors applied to the wide GEM foils of the GE1/1 chambers. A network of FBG sensors have been used to determine the optimal mechanical tension applied and to characterise the mechanical tension that should be applied to the foils. We discuss the results of the test done on a full-sized GE1/1 final prototype, the studies done to fully characterise the GEM material, how this information was used to define a standard assembly procedure and possible future developments.

Inductive Linear-Position Sensor/Limit-Sensor Units

NASA Technical Reports Server (NTRS)

Alhom, Dean; Howard, David; Smith, Dennis; Dutton, Kenneth

2007-01-01

A new sensor provides an absolute position measurement. A schematic view of a motorized linear-translation stage that contains, at each end, an electronic unit that functions as both (1) a non-contact sensor that measures the absolute position of the stage and (2) a non-contact equivalent of a limit switch that is tripped when the stage reaches the nominal limit position. The need for such an absolute linear position-sensor/limit-sensor unit arises in the case of a linear-translation stage that is part of a larger system in which the actual stopping position of the stage (relative to the nominal limit position) must be known. Because inertia inevitably causes the stage to run somewhat past the nominal limit position, tripping of a standard limit switch or other limit sensor does not provide the required indication of the actual stopping position. This innovative sensor unit operates on an electromagnetic-induction principle similar to that of linear variable differential transformers (LVDTs)

Multi-Sensor Detection with Particle Swarm Optimization for Time-Frequency Coded Cooperative WSNs Based on MC-CDMA for Underground Coal Mines

PubMed Central

Xu, Jingjing; Yang, Wei; Zhang, Linyuan; Han, Ruisong; Shao, Xiaotao

2015-01-01

In this paper, a wireless sensor network (WSN) technology adapted to underground channel conditions is developed, which has important theoretical and practical value for safety monitoring in underground coal mines. According to the characteristics that the space, time and frequency resources of underground tunnel are open, it is proposed to constitute wireless sensor nodes based on multicarrier code division multiple access (MC-CDMA) to make full use of these resources. To improve the wireless transmission performance of source sensor nodes, it is also proposed to utilize cooperative sensors with good channel conditions from the sink node to assist source sensors with poor channel conditions. Moreover, the total power of the source sensor and its cooperative sensors is allocated on the basis of their channel conditions to increase the energy efficiency of the WSN. To solve the problem that multiple access interference (MAI) arises when multiple source sensors transmit monitoring information simultaneously, a kind of multi-sensor detection (MSD) algorithm with particle swarm optimization (PSO), namely D-PSO, is proposed for the time-frequency coded cooperative MC-CDMA WSN. Simulation results show that the average bit error rate (BER) performance of the proposed WSN in an underground coal mine is improved significantly by using wireless sensor nodes based on MC-CDMA, adopting time-frequency coded cooperative transmission and D-PSO algorithm with particle swarm optimization. PMID:26343660

Multi-Sensor Detection with Particle Swarm Optimization for Time-Frequency Coded Cooperative WSNs Based on MC-CDMA for Underground Coal Mines.

PubMed

Xu, Jingjing; Yang, Wei; Zhang, Linyuan; Han, Ruisong; Shao, Xiaotao

2015-08-27

In this paper, a wireless sensor network (WSN) technology adapted to underground channel conditions is developed, which has important theoretical and practical value for safety monitoring in underground coal mines. According to the characteristics that the space, time and frequency resources of underground tunnel are open, it is proposed to constitute wireless sensor nodes based on multicarrier code division multiple access (MC-CDMA) to make full use of these resources. To improve the wireless transmission performance of source sensor nodes, it is also proposed to utilize cooperative sensors with good channel conditions from the sink node to assist source sensors with poor channel conditions. Moreover, the total power of the source sensor and its cooperative sensors is allocated on the basis of their channel conditions to increase the energy efficiency of the WSN. To solve the problem that multiple access interference (MAI) arises when multiple source sensors transmit monitoring information simultaneously, a kind of multi-sensor detection (MSD) algorithm with particle swarm optimization (PSO), namely D-PSO, is proposed for the time-frequency coded cooperative MC-CDMA WSN. Simulation results show that the average bit error rate (BER) performance of the proposed WSN in an underground coal mine is improved significantly by using wireless sensor nodes based on MC-CDMA, adopting time-frequency coded cooperative transmission and D-PSO algorithm with particle swarm optimization.

Unobtrusive Monitoring of Neonatal Brain Temperature Using a Zero-Heat-Flux Sensor Matrix.

PubMed

Atallah, Louis; Bongers, Edwin; Lamichhane, Bishal; Bambang-Oetomo, Sidarto

2016-01-01

The temperature of preterm neonates must be maintained within a narrow window to ensure their survival. Continuously measuring their core temperature provides an optimal means of monitoring their thermoregulation and their response to environmental changes. However, existing methods of measuring core temperature can be very obtrusive, such as rectal probes, or inaccurate/lagging, such as skin temperature sensors and spot-checks using tympanic temperature sensors. This study investigates an unobtrusive method of measuring brain temperature continuously using an embedded zero-heat-flux (ZHF) sensor matrix placed under the head of the neonate. The measured temperature profile is used to segment areas of motion and incorrect positioning, where the neonate's head is not above the sensors. We compare our measurements during low motion/stable periods to esophageal temperatures for 12 preterm neonates, measured for an average of 5 h per neonate. The method we propose shows good correlation with the reference temperature for most of the neonates. The unobtrusive embedding of the matrix in the neonate's environment poses no harm or disturbance to the care work-flow, while measuring core temperature. To address the effect of motion on the ZHF measurements in the current embodiment, we recommend a more ergonomic embedding ensuring the sensors are continuously placed under the neonate's head.

Overcoming urban GPS navigation challenges through the use of MEMS inertial sensors and proper verification of navigation system performance

NASA Astrophysics Data System (ADS)

Vinande, Eric T.

This research proposes several means to overcome challenges in the urban environment to ground vehicle global positioning system (GPS) receiver navigation performance through the integration of external sensor information. The effects of narrowband radio frequency interference and signal attenuation, both common in the urban environment, are examined with respect to receiver signal tracking processes. Low-cost microelectromechanical systems (MEMS) inertial sensors, suitable for the consumer market, are the focus of receiver augmentation as they provide an independent measure of motion and are independent of vehicle systems. A method for estimating the mounting angles of an inertial sensor cluster utilizing typical urban driving maneuvers is developed and is able to provide angular measurements within two degrees of truth. The integration of GPS and MEMS inertial sensors is developed utilizing a full state navigation filter. Appropriate statistical methods are developed to evaluate the urban environment navigation improvement due to the addition of MEMS inertial sensors. A receiver evaluation metric that combines accuracy, availability, and maximum error measurements is presented and evaluated over several drive tests. Following a description of proper drive test techniques, record and playback systems are evaluated as the optimal way of testing multiple receivers and/or integrated navigation systems in the urban environment as they simplify vehicle testing requirements.

Kalman filter-based EM-optical sensor fusion for needle deflection estimation.

PubMed

Jiang, Baichuan; Gao, Wenpeng; Kacher, Daniel; Nevo, Erez; Fetics, Barry; Lee, Thomas C; Jayender, Jagadeesan

2018-04-01

In many clinical procedures such as cryoablation that involves needle insertion, accurate placement of the needle's tip at the desired target is the major issue for optimizing the treatment and minimizing damage to the neighboring anatomy. However, due to the interaction force between the needle and tissue, considerable error in intraoperative tracking of the needle tip can be observed as needle deflects. In this paper, measurements data from an optical sensor at the needle base and a magnetic resonance (MR) gradient field-driven electromagnetic (EM) sensor placed 10 cm from the needle tip are used within a model-integrated Kalman filter-based sensor fusion scheme. Bending model-based estimations and EM-based direct estimation are used as the measurement vectors in the Kalman filter, thus establishing an online estimation approach. Static tip bending experiments show that the fusion method can reduce the mean error of the tip position estimation from 29.23 mm of the optical sensor-based approach to 3.15 mm of the fusion-based approach and from 39.96 to 6.90 mm, at the MRI isocenter and the MRI entrance, respectively. This work established a novel sensor fusion scheme that incorporates model information, which enables real-time tracking of needle deflection with MRI compatibility, in a free-hand operating setup.

Simultaneous Intrinsic and Extrinsic Parameter Identification of a Hand-Mounted Laser-Vision Sensor

PubMed Central

Lee, Jong Kwang; Kim, Kiho; Lee, Yongseok; Jeong, Taikyeong

2011-01-01

In this paper, we propose a simultaneous intrinsic and extrinsic parameter identification of a hand-mounted laser-vision sensor (HMLVS). A laser-vision sensor (LVS), consisting of a camera and a laser stripe projector, is used as a sensor component of the robotic measurement system, and it measures the range data with respect to the robot base frame using the robot forward kinematics and the optical triangulation principle. For the optimal estimation of the model parameters, we applied two optimization techniques: a nonlinear least square optimizer and a particle swarm optimizer. Best-fit parameters, including both the intrinsic and extrinsic parameters of the HMLVS, are simultaneously obtained based on the least-squares criterion. From the simulation and experimental results, it is shown that the parameter identification problem considered was characterized by a highly multimodal landscape; thus, the global optimization technique such as a particle swarm optimization can be a promising tool to identify the model parameters for a HMLVS, while the nonlinear least square optimizer often failed to find an optimal solution even when the initial candidate solutions were selected close to the true optimum. The proposed optimization method does not require good initial guesses of the system parameters to converge at a very stable solution and it could be applied to a kinematically dissimilar robot system without loss of generality. PMID:22164104

Optimal Sensor Selection for Health Monitoring Systems

NASA Technical Reports Server (NTRS)

Santi, L. Michael; Sowers, T. Shane; Aguilar, Robert B.

2005-01-01

Sensor data are the basis for performance and health assessment of most complex systems. Careful selection and implementation of sensors is critical to enable high fidelity system health assessment. A model-based procedure that systematically selects an optimal sensor suite for overall health assessment of a designated host system is described. This procedure, termed the Systematic Sensor Selection Strategy (S4), was developed at NASA John H. Glenn Research Center in order to enhance design phase planning and preparations for in-space propulsion health management systems (HMS). Information and capabilities required to utilize the S4 approach in support of design phase development of robust health diagnostics are outlined. A merit metric that quantifies diagnostic performance and overall risk reduction potential of individual sensor suites is introduced. The conceptual foundation for this merit metric is presented and the algorithmic organization of the S4 optimization process is described. Representative results from S4 analyses of a boost stage rocket engine previously under development as part of NASA's Next Generation Launch Technology (NGLT) program are presented.

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.

Joint Resource Optimization for Cognitive Sensor Networks with SWIPT-Enabled Relay.

PubMed

Lu, Weidang; Lin, Yuanrong; Peng, Hong; Nan, Tian; Liu, Xin

2017-09-13

Energy-constrained wireless networks, such as wireless sensor networks (WSNs), are usually powered by fixed energy supplies (e.g., batteries), which limits the operation time of networks. Simultaneous wireless information and power transfer (SWIPT) is a promising technique to prolong the lifetime of energy-constrained wireless networks. This paper investigates the performance of an underlay cognitive sensor network (CSN) with SWIPT-enabled relay node. In the CSN, the amplify-and-forward (AF) relay sensor node harvests energy from the ambient radio-frequency (RF) signals using power splitting-based relaying (PSR) protocol. Then, it helps forward the signal of source sensor node (SSN) to the destination sensor node (DSN) by using the harvested energy. We study the joint resource optimization including the transmit power and power splitting ratio to maximize CSN's achievable rate with the constraint that the interference caused by the CSN to the primary users (PUs) is within the permissible threshold. Simulation results show that the performance of our proposed joint resource optimization can be significantly improved.

Recognition physical activities with optimal number of wearable sensors using data mining algorithms and deep belief network.

PubMed

Al-Fatlawi, Ali H; Fatlawi, Hayder K; Sai Ho Ling

2017-07-01

Daily physical activities monitoring is benefiting the health care field in several ways, in particular with the development of the wearable sensors. This paper adopts effective ways to calculate the optimal number of the necessary sensors and to build a reliable and a high accuracy monitoring system. Three data mining algorithms, namely Decision Tree, Random Forest and PART Algorithm, have been applied for the sensors selection process. Furthermore, the deep belief network (DBN) has been investigated to recognise 33 physical activities effectively. The results indicated that the proposed method is reliable with an overall accuracy of 96.52% and the number of sensors is minimised from nine to six sensors.

Graph SLAM correction for single scanner MLS forest data under boreal forest canopy

NASA Astrophysics Data System (ADS)

Kukko, Antero; Kaijaluoto, Risto; Kaartinen, Harri; Lehtola, Ville V.; Jaakkola, Anttoni; Hyyppä, Juha

2017-10-01

Mobile laser scanning (MLS) provides kinematic means to collect three dimensional data from surroundings for various mapping and environmental analysis purposes. Vehicle based MLS has been used for road and urban asset surveys for about a decade. The equipment to derive the trajectory information for the point cloud generation from the laser data is almost without exception based on GNSS-IMU (Global Navigation Satellite System - Inertial Measurement Unit) technique. That is because of the GNSS ability to maintain global accuracy, and IMU to produce the attitude information needed to orientate the laser scanning and imaging sensor data. However, there are known challenges in maintaining accurate positioning when GNSS signal is weak or even absent over long periods of time. The duration of the signal loss affects the severity of degradation of the positioning solution depending on the quality/performance level of the IMU in use. The situation could be improved to a certain extent with higher performance IMUs, but increasing system expenses make such approach unsustainable in general. Another way to tackle the problem is to attach additional sensors to the system to overcome the degrading position accuracy: such that observe features from the environment to solve for short term system movements accurately enough to prevent the IMU solution to drift. This results in more complex system integration with need for more calibration and synchronization of multiple sensors into an operational approach. In this paper we study operation of an ATV (All -terrain vehicle) mounted, GNSS-IMU based single scanner MLS system in boreal forest conditions. The data generated by RoamerR2 system is targeted for generating 3D terrain and tree maps for optimizing harvester operations and forest inventory purposes at individual tree level. We investigate a process-flow and propose a graph optimization based method which uses data from a single scanner MLS for correcting the post-processed GNSS-IMU trajectory for positional drift under mature boreal forest canopy conditions. The result shows that we can improve the internal conformity of the data significantly from 0.7 m to 1 cm based on tree stem feature location data. When the optimization result is compared to reference at plot level we reach down to 6 cm mean error in absolute tree stem locations. The approach can be generalized to any MLS point cloud data, and provides as such a remarkable contribution to harness MLS for practical forestry and high precision terrain and structural modeling in GNSS obstructed environments.

Method and system having ultrasonic sensor movable by translation device for ultrasonic profiling of weld samples

DOEpatents

Panyard, James; Potter, Timothy; Charron, William; Hopkins, Deborah; Reverdy, Frederic

2010-04-06

A system for ultrasonic profiling of a weld sample includes a carriage movable in opposite first and second directions. An ultrasonic sensor is coupled to the carriage to move over the sample as the carriage moves. An encoder determines the position of the carriage to determine the position of the sensor. A spring is connected at one end of the carriage. Upon the carriage being moved in the first direction toward the spring such that the carriage and the sensor are at a beginning position and the spring is compressed the spring decompresses to push the carriage back along the second direction to move the carriage and the sensor from the beginning position to an ending position. The encoder triggers the sensor to take the ultrasonic measurements of the sample when the sensor is at predetermined positions while the sensor moves over the sample between the beginning and positions.

Finite Element Analysis of Film Stack Architecture for Complementary Metal-Oxide-Semiconductor Image Sensors.

PubMed

Wu, Kuo-Tsai; Hwang, Sheng-Jye; Lee, Huei-Huang

2017-05-02

Image sensors are the core components of computer, communication, and consumer electronic products. Complementary metal oxide semiconductor (CMOS) image sensors have become the mainstay of image-sensing developments, but are prone to leakage current. In this study, we simulate the CMOS image sensor (CIS) film stacking process by finite element analysis. To elucidate the relationship between the leakage current and stack architecture, we compare the simulated and measured leakage currents in the elements. Based on the analysis results, we further improve the performance by optimizing the architecture of the film stacks or changing the thin-film material. The material parameters are then corrected to improve the accuracy of the simulation results. The simulated and experimental results confirm a positive correlation between measured leakage current and stress. This trend is attributed to the structural defects induced by high stress, which generate leakage. Using this relationship, we can change the structure of the thin-film stack to reduce the leakage current and thereby improve the component life and reliability of the CIS components.

Finite Element Analysis of Film Stack Architecture for Complementary Metal-Oxide–Semiconductor Image Sensors

PubMed Central

Wu, Kuo-Tsai; Hwang, Sheng-Jye; Lee, Huei-Huang

2017-01-01

Image sensors are the core components of computer, communication, and consumer electronic products. Complementary metal oxide semiconductor (CMOS) image sensors have become the mainstay of image-sensing developments, but are prone to leakage current. In this study, we simulate the CMOS image sensor (CIS) film stacking process by finite element analysis. To elucidate the relationship between the leakage current and stack architecture, we compare the simulated and measured leakage currents in the elements. Based on the analysis results, we further improve the performance by optimizing the architecture of the film stacks or changing the thin-film material. The material parameters are then corrected to improve the accuracy of the simulation results. The simulated and experimental results confirm a positive correlation between measured leakage current and stress. This trend is attributed to the structural defects induced by high stress, which generate leakage. Using this relationship, we can change the structure of the thin-film stack to reduce the leakage current and thereby improve the component life and reliability of the CIS components. PMID:28468324

Active control of flexural vibrations in beams

NASA Technical Reports Server (NTRS)

Gerhold, Carl H.

1987-01-01

The feasibility of using piezoelectric actuators to control the flexural oscillations of large structures in space is investigated. Flexural oscillations are excited by impulsive loads. The vibratory response can degrade the pointing accuracy of cameras and antennae, and can cause high stresses at structural node points. Piezoelectric actuators have the advantage of exerting localized bending moments. In this way, vibration is controlled without exciting rigid body modes. The actuators are used in collocated sensor/driver pairs to form a feedback control system. The sensor produces a voltage that is proportional to the dynamic stress at the sensor location, and the driver produces a force that is proportional to the voltage applied to it. The analog control system amplifies and phase shifts the sensor signal to produce the voltage signal that is applied to the driver. The feedback control is demonstrated to increase the first mode damping in a cantilever beam by up to 100 percent, depending on the amplifier gain. The damping efficiency of the control system when the piezoelectrics are not optimally positioned at points of high stress in the beam is evaluated.

Adaptive and mobile ground sensor array.

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

Holzrichter, Michael Warren; O'Rourke, William T.; Zenner, Jennifer

The goal of this LDRD was to demonstrate the use of robotic vehicles for deploying and autonomously reconfiguring seismic and acoustic sensor arrays with high (centimeter) accuracy to obtain enhancement of our capability to locate and characterize remote targets. The capability to accurately place sensors and then retrieve and reconfigure them allows sensors to be placed in phased arrays in an initial monitoring configuration and then to be reconfigured in an array tuned to the specific frequencies and directions of the selected target. This report reviews the findings and accomplishments achieved during this three-year project. This project successfully demonstrated autonomousmore » deployment and retrieval of a payload package with an accuracy of a few centimeters using differential global positioning system (GPS) signals. It developed an autonomous, multisensor, temporally aligned, radio-frequency communication and signal processing capability, and an array optimization algorithm, which was implemented on a digital signal processor (DSP). Additionally, the project converted the existing single-threaded, monolithic robotic vehicle control code into a multi-threaded, modular control architecture that enhances the reuse of control code in future projects.« less

Design of a correlated validated CFD and genetic algorithm model for optimized sensors placement for indoor air quality monitoring

NASA Astrophysics Data System (ADS)

Mousavi, Monireh Sadat; Ashrafi, Khosro; Motlagh, Majid Shafie Pour; Niksokhan, Mohhamad Hosein; Vosoughifar, HamidReza

2018-02-01

In this study, coupled method for simulation of flow pattern based on computational methods for fluid dynamics with optimization technique using genetic algorithms is presented to determine the optimal location and number of sensors in an enclosed residential complex parking in Tehran. The main objective of this research is costs reduction and maximum coverage with regard to distribution of existing concentrations in different scenarios. In this study, considering all the different scenarios for simulation of pollution distribution using CFD simulations has been challenging due to extent of parking and number of cars available. To solve this problem, some scenarios have been selected based on random method. Then, maximum concentrations of scenarios are chosen for performing optimization. CFD simulation outputs are inserted as input in the optimization model using genetic algorithm. The obtained results stated optimal number and location of sensors.

A Parameter Communication Optimization Strategy for Distributed Machine Learning in Sensors.

PubMed

Zhang, Jilin; Tu, Hangdi; Ren, Yongjian; Wan, Jian; Zhou, Li; Li, Mingwei; Wang, Jue; Yu, Lifeng; Zhao, Chang; Zhang, Lei

2017-09-21

In order to utilize the distributed characteristic of sensors, distributed machine learning has become the mainstream approach, but the different computing capability of sensors and network delays greatly influence the accuracy and the convergence rate of the machine learning model. Our paper describes a reasonable parameter communication optimization strategy to balance the training overhead and the communication overhead. We extend the fault tolerance of iterative-convergent machine learning algorithms and propose the Dynamic Finite Fault Tolerance (DFFT). Based on the DFFT, we implement a parameter communication optimization strategy for distributed machine learning, named Dynamic Synchronous Parallel Strategy (DSP), which uses the performance monitoring model to dynamically adjust the parameter synchronization strategy between worker nodes and the Parameter Server (PS). This strategy makes full use of the computing power of each sensor, ensures the accuracy of the machine learning model, and avoids the situation that the model training is disturbed by any tasks unrelated to the sensors.

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.

AUV Underwater Positioning Algorithm Based on Interactive Assistance of SINS and LBL

PubMed Central

Zhang, Tao; Chen, Liping; Li, Yao

2015-01-01

This paper studies an underwater positioning algorithm based on the interactive assistance of a strapdown inertial navigation system (SINS) and LBL, and this algorithm mainly includes an optimal correlation algorithm with aided tracking of an SINS/Doppler velocity log (DVL)/magnetic compass pilot (MCP), a three-dimensional TDOA positioning algorithm of Taylor series expansion and a multi-sensor information fusion algorithm. The final simulation results show that compared to traditional underwater positioning algorithms, this scheme can not only directly correct accumulative errors caused by a dead reckoning algorithm, but also solves the problem of ambiguous correlation peaks caused by multipath transmission of underwater acoustic signals. The proposed method can calibrate the accumulative error of the AUV position more directly and effectively, which prolongs the underwater operating duration of the AUV. PMID:26729120

Exponential Modelling for Mutual-Cohering of Subband Radar Data

NASA Astrophysics Data System (ADS)

Siart, U.; Tejero, S.; Detlefsen, J.

2005-05-01

Increasing resolution and accuracy is an important issue in almost any type of radar sensor application. However, both resolution and accuracy are strongly related to the available signal bandwidth and energy that can be used. Nowadays, often several sensors operating in different frequency bands become available on a sensor platform. It is an attractive goal to use the potential of advanced signal modelling and optimization procedures by making proper use of information stemming from different frequency bands at the RF signal level. An important prerequisite for optimal use of signal energy is coherence between all contributing sensors. Coherent multi-sensor platforms are greatly expensive and are thus not available in general. This paper presents an approach for accurately estimating object radar responses using subband measurements at different RF frequencies. An exponential model approach allows to compensate for the lack of mutual coherence between independently operating sensors. Mutual coherence is recovered from the a-priori information that both sensors have common scattering centers in view. Minimizing the total squared deviation between measured data and a full-range exponential signal model leads to more accurate pole angles and pole magnitudes compared to single-band optimization. The model parameters (range and magnitude of point scatterers) after this full-range optimization process are also more accurate than the parameters obtained from a commonly used super-resolution procedure (root-MUSIC) applied to the non-coherent subband data.

Improved laser-based triangulation sensor with enhanced range and resolution through adaptive optics-based active beam control.

PubMed

Reza, Syed Azer; Khwaja, Tariq Shamim; Mazhar, Mohsin Ali; Niazi, Haris Khan; Nawab, Rahma

2017-07-20

Various existing target ranging techniques are limited in terms of the dynamic range of operation and measurement resolution. These limitations arise as a result of a particular measurement methodology, the finite processing capability of the hardware components deployed within the sensor module, and the medium through which the target is viewed. Generally, improving the sensor range adversely affects its resolution and vice versa. Often, a distance sensor is designed for an optimal range/resolution setting depending on its intended application. Optical triangulation is broadly classified as a spatial-signal-processing-based ranging technique and measures target distance from the location of the reflected spot on a position sensitive detector (PSD). In most triangulation sensors that use lasers as a light source, beam divergence-which severely affects sensor measurement range-is often ignored in calculations. In this paper, we first discuss in detail the limitations to ranging imposed by beam divergence, which, in effect, sets the sensor dynamic range. Next, we show how the resolution of laser-based triangulation sensors is limited by the interpixel pitch of a finite-sized PSD. In this paper, through the use of tunable focus lenses (TFLs), we propose a novel design of a triangulation-based optical rangefinder that improves both the sensor resolution and its dynamic range through adaptive electronic control of beam propagation parameters. We present the theory and operation of the proposed sensor and clearly demonstrate a range and resolution improvement with the use of TFLs. Experimental results in support of our claims are shown to be in strong agreement with theory.

An optimized BP neural network based on genetic algorithm for static decoupling of a six-axis force/torque sensor

NASA Astrophysics Data System (ADS)

Fu, Liyue; Song, Aiguo

2018-02-01

In order to improve the measurement precision of 6-axis force/torque sensor for robot, BP decoupling algorithm optimized by GA (GA-BP algorithm) is proposed in this paper. The weights and thresholds of a BP neural network with 6-10-6 topology are optimized by GA to develop decouple a six-axis force/torque sensor. By comparison with other traditional decoupling algorithm, calculating the pseudo-inverse matrix of calibration and classical BP algorithm, the decoupling results validate the good decoupling performance of GA-BP algorithm and the coupling errors are reduced.

Effect of heater geometry and cavity volume on the sensitivity of a thermal convection-based tilt sensor

NASA Astrophysics Data System (ADS)

Han, Maeum; Keon Kim, Jae; Kong, Seong Ho; Kang, Shin-Won; Jung, Daewoong

2018-06-01

This paper reports a micro-electro-mechanical-system (MEMS)-based tilt sensor using air medium. Since the working mechanism of the sensor is the thermal convection in a sealed chamber, structural parameters that can affect thermal convection must be considered to optimize the performance of the sensor. This paper presents the experimental results that were conducted by optimizing several parameters such as the heater geometry, input power and cavity volume. We observed that an increase in the heating power and cavity volume can improve the sensitivity, and heater geometry plays important role in performance of the sensor.

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

Sword, Charles Keith

A scanner system and method for acquisition of position-based ultrasonic inspection data are described. The scanner system includes an inspection probe and a first non-contact linear encoder having a first sensor and a first scale to track inspection probe position. The first sensor is positioned to maintain a continuous non-contact interface between the first sensor and the first scale and to maintain a continuous alignment of the first sensor with the inspection probe. The scanner system may be used to acquire two-dimensional inspection probe position data by including a second non-contact linear encoder having a second sensor and a secondmore » scale, the second sensor positioned to maintain a continuous non-contact interface between the second sensor and the second scale and to maintain a continuous alignment of the second sensor with the first sensor.« less

A technique for position sensing and improved momentum evaluation of microparticle impacts in space.

NASA Technical Reports Server (NTRS)

Mcdonnell, J. A. M.; Abellanas, C.

1972-01-01

The design of a three element piezoelectric microparticle impact sensing diaphragm is described which is sensitive to the detection of momentum propagated by the bending wave. The design achieves a sensitivity of .03 microdyn/sec and optimizes the detection of the direct-path pulse from impact relative to secondary reflections and interference from discontinuities. Measurement of the relative arrival times and the maximum amplitudes of the outputs from the three piezoelectric sensors leads to the determination of the impact position and the normally resolved impact momentum exchange. Coincidence of the signals and a partial redundancy of data leads to a very high noise discrimination.

A novel cooperative localization algorithm using enhanced particle filter technique in maritime search and rescue wireless sensor network.

PubMed

Wu, Huafeng; Mei, Xiaojun; Chen, Xinqiang; Li, Junjun; Wang, Jun; Mohapatra, Prasant

2018-07-01

Maritime search and rescue (MSR) play a significant role in Safety of Life at Sea (SOLAS). However, it suffers from scenarios that the measurement information is inaccurate due to wave shadow effect when utilizing wireless Sensor Network (WSN) technology in MSR. In this paper, we develop a Novel Cooperative Localization Algorithm (NCLA) in MSR by using an enhanced particle filter method to reduce measurement errors on observation model caused by wave shadow effect. First, we take into account the mobility of nodes at sea to develop a motion model-Lagrangian model. Furthermore, we introduce both state model and observation model to constitute a system model for particle filter (PF). To address the impact of the wave shadow effect on the observation model, we develop an optimal parameter derived by Kullback-Leibler divergence (KLD) to mitigate the error. After the optimal parameter is acquired, an improved likelihood function is presented. Finally, the estimated position is acquired. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Optimal sensor placement for leak location in water distribution networks using genetic algorithms.

PubMed

Casillas, Myrna V; Puig, Vicenç; Garza-Castañón, Luis E; Rosich, Albert

2013-11-04

This paper proposes a new sensor placement approach for leak location in water distribution networks (WDNs). The sensor placement problem is formulated as an integer optimization problem. The optimization criterion consists in minimizing the number of non-isolable leaks according to the isolability criteria introduced. Because of the large size and non-linear integer nature of the resulting optimization problem, genetic algorithms (GAs) are used as the solution approach. The obtained results are compared with a semi-exhaustive search method with higher computational effort, proving that GA allows one to find near-optimal solutions with less computational load. Moreover, three ways of increasing the robustness of the GA-based sensor placement method have been proposed using a time horizon analysis, a distance-based scoring and considering different leaks sizes. A great advantage of the proposed methodology is that it does not depend on the isolation method chosen by the user, as long as it is based on leak sensitivity analysis. Experiments in two networks allow us to evaluate the performance of the proposed approach.

Optimal Sensor Placement for Leak Location in Water Distribution Networks Using Genetic Algorithms

PubMed Central

Casillas, Myrna V.; Puig, Vicenç; Garza-Castañón, Luis E.; Rosich, Albert

2013-01-01

This paper proposes a new sensor placement approach for leak location in water distribution networks (WDNs). The sensor placement problem is formulated as an integer optimization problem. The optimization criterion consists in minimizing the number of non-isolable leaks according to the isolability criteria introduced. Because of the large size and non-linear integer nature of the resulting optimization problem, genetic algorithms (GAs) are used as the solution approach. The obtained results are compared with a semi-exhaustive search method with higher computational effort, proving that GA allows one to find near-optimal solutions with less computational load. Moreover, three ways of increasing the robustness of the GA-based sensor placement method have been proposed using a time horizon analysis, a distance-based scoring and considering different leaks sizes. A great advantage of the proposed methodology is that it does not depend on the isolation method chosen by the user, as long as it is based on leak sensitivity analysis. Experiments in two networks allow us to evaluate the performance of the proposed approach. PMID:24193099

Multi-Sensor Optimal Data Fusion Based on the Adaptive Fading Unscented Kalman Filter

PubMed Central

Gao, Bingbing; Hu, Gaoge; Gao, Shesheng; Gu, Chengfan

2018-01-01

This paper presents a new optimal data fusion methodology based on the adaptive fading unscented Kalman filter for multi-sensor nonlinear stochastic systems. This methodology has a two-level fusion structure: at the bottom level, an adaptive fading unscented Kalman filter based on the Mahalanobis distance is developed and serves as local filters to improve the adaptability and robustness of local state estimations against process-modeling error; at the top level, an unscented transformation-based multi-sensor optimal data fusion for the case of N local filters is established according to the principle of linear minimum variance to calculate globally optimal state estimation by fusion of local estimations. The proposed methodology effectively refrains from the influence of process-modeling error on the fusion solution, leading to improved adaptability and robustness of data fusion for multi-sensor nonlinear stochastic systems. It also achieves globally optimal fusion results based on the principle of linear minimum variance. Simulation and experimental results demonstrate the efficacy of the proposed methodology for INS/GNSS/CNS (inertial navigation system/global navigation satellite system/celestial navigation system) integrated navigation. PMID:29415509

Multi-Sensor Optimal Data Fusion Based on the Adaptive Fading Unscented Kalman Filter.

PubMed

Gao, Bingbing; Hu, Gaoge; Gao, Shesheng; Zhong, Yongmin; Gu, Chengfan

2018-02-06

This paper presents a new optimal data fusion methodology based on the adaptive fading unscented Kalman filter for multi-sensor nonlinear stochastic systems. This methodology has a two-level fusion structure: at the bottom level, an adaptive fading unscented Kalman filter based on the Mahalanobis distance is developed and serves as local filters to improve the adaptability and robustness of local state estimations against process-modeling error; at the top level, an unscented transformation-based multi-sensor optimal data fusion for the case of N local filters is established according to the principle of linear minimum variance to calculate globally optimal state estimation by fusion of local estimations. The proposed methodology effectively refrains from the influence of process-modeling error on the fusion solution, leading to improved adaptability and robustness of data fusion for multi-sensor nonlinear stochastic systems. It also achieves globally optimal fusion results based on the principle of linear minimum variance. Simulation and experimental results demonstrate the efficacy of the proposed methodology for INS/GNSS/CNS (inertial navigation system/global navigation satellite system/celestial navigation system) integrated navigation.

Mechanical Structural Design of a MEMS-Based Piezoresistive Accelerometer for Head Injuries Monitoring: A Computational Analysis by Increments of the Sensor Mass Moment of Inertia †

PubMed Central

Messina, Marco; Njuguna, James; Palas, Chrysovalantis

2018-01-01

This work focuses on the proof-mass mechanical structural design improvement of a tri-axial piezoresistive accelerometer specifically designed for head injuries monitoring where medium-G impacts are common; for example, in sports such as racing cars or American Football. The device requires the highest sensitivity achievable with a single proof-mass approach, and a very low error (<1%) as the accuracy for these types of applications is paramount. The optimization method differs from previous work as it is based on the progressive increment of the sensor proof-mass mass moment of inertia (MMI) in all three axes. Three different designs are presented in this study, where at each step of design evolution, the MMI of the sensor proof-mass gradually increases in all axes. The work numerically demonstrates that an increment of MMI determines an increment of device sensitivity with a simultaneous reduction of cross-axis sensitivity in the particular axis under study. This is due to the linkage between the external applied stress and the distribution of mass (of the proof-mass), and therefore of its mass moment of inertia. Progressively concentrating the mass on the axes where the piezoresistors are located (i.e., x- and y-axis) by increasing the MMI in the x- and y-axis, will undoubtedly increase the longitudinal stresses applied in that areas for a given external acceleration, therefore increasing the piezoresistors fractional resistance change and eventually positively affecting the sensor sensitivity. The final device shows a sensitivity increase of about 80% in the z-axis and a reduction of cross-axis sensitivity of 18% respect to state-of-art sensors available in the literature from a previous work of the authors. Sensor design, modelling, and optimization are presented, concluding the work with results, discussion, and conclusion. PMID:29351221

Modeling the milling tool wear by using an evolutionary SVM-based model from milling runs experimental data

NASA Astrophysics Data System (ADS)

Nieto, Paulino José García; García-Gonzalo, Esperanza; Vilán, José Antonio Vilán; Robleda, Abraham Segade

2015-12-01

The main aim of this research work is to build a new practical hybrid regression model to predict the milling tool wear in a regular cut as well as entry cut and exit cut of a milling tool. The model was based on Particle Swarm Optimization (PSO) in combination with support vector machines (SVMs). This optimization mechanism involved kernel parameter setting in the SVM training procedure, which significantly influences the regression accuracy. Bearing this in mind, a PSO-SVM-based model, which is based on the statistical learning theory, was successfully used here to predict the milling tool flank wear (output variable) as a function of the following input variables: the time duration of experiment, depth of cut, feed, type of material, etc. To accomplish the objective of this study, the experimental dataset represents experiments from runs on a milling machine under various operating conditions. In this way, data sampled by three different types of sensors (acoustic emission sensor, vibration sensor and current sensor) were acquired at several positions. A second aim is to determine the factors with the greatest bearing on the milling tool flank wear with a view to proposing milling machine's improvements. Firstly, this hybrid PSO-SVM-based regression model captures the main perception of statistical learning theory in order to obtain a good prediction of the dependence among the flank wear (output variable) and input variables (time, depth of cut, feed, etc.). Indeed, regression with optimal hyperparameters was performed and a determination coefficient of 0.95 was obtained. The agreement of this model with experimental data confirmed its good performance. Secondly, the main advantages of this PSO-SVM-based model are its capacity to produce a simple, easy-to-interpret model, its ability to estimate the contributions of the input variables, and its computational efficiency. Finally, the main conclusions of this study are exposed.

Optimization of Self-Directed Target Coverage in Wireless Multimedia Sensor Network

PubMed Central

Yang, Yang; Wang, Yufei; Pi, Dechang; Wang, Ruchuan

2014-01-01

Video and image sensors in wireless multimedia sensor networks (WMSNs) have directed view and limited sensing angle. So the methods to solve target coverage problem for traditional sensor networks, which use circle sensing model, are not suitable for WMSNs. Based on the FoV (field of view) sensing model and FoV disk model proposed, how expected multimedia sensor covers the target is defined by the deflection angle between target and the sensor's current orientation and the distance between target and the sensor. Then target coverage optimization algorithms based on expected coverage value are presented for single-sensor single-target, multisensor single-target, and single-sensor multitargets problems distinguishingly. Selecting the orientation that sensor rotated to cover every target falling in the FoV disk of that sensor for candidate orientations and using genetic algorithm to multisensor multitargets problem, which has NP-complete complexity, then result in the approximated minimum subset of sensors which covers all the targets in networks. Simulation results show the algorithm's performance and the effect of number of targets on the resulting subset. PMID:25136667

Gyroscopic sensing in the wings of the hawkmoth Manduca sexta: the role of sensor location and directional sensitivity.

PubMed

Hinson, Brian T; Morgansen, Kristi A

2015-10-06

The wings of the hawkmoth Manduca sexta are lined with mechanoreceptors called campaniform sensilla that encode wing deformations. During flight, the wings deform in response to a variety of stimuli, including inertial-elastic loads due to the wing flapping motion, aerodynamic loads, and exogenous inertial loads transmitted by disturbances. Because the wings are actuated, flexible structures, the strain-sensitive campaniform sensilla are capable of detecting inertial rotations and accelerations, allowing the wings to serve not only as a primary actuator, but also as a gyroscopic sensor for flight control. We study the gyroscopic sensing of the hawkmoth wings from a control theoretic perspective. Through the development of a low-order model of flexible wing flapping dynamics, and the use of nonlinear observability analysis, we show that the rotational acceleration inherent in wing flapping enables the wings to serve as gyroscopic sensors. We compute a measure of sensor fitness as a function of sensor location and directional sensitivity by using the simulation-based empirical observability Gramian. Our results indicate that gyroscopic information is encoded primarily through shear strain due to wing twisting, where inertial rotations cause detectable changes in pronation and supination timing and magnitude. We solve an observability-based optimal sensor placement problem to find the optimal configuration of strain sensor locations and directional sensitivities for detecting inertial rotations. The optimal sensor configuration shows parallels to the campaniform sensilla found on hawkmoth wings, with clusters of sensors near the wing root and wing tip. The optimal spatial distribution of strain directional sensitivity provides a hypothesis for how heterogeneity of campaniform sensilla may be distributed.

Optimizing Retransmission Threshold in Wireless Sensor Networks

PubMed Central

Bi, Ran; Li, Yingshu; Tan, Guozhen; Sun, Liang

2016-01-01

The retransmission threshold in wireless sensor networks is critical to the latency of data delivery in the networks. However, existing works on data transmission in sensor networks did not consider the optimization of the retransmission threshold, and they simply set the same retransmission threshold for all sensor nodes in advance. The method did not take link quality and delay requirement into account, which decreases the probability of a packet passing its delivery path within a given deadline. This paper investigates the problem of finding optimal retransmission thresholds for relay nodes along a delivery path in a sensor network. The object of optimizing retransmission thresholds is to maximize the summation of the probability of the packet being successfully delivered to the next relay node or destination node in time. A dynamic programming-based distributed algorithm for finding optimal retransmission thresholds for relay nodes along a delivery path in the sensor network is proposed. The time complexity is OnΔ·max1≤i≤n{ui}, where ui is the given upper bound of the retransmission threshold of sensor node i in a given delivery path, n is the length of the delivery path and Δ is the given upper bound of the transmission delay of the delivery path. If Δ is greater than the polynomial, to reduce the time complexity, a linear programming-based (1+pmin)-approximation algorithm is proposed. Furthermore, when the ranges of the upper and lower bounds of retransmission thresholds are big enough, a Lagrange multiplier-based distributed O(1)-approximation algorithm with time complexity O(1) is proposed. Experimental results show that the proposed algorithms have better performance. PMID:27171092

Application of a COTS Resource Optimization Framework to the SSN Sensor Tasking Domain - Part I: Problem Definition

NASA Astrophysics Data System (ADS)

Tran, T.

With the onset of the SmallSat era, the RSO catalog is expected to see continuing growth in the near future. This presents a significant challenge to the current sensor tasking of the SSN. The Air Force is in need of a sensor tasking system that is robust, efficient, scalable, and able to respond in real-time to interruptive events that can change the tracking requirements of the RSOs. Furthermore, the system must be capable of using processed data from heterogeneous sensors to improve tasking efficiency. The SSN sensor tasking can be regarded as an economic problem of supply and demand: the amount of tracking data needed by each RSO represents the demand side while the SSN sensor tasking represents the supply side. As the number of RSOs to be tracked grows, demand exceeds supply. The decision-maker is faced with the problem of how to allocate resources in the most efficient manner. Braxton recently developed a framework called Multi-Objective Resource Optimization using Genetic Algorithm (MOROUGA) as one of its modern COTS software products. This optimization framework took advantage of the maturing technology of evolutionary computation in the last 15 years. This framework was applied successfully to address the resource allocation of an AFSCN-like problem. In any resource allocation problem, there are five key elements: (1) the resource pool, (2) the tasks using the resources, (3) a set of constraints on the tasks and the resources, (4) the objective functions to be optimized, and (5) the demand levied on the resources. In this paper we explain in detail how the design features of this optimization framework are directly applicable to address the SSN sensor tasking domain. We also discuss our validation effort as well as present the result of the AFSCN resource allocation domain using a prototype based on this optimization framework.

Distributed cluster management techniques for unattended ground sensor networks

NASA Astrophysics Data System (ADS)

Essawy, Magdi A.; Stelzig, Chad A.; Bevington, James E.; Minor, Sharon

2005-05-01

Smart Sensor Networks are becoming important target detection and tracking tools. The challenging problems in such networks include the sensor fusion, data management and communication schemes. This work discusses techniques used to distribute sensor management and multi-target tracking responsibilities across an ad hoc, self-healing cluster of sensor nodes. Although miniaturized computing resources possess the ability to host complex tracking and data fusion algorithms, there still exist inherent bandwidth constraints on the RF channel. Therefore, special attention is placed on the reduction of node-to-node communications within the cluster by minimizing unsolicited messaging, and distributing the sensor fusion and tracking tasks onto local portions of the network. Several challenging problems are addressed in this work including track initialization and conflict resolution, track ownership handling, and communication control optimization. Emphasis is also placed on increasing the overall robustness of the sensor cluster through independent decision capabilities on all sensor nodes. Track initiation is performed using collaborative sensing within a neighborhood of sensor nodes, allowing each node to independently determine if initial track ownership should be assumed. This autonomous track initiation prevents the formation of duplicate tracks while eliminating the need for a central "management" node to assign tracking responsibilities. Track update is performed as an ownership node requests sensor reports from neighboring nodes based on track error covariance and the neighboring nodes geo-positional location. Track ownership is periodically recomputed using propagated track states to determine which sensing node provides the desired coverage characteristics. High fidelity multi-target simulation results are presented, indicating the distribution of sensor management and tracking capabilities to not only reduce communication bandwidth consumption, but to also simplify multi-target tracking within the cluster.

Design optimization and fabrication of a novel structural piezoresistive pressure sensor for micro-pressure measurement

NASA Astrophysics Data System (ADS)

Li, Chuang; Cordovilla, Francisco; Ocaña, José L.

2018-01-01

This paper presents a novel structural piezoresistive pressure sensor with a four-beams-bossed-membrane (FBBM) structure that consisted of four short beams and a central mass to measure micro-pressure. The proposed structure can alleviate the contradiction between sensitivity and linearity to realize the micro measurement with high accuracy. In this study, the design, fabrication and test of the sensor are involved. By utilizing the finite element analysis (FEA) to analyze the stress distribution of sensitive elements and subsequently deducing the relationships between structural dimensions and mechanical performance, the optimization process makes the sensor achieve a higher sensitivity and a lower pressure nonlinearity. Based on the deduced equations, a series of optimized FBBM structure dimensions are ultimately determined. The designed sensor is fabricated on a silicon wafer by using traditional MEMS bulk-micromachining and anodic bonding technology. Experimental results show that the sensor achieves the sensitivity of 4.65 mV/V/kPa and pressure nonlinearity of 0.25% FSS in the operating range of 0-5 kPa at room temperature, indicating that this novel structure sensor can be applied in measuring the absolute micro pressure lower than 5 kPa.

Steam distribution and energy delivery optimization using wireless sensors

NASA Astrophysics Data System (ADS)

Olama, Mohammed M.; Allgood, Glenn O.; Kuruganti, Teja P.; Sukumar, Sreenivas R.; Djouadi, Seddik M.; Lake, Joe E.

2011-05-01

The Extreme Measurement Communications Center at Oak Ridge National Laboratory (ORNL) explores the deployment of a wireless sensor system with a real-time measurement-based energy efficiency optimization framework in the ORNL campus. With particular focus on the 12-mile long steam distribution network in our campus, we propose an integrated system-level approach to optimize the energy delivery within the steam distribution system. We address the goal of achieving significant energy-saving in steam lines by monitoring and acting on leaking steam valves/traps. Our approach leverages an integrated wireless sensor and real-time monitoring capabilities. We make assessments on the real-time status of the distribution system by mounting acoustic sensors on the steam pipes/traps/valves and observe the state measurements of these sensors. Our assessments are based on analysis of the wireless sensor measurements. We describe Fourier-spectrum based algorithms that interpret acoustic vibration sensor data to characterize flows and classify the steam system status. We are able to present the sensor readings, steam flow, steam trap status and the assessed alerts as an interactive overlay within a web-based Google Earth geographic platform that enables decision makers to take remedial action. We believe our demonstration serves as an instantiation of a platform that extends implementation to include newer modalities to manage water flow, sewage and energy consumption.

Comparative Investigation of Peripheral and Nonperipheral Zinc Phthalocyanine-Based Polycarbazoles in Terms of Optical, Electrical, and Sensing Properties.

PubMed

Soganci, Tugba; Baygu, Yasemin; Kabay, Nilgün; Gök, Yaşar; Ak, Metin

2018-06-15

In this study, nonperipherally alkyl-linked carbazole conjugated novel zinc(II) phthalocyanine was synthesized by cyclotetramerization reaction of 6-(9 H-carbazol-9-yl)hexane-1-thiol and 3,6-bis(tosyloxy) phthalonitrile in a one-step reaction. Optical, electrical, and sensing properties of this super structured polycarbazole obtained by electropolymerization are compared with peripherally alkyl-linked polycarbazole-based zinc(II) phthalocyanine. It has been found that the attachment of alkyl-linked carbazoles to the phthalocyanine molecule in either peripheral or nonperipheral positions has a great effect on the optical and electrical properties and sensing ability of the resulting polycarbazole derivatives. P(n-ZnPc) has the highest electrochromic contrast (70.5%) among the derivatives of zinc(II) phthalocyanines in the literature. In addition to these, the sensor platform has been successfully established, and analytical optimizations have been carried out. When the sensors prepared with zinc(II) phthalocyanine are examined, it was specified that the n-ZnPc- co-TP/GOx was ranked first in the literature with high sensor response and stability. As a result, by changing of the peripheral and nonperipheral position of phthalocyanines, their physical properties can be tuned to meet the requirements of desired technological application.

Highly sensitive lactate biosensor by engineering chitosan/PVI-Os/CNT/LOD network nanocomposite.

PubMed

Cui, Xiaoqiang; Li, Chang Ming; Zang, Jianfeng; Yu, Shucong

2007-06-15

A novel chitosan/PVI-Os(polyvinylimidazole-Os)/CNT(carbon nanotube)/LOD (lactate oxidase) network nanocomposite was constructed on gold electrode for detection of lactate. The composite was nanoengineered by selected matched material components and optimized composition ratio to produce a superior lactate sensor. Positively charged chitosan and PVI-Os were used as the matrix and the mediator to immobilize the negatively charged LOD and to enhance the electron transfer, respectively. CNTs were introduced as the essential component in the composite for the network nanostructure. FESEM (field emission scan electron microscopy) and electrochemical characterization demonstrated that CNT behaved as a cross-linker to network PVI and chitosan due to its nanoscaled and negative charged nature. This significantly improved the conductivity, stability and electroactivity for detection of lactate. The standard deviation of the sensor without CNT in the composite was greatly reduced from 19.6 to 4.9% by addition of CNTs. With optimized conditions the sensitivity and detection limit of the lactate sensor was 19.7 microA mM(-1)cm(-2) and 5 microM, respectively. The sensitivity was remarkably improved in comparison to the newly reported values of 0.15-3.85 microA mM(-1)cm(-2). This novel nanoengineering approach for selecting matched components to form a network nanostructure could be extended to other enzyme biosensors, and to have broad potential applications in diagnostics, life science and food analysis.

Efficient Convex Optimization for Energy-Based Acoustic Sensor Self-Localization and Source Localization in Sensor Networks.

PubMed

Yan, Yongsheng; Wang, Haiyan; Shen, Xiaohong; Leng, Bing; Li, Shuangquan

2018-05-21

The energy reading has been an efficient and attractive measure for collaborative acoustic source localization in practical application due to its cost saving in both energy and computation capability. The maximum likelihood problems by fusing received acoustic energy readings transmitted from local sensors are derived. Aiming to efficiently solve the nonconvex objective of the optimization problem, we present an approximate estimator of the original problem. Then, a direct norm relaxation and semidefinite relaxation, respectively, are utilized to derive the second-order cone programming, semidefinite programming or mixture of them for both cases of sensor self-location and source localization. Furthermore, by taking the colored energy reading noise into account, several minimax optimization problems are formulated, which are also relaxed via the direct norm relaxation and semidefinite relaxation respectively into convex optimization problems. Performance comparison with the existing acoustic energy-based source localization methods is given, where the results show the validity of our proposed methods.

Improved GSO Optimized ESN Soft-Sensor Model of Flotation Process Based on Multisource Heterogeneous Information Fusion

PubMed Central

Wang, Jie-sheng; Han, Shuang; Shen, Na-na

2014-01-01

For predicting the key technology indicators (concentrate grade and tailings recovery rate) of flotation process, an echo state network (ESN) based fusion soft-sensor model optimized by the improved glowworm swarm optimization (GSO) algorithm is proposed. Firstly, the color feature (saturation and brightness) and texture features (angular second moment, sum entropy, inertia moment, etc.) based on grey-level co-occurrence matrix (GLCM) are adopted to describe the visual characteristics of the flotation froth image. Then the kernel principal component analysis (KPCA) method is used to reduce the dimensionality of the high-dimensional input vector composed by the flotation froth image characteristics and process datum and extracts the nonlinear principal components in order to reduce the ESN dimension and network complex. The ESN soft-sensor model of flotation process is optimized by the GSO algorithm with congestion factor. Simulation results show that the model has better generalization and prediction accuracy to meet the online soft-sensor requirements of the real-time control in the flotation process. PMID:24982935

Efficient Convex Optimization for Energy-Based Acoustic Sensor Self-Localization and Source Localization in Sensor Networks

PubMed Central

Yan, Yongsheng; Wang, Haiyan; Shen, Xiaohong; Leng, Bing; Li, Shuangquan

2018-01-01

The energy reading has been an efficient and attractive measure for collaborative acoustic source localization in practical application due to its cost saving in both energy and computation capability. The maximum likelihood problems by fusing received acoustic energy readings transmitted from local sensors are derived. Aiming to efficiently solve the nonconvex objective of the optimization problem, we present an approximate estimator of the original problem. Then, a direct norm relaxation and semidefinite relaxation, respectively, are utilized to derive the second-order cone programming, semidefinite programming or mixture of them for both cases of sensor self-location and source localization. Furthermore, by taking the colored energy reading noise into account, several minimax optimization problems are formulated, which are also relaxed via the direct norm relaxation and semidefinite relaxation respectively into convex optimization problems. Performance comparison with the existing acoustic energy-based source localization methods is given, where the results show the validity of our proposed methods. PMID:29883410

Optimal Sensor-Based Motion Planning for Autonomous Vehicle Teams

DTIC Science & Technology

2017-03-01

calculated for non -dimensional ranges with Equation (3.26) and DU = 100 meters (shown at right) are equivalent to propagation loss calculated for 72 0 100...sensor and uniform target PDF, both choices are equivalent and the probability of non -detection equals the fraction of un- searched area. Time...feasible. Another goal is maximizing sensor performance in the presence of uncertainty. Optimal control provides a useful frame- work for solving these

Virtual sensors for active noise control in acoustic-structural coupled enclosures using structural sensing: robust virtual sensor design.

PubMed

Halim, Dunant; Cheng, Li; Su, Zhongqing

2011-03-01

The work was aimed to develop a robust virtual sensing design methodology for sensing and active control applications of vibro-acoustic systems. The proposed virtual sensor was designed to estimate a broadband acoustic interior sound pressure using structural sensors, with robustness against certain dynamic uncertainties occurring in an acoustic-structural coupled enclosure. A convex combination of Kalman sub-filters was used during the design, accommodating different sets of perturbed dynamic model of the vibro-acoustic enclosure. A minimax optimization problem was set up to determine an optimal convex combination of Kalman sub-filters, ensuring an optimal worst-case virtual sensing performance. The virtual sensing and active noise control performance was numerically investigated on a rectangular panel-cavity system. It was demonstrated that the proposed virtual sensor could accurately estimate the interior sound pressure, particularly the one dominated by cavity-controlled modes, by using a structural sensor. With such a virtual sensing technique, effective active noise control performance was also obtained even for the worst-case dynamics. © 2011 Acoustical Society of America

Geometry optimization for micro-pressure sensor considering dynamic interference

NASA Astrophysics Data System (ADS)

Yu, Zhongliang; Zhao, Yulong; Li, Lili; Tian, Bian; Li, Cun

2014-09-01

Presented is the geometry optimization for piezoresistive absolute micro-pressure sensor. A figure of merit called the performance factor (PF) is defined as a quantitative index to describe the comprehensive performances of a sensor including sensitivity, resonant frequency, and acceleration interference. Three geometries are proposed through introducing islands and sensitive beams into typical flat diaphragm. The stress distributions of sensitive elements are analyzed by finite element method. Multivariate fittings based on ANSYS simulation results are performed to establish the equations about surface stress, deflection, and resonant frequency. Optimization by MATLAB is carried out to determine the dimensions of the geometries. Convex corner undercutting is evaluated. Each PF of the three geometries with the determined dimensions is calculated and compared. Silicon bulk micromachining is utilized to fabricate the prototypes of the sensors. The outputs of the sensors under both static and dynamic conditions are tested. Experimental results demonstrate the rationality of the defined performance factor and reveal that the geometry with quad islands presents the highest PF of 210.947 Hz1/4. The favorable overall performances enable the sensor more suitable for altimetry.

Optimized autonomous space in-situ sensor web for volcano monitoring

USGS Publications Warehouse

Song, W.-Z.; Shirazi, B.; Huang, R.; Xu, M.; Peterson, N.; LaHusen, R.; Pallister, J.; Dzurisin, D.; Moran, S.; Lisowski, M.; Kedar, S.; Chien, S.; Webb, F.; Kiely, A.; Doubleday, J.; Davies, A.; Pieri, D.

2010-01-01

In response to NASA's announced requirement for Earth hazard monitoring sensor-web technology, a multidisciplinary team involving sensor-network experts (Washington State University), space scientists (JPL), and Earth scientists (USGS Cascade Volcano Observatory (CVO)), have developed a prototype of dynamic and scalable hazard monitoring sensor-web and applied it to volcano monitoring. The combined Optimized Autonomous Space In-situ Sensor-web (OASIS) has two-way communication capability between ground and space assets, uses both space and ground data for optimal allocation of limited bandwidth resources on the ground, and uses smart management of competing demands for limited space assets. It also enables scalability and seamless infusion of future space and in-situ assets into the sensor-web. The space and in-situ control components of the system are integrated such that each element is capable of autonomously tasking the other. The ground in-situ was deployed into the craters and around the flanks of Mount St. Helens in July 2009, and linked to the command and control of the Earth Observing One (EO-1) satellite. ?? 2010 IEEE.

The research of conformal optical design

NASA Astrophysics Data System (ADS)

Li, Lin; Li, Yan; Huang, Yi-fan; Du, Bao-lin

2009-07-01

Conformal optical domes are characterized as having external more elongated optical surfaces that are optimized to minimize drag, increased missile velocity and extended operational range. The outer surface of the conformal domes typically deviate greatly from spherical surface descriptions, so the inherent asymmetry of conformal surfaces leads to variations in the aberration content presented to the optical sensor as it is gimbaled across the field of regard, which degrades the sensor's ability to properly image targets of interest and then undermine the overall system performance. Consequently, the aerodynamic advantages of conformal domes cannot be realized in practical systems unless the dynamic aberration correction techniques are developed to restore adequate optical imaging capabilities. Up to now, many optical correction solutions have been researched in conformal optical design, including static aberrations corrections and dynamic aberrations corrections. There are three parts in this paper. Firstly, the combination of static and dynamic aberration correction is introduced. A system for correcting optical aberration created by a conformal dome has an outer surface and an inner surface. The optimization of the inner surface is regard as the static aberration correction; moreover, a deformable mirror is placed at the position of the secondary mirror in the two-mirror all reflective imaging system, which is the dynamic aberration correction. Secondly, the using of appropriate surface types is very important in conformal dome design. Better performing optical systems can result from surface types with adequate degrees of freedom to describe the proper corrector shape. Two surface types and the methods of using them are described, including Zernike polynomial surfaces used in correct elements and user-defined surfaces used in deformable mirror (DM). Finally, the Adaptive optics (AO) correction is presented. In order to correct the dynamical residual aberration in conformal optical design, the SPGD optimization algorithm is operated at each zoom position to calculate the optimized surface shape of the MEMS DM. The communication between MATLAB and Code V established via ActiveX technique is applied in simulation analysis.

Software Tools to Support the Assessment of System Health

NASA Technical Reports Server (NTRS)

Melcher, Kevin J.

2013-01-01

This presentation provides an overview of three software tools that were developed by the NASA Glenn Research Center to support the assessment of system health: the Propulsion Diagnostic Method Evaluation Strategy (ProDIMES), the Systematic Sensor Selection Strategy (S4), and the Extended Testability Analysis (ETA) tool. Originally developed to support specific NASA projects in aeronautics and space, these software tools are currently available to U.S. citizens through the NASA Glenn Software Catalog. The ProDiMES software tool was developed to support a uniform comparison of propulsion gas path diagnostic methods. Methods published in the open literature are typically applied to dissimilar platforms with different levels of complexity. They often address different diagnostic problems and use inconsistent metrics for evaluating performance. As a result, it is difficult to perform a one ]to ]one comparison of the various diagnostic methods. ProDIMES solves this problem by serving as a theme problem to aid in propulsion gas path diagnostic technology development and evaluation. The overall goal is to provide a tool that will serve as an industry standard, and will truly facilitate the development and evaluation of significant Engine Health Management (EHM) capabilities. ProDiMES has been developed under a collaborative project of The Technical Cooperation Program (TTCP) based on feedback provided by individuals within the aircraft engine health management community. The S4 software tool provides a framework that supports the optimal selection of sensors for health management assessments. S4 is structured to accommodate user ]defined applications, diagnostic systems, search techniques, and system requirements/constraints. One or more sensor suites that maximize this performance while meeting other user ]defined system requirements that are presumed to exist. S4 provides a systematic approach for evaluating combinations of sensors to determine the set or sets of sensors that optimally meet the performance goals and the constraints. It identifies optimal sensor suite solutions by utilizing a merit (i.e., cost) function with one of several available optimization approaches. As part of its analysis, S4 can expose fault conditions that are difficult to diagnose due to an incomplete diagnostic philosophy and/or a lack of sensors. S4 was originally developed and applied to liquid rocket engines. It was subsequently used to study the optimized selection of sensors for a simulation ]based aircraft engine diagnostic system. The ETA Tool is a software ]based analysis tool that augments the testability analysis and reporting capabilities of a commercial ]off ]the ]shelf (COTS) package. An initial diagnostic assessment is performed by the COTS software using a user ]developed, qualitative, directed ]graph model of the system being analyzed. The ETA Tool accesses system design information captured within the model and the associated testability analysis output to create a series of six reports for various system engineering needs. These reports are highlighted in the presentation. The ETA Tool was developed by NASA to support the verification of fault management requirements early in the Launch Vehicle process. Due to their early development during the design process, the TEAMS ]based diagnostic model and the ETA Tool were able to positively influence the system design by highlighting gaps in failure detection, fault isolation, and failure recovery.

A voting-based star identification algorithm utilizing local and global distribution

NASA Astrophysics Data System (ADS)

Fan, Qiaoyun; Zhong, Xuyang; Sun, Junhua

2018-03-01

A novel star identification algorithm based on voting scheme is presented in this paper. In the proposed algorithm, the global distribution and local distribution of sensor stars are fully utilized, and the stratified voting scheme is adopted to obtain the candidates for sensor stars. The database optimization is employed to reduce its memory requirement and improve the robustness of the proposed algorithm. The simulation shows that the proposed algorithm exhibits 99.81% identification rate with 2-pixel standard deviations of positional noises and 0.322-Mv magnitude noises. Compared with two similar algorithms, the proposed algorithm is more robust towards noise, and the average identification time and required memory is less. Furthermore, the real sky test shows that the proposed algorithm performs well on the real star images.

Position-insensitive long range inductive power transfer

NASA Astrophysics Data System (ADS)

Kwan, Christopher H.; Lawson, James; Yates, David C.; Mitcheson, Paul D.

2014-11-01

This paper presents results of an improved inductive wireless power transfer system for reliable long range powering of sensors with milliwatt-level consumption. An ultra-low power flyback impedance emulator operating in open loop is used to present the optimal load to the receiver's resonant tank. Transmitter power modulation is implemented in order to maintain constant receiver power and to prevent damage to the receiver electronics caused by excessive received voltage. Received power is steady up to 3 m at around 30 mW. The receiver electronics and feedback system consumes 3.1 mW and so with a transmitter input power of 163.3 W the receiver becomes power neutral at 4.75 m. Such an IPT system can provide a reliable alternative to energy harvesters for supplying power concurrently to multiple remote sensors.

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.

Directed Diffusion Modelling for Tesso Nilo National Parks Case Study

NASA Astrophysics Data System (ADS)

Yasri, Indra; Safrianti, Ery

2018-01-01

— Directed Diffusion (DD has ability to achieve energy efficiency in Wireless Sensor Network (WSN). This paper proposes Directed Diffusion (DD) modelling for Tesso Nilo National Parks (TNNP) case study. There are 4 stages of scenarios involved in this modelling. It’s started by appointing of sampling area through GPS coordinate. The sampling area is determined by optimization processes from 500m x 500m up to 1000m x 1000m with 100m increment in between. The next stage is sensor node placement. Sensor node is distributed in sampling area with three different quantities i.e. 20 nodes, 30 nodes and 40 nodes. One of those quantities is choose as an optimized sensor node placement. The third stage is to implement all scenarios in stages 1 and stages 2 on DD modelling. In the last stage, the evaluation process to achieve most energy efficient in the combination of optimized sampling area and optimized sensor node placement on Direct Diffusion (DD) routing protocol. The result shows combination between sampling area 500m x 500m and 20 nodes able to achieve energy efficient to support a forest preventive fire system at Tesso Nilo National Parks.

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

Exploiting a new electrochemical sensor for biofilm monitoring and water treatment optimization.

PubMed

Pavanello, Giovanni; Faimali, Marco; Pittore, Massimiliano; Mollica, Angelo; Mollica, Alessandro; Mollica, Alfonso

2011-02-01

Bacterial biofilm development is a serious problem in many fields, and the existing biofilm monitoring sensors often turn out to be inadequate. In this perspective, a new sensor (ALVIM) has been developed, exploiting the natural marine and freshwater biofilms electrochemical activity, proportional to surface covering. The results presented in this work, obtained testing the ALVIM system both in laboratory and in an industrial environment, show that the sensor gives a fast and accurate response to biofilm growth, and that this response can be used to optimize cleaning treatments inside pipelines. Compared to the existing biofilm sensors, the proposed system show significant technological innovations, higher sensitivity and precision. © 2010 Elsevier Ltd. All rights reserved.

Communal Sensor Network for Adaptive Noise Reduction in Aircraft Engine Nacelles

NASA Technical Reports Server (NTRS)

Jones, Kennie H.; Nark, Douglas M.; Jones, Michael G.

2011-01-01

Emergent behavior, a subject of much research in biology, sociology, and economics, is a foundational element of Complex Systems Science and is apropos in the design of sensor network systems. To demonstrate engineering for emergent behavior, a novel approach in the design of a sensor/actuator network is presented maintaining optimal noise attenuation as an adaptation to changing acoustic conditions. Rather than use the conventional approach where sensors are managed by a central controller, this new paradigm uses a biomimetic model where sensor/actuators cooperate as a community of autonomous organisms, sharing with neighbors to control impedance based on local information. From the combination of all individual actions, an optimal attenuation emerges for the global system.

Statistical evaluation of a project to estimate fish trajectories through the intakes of Kaplan hydropower turbines

NASA Astrophysics Data System (ADS)

Sutton, Virginia Kay

This paper examines statistical issues associated with estimating paths of juvenile salmon through the intakes of Kaplan turbines. Passive sensors, hydrophones, detecting signals from ultrasonic transmitters implanted in individual fish released into the preturbine region were used to obtain the information to estimate fish paths through the intake. Aim and location of the sensors affects the spatial region in which the transmitters can be detected, and formulas relating this region to sensor aiming directions are derived. Cramer-Rao lower bounds for the variance of estimators of fish location are used to optimize placement of each sensor. Finally, a statistical methodology is developed for analyzing angular data collected from optimally placed sensors.

Development of Position-Sensitive Magnetic Calorimeters for X-Ray Astronomy

NASA Technical Reports Server (NTRS)

Bandler, SImon; Stevenson, Thomas; Hsieh, Wen-Ting

2011-01-01

Metallic magnetic calorimeters (MMC) are one of the most promising devices to provide very high energy resolution needed for future astronomical x-ray spectroscopy. MMC detectors can be built to large detector arrays having thousands of pixels. Position-sensitive magnetic (PoSM) microcalorimeters consist of multiple absorbers thermally coupled to one magnetic micro calorimeter. Each absorber element has a different thermal coupling to the MMC, resulting in a distribution of different pulse shapes and enabling position discrimination between the absorber elements. PoSMs therefore achieve the large focal plane area with fewer number of readout channels without compromising spatial sampling. Excellent performance of PoSMs was achieved by optimizing the designs of key parameters such as the thermal conductance among the absorbers, magnetic sensor, and heat sink, as well as the absorber heat capacities. Micro fab ri - cation techniques were developed to construct four-absorber PoSMs, in which each absorber consists of a two-layer composite of bismuth and gold. The energy resolution (FWHM full width at half maximum) was measured to be better than 5 eV at 6 keV x-rays for all four absorbers. Position determination was demonstrated with pulse-shape discrimination, as well as with pulse rise time. X-ray microcalorimeters are usually designed to thermalize as quickly as possible to avoid degradation in energy resolution from position dependence to the pulse shapes. Each pixel consists of an absorber and a temperature sensor, both decoupled from the cold bath through a weak thermal link. Each pixel requires a separate readout channel; for instance, with a SQUID (superconducting quantum interference device). For future astronomy missions where thousands to millions of resolution elements are required, having an individual SQUID readout channel for each pixel becomes difficult. One route to attaining these goals is a position-sensitive detector in which a large continuous or pixilated array of x-ray absorbers shares fewer numbers of temperature sensors. A means of discriminating the signals from different absorber positions, however, needs to be built into the device for each sensor. The design concept for the device is such that the shape of the temperature pulse with time depends on the location of the absorber. This inherent position sensitivity of the signal is then analyzed to determine the location of the event precisely, effectively yielding one device with many sub-pixels. With such devices, the total number of electronic channels required to read out a given number of pixels is significantly reduced. PoSMs were developed that consist of four discrete absorbers connected to a single magnetic sensor. The design concept can be extended to more than four absorbers per sensor. The thermal conductance between the sensor and each absorber is different by design and consequently, the pulse shapes are different depending upon which absorber the xrays are received, allowing position discrimination. A magnetic sensor was used in which a paramagnetic Au:Er temperature-sensitive material is located in a weak magnetic field. Deposition of energy from an x-ray photon causes an increase in temperature, which leads to a change of magnetization of the paramagnetic sensor, which is subsequently read out using a low noise dc-SQUID. The PoSM microcalorimeters are fully microfabricated: the Au:Er sensor is located above the meander, with a thin insulation gap in between. For this position-sensitive device, four electroplated absorbers are thermally linked to the sensor via heat links of different thermal conductance. One pixel is identical to that of a single-pixel design, consisting of an overhanging absorber fabricated directly on top of the sensor. It is therefore very strongly thermally coupled to it. The three other absorbers are supported directly on a silicon-nitride membrane. These absorbers are thermally coupled to the sensor via Ti (5 nm)/Au250 nm) metal links. The strength of the links is parameterized by the number of gold squares making up the link. For detector performance, experimentally different pulse-shapes were demonstrated with 6 keV x-rays, which clearly show different rise times for different absorber positions. For energy resolution measurement, the PoSM was operated at 32 mK with an applied field that was generated using a persistent current of 50 mA. Over the four pixels, energy resolution ranges from 4.4 to 4.7 eV were demonstrated.

Evolutionary Beamforming Optimization for Radio Frequency Charging in Wireless Rechargeable Sensor Networks.

PubMed

Yao, Ke-Han; Jiang, Jehn-Ruey; Tsai, Chung-Hsien; Wu, Zong-Syun

2017-08-20

This paper investigates how to efficiently charge sensor nodes in a wireless rechargeable sensor network (WRSN) with radio frequency (RF) chargers to make the network sustainable. An RF charger is assumed to be equipped with a uniform circular array (UCA) of 12 antennas with the radius λ , where λ is the RF wavelength. The UCA can steer most RF energy in a target direction to charge a specific WRSN node by the beamforming technology. Two evolutionary algorithms (EAs) using the evolution strategy (ES), namely the Evolutionary Beamforming Optimization (EBO) algorithm and the Evolutionary Beamforming Optimization Reseeding (EBO-R) algorithm, are proposed to nearly optimize the power ratio of the UCA beamforming peak side lobe (PSL) and the main lobe (ML) aimed at the given target direction. The proposed algorithms are simulated for performance evaluation and are compared with a related algorithm, called Particle Swarm Optimization Gravitational Search Algorithm-Explore (PSOGSA-Explore), to show their superiority.

Position and orientation determination system and method

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

Harpring, Lawrence J.; Farfan, Eduardo B.; Gordon, John R.

A position determination system and method is provided that may be used for obtaining position and orientation information of a detector in a contaminated room. The system includes a detector, a sensor operably coupled to the detector, and a motor coupled to the sensor to move the sensor around the detector. A CPU controls the operation of the motor to move the sensor around the detector and determines distance and angle data from the sensor to an object. The method includes moving a sensor around the detector and measuring distance and angle data from the sensor to an object atmore » incremental positions around the detector.« less

Analytical instrumentation infrastructure for combinatorial and high-throughput development of formulated discrete and gradient polymeric sensor materials arrays

NASA Astrophysics Data System (ADS)

Potyrailo, Radislav A.; Hassib, Lamyaa

2005-06-01

Multicomponent polymer-based formulations of optical sensor materials are difficult and time consuming to optimize using conventional approaches. To address these challenges, our long-term goal is to determine relationships between sensor formulation and sensor response parameters using new scientific methodologies. As the first step, we have designed and implemented an automated analytical instrumentation infrastructure for combinatorial and high-throughput development of polymeric sensor materials for optical sensors. Our approach is based on the fabrication and performance screening of discrete and gradient sensor arrays. Simultaneous formation of multiple sensor coatings into discrete 4×6, 6×8, and 8×12 element arrays (3-15μL volume per element) and their screening provides not only a well-recognized acceleration in the screening rate, but also considerably reduces or even eliminates sources of variability, which are randomly affecting sensors response during a conventional one-at-a-time sensor coating evaluation. The application of gradient sensor arrays provides additional capabilities for rapid finding of the optimal formulation parameters.

Sensors for rate responsive pacing

PubMed Central

Dell'Orto, Simonetta; Valli, Paolo; Greco, Enrico Maria

2004-01-01

Advances in pacemaker technology in the 1980s have generated a wide variety of complex multiprogrammable pacemakers and pacing modes. The aim of the present review is to address the different rate responsive pacing modalities presently available in respect to physiological situations and pathological conditions. Rate adaptive pacing has been shown to improve exercise capacity in patients with chronotropic incompetence. A number of activity and metabolic sensors have been proposed and used for rate control. However, all sensors used to optimize pacing rate metabolic demands show typical limitations. To overcome these weaknesses the use of two sensors has been proposed. Indeed an unspecific but fast reacting sensor is combined with a more specific but slower metabolic one. Clinical studies have demonstrated that this methodology is suitable to reproduce normal sinus behavior during different types and loads of exercise. Sensor combinations require adequate sensor blending and cross checking possibly controlled by automatic algorithms for sensors optimization and simplicity of programming. Assessment and possibly deactivation of some automatic functions should be also possible to maximize benefits from the dual sensor system in particular conditions. This is of special relevance in patient whose myocardial contractility is limited such as in subjects with implantable defibrillators and biventricular pacemakers. The concept of closed loop pacing, implementing a negative feedback relating pacing rate and the control signal, will provide new opportunities to optimize dual-sensors system and deserves further investigation. The integration of rate adaptive pacing into defibrillators is the natural consequence of technical evolution. PMID:16943981

Multi-Sensor Information Fusion for Optimizing Electric Bicycle Routes Using a Swarm Intelligence Algorithm

PubMed Central

Villarubia, Gabriel; De Paz, Juan F.; Bajo, Javier

2017-01-01

The use of electric bikes (e-bikes) has grown in popularity, especially in large cities where overcrowding and traffic congestion are common. This paper proposes an intelligent engine management system for e-bikes which uses the information collected from sensors to optimize battery energy and time. The intelligent engine management system consists of a built-in network of sensors in the e-bike, which is used for multi-sensor data fusion; the collected data is analysed and fused and on the basis of this information the system can provide the user with optimal and personalized assistance. The user is given recommendations related to battery consumption, sensors, and other parameters associated with the route travelled, such as duration, speed, or variation in altitude. To provide a user with these recommendations, artificial neural networks are used to estimate speed and consumption for each of the segments of a route. These estimates are incorporated into evolutionary algorithms in order to make the optimizations. A comparative analysis of the results obtained has been conducted for when routes were travelled with and without the optimization system. From the experiments, it is evident that the use of an engine management system results in significant energy and time savings. Moreover, user satisfaction increases as the level of assistance adapts to user behavior and the characteristics of the route. PMID:29088087

Multi-Sensor Information Fusion for Optimizing Electric Bicycle Routes Using a Swarm Intelligence Algorithm.

PubMed

De La Iglesia, Daniel H; Villarrubia, Gabriel; De Paz, Juan F; Bajo, Javier

2017-10-31

The use of electric bikes (e-bikes) has grown in popularity, especially in large cities where overcrowding and traffic congestion are common. This paper proposes an intelligent engine management system for e-bikes which uses the information collected from sensors to optimize battery energy and time. The intelligent engine management system consists of a built-in network of sensors in the e-bike, which is used for multi-sensor data fusion; the collected data is analysed and fused and on the basis of this information the system can provide the user with optimal and personalized assistance. The user is given recommendations related to battery consumption, sensors, and other parameters associated with the route travelled, such as duration, speed, or variation in altitude. To provide a user with these recommendations, artificial neural networks are used to estimate speed and consumption for each of the segments of a route. These estimates are incorporated into evolutionary algorithms in order to make the optimizations. A comparative analysis of the results obtained has been conducted for when routes were travelled with and without the optimization system. From the experiments, it is evident that the use of an engine management system results in significant energy and time savings. Moreover, user satisfaction increases as the level of assistance adapts to user behavior and the characteristics of the route.

Enhancement of the Wear Particle Monitoring Capability of Oil Debris Sensors Using a Maximal Overlap Discrete Wavelet Transform with Optimal Decomposition Depth

PubMed Central

Li, Chuan; Peng, Juan; Liang, Ming

2014-01-01

Oil debris sensors are effective tools to monitor wear particles in lubricants. For in situ applications, surrounding noise and vibration interferences often distort the oil debris signature of the sensor. Hence extracting oil debris signatures from sensor signals is a challenging task for wear particle monitoring. In this paper we employ the maximal overlap discrete wavelet transform (MODWT) with optimal decomposition depth to enhance the wear particle monitoring capability. The sensor signal is decomposed by the MODWT into different depths for detecting the wear particle existence. To extract the authentic particle signature with minimal distortion, the root mean square deviation of kurtosis value of the segmented signal residue is adopted as a criterion to obtain the optimal decomposition depth for the MODWT. The proposed approach is evaluated using both simulated and experimental wear particles. The results show that the present method can improve the oil debris monitoring capability without structural upgrade requirements. PMID:24686730

Enhancement of the wear particle monitoring capability of oil debris sensors using a maximal overlap discrete wavelet transform with optimal decomposition depth.

PubMed

Li, Chuan; Peng, Juan; Liang, Ming

2014-03-28

Oil debris sensors are effective tools to monitor wear particles in lubricants. For in situ applications, surrounding noise and vibration interferences often distort the oil debris signature of the sensor. Hence extracting oil debris signatures from sensor signals is a challenging task for wear particle monitoring. In this paper we employ the maximal overlap discrete wavelet transform (MODWT) with optimal decomposition depth to enhance the wear particle monitoring capability. The sensor signal is decomposed by the MODWT into different depths for detecting the wear particle existence. To extract the authentic particle signature with minimal distortion, the root mean square deviation of kurtosis value of the segmented signal residue is adopted as a criterion to obtain the optimal decomposition depth for the MODWT. The proposed approach is evaluated using both simulated and experimental wear particles. The results show that the present method can improve the oil debris monitoring capability without structural upgrade requirements.

A Parameter Communication Optimization Strategy for Distributed Machine Learning in Sensors

PubMed Central

Zhang, Jilin; Tu, Hangdi; Ren, Yongjian; Wan, Jian; Zhou, Li; Li, Mingwei; Wang, Jue; Yu, Lifeng; Zhao, Chang; Zhang, Lei

2017-01-01

In order to utilize the distributed characteristic of sensors, distributed machine learning has become the mainstream approach, but the different computing capability of sensors and network delays greatly influence the accuracy and the convergence rate of the machine learning model. Our paper describes a reasonable parameter communication optimization strategy to balance the training overhead and the communication overhead. We extend the fault tolerance of iterative-convergent machine learning algorithms and propose the Dynamic Finite Fault Tolerance (DFFT). Based on the DFFT, we implement a parameter communication optimization strategy for distributed machine learning, named Dynamic Synchronous Parallel Strategy (DSP), which uses the performance monitoring model to dynamically adjust the parameter synchronization strategy between worker nodes and the Parameter Server (PS). This strategy makes full use of the computing power of each sensor, ensures the accuracy of the machine learning model, and avoids the situation that the model training is disturbed by any tasks unrelated to the sensors. PMID:28934163

Sensitive zone parameters and curvature radius evaluation for polymer optical fiber curvature sensors

NASA Astrophysics Data System (ADS)

Leal-Junior, Arnaldo G.; Frizera, Anselmo; José Pontes, Maria

2018-03-01

Polymer optical fibers (POFs) are suitable for applications such as curvature sensors, strain, temperature, liquid level, among others. However, for enhancing sensitivity, many polymer optical fiber curvature sensors based on intensity variation require a lateral section. Lateral section length, depth, and surface roughness have great influence on the sensor sensitivity, hysteresis, and linearity. Moreover, the sensor curvature radius increase the stress on the fiber, which leads on variation of the sensor behavior. This paper presents the analysis relating the curvature radius and lateral section length, depth and surface roughness with the sensor sensitivity, hysteresis and linearity for a POF curvature sensor. Results show a strong correlation between the decision parameters behavior and the performance for sensor applications based on intensity variation. Furthermore, there is a trade-off among the sensitive zone length, depth, surface roughness, and curvature radius with the sensor desired performance parameters, which are minimum hysteresis, maximum sensitivity, and maximum linearity. The optimization of these parameters is applied to obtain a sensor with sensitivity of 20.9 mV/°, linearity of 0.9992 and hysteresis below 1%, which represent a better performance of the sensor when compared with the sensor without the optimization.

Optimal power allocation and joint source-channel coding for wireless DS-CDMA visual sensor networks

NASA Astrophysics Data System (ADS)

Pandremmenou, Katerina; Kondi, Lisimachos P.; Parsopoulos, Konstantinos E.

2011-01-01

In this paper, we propose a scheme for the optimal allocation of power, source coding rate, and channel coding rate for each of the nodes of a wireless Direct Sequence Code Division Multiple Access (DS-CDMA) visual sensor network. The optimization is quality-driven, i.e. the received quality of the video that is transmitted by the nodes is optimized. The scheme takes into account the fact that the sensor nodes may be imaging scenes with varying levels of motion. Nodes that image low-motion scenes will require a lower source coding rate, so they will be able to allocate a greater portion of the total available bit rate to channel coding. Stronger channel coding will mean that such nodes will be able to transmit at lower power. This will both increase battery life and reduce interference to other nodes. Two optimization criteria are considered. One that minimizes the average video distortion of the nodes and one that minimizes the maximum distortion among the nodes. The transmission powers are allowed to take continuous values, whereas the source and channel coding rates can assume only discrete values. Thus, the resulting optimization problem lies in the field of mixed-integer optimization tasks and is solved using Particle Swarm Optimization. Our experimental results show the importance of considering the characteristics of the video sequences when determining the transmission power, source coding rate and channel coding rate for the nodes of the visual sensor network.

A Fiber Bragg Grating Sensor for Radial Artery Pulse Waveform Measurement.

PubMed

Jia, Dagong; Chao, Jing; Li, Shuai; Zhang, Hongxia; Yan, Yingzhan; Liu, Tiegen; Sun, Ye

2018-04-01

In this paper, we report the design and experimental validation of a novel optical sensor for radial artery pulse measurement based on fiber Bragg grating (FBG) and lever amplification mechanism. Pulse waveform analysis is a diagnostic tool for clinical examination and disease diagnosis. High fidelity radial artery pulse waveform has been investigated in clinical studies for estimating central aortic pressure, which is proved to be predictors of cardiovascular diseases. As a three-dimensional cylinder, the radial artery needs to be examined from different locations to achieve optimal pulse waveform for estimation and diagnosis. The proposed optical sensing system is featured as high sensitivity and immunity to electromagnetic interference for multilocation radial artery pulse waveform measurement. The FBG sensor can achieve the sensitivity of 8.236 nm/N, which is comparable to a commonly used electrical sensor. This FBG-based system can provide high accurate measurement, and the key characteristic parameters can be then extracted from the raw signals for clinical applications. The detecting performance is validated through experiments guided by physicians. In the experimental validation, we applied this sensor to measure the pulse waveforms at various positions and depths of the radial artery in the wrist according to the diagnostic requirements. The results demonstrate the high feasibility of using optical systems for physiological measurement and using this FBG sensor for radial artery pulse waveform in clinical applications.

Experimental Robot Position Sensor Fault Tolerance Using Accelerometers and Joint Torque Sensors

NASA Technical Reports Server (NTRS)

Aldridge, Hal A.; Juang, Jer-Nan

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. The proposed method uses joint torque sensors found in most existing advanced robot designs along with easily locatable, lightweight accelerometers to provide a joint position sensor fault recovery mode. This mode uses the torque sensors along with a virtual passive control law for stability and accelerometers for joint position information. Two methods for conversion from Cartesian acceleration to joint position based on robot kinematics, not integration, are presented. The fault tolerant control method was tested on several joints of a laboratory robot. The controllers performed well with noisy, biased data and a model with uncertain parameters.

Radar coordination and resource management in a distributed sensor network using emergent control

NASA Astrophysics Data System (ADS)

Weir, B. S.; Sokol, T. M.

2009-05-01

As the list of anti-air warfare and ballistic missile defense missions grows, there is an increasing need to coordinate and optimize usage of radar resources across the netted force. Early attempts at this optimization involved top-down control mechanisms whereby sensors accept resource tasking orders from networked tracking elements. These approaches rely heavily on uncertain knowledge of sensor constraints and capabilities. Furthermore, advanced sensor systems may support self-defense missions of the host platform and are therefore unable to relinquish control to an external function. To surmount these issues, the use of bottom-up emergent control techniques is proposed. The information necessary to make quality, network-wide resource allocations is readily available to sensor nodes with access to a netted track picture. By assessing resource priorities relative to the network (versus local) track picture, sensors can understand the contribution of their resources to the netted force. This allows the sensors to apply resources where most needed and remove waste. Furthermore, simple local rules for resource usage, when properly constructed, allow sensors to obtain a globally optimal resource allocation without direct coordination (emergence). These results are robust to partial implementation (i.e., not all nodes upgraded at once) and failures on individual nodes (whether from casualty or reallocation to other sensor missions), and they leave resource control decisions in the hands of the sensor systems instead of an external function. This paper presents independent research and development work on emergent control of sensor resources and the impact to resource allocation and tracking performance.

Analysis of a Smartphone-Based Architecture with Multiple Mobility Sensors for Fall Detection with Supervised Learning

PubMed Central

Santoyo-Ramón, José Antonio

2018-01-01

This paper describes a wearable Fall Detection System (FDS) based on a body-area network consisting of four nodes provided with inertial sensors and Bluetooth wireless interfaces. The signals captured by the nodes are sent to a smartphone which simultaneously acts as another sensing point. In contrast to many FDSs proposed by the literature (which only consider a single sensor), the multisensory nature of the prototype is utilized to investigate the impact of the number and the positions of the sensors on the effectiveness of the production of the fall detection decision. In particular, the study assesses the capability of four popular machine learning algorithms to discriminate the dynamics of the Activities of Daily Living (ADLs) and falls generated by a set of experimental subjects, when the combined use of the sensors located on different parts of the body is considered. Prior to this, the election of the statistics that optimize the characterization of the acceleration signals and the efficacy of the FDS is also investigated. As another important methodological novelty in this field, the statistical significance of all the results (an aspect which is usually neglected by other works) is validated by an analysis of variance (ANOVA). PMID:29642638

Automatic development of normal zone in composite MgB2/CuNi wires with different diameters

NASA Astrophysics Data System (ADS)

Jokinen, A.; Kajikawa, K.; Takahashi, M.; Okada, M.

2010-06-01

One of the promising applications with superconducting technology for hydrogen utilization is a sensor with a magnesium-diboride (MgB2) superconductor to detect the position of boundary between the liquid hydrogen and the evaporated gas stored in a Dewar vessel. In our previous experiment for the level sensor, the normal zone has been automatically developed and therefore any energy input with the heater has not been required for normal operation. Although the physical mechanism for such a property of the MgB2 wire has not been clarified yet, the deliberate application might lead to the realization of a simpler superconducting level sensor without heater system. In the present study, the automatic development of normal zone with increasing a transport current is evaluated for samples consisting of three kinds of MgB2 wires with CuNi sheath and different diameters immersed in liquid helium. The influences of the repeats of current excitation and heat cycle on the normal zone development are discussed experimentally. The aim of this paper is to confirm the suitability of MgB2 wire in a heater free level sensor application. This could lead to even more optimized design of the liquid hydrogen level sensor and the removal of extra heater input.

Wearable Textile Platform for Assessing Stroke Patient Treatment in Daily Life Conditions

PubMed Central

Lorussi, Federico; Carbonaro, Nicola; De Rossi, Danilo; Paradiso, Rita; Veltink, Peter; Tognetti, Alessandro

2016-01-01

Monitoring physical activities during post-stroke rehabilitation in daily life may help physicians to optimize and tailor the training program for patients. The European research project INTERACTION (FP7-ICT-2011-7-287351) evaluated motor capabilities in stroke patients during the recovery treatment period. We developed wearable sensing platform based on the sensor fusion among inertial, knitted piezoresistive sensors and textile EMG electrodes. The device was conceived in modular form and consists of a separate shirt, trousers, glove, and shoe. Thanks to the novel fusion approach it has been possible to develop a model for the shoulder taking into account the scapulo-thoracic joint of the scapular girdle, considerably improving the estimation of the hand position in reaching activities. In order to minimize the sensor set used to monitor gait, a single inertial sensor fused with a textile goniometer proved to reconstruct the orientation of all the body segments of the leg. Finally, the sensing glove, endowed with three textile goniometers and three force sensors showed good capabilities in the reconstruction of grasping activities and evaluating the interaction of the hand with the environment, according to the project specifications. This paper reports on the design and the technical evaluation of the performance of the sensing platform, tested on healthy subjects. PMID:27047939

A three-axis force sensor for dual finger haptic interfaces.

PubMed

Fontana, Marco; Marcheschi, Simone; Salsedo, Fabio; Bergamasco, Massimo

2012-10-10

In this work we present the design process, the characterization and testing of a novel three-axis mechanical force sensor. This sensor is optimized for use in closed-loop force control of haptic devices with three degrees of freedom. In particular the sensor has been conceived for integration with a dual finger haptic interface that aims at simulating forces that occur during grasping and surface exploration. The sensing spring structure has been purposely designed in order to match force and layout specifications for the application. In this paper the design of the sensor is presented, starting from an analytic model that describes the characteristic matrix of the sensor. A procedure for designing an optimal overload protection mechanism is proposed. In the last part of the paper the authors describe the experimental characterization and the integrated test on a haptic hand exoskeleton showing the improvements in the controller performances provided by the inclusion of the force sensor.

A Two-Phase Time Synchronization-Free Localization Algorithm for Underwater Sensor Networks.

PubMed

Luo, Junhai; Fan, Liying

2017-03-30

Underwater Sensor Networks (UWSNs) can enable a broad range of applications such as resource monitoring, disaster prevention, and navigation-assistance. Sensor nodes location in UWSNs is an especially relevant topic. Global Positioning System (GPS) information is not suitable for use in UWSNs because of the underwater propagation problems. Hence, some localization algorithms based on the precise time synchronization between sensor nodes that have been proposed for UWSNs are not feasible. In this paper, we propose a localization algorithm called Two-Phase Time Synchronization-Free Localization Algorithm (TP-TSFLA). TP-TSFLA contains two phases, namely, range-based estimation phase and range-free evaluation phase. In the first phase, we address a time synchronization-free localization scheme based on the Particle Swarm Optimization (PSO) algorithm to obtain the coordinates of the unknown sensor nodes. In the second phase, we propose a Circle-based Range-Free Localization Algorithm (CRFLA) to locate the unlocalized sensor nodes which cannot obtain the location information through the first phase. In the second phase, sensor nodes which are localized in the first phase act as the new anchor nodes to help realize localization. Hence, in this algorithm, we use a small number of mobile beacons to help obtain the location information without any other anchor nodes. Besides, to improve the precision of the range-free method, an extension of CRFLA achieved by designing a coordinate adjustment scheme is updated. The simulation results show that TP-TSFLA can achieve a relative high localization ratio without time synchronization.

A Two-Phase Time Synchronization-Free Localization Algorithm for Underwater Sensor Networks

PubMed Central

Luo, Junhai; Fan, Liying

2017-01-01

Underwater Sensor Networks (UWSNs) can enable a broad range of applications such as resource monitoring, disaster prevention, and navigation-assistance. Sensor nodes location in UWSNs is an especially relevant topic. Global Positioning System (GPS) information is not suitable for use in UWSNs because of the underwater propagation problems. Hence, some localization algorithms based on the precise time synchronization between sensor nodes that have been proposed for UWSNs are not feasible. In this paper, we propose a localization algorithm called Two-Phase Time Synchronization-Free Localization Algorithm (TP-TSFLA). TP-TSFLA contains two phases, namely, range-based estimation phase and range-free evaluation phase. In the first phase, we address a time synchronization-free localization scheme based on the Particle Swarm Optimization (PSO) algorithm to obtain the coordinates of the unknown sensor nodes. In the second phase, we propose a Circle-based Range-Free Localization Algorithm (CRFLA) to locate the unlocalized sensor nodes which cannot obtain the location information through the first phase. In the second phase, sensor nodes which are localized in the first phase act as the new anchor nodes to help realize localization. Hence, in this algorithm, we use a small number of mobile beacons to help obtain the location information without any other anchor nodes. Besides, to improve the precision of the range-free method, an extension of CRFLA achieved by designing a coordinate adjustment scheme is updated. The simulation results show that TP-TSFLA can achieve a relative high localization ratio without time synchronization. PMID:28358342

Robust electromagnetically guided endoscopic procedure using enhanced particle swarm optimization for multimodal information fusion

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

Luo, Xiongbiao, E-mail: xluo@robarts.ca, E-mail: Ying.Wan@student.uts.edu.au; Wan, Ying, E-mail: xluo@robarts.ca, E-mail: Ying.Wan@student.uts.edu.au; He, Xiangjian

Purpose: Electromagnetically guided endoscopic procedure, which aims at accurately and robustly localizing the endoscope, involves multimodal sensory information during interventions. However, it still remains challenging in how to integrate these information for precise and stable endoscopic guidance. To tackle such a challenge, this paper proposes a new framework on the basis of an enhanced particle swarm optimization method to effectively fuse these information for accurate and continuous endoscope localization. Methods: The authors use the particle swarm optimization method, which is one of stochastic evolutionary computation algorithms, to effectively fuse the multimodal information including preoperative information (i.e., computed tomography images) asmore » a frame of reference, endoscopic camera videos, and positional sensor measurements (i.e., electromagnetic sensor outputs). Since the evolutionary computation method usually limits its possible premature convergence and evolutionary factors, the authors introduce the current (endoscopic camera and electromagnetic sensor’s) observation to boost the particle swarm optimization and also adaptively update evolutionary parameters in accordance with spatial constraints and the current observation, resulting in advantageous performance in the enhanced algorithm. Results: The experimental results demonstrate that the authors’ proposed method provides a more accurate and robust endoscopic guidance framework than state-of-the-art methods. The average guidance accuracy of the authors’ framework was about 3.0 mm and 5.6° while the previous methods show at least 3.9 mm and 7.0°. The average position and orientation smoothness of their method was 1.0 mm and 1.6°, which is significantly better than the other methods at least with (2.0 mm and 2.6°). Additionally, the average visual quality of the endoscopic guidance was improved to 0.29. Conclusions: A robust electromagnetically guided endoscopy framework was proposed on the basis of an enhanced particle swarm optimization method with using the current observation information and adaptive evolutionary factors. The authors proposed framework greatly reduced the guidance errors from (4.3, 7.8) to (3.0 mm, 5.6°), compared to state-of-the-art methods.« less

On the Design of Smart Parking Networks in the Smart Cities: An Optimal Sensor Placement Model

PubMed Central

Bagula, Antoine; Castelli, Lorenzo; Zennaro, Marco

2015-01-01

Smart parking is a typical IoT application that can benefit from advances in sensor, actuator and RFID technologies to provide many services to its users and parking owners of a smart city. This paper considers a smart parking infrastructure where sensors are laid down on the parking spots to detect car presence and RFID readers are embedded into parking gates to identify cars and help in the billing of the smart parking. Both types of devices are endowed with wired and wireless communication capabilities for reporting to a gateway where the situation recognition is performed. The sensor devices are tasked to play one of the three roles: (1) slave sensor nodes located on the parking spot to detect car presence/absence; (2) master nodes located at one of the edges of a parking lot to detect presence and collect the sensor readings from the slave nodes; and (3) repeater sensor nodes, also called “anchor” nodes, located strategically at specific locations in the parking lot to increase the coverage and connectivity of the wireless sensor network. While slave and master nodes are placed based on geographic constraints, the optimal placement of the relay/anchor sensor nodes in smart parking is an important parameter upon which the cost and efficiency of the parking system depends. We formulate the optimal placement of sensors in smart parking as an integer linear programming multi-objective problem optimizing the sensor network engineering efficiency in terms of coverage and lifetime maximization, as well as its economic gain in terms of the number of sensors deployed for a specific coverage and lifetime. We propose an exact solution to the node placement problem using single-step and two-step solutions implemented in the Mosel language based on the Xpress-MPsuite of libraries. Experimental results reveal the relative efficiency of the single-step compared to the two-step model on different performance parameters. These results are consolidated by simulation results, which reveal that our solution outperforms a random placement in terms of both energy consumption, delay and throughput achieved by a smart parking network. PMID:26134104

On the Design of Smart Parking Networks in the Smart Cities: An Optimal Sensor Placement Model.

PubMed

Bagula, Antoine; Castelli, Lorenzo; Zennaro, Marco

2015-06-30

Smart parking is a typical IoT application that can benefit from advances in sensor, actuator and RFID technologies to provide many services to its users and parking owners of a smart city. This paper considers a smart parking infrastructure where sensors are laid down on the parking spots to detect car presence and RFID readers are embedded into parking gates to identify cars and help in the billing of the smart parking. Both types of devices are endowed with wired and wireless communication capabilities for reporting to a gateway where the situation recognition is performed. The sensor devices are tasked to play one of the three roles: (1) slave sensor nodes located on the parking spot to detect car presence/absence; (2) master nodes located at one of the edges of a parking lot to detect presence and collect the sensor readings from the slave nodes; and (3) repeater sensor nodes, also called "anchor" nodes, located strategically at specific locations in the parking lot to increase the coverage and connectivity of the wireless sensor network. While slave and master nodes are placed based on geographic constraints, the optimal placement of the relay/anchor sensor nodes in smart parking is an important parameter upon which the cost and efficiency of the parking system depends. We formulate the optimal placement of sensors in smart parking as an integer linear programming multi-objective problem optimizing the sensor network engineering efficiency in terms of coverage and lifetime maximization, as well as its economic gain in terms of the number of sensors deployed for a specific coverage and lifetime. We propose an exact solution to the node placement problem using single-step and two-step solutions implemented in the Mosel language based on the Xpress-MPsuite of libraries. Experimental results reveal the relative efficiency of the single-step compared to the two-step model on different performance parameters. These results are consolidated by simulation results, which reveal that our solution outperforms a random placement in terms of both energy consumption, delay and throughput achieved by a smart parking network.

Position Sensor with Integrated Signal-Conditioning Electronics on a Printed Wiring Board

NASA Technical Reports Server (NTRS)

Alhorn, Dean C. (Inventor); Howard, David E. (Inventor); Smith, Dennis A. (Inventor)

2001-01-01

A position sensor, such as a rotary position sensor, includes the signal-conditioning electronics in the housing. The signal-conditioning electronics are disposed on a printed wiring board, which is assembled with another printed wiring board including the sensor windings to provide a sub-assembly. A mu-metal shield is interposed between the printed wiring boards to prevent magnetic interference. The sub-assembly is disposed in the sensor housing adjacent to an inductor board which turns on a shaft. The inductor board emanates an internally or externally generated excitation signal that induces a signal in the sensor windings. The induced signal represents the rotary position of the inductor board relative to the sensor winding board.

Evaluation and Improvement of Eddy Current Position Sensors in Magnetically Suspended Flywheel Systems

NASA Technical Reports Server (NTRS)

Dever, Timothy P.; Palazzolo, Alan B.; Thomas, Erwin M., III; Jansen, Ralph H.; McLallin, Kerry (Technical Monitor); Soeder, James (Technical Monitor)

2001-01-01

Eddy current position sensor performance is evaluated for use in a high-speed flywheel development system. The flywheel utilizes a five axis active magnetic bearing system. The eddy current sensors are used for position feedback for the bearing controller. Measured characteristics include sensitivity to multiple target materials and susceptibility to noise from the magnetic bearings and from sensor-to-sensor crosstalk. Improvements in axial sensor configuration and techniques for noise reduction are described.

Optimization of the coplanar interdigital capacitive sensor

NASA Astrophysics Data System (ADS)

Huang, Yunzhi; Zhan, Zheng; Bowler, Nicola

2017-02-01

Interdigital capacitive sensors are applied in nondestructive testing and material property characterization of low-conductivity materials. The sensor performance is typically described based on the penetration depth of the electric field into the sample material, the sensor signal strength and its sensitivity. These factors all depend on the geometry and material properties of the sensor and sample. In this paper, a detailed analysis is provided, through finite element simulations, of the ways in which the sensor's geometrical parameters affect its performance. The geometrical parameters include the number of digits forming the interdigital electrodes and the ratio of digit width to their separation. In addition, the influence of the presence or absence of a metal backplane on the sample is analyzed. Further, the effects of sensor substrate thickness and material on signal strength are studied. The results of the analysis show that it is necessary to take into account a trade-off between the desired sensitivity and penetration depth when designing the sensor. Parametric equations are presented to assist the sensor designer or nondestructive evaluation specialist in optimizing the design of a capacitive sensor.

Electronic Position Sensor for Power Operated Accessory

DOEpatents

Haag, Ronald H.; Chia, Michael I.

2005-05-31

An electronic position sensor for use with a power operated vehicle accessory, such as a power liftgate. The position sensor includes an elongated resistive circuit that is mounted such that it is stationary and extends along the path of a track portion of the power operated accessory. The position sensor further includes a contact nub mounted to a link member that moves within the track portion such that the contact nub is slidingly biased against the elongated circuit. As the link member moves under the force of a motor-driven output gear, the contact nub slides along the surface of the resistive circuit, thereby affecting the overall resistance of the circuit. The position sensor uses the overall resistance to provide an electronic position signal to an ECU, wherein the signal is indicative of the absolute position of the power operated accessory. Accordingly, the electronic position sensor is capable of providing an electronic signal that enables the ECU to track the absolute position of the power operated accessory.

Comparing position and orientation accuracy of different electromagnetic sensors for tracking during interventions.

PubMed

Nijkamp, Jasper; Schermers, Bram; Schmitz, Sander; de Jonge, Sofieke; Kuhlmann, Koert; van der Heijden, Ferdinand; Sonke, Jan-Jakob; Ruers, Theo

2016-08-01

To compare the position and orientation accuracy between using one 6-degree of freedom (DOF) electromagnetic (EM) sensor, or the position information of three 5DOF sensors within the scope of tumor tracking. The position accuracy of Northern Digital Inc Aurora 5DOF and 6DOF sensors was determined for a table-top field generator (TTFG) up to a distance of 52 cm. For each sensor 716 positions were measured for 10 s at 15 Hz. Orientation accuracy was determined for each of the orthogonal axis at the TTFG distances of 17, 27, 37 and 47 cm. For the 6DOF sensors, orientation was determined for sensors in-line with the orientation axis, and perpendicular. 5DOF orientation accuracy was determined for a theoretical 4 cm tumor. An optical tracking system was used as reference. Position RMSE and jitter were comparable between the sensors and increasing with distance. Jitter was within 0.1 cm SD within 45 cm distance to the TTFG. Position RMSE was approximately 0.1 cm up to 32 cm distance, increasing to 0.4 cm at 52 cm distance. Orientation accuracy of the 6DOF sensor was within 1[Formula: see text], except when the sensor was in-line with the rotation axis perpendicular to the TTFG plane (4[Formula: see text] errors at 47 cm). Orientation accuracy using 5DOF positions was within 1[Formula: see text] up to 37 cm and 2[Formula: see text] at 47 cm. The position and orientation accuracy of a 6DOF sensor was comparable with a sensor configuration consisting of three 5DOF sensors. To achieve tracking accuracy within 1 mm and 1[Formula: see text], the distance to the TTFG should be limited to approximately 30 cm.

Adaptive torque estimation of robot joint with harmonic drive transmission

NASA Astrophysics Data System (ADS)

Shi, Zhiguo; Li, Yuankai; Liu, Guangjun

2017-11-01

Robot joint torque estimation using input and output position measurements is a promising technique, but the result may be affected by the load variation of the joint. In this paper, a torque estimation method with adaptive robustness and optimality adjustment according to load variation is proposed for robot joint with harmonic drive transmission. Based on a harmonic drive model and a redundant adaptive robust Kalman filter (RARKF), the proposed approach can adapt torque estimation filtering optimality and robustness to the load variation by self-tuning the filtering gain and self-switching the filtering mode between optimal and robust. The redundant factor of RARKF is designed as a function of the motor current for tolerating the modeling error and load-dependent filtering mode switching. The proposed joint torque estimation method has been experimentally studied in comparison with a commercial torque sensor and two representative filtering methods. The results have demonstrated the effectiveness of the proposed torque estimation technique.

Wireless sensor placement for structural monitoring using information-fusing firefly algorithm

NASA Astrophysics Data System (ADS)

Zhou, Guang-Dong; Yi, Ting-Hua; Xie, Mei-Xi; Li, Hong-Nan

2017-10-01

Wireless sensor networks (WSNs) are promising technology in structural health monitoring (SHM) applications for their low cost and high efficiency. The limited wireless sensors and restricted power resources in WSNs highlight the significance of optimal wireless sensor placement (OWSP) during designing SHM systems to enable the most useful information to be captured and to achieve the longest network lifetime. This paper presents a holistic approach, including an optimization criterion and a solution algorithm, for optimally deploying self-organizing multi-hop WSNs on large-scale structures. The combination of information effectiveness represented by the modal independence and the network performance specified by the network connectivity and network lifetime is first formulated to evaluate the performance of wireless sensor configurations. Then, an information-fusing firefly algorithm (IFFA) is developed to solve the OWSP problem. The step sizes drawn from a Lévy distribution are adopted to drive fireflies toward brighter individuals. Following the movement with Lévy flights, information about the contributions of wireless sensors to the objective function as carried by the fireflies is fused and applied to move inferior wireless sensors to better locations. The reliability of the proposed approach is verified via a numerical example on a long-span suspension bridge. The results demonstrate that the evaluation criterion provides a good performance metric of wireless sensor configurations, and the IFFA outperforms the simple discrete firefly algorithm.

Optimization and validation of highly selective microfluidic integrated silicon nanowire chemical sensor

NASA Astrophysics Data System (ADS)

Ehfaed, Nuri. A. K. H.; Bathmanathan, Shillan A. L.; Dhahi, Th S.; Adam, Tijjani; Hashim, Uda; Noriman, N. Z.

2017-09-01

The study proposed characterization and optimization of silicon nanosensor for specific detection of heavy metal. The sensor was fabricated in-house and conventional photolithography coupled with size reduction via dry etching process in an oxidation furnace. Prior to heavy metal heavy metal detection, the capability to aqueous sample was determined utilizing serial DI water at various. The sensor surface was surface modified with Organofunctional alkoxysilanes (3-aminopropyl) triethoxysilane (APTES) to create molecular binding chemistry. This has allowed interaction between heavy metals being measured and the sensor component resulting in increasing the current being measured. Due to its, excellent detection capabilities, this sensor was able to identify different group heavy metal species. The device was further integrated with sub-50 µm for chemical delivery.

Temperature-programmed technique accompanied with high-throughput methodology for rapidly searching the optimal operating temperature of MOX gas sensors.

PubMed

Zhang, Guozhu; Xie, Changsheng; Zhang, Shunping; Zhao, Jianwei; Lei, Tao; Zeng, Dawen

2014-09-08

A combinatorial high-throughput temperature-programmed method to obtain the optimal operating temperature (OOT) of gas sensor materials is demonstrated here for the first time. A material library consisting of SnO2, ZnO, WO3, and In2O3 sensor films was fabricated by screen printing. Temperature-dependent conductivity curves were obtained by scanning this gas sensor library from 300 to 700 K in different atmospheres (dry air, formaldehyde, carbon monoxide, nitrogen dioxide, toluene and ammonia), giving the OOT of each sensor formulation as a function of the carrier and analyte gases. A comparative study of the temperature-programmed method and a conventional method showed good agreement in measured OOT.

Desensitized Optimal Filtering and Sensor Fusion Toolkit

NASA Technical Reports Server (NTRS)

Karlgaard, Christopher D.

2015-01-01

Analytical Mechanics Associates, Inc., has developed a software toolkit that filters and processes navigational data from multiple sensor sources. A key component of the toolkit is a trajectory optimization technique that reduces the sensitivity of Kalman filters with respect to model parameter uncertainties. The sensor fusion toolkit also integrates recent advances in adaptive Kalman and sigma-point filters for non-Gaussian problems with error statistics. This Phase II effort provides new filtering and sensor fusion techniques in a convenient package that can be used as a stand-alone application for ground support and/or onboard use. Its modular architecture enables ready integration with existing tools. A suite of sensor models and noise distribution as well as Monte Carlo analysis capability are included to enable statistical performance evaluations.

Review of fall risk assessment in geriatric populations using inertial sensors

PubMed Central

2013-01-01

Background Falls are a prevalent issue in the geriatric population and can result in damaging physical and psychological consequences. Fall risk assessment can provide information to enable appropriate interventions for those at risk of falling. Wearable inertial-sensor-based systems can provide quantitative measures indicative of fall risk in the geriatric population. Methods Forty studies that used inertial sensors to evaluate geriatric fall risk were reviewed and pertinent methodological features were extracted; including, sensor placement, derived parameters used to assess fall risk, fall risk classification method, and fall risk classification model outcomes. Results Inertial sensors were placed only on the lower back in the majority of papers (65%). One hundred and thirty distinct variables were assessed, which were categorized as position and angle (7.7%), angular velocity (11.5%), linear acceleration (20%), spatial (3.8%), temporal (23.1%), energy (3.8%), frequency (15.4%), and other (14.6%). Fallers were classified using retrospective fall history (30%), prospective fall occurrence (15%), and clinical assessment (32.5%), with 22.5% using a combination of retrospective fall occurrence and clinical assessments. Half of the studies derived models for fall risk prediction, which reached high levels of accuracy (62-100%), specificity (35-100%), and sensitivity (55-99%). Conclusions Inertial sensors are promising sensors for fall risk assessment. Future studies should identify fallers using prospective techniques and focus on determining the most promising sensor sites, in conjunction with determination of optimally predictive variables. Further research should also attempt to link predictive variables to specific fall risk factors and investigate disease populations that are at high risk of falls. PMID:23927446

Research Trends in Wireless Visual Sensor Networks When Exploiting Prioritization

PubMed Central

Costa, Daniel G.; Guedes, Luiz Affonso; Vasques, Francisco; Portugal, Paulo

2015-01-01

The development of wireless sensor networks for control and monitoring functions has created a vibrant investigation scenario, where many critical topics, such as communication efficiency and energy consumption, have been investigated in the past few years. However, when sensors are endowed with low-power cameras for visual monitoring, a new scope of challenges is raised, demanding new research efforts. In this context, the resource-constrained nature of sensor nodes has demanded the use of prioritization approaches as a practical mechanism to lower the transmission burden of visual data over wireless sensor networks. Many works in recent years have considered local-level prioritization parameters to enhance the overall performance of those networks, but global-level policies can potentially achieve better results in terms of visual monitoring efficiency. In this paper, we make a broad review of some recent works on priority-based optimizations in wireless visual sensor networks. Moreover, we envisage some research trends when exploiting prioritization, potentially fostering the development of promising optimizations for wireless sensor networks composed of visual sensors. PMID:25599425

Engineering New Aptamer Geometries for Electrochemical Aptamer-Based Sensors

PubMed Central

White, Ryan J.; Plaxco, Kevin W.

2010-01-01

Electrochemical aptamer-based sensors (E-AB sensors) represent a promising new approach to the detection of small molecules. E-AB sensors comprise an aptamer that is attached at one end to an electrode surface. The distal end of the aptamer probed is modified with an electroactive redox marker for signal transduction. Herein we report on the optimization of a cocaine-detecting E-AB sensor via optimization of the geometry of the aptamer. We explore two new aptamer architectures, one in which we concatenate three cocaine aptamers into a poly-aptamer and a second in which we divide the cocaine aptamer into pieces connected via an unstructured, 60-thymine linker. Both of these structures are designed such that the reporting redox tag will be located farther from the electrode in the unfolded, target-free conformation. Consistent with this, we find that signal gains of these two constructs are two to three times higher than that of the original E-AB architecture. Likewise all three architectures are selective enough to deploy directly in complex sample matrices, such as undiluted whole blood, with all three sensors successfully detecting the presence of cocaine. The findings in this ongoing study should be of value in future efforts to optimize the signaling of electrochemical aptamer-based sensors. PMID:20436792

Tier-scalable reconnaissance: the challenge of sensor optimization, sensor deployment, sensor fusion, and sensor interoperability

NASA Astrophysics Data System (ADS)

Fink, Wolfgang; George, Thomas; Tarbell, Mark A.

2007-04-01

Robotic reconnaissance operations are called for in extreme environments, not only those such as space, including planetary atmospheres, surfaces, and subsurfaces, but also in potentially hazardous or inaccessible operational areas on Earth, such as mine fields, battlefield environments, enemy occupied territories, terrorist infiltrated environments, or areas that have been exposed to biochemical agents or radiation. Real time reconnaissance enables the identification and characterization of transient events. A fundamentally new mission concept for tier-scalable reconnaissance of operational areas, originated by Fink et al., is aimed at replacing the engineering and safety constrained mission designs of the past. The tier-scalable paradigm integrates multi-tier (orbit atmosphere surface/subsurface) and multi-agent (satellite UAV/blimp surface/subsurface sensing platforms) hierarchical mission architectures, introducing not only mission redundancy and safety, but also enabling and optimizing intelligent, less constrained, and distributed reconnaissance in real time. Given the mass, size, and power constraints faced by such a multi-platform approach, this is an ideal application scenario for a diverse set of MEMS sensors. To support such mission architectures, a high degree of operational autonomy is required. Essential elements of such operational autonomy are: (1) automatic mapping of an operational area from different vantage points (including vehicle health monitoring); (2) automatic feature extraction and target/region-of-interest identification within the mapped operational area; and (3) automatic target prioritization for close-up examination. These requirements imply the optimal deployment of MEMS sensors and sensor platforms, sensor fusion, and sensor interoperability.

System Wide Joint Position Sensor Fault Tolerance in Robot Systems Using Cartesian Accelerometers

NASA Technical Reports Server (NTRS)

Aldridge, Hal A.; Juang, Jer-Nan

1997-01-01

Joint position sensors are necessary for most robot control systems. A single position sensor failure in a normal robot system can greatly degrade performance. This paper presents a method to obtain position information from Cartesian accelerometers without integration. Depending on the number and location of the accelerometers. the proposed system can tolerate the loss of multiple position sensors. A solution technique suitable for real-time implementation is presented. Simulations were conducted using 5 triaxial accelerometers to recover from the loss of up to 4 joint position sensors on a 7 degree of freedom robot moving in general three dimensional space. The simulations show good estimation performance using non-ideal accelerometer measurements.

Patient positioning using artificial intelligence neural networks, trained magnetic field sensors and magnetic implants.

PubMed

Lennernäs, B; Edgren, M; Nilsson, S

1999-01-01

The purpose of this study was to evaluate the precision of a sensor and to ascertain the maximum distance between the sensor and the magnet, in a magnetic positioning system for external beam radiotherapy using a trained artificial intelligence neural network for position determination. Magnetic positioning for radiotherapy, previously described by Lennernäs and Nilsson, is a functional technique, but it is time consuming. The sensors are large and the distance between the sensor and the magnetic implant is limited to short distances. This paper presents a new technique for positioning, using an artificial intelligence neural network, which was trained to position the magnetic implant with at least 0.5 mm resolution in X and Y dimensions. The possibility of using the system for determination in the Z dimension, that is the distance between the magnet and the sensor, was also investigated. After training, this system positioned the magnet with a mean error of maximum 0.15 mm in all dimensions and up to 13 mm from the sensor. Of 400 test positions, 8 determinations had an error larger than 0.5 mm, maximum 0.55 mm. A position was determined in approximately 0.01 s.

Coupled sensor/platform control design for low-level chemical detection with position-adaptive micro-UAVs

NASA Astrophysics Data System (ADS)

Goodwin, Thomas; Carr, Ryan; Mitra, Atindra K.; Selmic, Rastko R.

2009-05-01

We discuss the development of Position-Adaptive Sensors [1] for purposes for detecting embedded chemical substances in challenging environments. This concept is a generalization of patented Position-Adaptive Radar Concepts developed at AFRL for challenging conditions such as urban environments. For purposes of investigating the detection of chemical substances using multiple MAV (Micro-UAV) platforms, we have designed and implemented an experimental testbed with sample structures such as wooden carts that contain controlled leakage points. Under this general concept, some of the members of a MAV swarm can serve as external position-adaptive "transmitters" by blowing air over the cart and some of the members of a MAV swarm can serve as external position-adaptive "receivers" that are equipped with chemical or biological (chem/bio) sensors that function as "electronic noses". The objective can be defined as improving the particle count of chem/bio concentrations that impinge on a MAV-based position-adaptive sensor that surrounds a chemical repository, such as a cart, via the development of intelligent position-adaptive control algorithms. The overall effect is to improve the detection and false-alarm statistics of the overall system. Within the major sections of this paper, we discuss a number of different aspects of developing our initial MAV-Based Sensor Testbed. This testbed includes blowers to simulate position-adaptive excitations and a MAV from Draganfly Innovations Inc. with stable design modifications to accommodate our chem/bio sensor boom design. We include details with respect to several critical phases of the development effort including development of the wireless sensor network and experimental apparatus, development of the stable sensor boom for the MAV, integration of chem/bio sensors and sensor node onto the MAV and boom, development of position-adaptive control algorithms and initial tests at IDCAST (Institute for the Development and Commercialization of Advanced Sensor Technologies), and autonomous positionadaptive chem/bio tests and demos in the MAV Lab at AFRL Air Vehicles Directorate. For this particular MAV implementation of chem/bio sensors, we selected miniature Methane, Nitrogen Dioxide, and Carbon Monoxide sensors. To safely simulate the behavior of chem/bio substances in our laboratory environment, we used either cigarette smoke or incense. We present a set of concise parametric results along with visual demonstration of our new position-adaptive sensor capability. Two types of experiments were conducted: with sensor nodes screening the chemical contaminant (cigarette smoke or incense) without MAVs, and with a sensor node integrated with the MAV. It was shown that the MOS-based chemical sensors could be used for chemical leakage detection, as well as for position-adaptive sensors on air/ground vehicles as sniffers for chemical contaminants.

Heimdall System for MSSS Sensor Tasking

NASA Astrophysics Data System (ADS)

Herz, A.; Jones, B.; Herz, E.; George, D.; Axelrad, P.; Gehly, S.

In Norse Mythology, Heimdall uses his foreknowledge and keen eyesight to keep watch for disaster from his home near the Rainbow Bridge. Orbit Logic and the Colorado Center for Astrodynamics Research (CCAR) at the University of Colorado (CU) have developed the Heimdall System to schedule observations of known and uncharacterized objects and search for new objects from the Maui Space Surveillance Site. Heimdall addresses the current need for automated and optimized SSA sensor tasking driven by factors associated with improved space object catalog maintenance. Orbit Logic and CU developed an initial baseline prototype SSA sensor tasking capability for select sensors at the Maui Space Surveillance Site (MSSS) using STK and STK Scheduler, and then added a new Track Prioritization Component for FiSST-inspired computations for predicted Information Gain and Probability of Detection, and a new SSA-specific Figure-of-Merit (FOM) for optimized SSA sensor tasking. While the baseline prototype addresses automation and some of the multi-sensor tasking optimization, the SSA-improved prototype addresses all of the key elements required for improved tasking leading to enhanced object catalog maintenance. The Heimdall proof-of-concept was demonstrated for MSSS SSA sensor tasking for a 24 hour period to attempt observations of all operational satellites in the unclassified NORAD catalog, observe a small set of high priority GEO targets every 30 minutes, make a sky survey of the GEO belt region accessible to MSSS sensors, and observe particular GEO regions that have a high probability of finding new objects with any excess sensor time. This Heimdall prototype software paves the way for further R&D that will integrate this technology into the MSSS systems for operational scheduling, improve the software's scalability, and further tune and enhance schedule optimization. The Heimdall software for SSA sensor tasking provides greatly improved performance over manual tasking, improved coordinated sensor usage, and tasking schedules driven by catalog improvement goals (reduced overall covariance, etc.). The improved performance also enables more responsive sensor tasking to address external events, newly detected objects, newly detected object activity, and sensor anomalies. Instead of having to wait until the next day's scheduling phase, events can be addressed with new tasking schedules immediately (within seconds or minutes). Perhaps the most important benefit is improved SSA based on an overall improvement to the quality of the space catalog. By driving sensor tasking and scheduling based on predicted Information Gain and other relevant factors, better decisions are made in the application of available sensor resources, leading to an improved catalog and better information about the objects of most interest. The Heimdall software solution provides a configurable, automated system to improve sensor tasking efficiency and responsiveness for SSA applications. The FISST algorithms for Track Prioritization, SSA specific task and resource attributes, Scheduler algorithms, and configurable SSA-specific Figure-of-Merit together provide optimized and tunable scheduling for the Maui Space Surveillance Site and possibly other sites and organizations across the U.S. military and for allies around the world.

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.

Magnetic localization and orientation of the capsule endoscope based on a random complex algorithm.

PubMed

He, Xiaoqi; Zheng, Zizhao; Hu, Chao

2015-01-01

The development of the capsule endoscope has made possible the examination of the whole gastrointestinal tract without much pain. However, there are still some important problems to be solved, among which, one important problem is the localization of the capsule. Currently, magnetic positioning technology is a suitable method for capsule localization, and this depends on a reliable system and algorithm. In this paper, based on the magnetic dipole model as well as magnetic sensor array, we propose nonlinear optimization algorithms using a random complex algorithm, applied to the optimization calculation for the nonlinear function of the dipole, to determine the three-dimensional position parameters and two-dimensional direction parameters. The stability and the antinoise ability of the algorithm is compared with the Levenberg-Marquart algorithm. The simulation and experiment results show that in terms of the error level of the initial guess of magnet location, the random complex algorithm is more accurate, more stable, and has a higher "denoise" capacity, with a larger range for initial guess values.

Features Extraction of Flotation Froth Images and BP Neural Network Soft-Sensor Model of Concentrate Grade Optimized by Shuffled Cuckoo Searching Algorithm

PubMed Central

Wang, Jie-sheng; Han, Shuang; Shen, Na-na; Li, Shu-xia

2014-01-01

For meeting the forecasting target of key technology indicators in the flotation process, a BP neural network soft-sensor model based on features extraction of flotation froth images and optimized by shuffled cuckoo search algorithm is proposed. Based on the digital image processing technique, the color features in HSI color space, the visual features based on the gray level cooccurrence matrix, and the shape characteristics based on the geometric theory of flotation froth images are extracted, respectively, as the input variables of the proposed soft-sensor model. Then the isometric mapping method is used to reduce the input dimension, the network size, and learning time of BP neural network. Finally, a shuffled cuckoo search algorithm is adopted to optimize the BP neural network soft-sensor model. Simulation results show that the model has better generalization results and prediction accuracy. PMID:25133210

Design Optimization and Fabrication of a Novel Structural SOI Piezoresistive Pressure Sensor with High Accuracy

PubMed Central

Li, Chuang; Cordovilla, Francisco; Jagdheesh, R.

2018-01-01

This paper presents a novel structural piezoresistive pressure sensor with four-grooved membrane combined with rood beam to measure low pressure. In this investigation, the design, optimization, fabrication, and measurements of the sensor are involved. By analyzing the stress distribution and deflection of sensitive elements using finite element method, a novel structure featuring high concentrated stress profile (HCSP) and locally stiffened membrane (LSM) is built. Curve fittings of the mechanical stress and deflection based on FEM simulation results are performed to establish the relationship between mechanical performance and structure dimension. A combination of FEM and curve fitting method is carried out to determine the structural dimensions. The optimized sensor chip is fabricated on a SOI wafer by traditional MEMS bulk-micromachining and anodic bonding technology. When the applied pressure is 1 psi, the sensor achieves a sensitivity of 30.9 mV/V/psi, a pressure nonlinearity of 0.21% FSS and an accuracy of 0.30%, and thereby the contradiction between sensitivity and linearity is alleviated. In terms of size, accuracy and high temperature characteristic, the proposed sensor is a proper choice for measuring pressure of less than 1 psi. PMID:29393916

Optimization and evaluation of a proportional derivative controller for planar arm movement.

PubMed

Jagodnik, Kathleen M; van den Bogert, Antonie J

2010-04-19

In most clinical applications of functional electrical stimulation (FES), the timing and amplitude of electrical stimuli have been controlled by open-loop pattern generators. The control of upper extremity reaching movements, however, will require feedback control to achieve the required precision. Here we present three controllers using proportional derivative (PD) feedback to stimulate six arm muscles, using two joint angle sensors. Controllers were first optimized and then evaluated on a computational arm model that includes musculoskeletal dynamics. Feedback gains were optimized by minimizing a weighted sum of position errors and muscle forces. Generalizability of the controllers was evaluated by performing movements for which the controller was not optimized, and robustness was tested via model simulations with randomly weakened muscles. Robustness was further evaluated by adding joint friction and doubling the arm mass. After optimization with a properly weighted cost function, all PD controllers performed fast, accurate, and robust reaching movements in simulation. Oscillatory behavior was seen after improper tuning. Performance improved slightly as the complexity of the feedback gain matrix increased. Copyright 2009 Elsevier Ltd. All rights reserved.

Optimization and evaluation of a proportional derivative controller for planar arm movement

PubMed Central

Jagodnik, Kathleen M.; van den Bogert, Antonie J.

2013-01-01

In most clinical applications of functional electrical stimulation (FES), the timing and amplitude of electrical stimuli have been controlled by open-loop pattern generators. The control of upper extremity reaching movements, however, will require feedback control to achieve the required precision. Here we present three controllers using proportional derivative (PD) feedback to stimulate six arm muscles, using two joint angle sensors. Controllers were first optimized and then evaluated on a computational arm model that includes musculoskeletal dynamics. Feedback gains were optimized by minimizing a weighted sum of position errors and muscle forces. Generalizability of the controllers was evaluated by performing movements for which the controller was not optimized, and robustness was tested via model simulations with randomly weakened muscles. Robustness was further evaluated by adding joint friction and doubling the arm mass. After optimization with a properly weighted cost function, all PD controllers performed fast, accurate, and robust reaching movements in simulation. Oscillatory behavior was seen after improper tuning. Performance improved slightly as the complexity of the feedback gain matrix increased. PMID:20097345

An Optimal Algorithm towards Successive Location Privacy in Sensor Networks with Dynamic Programming

NASA Astrophysics Data System (ADS)

Zhao, Baokang; Wang, Dan; Shao, Zili; Cao, Jiannong; Chan, Keith C. C.; Su, Jinshu

In wireless sensor networks, preserving location privacy under successive inference attacks is extremely critical. Although this problem is NP-complete in general cases, we propose a dynamic programming based algorithm and prove it is optimal in special cases where the correlation only exists between p immediate adjacent observations.

Determination of a temperature sensor location for monitoring weld pool size in GMAW

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

Boo, K.S.; Cho, H.S.

1994-11-01

This paper describes a method of determining the optimal sensor location to measure weldment surface temperature, which has a close correlation with weld pool size in the gas metal arc (GMA) welding process. Due to the inherent complexity and nonlinearity in the GMA welding process, the relationship between the weldment surface temperature and the weld pool size varies with the point of measurement. This necessitates an optimal selection of the measurement point to minimize the process nonlinearity effect in estimating the weld pool size from the measured temperature. To determine the optimal sensor location on the top surface of themore » weldment, the correlation between the measured temperature and the weld pool size is analyzed. The analysis is done by calculating the correlation function, which is based upon an analytical temperature distribution model. To validate the optimal sensor location, a series of GMA bead-on-plate welds are performed on a medium-carbon steel under various welding conditions. A comparison study is given in detail based upon the simulation and experimental results.« less

A Computational Framework for Quantifying and Optimizing the Performance of Observational Networks in 4D-Var Data Assimilation

NASA Astrophysics Data System (ADS)

Cioaca, Alexandru

A deep scientific understanding of complex physical systems, such as the atmosphere, can be achieved neither by direct measurements nor by numerical simulations alone. Data assimila- tion is a rigorous procedure to fuse information from a priori knowledge of the system state, the physical laws governing the evolution of the system, and real measurements, all with associated error statistics. Data assimilation produces best (a posteriori) estimates of model states and parameter values, and results in considerably improved computer simulations. The acquisition and use of observations in data assimilation raises several important scientific questions related to optimal sensor network design, quantification of data impact, pruning redundant data, and identifying the most beneficial additional observations. These questions originate in operational data assimilation practice, and have started to attract considerable interest in the recent past. This dissertation advances the state of knowledge in four dimensional variational (4D-Var) data assimilation by developing, implementing, and validating a novel computational framework for estimating observation impact and for optimizing sensor networks. The framework builds on the powerful methodologies of second-order adjoint modeling and the 4D-Var sensitivity equations. Efficient computational approaches for quantifying the observation impact include matrix free linear algebra algorithms and low-rank approximations of the sensitivities to observations. The sensor network configuration problem is formulated as a meta-optimization problem. Best values for parameters such as sensor location are obtained by optimizing a performance criterion, subject to the constraint posed by the 4D-Var optimization. Tractable computational solutions to this "optimization-constrained" optimization problem are provided. The results of this work can be directly applied to the deployment of intelligent sensors and adaptive observations, as well as to reducing the operating costs of measuring networks, while preserving their ability to capture the essential features of the system under consideration.

Pixel electronic noise as a function of position in an active matrix flat panel imaging array

NASA Astrophysics Data System (ADS)

Yazdandoost, Mohammad Y.; Wu, Dali; Karim, Karim S.

2010-04-01

We present an analysis of output referred pixel electronic noise as a function of position in the active matrix array for both active and passive pixel architectures. Three different noise sources for Active Pixel Sensor (APS) arrays are considered: readout period noise, reset period noise and leakage current noise of the reset TFT during readout. For the state-of-the-art Passive Pixel Sensor (PPS) array, the readout noise of the TFT switch is considered. Measured noise results are obtained by modeling the array connections with RC ladders on a small in-house fabricated prototype. The results indicate that the pixels in the rows located in the middle part of the array have less random electronic noise at the output of the off-panel charge amplifier compared to the ones in rows at the two edges of the array. These results can help optimize for clearer images as well as help define the region-of-interest with the best signal-to-noise ratio in an active matrix digital flat panel imaging array.

Optimizing Sensor and Actuator Arrays for ASAC Noise Control

NASA Technical Reports Server (NTRS)

Palumbo, Dan; Cabell, Ran

2000-01-01

This paper summarizes the development of an approach to optimizing the locations for arrays of sensors and actuators in active noise control systems. A type of directed combinatorial search, called Tabu Search, is used to select an optimal configuration from a much larger set of candidate locations. The benefit of using an optimized set is demonstrated. The importance of limiting actuator forces to realistic levels when evaluating the cost function is discussed. Results of flight testing an optimized system are presented. Although the technique has been applied primarily to Active Structural Acoustic Control systems, it can be adapted for use in other active noise control implementations.

Point Cloud Refinement with a Target-Free Intrinsic Calibration of a Mobile Multi-Beam LIDAR System

NASA Astrophysics Data System (ADS)

Nouiraa, H.; Deschaud, J. E.; Goulettea, F.

2016-06-01

LIDAR sensors are widely used in mobile mapping systems. The mobile mapping platforms allow to have fast acquisition in cities for example, which would take much longer with static mapping systems. The LIDAR sensors provide reliable and precise 3D information, which can be used in various applications: mapping of the environment; localization of objects; detection of changes. Also, with the recent developments, multi-beam LIDAR sensors have appeared, and are able to provide a high amount of data with a high level of detail. A mono-beam LIDAR sensor mounted on a mobile platform will have an extrinsic calibration to be done, so the data acquired and registered in the sensor reference frame can be represented in the body reference frame, modeling the mobile system. For a multibeam LIDAR sensor, we can separate its calibration into two distinct parts: on one hand, we have an extrinsic calibration, in common with mono-beam LIDAR sensors, which gives the transformation between the sensor cartesian reference frame and the body reference frame. On the other hand, there is an intrinsic calibration, which gives the relations between the beams of the multi-beam sensor. This calibration depends on a model given by the constructor, but the model can be non optimal, which would bring errors and noise into the acquired point clouds. In the litterature, some optimizations of the calibration parameters are proposed, but need a specific routine or environment, which can be constraining and time-consuming. In this article, we present an automatic method for improving the intrinsic calibration of a multi-beam LIDAR sensor, the Velodyne HDL-32E. The proposed approach does not need any calibration target, and only uses information from the acquired point clouds, which makes it simple and fast to use. Also, a corrected model for the Velodyne sensor is proposed. An energy function which penalizes points far from local planar surfaces is used to optimize the different proposed parameters for the corrected model, and we are able to give a confidence value for the calibration parameters found. Optimization results on both synthetic and real data are presented.

Design and performance of an integrated ground and space sensor web for monitoring active volcanoes.

NASA Astrophysics Data System (ADS)

Lahusen, Richard; Song, Wenzhan; Kedar, Sharon; Shirazi, Behrooz; Chien, Steve; Doubleday, Joshua; Davies, Ashley; Webb, Frank; Dzurisin, Dan; Pallister, John

2010-05-01

An interdisciplinary team of computer, earth and space scientists collaborated to develop a sensor web system for rapid deployment at active volcanoes. The primary goals of this Optimized Autonomous Space In situ Sensorweb (OASIS) are to: 1) integrate complementary space and in situ (ground-based) elements into an interactive, autonomous sensor web; 2) advance sensor web power and communication resource management technology; and 3) enable scalability for seamless addition sensors and other satellites into the sensor web. This three-year project began with a rigorous multidisciplinary interchange that resulted in definition of system requirements to guide the design of the OASIS network and to achieve the stated project goals. Based on those guidelines, we have developed fully self-contained in situ nodes that integrate GPS, seismic, infrasonic and lightning (ash) detection sensors. The nodes in the wireless sensor network are linked to the ground control center through a mesh network that is highly optimized for remote geophysical monitoring. OASIS also features an autonomous bidirectional interaction between ground nodes and instruments on the EO-1 space platform through continuous analysis and messaging capabilities at the command and control center. Data from both the in situ sensors and satellite-borne hyperspectral imaging sensors stream into a common database for real-time visualization and analysis by earth scientists. We have successfully completed a field deployment of 15 nodes within the crater and on the flanks of Mount St. Helens, Washington. The demonstration that sensor web technology facilitates rapid network deployments and that we can achieve real-time continuous data acquisition. We are now optimizing component performance and improving user interaction for additional deployments at erupting volcanoes in 2010.

Sea ice motion from low-resolution satellite sensors: An alternative method and its validation in the Arctic

NASA Astrophysics Data System (ADS)

Lavergne, T.; Eastwood, S.; Teffah, Z.; Schyberg, H.; Breivik, L.-A.

2010-10-01

The retrieval of sea ice motion with the Maximum Cross-Correlation (MCC) method from low-resolution (10-15 km) spaceborne imaging sensors is challenged by a dominating quantization noise as the time span of displacement vectors is shortened. To allow investigating shorter displacements from these instruments, we introduce an alternative sea ice motion tracking algorithm that builds on the MCC method but relies on a continuous optimization step for computing the motion vector. The prime effect of this method is to effectively dampen the quantization noise, an artifact of the MCC. It allows for retrieving spatially smooth 48 h sea ice motion vector fields in the Arctic. Strategies to detect and correct erroneous vectors as well as to optimally merge several polarization channels of a given instrument are also described. A test processing chain is implemented and run with several active and passive microwave imagers (Advanced Microwave Scanning Radiometer-EOS (AMSR-E), Special Sensor Microwave Imager, and Advanced Scatterometer) during three Arctic autumn, winter, and spring seasons. Ice motion vectors are collocated to and compared with GPS positions of in situ drifters. Error statistics are shown to be ranging from 2.5 to 4.5 km (standard deviation for components of the vectors) depending on the sensor, without significant bias. We discuss the relative contribution of measurement and representativeness errors by analyzing monthly validation statistics. The 37 GHz channels of the AMSR-E instrument allow for the best validation statistics. The operational low-resolution sea ice drift product of the EUMETSAT OSI SAF (European Organisation for the Exploitation of Meteorological Satellites Ocean and Sea Ice Satellite Application Facility) is based on the algorithms presented in this paper.

An Energy-Efficient Approach to Enhance Virtual Sensors Provisioning in Sensor Clouds Environments

PubMed Central

Filho, Raimir Holanda; Rabêlo, Ricardo de Andrade L.; de Carvalho, Carlos Giovanni N.; Mendes, Douglas Lopes de S.; Costa, Valney da Gama

2018-01-01

Virtual sensors provisioning is a central issue for sensors cloud middleware since it is responsible for selecting physical nodes, usually from Wireless Sensor Networks (WSN) of different owners, to handle user’s queries or applications. Recent works perform provisioning by clustering sensor nodes based on the correlation measurements and then selecting as few nodes as possible to preserve WSN energy. However, such works consider only homogeneous nodes (same set of sensors). Therefore, those works are not entirely appropriate for sensor clouds, which in most cases comprises heterogeneous sensor nodes. In this paper, we propose ACxSIMv2, an approach to enhance the provisioning task by considering heterogeneous environments. Two main algorithms form ACxSIMv2. The first one, ACASIMv1, creates multi-dimensional clusters of sensor nodes, taking into account the measurements correlations instead of the physical distance between nodes like most works on literature. Then, the second algorithm, ACOSIMv2, based on an Ant Colony Optimization system, selects an optimal set of sensors nodes from to respond user’s queries while attending all parameters and preserving the overall energy consumption. Results from initial experiments show that the approach reduces significantly the sensor cloud energy consumption compared to traditional works, providing a solution to be considered in sensor cloud scenarios. PMID:29495406

An Energy-Efficient Approach to Enhance Virtual Sensors Provisioning in Sensor Clouds Environments.

PubMed

Lemos, Marcus Vinícius de S; Filho, Raimir Holanda; Rabêlo, Ricardo de Andrade L; de Carvalho, Carlos Giovanni N; Mendes, Douglas Lopes de S; Costa, Valney da Gama

2018-02-26

Virtual sensors provisioning is a central issue for sensors cloud middleware since it is responsible for selecting physical nodes, usually from Wireless Sensor Networks (WSN) of different owners, to handle user's queries or applications. Recent works perform provisioning by clustering sensor nodes based on the correlation measurements and then selecting as few nodes as possible to preserve WSN energy. However, such works consider only homogeneous nodes (same set of sensors). Therefore, those works are not entirely appropriate for sensor clouds, which in most cases comprises heterogeneous sensor nodes. In this paper, we propose ACxSIMv2, an approach to enhance the provisioning task by considering heterogeneous environments. Two main algorithms form ACxSIMv2. The first one, ACASIMv1, creates multi-dimensional clusters of sensor nodes, taking into account the measurements correlations instead of the physical distance between nodes like most works on literature. Then, the second algorithm, ACOSIMv2, based on an Ant Colony Optimization system, selects an optimal set of sensors nodes from to respond user's queries while attending all parameters and preserving the overall energy consumption. Results from initial experiments show that the approach reduces significantly the sensor cloud energy consumption compared to traditional works, providing a solution to be considered in sensor cloud scenarios.

Optimizing Drilling Efficiency by PWD (Pressure-While-Drilling) Sensor in wells which were drilled in the Khazar-Caspian Sea of the Azerbaijan Republic

NASA Astrophysics Data System (ADS)

Amirov, Elnur

2017-04-01

Sperry Drilling Services' PWD sensor improve and support drilling efficiency by providing very important, real-time downhole pressure information that allows to make faster and better drilling decisions. The PWD service, provides accurate annular pressure, internal pressure and temperature measurements using any of well-known telemetry systems: positive mud pulse, negative mud pulse and electromagnetic. Pressure data can be transmitted in real time and recorded in downhole memory. In the pumpsoff mode, the minimum, maximum and average pressures observed during the non-circulating period are transmitted via mud pulse telemetry when circulation recommences. These measurements provide the knowledge to avoid lost circulation and detect flow/kicks before they happen. The PWD sensor also reduces the risk of problems related by unexpected fracture or collapse. Sperry's PWD sensor also helps to avoid lost circulation and flow/kick, which can lead to costly delays in drilling. Annular pressure increases often reflect ineffective cuttings removal and poor hole cleaning, both of which can lead to lost circulation. The PWD sensor detects the increase and drilling fluid parameters and operating procedures can be modified to improve hole-cleaning efficiency. On extended reach wells, real-time information helps to maintain wellbore pressures between safe operating limits and to monitor hole cleaning. The PWD sensor also provides early detection of well flows and kicks. A drop in pressure, can indicate gas, oil and water kicks. Because the sensor is making its measurement downhole, the PWD sensor makes it possible to detect such pressure drops earlier than more traditional surface measurements. The PWD sensor has high-accuracy quartz gauges and is able to record data because of its battery-powered operation. It is also extremely useful in specialized drilling environments, such as high-pressure/high-temperature, extended-reach and deepwater wells. When combined with the rig management system, surface and downhole measurements, can be compared for more accurate and extensive analysis. PWD sensor was utilized with encouraging results in many wells up to 3000-6000m subsurface reservoirs (these wells were drilled in the Khazar-Caspian region of the Azerbaijan Republic) and acquired PWD RT/RM data implemented for best drilling practices in other brand new drilled offset wells in order to help us achieve our mission to drill safe, faster, on target, optimize drilling efficiency, maximize well value and reservoir insight.

Prototyping a compact system for active vibration isolation using piezoelectric sensors and actuators.

PubMed

Shen, Hui; Wang, Chun; Li, Liufeng; Chen, Lisheng

2013-05-01

Being small in size and weight, piezoelectric transducers hold unique positions in vibration sensing and control. Here, we explore the possibility of building a compact vibration isolation system using piezoelectric sensors and actuators. The mechanical resonances of a piezoelectric actuator around a few kHz are suppressed by an order of magnitude via electrical damping, which improves the high-frequency response. Working with a strain gauge located on the piezoelectric actuator, an auxiliary control loop eliminates the drift associated with a large servo gain at dc. Following this approach, we design, optimize, and experimentally verify the loop responses using frequency domain analysis. The vibration isolation between 1 Hz and 200 Hz is achieved and the attenuation peaks at 60 near vibration frequency of 20 Hz. Restrictions and potentials for extending the isolation to lower vibration frequencies are discussed.

Optimal Location through Distributed Algorithm to Avoid Energy Hole in Mobile Sink WSNs

PubMed Central

Qing-hua, Li; Wei-hua, Gui; Zhi-gang, Chen

2014-01-01

In multihop data collection sensor network, nodes near the sink need to relay on remote data and, thus, have much faster energy dissipation rate and suffer from premature death. This phenomenon causes energy hole near the sink, seriously damaging the network performance. In this paper, we first compute energy consumption of each node when sink is set at any point in the network through theoretical analysis; then we propose an online distributed algorithm, which can adjust sink position based on the actual energy consumption of each node adaptively to get the actual maximum lifetime. Theoretical analysis and experimental results show that the proposed algorithms significantly improve the lifetime of wireless sensor network. It lowers the network residual energy by more than 30% when it is dead. Moreover, the cost for moving the sink is relatively smaller. PMID:24895668

Quadrant photodetector sensitivity.

PubMed

Manojlović, Lazo M

2011-07-10

A quantitative theoretical analysis of the quadrant photodetector (QPD) sensitivity in position measurement is presented. The Gaussian light spot irradiance distribution on the QPD surface was assumed to meet most of the real-life applications of this sensor. As the result of the mathematical treatment of the problem, we obtained, in a closed form, the sensitivity function versus the ratio of the light spot 1/e radius and the QPD radius. The obtained result is valid for the full range of the ratios. To check the influence of the finite light spot radius on the interaxis cross talk and linearity, we also performed a mathematical analysis to quantitatively measure these types of errors. An optimal range of the ratio of light spot radius and QPD radius has been found to simultaneously achieve low interaxis cross talk and high linearity of the sensor. © 2011 Optical Society of America

Haptic seat for fuel economy feedback

DOEpatents

Bobbitt, III, John Thomas

2016-08-30

A process of providing driver fuel economy feedback is disclosed in which vehicle sensors provide for haptic feedback on fuel usage. Such sensors may include one or more of a speed sensors, global position satellite units, vehicle pitch/roll angle sensors, suspension displacement sensors, longitudinal accelerometer sensors, throttle position in sensors, steering angle sensors, break pressure sensors, and lateral accelerometer sensors. Sensors used singlely or collectively can provide enhanced feedback as to various environmental conditions and operating conditions such that a more accurate assessment of fuel economy information can be provided to the driver.

Joint Power Charging and Routing in Wireless Rechargeable Sensor Networks.

PubMed

Jia, Jie; Chen, Jian; Deng, Yansha; Wang, Xingwei; Aghvami, Abdol-Hamid

2017-10-09

The development of wireless power transfer (WPT) technology has inspired the transition from traditional battery-based wireless sensor networks (WSNs) towards wireless rechargeable sensor networks (WRSNs). While extensive efforts have been made to improve charging efficiency, little has been done for routing optimization. In this work, we present a joint optimization model to maximize both charging efficiency and routing structure. By analyzing the structure of the optimization model, we first decompose the problem and propose a heuristic algorithm to find the optimal charging efficiency for the predefined routing tree. Furthermore, by coding the many-to-one communication topology as an individual, we further propose to apply a genetic algorithm (GA) for the joint optimization of both routing and charging. The genetic operations, including tree-based recombination and mutation, are proposed to obtain a fast convergence. Our simulation results show that the heuristic algorithm reduces the number of resident locations and the total moving distance. We also show that our proposed algorithm achieves a higher charging efficiency compared with existing algorithms.

Evolutionary Beamforming Optimization for Radio Frequency Charging in Wireless Rechargeable Sensor Networks

PubMed Central

Yao, Ke-Han; Jiang, Jehn-Ruey; Tsai, Chung-Hsien; Wu, Zong-Syun

2017-01-01

This paper investigates how to efficiently charge sensor nodes in a wireless rechargeable sensor network (WRSN) with radio frequency (RF) chargers to make the network sustainable. An RF charger is assumed to be equipped with a uniform circular array (UCA) of 12 antennas with the radius λ, where λ is the RF wavelength. The UCA can steer most RF energy in a target direction to charge a specific WRSN node by the beamforming technology. Two evolutionary algorithms (EAs) using the evolution strategy (ES), namely the Evolutionary Beamforming Optimization (EBO) algorithm and the Evolutionary Beamforming Optimization Reseeding (EBO-R) algorithm, are proposed to nearly optimize the power ratio of the UCA beamforming peak side lobe (PSL) and the main lobe (ML) aimed at the given target direction. The proposed algorithms are simulated for performance evaluation and are compared with a related algorithm, called Particle Swarm Optimization Gravitational Search Algorithm-Explore (PSOGSA-Explore), to show their superiority. PMID:28825648

Joint Power Charging and Routing in Wireless Rechargeable Sensor Networks

PubMed Central

Jia, Jie; Chen, Jian; Deng, Yansha; Wang, Xingwei; Aghvami, Abdol-Hamid

2017-01-01

The development of wireless power transfer (WPT) technology has inspired the transition from traditional battery-based wireless sensor networks (WSNs) towards wireless rechargeable sensor networks (WRSNs). While extensive efforts have been made to improve charging efficiency, little has been done for routing optimization. In this work, we present a joint optimization model to maximize both charging efficiency and routing structure. By analyzing the structure of the optimization model, we first decompose the problem and propose a heuristic algorithm to find the optimal charging efficiency for the predefined routing tree. Furthermore, by coding the many-to-one communication topology as an individual, we further propose to apply a genetic algorithm (GA) for the joint optimization of both routing and charging. The genetic operations, including tree-based recombination and mutation, are proposed to obtain a fast convergence. Our simulation results show that the heuristic algorithm reduces the number of resident locations and the total moving distance. We also show that our proposed algorithm achieves a higher charging efficiency compared with existing algorithms. PMID:28991200

A Fast and Scalable Method for A-Optimal Design of Experiments for Infinite-dimensional Bayesian Nonlinear Inverse Problems with Application to Porous Medium Flow

NASA Astrophysics Data System (ADS)

Petra, N.; Alexanderian, A.; Stadler, G.; Ghattas, O.

2015-12-01

We address the problem of optimal experimental design (OED) for Bayesian nonlinear inverse problems governed by partial differential equations (PDEs). The inverse problem seeks to infer a parameter field (e.g., the log permeability field in a porous medium flow model problem) from synthetic observations at a set of sensor locations and from the governing PDEs. The goal of the OED problem is to find an optimal placement of sensors so as to minimize the uncertainty in the inferred parameter field. We formulate the OED objective function by generalizing the classical A-optimal experimental design criterion using the expected value of the trace of the posterior covariance. This expected value is computed through sample averaging over the set of likely experimental data. Due to the infinite-dimensional character of the parameter field, we seek an optimization method that solves the OED problem at a cost (measured in the number of forward PDE solves) that is independent of both the parameter and the sensor dimension. To facilitate this goal, we construct a Gaussian approximation to the posterior at the maximum a posteriori probability (MAP) point, and use the resulting covariance operator to define the OED objective function. We use randomized trace estimation to compute the trace of this covariance operator. The resulting OED problem includes as constraints the system of PDEs characterizing the MAP point, and the PDEs describing the action of the covariance (of the Gaussian approximation to the posterior) to vectors. We control the sparsity of the sensor configurations using sparsifying penalty functions, and solve the resulting penalized bilevel optimization problem via an interior-point quasi-Newton method, where gradient information is computed via adjoints. We elaborate our OED method for the problem of determining the optimal sensor configuration to best infer the log permeability field in a porous medium flow problem. Numerical results show that the number of PDE solves required for the evaluation of the OED objective function and its gradient is essentially independent of both the parameter dimension and the sensor dimension (i.e., the number of candidate sensor locations). The number of quasi-Newton iterations for computing an OED also exhibits the same dimension invariance properties.

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.

Optical biosensor optimized for continuous in-line glucose monitoring in animal cell culture.

PubMed

Tric, Mircea; Lederle, Mario; Neuner, Lisa; Dolgowjasow, Igor; Wiedemann, Philipp; Wölfl, Stefan; Werner, Tobias

2017-09-01

Biosensors for continuous glucose monitoring in bioreactors could provide a valuable tool for optimizing culture conditions in biotechnological applications. We have developed an optical biosensor for long-term continuous glucose monitoring and demonstrated a tight glucose level control during cell culture in disposable bioreactors. The in-line sensor is based on a commercially available oxygen sensor that is coated with cross-linked glucose oxidase (GOD). The dynamic range of the sensor was tuned by a hydrophilic perforated diffusion membrane with an optimized permeability for glucose and oxygen. The biosensor was thoroughly characterized by experimental data and numerical simulations, which enabled insights into the internal concentration profile of the deactivating by-product hydrogen peroxide. The simulations were carried out with a one-dimensional biosensor model and revealed that, in addition to the internal hydrogen peroxide concentration, the turnover rate of the enzyme GOD plays a crucial role for biosensor stability. In the light of this finding, the glucose sensor was optimized to reach a long functional stability (>52 days) under continuous glucose monitoring conditions with a dynamic range of 0-20 mM and a response time of t 90  ≤ 10 min. In addition, we demonstrated that the sensor was sterilizable with beta and UV irradiation and only subjected to minor cross sensitivity to oxygen, when an oxygen reference sensor was applied. Graphical abstract Measuring setup of a glucose biosensor in a shake flask for continuous glucose monitoring in mammalian cell culture.

Switching algorithm for maglev train double-modular redundant positioning sensors.

PubMed

He, Ning; Long, Zhiqiang; Xue, Song

2012-01-01

High-resolution positioning for maglev trains is implemented by detecting the tooth-slot structure of the long stator installed along the rail, but there are large joint gaps between long stator sections. When a positioning sensor is below a large joint gap, its positioning signal is invalidated, thus double-modular redundant positioning sensors are introduced into the system. This paper studies switching algorithms for these redundant positioning sensors. At first, adaptive prediction is applied to the sensor signals. The prediction errors are used to trigger sensor switching. In order to enhance the reliability of the switching algorithm, wavelet analysis is introduced to suppress measuring disturbances without weakening the signal characteristics reflecting the stator joint gap based on the correlation between the wavelet coefficients of adjacent scales. The time delay characteristics of the method are analyzed to guide the algorithm simplification. Finally, the effectiveness of the simplified switching algorithm is verified through experiments.

Switching Algorithm for Maglev Train Double-Modular Redundant Positioning Sensors

PubMed Central

He, Ning; Long, Zhiqiang; Xue, Song

2012-01-01

High-resolution positioning for maglev trains is implemented by detecting the tooth-slot structure of the long stator installed along the rail, but there are large joint gaps between long stator sections. When a positioning sensor is below a large joint gap, its positioning signal is invalidated, thus double-modular redundant positioning sensors are introduced into the system. This paper studies switching algorithms for these redundant positioning sensors. At first, adaptive prediction is applied to the sensor signals. The prediction errors are used to trigger sensor switching. In order to enhance the reliability of the switching algorithm, wavelet analysis is introduced to suppress measuring disturbances without weakening the signal characteristics reflecting the stator joint gap based on the correlation between the wavelet coefficients of adjacent scales. The time delay characteristics of the method are analyzed to guide the algorithm simplification. Finally, the effectiveness of the simplified switching algorithm is verified through experiments. PMID:23112657

A quartz-based micro catalytic methane sensor by high resolution screen printing

NASA Astrophysics Data System (ADS)

Lu, Wenshuai; Jing, Gaoshan; Bian, Xiaomeng; Yu, Hongyan; Cui, Tianhong

2016-02-01

A micro catalytic methane sensor was proposed and fabricated on a bulk fused quartz substrate using a high resolution screen printing technique for the first time, with reduced power consumption and optimized sensitivity. The sensor was designed by the finite element method and quartz was chosen as the substrate material and alumina support with optimized dimensions. Fabrication of the sensor consisted of two MEMS processes, lift-off and high resolution screen printing, with the advantages of high yield and uniformity. When the sensor’s regional working temperature changes from 250 °C to 470 °C, its sensitivity increases, as well as the power consumption. The highest sensitivity can reach 1.52 mV/% CH4. A temperature of 300 °C was chosen as the optimized working temperature, and the sensor’s sensitivity, power consumption, nonlinearity and response time are 0.77 mV/% CH4, 415 mW, 2.6%, and 35 s, respectively. This simple, but highly uniform fabrication process and the reliable performance of this sensor may lead to wide applications for methane detection.

A Movement-Assisted Deployment of Collaborating Autonomous Sensors for Indoor and Outdoor Environment Monitoring

PubMed Central

Niewiadomska-Szynkiewicz, Ewa; Sikora, Andrzej; Marks, Michał

2016-01-01

Using mobile robots or unmanned vehicles to assist optimal wireless sensors deployment in a working space can significantly enhance the capability to investigate unknown environments. This paper addresses the issues of the application of numerical optimization and computer simulation techniques to on-line calculation of a wireless sensor network topology for monitoring and tracking purposes. We focus on the design of a self-organizing and collaborative mobile network that enables a continuous data transmission to the data sink (base station) and automatically adapts its behavior to changes in the environment to achieve a common goal. The pre-defined and self-configuring approaches to the mobile-based deployment of sensors are compared and discussed. A family of novel algorithms for the optimal placement of mobile wireless devices for permanent monitoring of indoor and outdoor dynamic environments is described. They employ a network connectivity-maintaining mobility model utilizing the concept of the virtual potential function for calculating the motion trajectories of platforms carrying sensors. Their quality and utility have been justified through simulation experiments and are discussed in the final part of the paper. PMID:27649186

A Movement-Assisted Deployment of Collaborating Autonomous Sensors for Indoor and Outdoor Environment Monitoring.

PubMed

Niewiadomska-Szynkiewicz, Ewa; Sikora, Andrzej; Marks, Michał

2016-09-14

Using mobile robots or unmanned vehicles to assist optimal wireless sensors deployment in a working space can significantly enhance the capability to investigate unknown environments. This paper addresses the issues of the application of numerical optimization and computer simulation techniques to on-line calculation of a wireless sensor network topology for monitoring and tracking purposes. We focus on the design of a self-organizing and collaborative mobile network that enables a continuous data transmission to the data sink (base station) and automatically adapts its behavior to changes in the environment to achieve a common goal. The pre-defined and self-configuring approaches to the mobile-based deployment of sensors are compared and discussed. A family of novel algorithms for the optimal placement of mobile wireless devices for permanent monitoring of indoor and outdoor dynamic environments is described. They employ a network connectivity-maintaining mobility model utilizing the concept of the virtual potential function for calculating the motion trajectories of platforms carrying sensors. Their quality and utility have been justified through simulation experiments and are discussed in the final part of the paper.

Design, optimization and evaluation of a "smart" pixel sensor array for low-dose digital radiography

NASA Astrophysics Data System (ADS)

Wang, Kai; Liu, Xinghui; Ou, Hai; Chen, Jun

2016-04-01

Amorphous silicon (a-Si:H) thin-film transistors (TFTs) have been widely used to build flat-panel X-ray detectors for digital radiography (DR). As the demand for low-dose X-ray imaging grows, a detector with high signal-to-noise-ratio (SNR) pixel architecture emerges. "Smart" pixel is intended to use a dual-gate photosensitive TFT for sensing, storage, and switch. It differs from a conventional passive pixel sensor (PPS) and active pixel sensor (APS) in that all these three functions are combined into one device instead of three separate units in a pixel. Thus, it is expected to have high fill factor and high spatial resolution. In addition, it utilizes the amplification effect of the dual-gate photosensitive TFT to form a one-transistor APS that leads to a potentially high SNR. This paper addresses the design, optimization and evaluation of the smart pixel sensor and array for low-dose DR. We will design and optimize the smart pixel from the scintillator to TFT levels and validate it through optical and electrical simulation and experiments of a 4x4 sensor array.

Application and Optimization of Stiffness Abruption Structures for Pressure Sensors with High Sensitivity and Anti-Overload Ability

PubMed Central

Xu, Tingzhong; Lu, Dejiang; Zhao, Libo; Jiang, Zhuangde; Wang, Hongyan; Guo, Xin; Li, Zhikang; Zhou, Xiangyang; Zhao, Yulong

2017-01-01

The influence of diaphragm bending stiffness distribution on the stress concentration characteristics of a pressure sensing chip had been analyzed and discussed systematically. According to the analysis, a novel peninsula-island-based diaphragm structure was presented and applied to two differenet diaphragm shapes as sensing chips for pressure sensors. By well-designed bending stiffness distribution of the diaphragm, the elastic potential energy induced by diaphragm deformation was concentrated above the gap position, which remarkably increased the sensitivity of the sensing chip. An optimization method and the distribution pattern of the peninsula-island based diaphragm structure were also discussed. Two kinds of sensing chips combined with the peninsula-island structures distributing along the side edge and diagonal directions of rectangular diaphragm were fabricated and analyzed. By bonding the sensing chips with anti-overload glass bases, these two sensing chips were demonstrated by testing to achieve not only high sensitivity, but also good anti-overload ability. The experimental results showed that the proposed structures had the potential to measure ultra-low absolute pressures with high sensitivity and good anti-overload ability in an atmospheric environment. PMID:28846599

Enhanced processing in arrays of optimally tuned nonlinear biomimetic sensors: A coupling-mediated Ringelmann effect and its dynamical mitigation

NASA Astrophysics Data System (ADS)

Nikitin, Alexander P.; Bulsara, Adi R.; Stocks, Nigel G.

2017-03-01

Inspired by recent results on self-tunability in the outer hair cells of the mammalian cochlea, we describe an array of magnetic sensors where each individual sensor can self-tune to an optimal operating regime. The self-tuning gives the array its "biomimetic" features. We show that the overall performance of the array can, as expected, be improved by increasing the number of sensors but, however, coupling between sensors reduces the overall performance even though the individual sensors in the system could see an improvement. We quantify the similarity of this phenomenon to the Ringelmann effect that was formulated 103 years ago to account for productivity losses in human and animal groups. We propose a global feedback scheme that can be used to greatly mitigate the performance degradation that would, normally, stem from the Ringelmann effect.

Improving the Response of a Wheel Speed Sensor by Using a RLS Lattice Algorithm

PubMed Central

Hernandez, Wilmar

2006-01-01

Among the complete family of sensors for automotive safety, consumer and industrial application, speed sensors stand out as one of the most important. Actually, speed sensors have the diversity to be used in a broad range of applications. In today's automotive industry, such sensors are used in the antilock braking system, the traction control system and the electronic stability program. Also, typical applications are cam and crank shaft position/speed and wheel and turbo shaft speed measurement. In addition, they are used to control a variety of functions, including fuel injection, ignition timing in engines, and so on. However, some types of speed sensors cannot respond to very low speeds for different reasons. What is more, the main reason why such sensors are not good at detecting very low speeds is that they are more susceptible to noise when the speed of the target is low. In short, they suffer from noise and generally only work at medium to high speeds. This is one of the drawbacks of the inductive (magnetic reluctance) speed sensors and is the case under study. Furthermore, there are other speed sensors like the differential Hall Effect sensors that are relatively immune to interference and noise, but they cannot detect static fields. This limits their operations to speeds which give a switching frequency greater than a minimum operating frequency. In short, this research is focused on improving the performance of a variable reluctance speed sensor placed in a car under performance tests by using a recursive least-squares (RLS) lattice algorithm. Such an algorithm is situated in an adaptive noise canceller and carries out an optimal estimation of the relevant signal coming from the sensor, which is buried in a broad-band noise background where we have little knowledge of the noise characteristics. The experimental results are satisfactory and show a significant improvement in the signal-to-noise ratio at the system output.

40 CFR 63.1452 - What are my monitoring requirements?

Code of Federal Regulations, 2013 CFR

2013-07-01

..., associated sensor(s), and recording equipment according to the manufacturers' specifications. Locate the sensor(s) used for monitoring in or as close to a position that provides a representative measurement of... the flow sensor and other necessary equipment such as straightening vanes in a position that provides...

Giant magnetoresistive sensor

DOEpatents

Stearns, Daniel G.; Vernon, Stephen P.; Ceglio, Natale M.; Hawryluk, Andrew M.

1999-01-01

A magnetoresistive sensor element with a three-dimensional micro-architecture is capable of significantly improved sensitivity and highly localized measurement of magnetic fields. The sensor is formed of a multilayer film of alternately magnetic and nonmagnetic materials. The sensor is optimally operated in a current perpendicular to plane mode. The sensor is useful in magnetic read/write heads, for high density magnetic information storage and retrieval.

Consensus positive position feedback control for vibration attenuation of smart structures

NASA Astrophysics Data System (ADS)

Omidi, Ehsan; Nima Mahmoodi, S.

2015-04-01

This paper presents a new network-based approach for active vibration control in smart structures. In this approach, a network with known topology connects collocated actuator/sensor elements of the smart structure to one another. Each of these actuators/sensors, i.e., agent or node, is enhanced by a separate multi-mode positive position feedback (PPF) controller. The decentralized PPF controlled agents collaborate with each other in the designed network, under a certain consensus dynamics. The consensus constraint forces neighboring agents to cooperate with each other such that the disagreement between the time-domain actuation of the agents is driven to zero. The controller output of each agent is calculated using state-space variables; hence, optimal state estimators are designed first for the proposed observer-based consensus PPF control. The consensus controller is numerically investigated for a flexible smart structure, i.e., a thin aluminum beam that is clamped at its both ends. Results demonstrate that the consensus law successfully imposes synchronization between the independently controlled agents, as the disagreements between the decentralized PPF controller variables converge to zero in a short time. The new consensus PPF controller brings extra robustness to vibration suppression in smart structures, where malfunctions of an agent can be compensated for by referencing the neighboring agents’ performance. This is demonstrated in the results by comparing the new controller with former centralized PPF approach.

Best-next-view algorithm for three-dimensional scene reconstruction using range images

NASA Astrophysics Data System (ADS)

Banta, J. E.; Zhien, Yu; Wang, X. Z.; Zhang, G.; Smith, M. T.; Abidi, Mongi A.

1995-10-01

The primary focus of the research detailed in this paper is to develop an intelligent sensing module capable of automatically determining the optimal next sensor position and orientation during scene reconstruction. To facilitate a solution to this problem, we have assembled a system for reconstructing a 3D model of an object or scene from a sequence of range images. Candidates for the best-next-view position are determined by detecting and measuring occlusions to the range camera's view in an image. Ultimately, the candidate which will reveal the greatest amount of unknown scene information is selected as the best-next-view position. Our algorithm uses ray tracing to determine how much new information a given sensor perspective will reveal. We have tested our algorithm successfully on several synthetic range data streams, and found the system's results to be consistent with an intuitive human search. The models recovered by our system from range data compared well with the ideal models. Essentially, we have proven that range information of physical objects can be employed to automatically reconstruct a satisfactory dynamic 3D computer model at a minimal computational expense. This has obvious implications in the contexts of robot navigation, manufacturing, and hazardous materials handling. The algorithm we developed takes advantage of no a priori information in finding the best-next-view position.

Experiences with Acquiring Highly Redundant Spatial Data to Support Driverless Vehicle Technologies

NASA Astrophysics Data System (ADS)

Koppanyi, Z.; Toth, C. K.

2018-05-01

As vehicle technology is moving towards higher autonomy, the demand for highly accurate geospatial data is rapidly increasing, as accurate maps have a huge potential of increasing safety. In particular, high definition 3D maps, including road topography and infrastructure, as well as city models along the transportation corridors represent the necessary support for driverless vehicles. In this effort, a vehicle equipped with high-, medium- and low-resolution active and passive cameras acquired data in a typical traffic environment, represented here by the OSU campus, where GPS/GNSS data are available along with other navigation sensor data streams. The data streams can be used for two purposes. First, high-definition 3D maps can be created by integrating all the sensory data, and Data Analytics/Big Data methods can be tested for automatic object space reconstruction. Second, the data streams can support algorithmic research for driverless vehicle technologies, including object avoidance, navigation/positioning, detecting pedestrians and bicyclists, etc. Crucial cross-performance analyses on map database resolution and accuracy with respect to sensor performance metrics to achieve economic solution for accurate driverless vehicle positioning can be derived. These, in turn, could provide essential information on optimizing the choice of geospatial map databases and sensors' quality to support driverless vehicle technologies. The paper reviews the data acquisition and primary data processing challenges and performance results.

Systematic methods for knowledge acquisition and expert system development

NASA Technical Reports Server (NTRS)

Belkin, Brenda L.; Stengel, Robert F.

1991-01-01

Nine cooperating rule-based systems, collectively called AUTOCREW, were designed to automate functions and decisions associated with a combat aircraft's subsystem. The organization of tasks within each system is described; performance metrics were developed to evaluate the workload of each rule base, and to assess the cooperation between the rule-bases. Each AUTOCREW subsystem is composed of several expert systems that perform specific tasks. AUTOCREW's NAVIGATOR was analyzed in detail to understand the difficulties involved in designing the system and to identify tools and methodologies that ease development. The NAVIGATOR determines optimal navigation strategies from a set of available sensors. A Navigation Sensor Management (NSM) expert system was systematically designed from Kalman filter covariance data; four ground-based, a satellite-based, and two on-board INS-aiding sensors were modeled and simulated to aid an INS. The NSM Expert was developed using the Analysis of Variance (ANOVA) and the ID3 algorithm. Navigation strategy selection is based on an RSS position error decision metric, which is computed from the covariance data. Results show that the NSM Expert predicts position error correctly between 45 and 100 percent of the time for a specified navaid configuration and aircraft trajectory. The NSM Expert adapts to new situations, and provides reasonable estimates of hybrid performance. The systematic nature of the ANOVA/ID3 method makes it broadly applicable to expert system design when experimental or simulation data is available.

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.

A Three-Axis Force Sensor for Dual Finger Haptic Interfaces

PubMed Central

Fontana, Marco; Marcheschi, Simone; Salsedo, Fabio; Bergamasco, Massimo

2012-01-01

In this work we present the design process, the characterization and testing of a novel three-axis mechanical force sensor. This sensor is optimized for use in closed-loop force control of haptic devices with three degrees of freedom. In particular the sensor has been conceived for integration with a dual finger haptic interface that aims at simulating forces that occur during grasping and surface exploration. The sensing spring structure has been purposely designed in order to match force and layout specifications for the application. In this paper the design of the sensor is presented, starting from an analytic model that describes the characteristic matrix of the sensor. A procedure for designing an optimal overload protection mechanism is proposed. In the last part of the paper the authors describe the experimental characterization and the integrated test on a haptic hand exoskeleton showing the improvements in the controller performances provided by the inclusion of the force sensor. PMID:23202012

Nitrogen dioxide observations from the Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument: Retrieval algorithm and measurements during DISCOVER-AQ Texas 2013

EPA Science Inventory

The Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument is a test bed for upcoming air quality satellite instruments that will measure backscattered ultraviolet, visible and near-infrared light from geostationary orbit. GeoTASO flew on the NASA F...

Development of Miniaturized Optimized Smart Sensors (MOSS) for space plasmas

NASA Technical Reports Server (NTRS)

Young, D. T.

1993-01-01

The cost of space plasma sensors is high for several reasons: (1) Most are one-of-a-kind and state-of-the-art, (2) the cost of launch to orbit is high, (3) ruggedness and reliability requirements lead to costly development and test programs, and (4) overhead is added by overly elaborate or generalized spacecraft interface requirements. Possible approaches to reducing costs include development of small 'sensors' (defined as including all necessary optics, detectors, and related electronics) that will ultimately lead to cheaper missions by reducing (2), improving (3), and, through work with spacecraft designers, reducing (4). Despite this logical approach, there is no guarantee that smaller sensors are necessarily either better or cheaper. We have previously advocated applying analytical 'quality factors' to plasma sensors (and spacecraft) and have begun to develop miniaturized particle optical systems by applying quantitative optimization criteria. We are currently designing a Miniaturized Optimized Smart Sensor (MOSS) in which miniaturized electronics (e.g., employing new power supply topology and extensive us of gate arrays and hybrid circuits) are fully integrated with newly developed particle optics to give significant savings in volume and mass. The goal of the SwRI MOSS program is development of a fully self-contained and functional plasma sensor weighing 1 lb and requiring 1 W. MOSS will require only a typical spacecraft DC power source (e.g., 30 V) and command/data interfaces in order to be fully functional, and will provide measurement capabilities comparable in most ways to current sensors.

A coatable, light-weight, fast-response nanocomposite sensor for the in situ acquisition of dynamic elastic disturbance: from structural vibration to ultrasonic waves

NASA Astrophysics Data System (ADS)

Zeng, Zhihui; Liu, Menglong; Xu, Hao; Liu, Weijian; Liao, Yaozhong; Jin, Hao; Zhou, Limin; Zhang, Zhong; Su, Zhongqing

2016-06-01

Inspired by an innovative sensing philosophy, a light-weight nanocomposite sensor made of a hybrid of carbon black (CB)/polyvinylidene fluoride (PVDF) has been developed. The nanoscalar architecture and percolation characteristics of the hybrid were optimized in order to fulfil the in situ acquisition of dynamic elastic disturbance from low-frequency vibration to high-frequency ultrasonic waves. Dynamic particulate motion induced by elastic disturbance modulates the infrastructure of the CB conductive network in the sensor, with the introduction of the tunneling effect, leading to dynamic alteration in the piezoresistivity measured by the sensor. Electrical analysis, morphological characterization, and static/dynamic electromechanical response interrogation were implemented to advance our insight into the sensing mechanism of the sensor, and meanwhile facilitate understanding of the optimal percolation threshold. At the optimal threshold (˜6.5 wt%), the sensor exhibits high fidelity, a fast response, and high sensitivity to ultrafast elastic disturbance (in an ultrasonic regime up to 400 kHz), yet with an ultralow magnitude (on the order of micrometers). The performance of the sensor was evaluated against a conventional strain gauge and piezoelectric transducer, showing excellent coincidence, yet a much greater gauge factor and frequency-independent piezoresistive behavior. Coatable on a structure and deployable in a large quantity to form a dense sensor network, this nanocomposite sensor has blazed a trail for implementing in situ sensing for vibration- or ultrasonic-wave-based structural health monitoring, by striking a compromise between ‘sensing cost’ and ‘sensing effectiveness’.

Multi-type sensor placement and response reconstruction for building structures: Experimental investigations

NASA Astrophysics Data System (ADS)

Hu, Rong-Pan; Xu, You-Lin; Zhan, Sheng

2018-01-01

Estimation of lateral displacement and acceleration responses is essential to assess safety and serviceability of high-rise buildings under dynamic loadings including earthquake excitations. However, the measurement information from the limited number of sensors installed in a building structure is often insufficient for the complete structural performance assessment. An integrated multi-type sensor placement and response reconstruction method has thus been proposed by the authors to tackle this problem. To validate the feasibility and effectiveness of the proposed method, an experimental investigation using a cantilever beam with multi-type sensors is performed and reported in this paper. The experimental setup is first introduced. The finite element modelling and model updating of the cantilever beam are then performed. The optimal sensor placement for the best response reconstruction is determined by the proposed method based on the updated FE model of the beam. After the sensors are installed on the physical cantilever beam, a number of experiments are carried out. The responses at key locations are reconstructed and compared with the measured ones. The reconstructed responses achieve a good match with the measured ones, manifesting the feasibility and effectiveness of the proposed method. Besides, the proposed method is also examined for the cases of different excitations and unknown excitation, and the results prove the proposed method to be robust and effective. The superiority of the optimized sensor placement scheme is finally demonstrated through comparison with two other different sensor placement schemes: the accelerometer-only scheme and non-optimal sensor placement scheme. The proposed method can be applied to high-rise buildings for seismic performance assessment.

Nonlinear optimal filter technique for analyzing energy depositions in TES sensors driven into saturation

DOE PAGES

Shank, B.; Yen, J. J.; Cabrera, B.; ...

2014-11-04

We present a detailed thermal and electrical model of superconducting transition edge sensors (TESs) connected to quasiparticle (qp) traps, such as the W TESs connected to Al qp traps used for CDMS (Cryogenic Dark Matter Search) Ge and Si detectors. We show that this improved model, together with a straightforward time-domain optimal filter, can be used to analyze pulses well into the nonlinear saturation region and reconstruct absorbed energies with optimal energy resolution.

Applications of Elpasolites as a Multimode Radiation Sensor

NASA Astrophysics Data System (ADS)

Guckes, Amber

This study consists of both computational and experimental investigations. The computational results enabled detector design selections and confirmed experimental results. The experimental results determined that the CLYC scintillation detector can be applied as a functional and field-deployable multimode radiation sensor. The computational study utilized MCNP6 code to investigate the response of CLYC to various incident radiations and to determine the feasibility of its application as a handheld multimode sensor and as a single-scintillator collimated directional detection system. These simulations include: • Characterization of the response of the CLYC scintillator to gamma-rays and neutrons; • Study of the isotopic enrichment of 7Li versus 6Li in the CLYC for optimal detection of both thermal neutrons and fast neutrons; • Analysis of collimator designs to determine the optimal collimator for the single CLYC sensor directional detection system to assay gamma rays and neutrons; Simulations of a handheld CLYC multimode sensor and a single CLYC scintillator collimated directional detection system with the optimized collimator to determine the feasibility of detecting nuclear materials that could be encountered during field operations. These nuclear materials include depleted uranium, natural uranium, low-enriched uranium, highly-enriched uranium, reactor-grade plutonium, and weapons-grade plutonium. The experimental study includes the design, construction, and testing of both a handheld CLYC multimode sensor and a single CLYC scintillator collimated directional detection system. Both were designed in the Inventor CAD software and based on results of the computational study to optimize its performance. The handheld CLYC multimode sensor is modular, scalable, low?power, and optimized for high count rates. Commercial?off?the?shelf components were used where possible in order to optimize size, increase robustness, and minimize cost. The handheld CLYC multimode sensor was successfully tested to confirm its ability for gamma-ray and neutron detection, and gamma?ray and neutron spectroscopy. The sensor utilizes wireless data transfer for possible radiation mapping and network?centric deployment. The handheld multimode sensor was tested by performing laboratory measurements with various gamma-ray sources and neutron sources. The single CLYC scintillator collimated directional detection system is portable, robust, and capable of source localization and identification. The collimator was designed based on the results of the computational study and is constructed with high density polyethylene (HDPE) and lead (Pb). The collimator design and construction allows for the directional detection of gamma rays and fast neutrons utilizing only one scintillator which is interchangeable. For this study, a CLYC-7 scintillator was used. The collimated directional detection system was tested by performing laboratory directional measurements with various gamma-ray sources, 252Cf and a 239PuBe source.

Piezoceramic devices and PVDF films as sensors and actuators for intelligent structures

NASA Astrophysics Data System (ADS)

Hanagud, S.; Obal, M. W.; Calise, A. G.

The use of bonded piezoceramic sensors and piezoceramic actuators to control vibrations in structural dynamic systems is discussed. Equations for developing optimum control strategies are derived. An example of a cantilever beam is considered to illustrate the development procedure for optimal vibration control of structures by the use of piezoceramic sensors, actuators, and rate feedbacks with appropriate gains. Research areas and future directions are outlined, including dynamic coupling and constitutive equations; load and energy transfer; composite structures; optimal dynamic compensation; estimation and identification; and distributed control.

Optimizing Floating Guard Ring Designs for FASPAX N-in-P Silicon Sensors

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

Shin, Kyung-Wook; Bradford, Robert; Lipton, Ronald

2016-10-06

FASPAX (Fermi-Argonne Semiconducting Pixel Array X-ray detector) is being developed as a fast integrating area detector with wide dynamic range for time resolved applications at the upgraded Advanced Photon Source (APS.) A burst mode detector with intendedmore » $$\\mbox{13 $$MHz$}$ image rate, FASPAX will also incorporate a novel integration circuit to achieve wide dynamic range, from single photon sensitivity to $$10^{\\text{5}}$$ x-rays/pixel/pulse. To achieve these ambitious goals, a novel silicon sensor design is required. This paper will detail early design of the FASPAX sensor. Results from TCAD optimization studies, and characterization of prototype sensors will be presented.« less

Front end optimization for the monolithic active pixel sensor of the ALICE Inner Tracking System upgrade

NASA Astrophysics Data System (ADS)

Kim, D.; Aglieri Rinella, G.; Cavicchioli, C.; Chanlek, N.; Collu, A.; Degerli, Y.; Dorokhov, A.; Flouzat, C.; Gajanana, D.; Gao, C.; Guilloux, F.; Hillemanns, H.; Hristozkov, S.; Junique, A.; Keil, M.; Kofarago, M.; Kugathasan, T.; Kwon, Y.; Lattuca, A.; Mager, M.; Sielewicz, K. M.; Marin Tobon, C. A.; Marras, D.; Martinengo, P.; Mazza, G.; Mugnier, H.; Musa, L.; Pham, T. H.; Puggioni, C.; Reidt, F.; Riedler, P.; Rousset, J.; Siddhanta, S.; Snoeys, W.; Song, M.; Usai, G.; Van Hoorne, J. W.; Yang, P.

2016-02-01

ALICE plans to replace its Inner Tracking System during the second long shut down of the LHC in 2019 with a new 10 m2 tracker constructed entirely with monolithic active pixel sensors. The TowerJazz 180 nm CMOS imaging Sensor process has been selected to produce the sensor as it offers a deep pwell allowing full CMOS in-pixel circuitry and different starting materials. First full-scale prototypes have been fabricated and tested. Radiation tolerance has also been verified. In this paper the development of the charge sensitive front end and in particular its optimization for uniformity of charge threshold and time response will be presented.

New multirate sampled-data control law structure and synthesis algorithm

NASA Technical Reports Server (NTRS)

Berg, Martin C.; Mason, Gregory S.; Yang, Gen-Sheng

1992-01-01

A new multirate sampled-data control law structure is defined and a new parameter-optimization-based synthesis algorithm for that structure is introduced. The synthesis algorithm can be applied to multirate, multiple-input/multiple-output, sampled-data control laws having a prescribed dynamic order and structure, and a priori specified sampling/update rates for all sensors, processor states, and control inputs. The synthesis algorithm is applied to design two-input, two-output tip position controllers of various dynamic orders for a sixth-order, two-link robot arm model.

Applications of a shadow camera system for energy meteorology

NASA Astrophysics Data System (ADS)

Kuhn, Pascal; Wilbert, Stefan; Prahl, Christoph; Garsche, Dominik; Schüler, David; Haase, Thomas; Ramirez, Lourdes; Zarzalejo, Luis; Meyer, Angela; Blanc, Philippe; Pitz-Paal, Robert

2018-02-01

Downward-facing shadow cameras might play a major role in future energy meteorology. Shadow cameras directly image shadows on the ground from an elevated position. They are used to validate other systems (e.g. all-sky imager based nowcasting systems, cloud speed sensors or satellite forecasts) and can potentially provide short term forecasts for solar power plants. Such forecasts are needed for electricity grids with high penetrations of renewable energy and can help to optimize plant operations. In this publication, two key applications of shadow cameras are briefly presented.

Joint sparsity based heterogeneous data-level fusion for target detection and estimation

NASA Astrophysics Data System (ADS)

Niu, Ruixin; Zulch, Peter; Distasio, Marcello; Blasch, Erik; Shen, Dan; Chen, Genshe

2017-05-01

Typical surveillance systems employ decision- or feature-level fusion approaches to integrate heterogeneous sensor data, which are sub-optimal and incur information loss. In this paper, we investigate data-level heterogeneous sensor fusion. Since the sensors monitor the common targets of interest, whose states can be determined by only a few parameters, it is reasonable to assume that the measurement domain has a low intrinsic dimensionality. For heterogeneous sensor data, we develop a joint-sparse data-level fusion (JSDLF) approach based on the emerging joint sparse signal recovery techniques by discretizing the target state space. This approach is applied to fuse signals from multiple distributed radio frequency (RF) signal sensors and a video camera for joint target detection and state estimation. The JSDLF approach is data-driven and requires minimum prior information, since there is no need to know the time-varying RF signal amplitudes, or the image intensity of the targets. It can handle non-linearity in the sensor data due to state space discretization and the use of frequency/pixel selection matrices. Furthermore, for a multi-target case with J targets, the JSDLF approach only requires discretization in a single-target state space, instead of discretization in a J-target state space, as in the case of the generalized likelihood ratio test (GLRT) or the maximum likelihood estimator (MLE). Numerical examples are provided to demonstrate that the proposed JSDLF approach achieves excellent performance with near real-time accurate target position and velocity estimates.

Evaluation of a mass flow sensor at a gin

USDA-ARS?s Scientific Manuscript database

As part of a system to optimize the cotton ginning process, a custom-built mass flow sensor was evaluated at USDA-ARS Cotton Ginning Research Unit at Stoneville, Mississippi. The mass flow sensor was fabricated based on the principle of the sensor patented by Thomasson and Sui. The optical and ele...

Biomechanics of the Sensor–Tissue Interface—Effects of Motion, Pressure, and Design on Sensor Performance and Foreign Body Response—Part II: Examples and Application

PubMed Central

Helton, Kristen L; Ratner, Buddy D; Wisniewski, Natalie A

2011-01-01

This article is the second part of a two-part review in which we explore the biomechanics of the sensor–tissue interface as an important aspect of continuous glucose sensor biocompatibility. Part I, featured in this issue of Journal of Diabetes Science and Technology, describes a theoretical framework of how biomechanical factors such as motion and pressure (typically micromotion and micropressure) affect tissue physiology around a sensor and in turn, impact sensor performance. Here in Part II, a literature review is presented that summarizes examples of motion or pressure affecting sensor performance. Data are presented that show how both acute and chronic forces can impact continuous glucose monitor signals. Also presented are potential strategies for countering the ill effects of motion and pressure on glucose sensors. Improved engineering and optimized chemical biocompatibility have advanced sensor design and function, but we believe that mechanical biocompatibility, a rarely considered factor, must also be optimized in order to achieve an accurate, long-term, implantable sensor. PMID:21722579

A controllable sensor management algorithm capable of learning

NASA Astrophysics Data System (ADS)

Osadciw, Lisa A.; Veeramacheneni, Kalyan K.

2005-03-01

Sensor management technology progress is challenged by the geographic space it spans, the heterogeneity of the sensors, and the real-time timeframes within which plans controlling the assets are executed. This paper presents a new sensor management paradigm and demonstrates its application in a sensor management algorithm designed for a biometric access control system. This approach consists of an artificial intelligence (AI) algorithm focused on uncertainty measures, which makes the high level decisions to reduce uncertainties and interfaces with the user, integrated cohesively with a bottom up evolutionary algorithm, which optimizes the sensor network"s operation as determined by the AI algorithm. The sensor management algorithm presented is composed of a Bayesian network, the AI algorithm component, and a swarm optimization algorithm, the evolutionary algorithm. Thus, the algorithm can change its own performance goals in real-time and will modify its own decisions based on observed measures within the sensor network. The definition of the measures as well as the Bayesian network determine the robustness of the algorithm and its utility in reacting dynamically to changes in the global system.

Current sensor

DOEpatents

Yakymyshyn, Christopher Paul; Brubaker, Michael Allen; Yakymyshyn, Pamela Jane

2007-01-16

A current sensor is described that uses a plurality of magnetic field sensors positioned around a current carrying conductor. The sensor can be hinged to allow clamping to a conductor. The current sensor provides high measurement accuracy for both DC and AC currents, and is substantially immune to the effects of temperature, conductor position, nearby current carrying conductors and aging.

Probabilistic Multi-Sensor Fusion Based Indoor Positioning System on a Mobile Device

PubMed Central

He, Xiang; Aloi, Daniel N.; Li, Jia

2015-01-01

Nowadays, smart mobile devices include more and more sensors on board, such as motion sensors (accelerometer, gyroscope, magnetometer), wireless signal strength indicators (WiFi, Bluetooth, Zigbee), and visual sensors (LiDAR, camera). People have developed various indoor positioning techniques based on these sensors. In this paper, the probabilistic fusion of multiple sensors is investigated in a hidden Markov model (HMM) framework for mobile-device user-positioning. We propose a graph structure to store the model constructed by multiple sensors during the offline training phase, and a multimodal particle filter to seamlessly fuse the information during the online tracking phase. Based on our algorithm, we develop an indoor positioning system on the iOS platform. The experiments carried out in a typical indoor environment have shown promising results for our proposed algorithm and system design. PMID:26694387

Probabilistic Multi-Sensor Fusion Based Indoor Positioning System on a Mobile Device.

PubMed

He, Xiang; Aloi, Daniel N; Li, Jia

2015-12-14

Nowadays, smart mobile devices include more and more sensors on board, such as motion sensors (accelerometer, gyroscope, magnetometer), wireless signal strength indicators (WiFi, Bluetooth, Zigbee), and visual sensors (LiDAR, camera). People have developed various indoor positioning techniques based on these sensors. In this paper, the probabilistic fusion of multiple sensors is investigated in a hidden Markov model (HMM) framework for mobile-device user-positioning. We propose a graph structure to store the model constructed by multiple sensors during the offline training phase, and a multimodal particle filter to seamlessly fuse the information during the online tracking phase. Based on our algorithm, we develop an indoor positioning system on the iOS platform. The experiments carried out in a typical indoor environment have shown promising results for our proposed algorithm and system design.

Noise-cancelling quadrature magnetic position, speed and direction sensor

DOEpatents

Preston, Mark A.; King, Robert D.

1996-01-01

An array of three magnetic sensors in a single package is employed with a single bias magnet for sensing shaft position, speed and direction of a motor in a high magnetic noise environment. Two of the three magnetic sensors are situated in an anti-phase relationship (i.e., 180.degree. out-of-phase) with respect to the relationship between the other of the two sensors and magnetically salient target, and the third magnetic sensor is situated between the anti-phase sensors. The result is quadrature sensing with noise immunity for accurate relative position, speed and direction measurements.

An Alignment Method for the Integration of Underwater 3D Data Captured by a Stereovision System and an Acoustic Camera.

PubMed

Lagudi, Antonio; Bianco, Gianfranco; Muzzupappa, Maurizio; Bruno, Fabio

2016-04-14

The integration of underwater 3D data captured by acoustic and optical systems is a promising technique in various applications such as mapping or vehicle navigation. It allows for compensating the drawbacks of the low resolution of acoustic sensors and the limitations of optical sensors in bad visibility conditions. Aligning these data is a challenging problem, as it is hard to make a point-to-point correspondence. This paper presents a multi-sensor registration for the automatic integration of 3D data acquired from a stereovision system and a 3D acoustic camera in close-range acquisition. An appropriate rig has been used in the laboratory tests to determine the relative position between the two sensor frames. The experimental results show that our alignment approach, based on the acquisition of a rig in several poses, can be adopted to estimate the rigid transformation between the two heterogeneous sensors. A first estimation of the unknown geometric transformation is obtained by a registration of the two 3D point clouds, but it ends up to be strongly affected by noise and data dispersion. A robust and optimal estimation is obtained by a statistical processing of the transformations computed for each pose. The effectiveness of the method has been demonstrated in this first experimentation of the proposed 3D opto-acoustic camera.

An Alignment Method for the Integration of Underwater 3D Data Captured by a Stereovision System and an Acoustic Camera

PubMed Central

Lagudi, Antonio; Bianco, Gianfranco; Muzzupappa, Maurizio; Bruno, Fabio

2016-01-01

The integration of underwater 3D data captured by acoustic and optical systems is a promising technique in various applications such as mapping or vehicle navigation. It allows for compensating the drawbacks of the low resolution of acoustic sensors and the limitations of optical sensors in bad visibility conditions. Aligning these data is a challenging problem, as it is hard to make a point-to-point correspondence. This paper presents a multi-sensor registration for the automatic integration of 3D data acquired from a stereovision system and a 3D acoustic camera in close-range acquisition. An appropriate rig has been used in the laboratory tests to determine the relative position between the two sensor frames. The experimental results show that our alignment approach, based on the acquisition of a rig in several poses, can be adopted to estimate the rigid transformation between the two heterogeneous sensors. A first estimation of the unknown geometric transformation is obtained by a registration of the two 3D point clouds, but it ends up to be strongly affected by noise and data dispersion. A robust and optimal estimation is obtained by a statistical processing of the transformations computed for each pose. The effectiveness of the method has been demonstrated in this first experimentation of the proposed 3D opto-acoustic camera. PMID:27089344

Gaussian Decomposition of Laser Altimeter Waveforms

NASA Technical Reports Server (NTRS)

Hofton, Michelle A.; Minster, J. Bernard; Blair, J. Bryan

1999-01-01

We develop a method to decompose a laser altimeter return waveform into its Gaussian components assuming that the position of each Gaussian within the waveform can be used to calculate the mean elevation of a specific reflecting surface within the laser footprint. We estimate the number of Gaussian components from the number of inflection points of a smoothed copy of the laser waveform, and obtain initial estimates of the Gaussian half-widths and positions from the positions of its consecutive inflection points. Initial amplitude estimates are obtained using a non-negative least-squares method. To reduce the likelihood of fitting the background noise within the waveform and to minimize the number of Gaussians needed in the approximation, we rank the "importance" of each Gaussian in the decomposition using its initial half-width and amplitude estimates. The initial parameter estimates of all Gaussians ranked "important" are optimized using the Levenburg-Marquardt method. If the sum of the Gaussians does not approximate the return waveform to a prescribed accuracy, then additional Gaussians are included in the optimization procedure. The Gaussian decomposition method is demonstrated on data collected by the airborne Laser Vegetation Imaging Sensor (LVIS) in October 1997 over the Sequoia National Forest, California.

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.

Self-evaluation on Motion Adaptation for Service Robots

NASA Astrophysics Data System (ADS)

Funabora, Yuki; Yano, Yoshikazu; Doki, Shinji; Okuma, Shigeru

We suggest self motion evaluation method to adapt to environmental changes for service robots. Several motions such as walking, dancing, demonstration and so on are described with time series patterns. These motions are optimized with the architecture of the robot and under certain surrounding environment. Under unknown operating environment, robots cannot accomplish their tasks. We propose autonomous motion generation techniques based on heuristic search with histories of internal sensor values. New motion patterns are explored under unknown operating environment based on self-evaluation. Robot has some prepared motions which realize the tasks under the designed environment. Internal sensor values observed under the designed environment with prepared motions show the interaction results with the environment. Self-evaluation is composed of difference of internal sensor values between designed environment and unknown operating environment. Proposed method modifies the motions to synchronize the interaction results on both environment. New motion patterns are generated to maximize self-evaluation function without external information, such as run length, global position of robot, human observation and so on. Experimental results show that the possibility to adapt autonomously patterned motions to environmental changes.

Pulsed laser deposited ZnO film on side-polished fiber as a gas sensing element.

PubMed

Dikovska, Anna Og; Atanasov, Petar A; Stoyanchov, Toshko R; Andreev, Andrey T; Karakoleva, Elka I; Zafirova, Blagovesta S

2007-05-01

A simple sensor element consisting of a side-polished single-mode fiber and a planar metal oxide waveguide is described. The thin ZnO planar waveguide was produced on the polished fiber surface by pulsed laser deposition at optimized processing parameters. A measurement scheme for in situ control of the film thickness during the deposition process was developed and used. X-ray diffraction measurements and scanning electron microscopy were used to characterize the structure and the surface morphology of the planar waveguide, respectively. The numerical evaluation of the sensor sensitivity predicts the possibility to detect refractive index changes of less than 10(-4). Furthermore, preliminary gas sensor tests were performed by using a mixture of 1.5% butane diluted in N(2) and pure butane. A shift of the spectral position of the resonance points was observed from 3 to 5 s after gas exposure, which corresponds to refractive index changes of 3 x 10(-5) and 1.2 x 10(-3) for 1.5% butane and for pure butane, respectively.

A comparison of long-term parallel measurements of sunshine duration obtained with a Campbell-Stokes sunshine recorder and two automated sunshine sensors

NASA Astrophysics Data System (ADS)

Baumgartner, D. J.; Pötzi, W.; Freislich, H.; Strutzmann, H.; Veronig, A. M.; Foelsche, U.; Rieder, H. E.

2017-06-01

In recent decades, automated sensors for sunshine duration (SD) measurements have been introduced in meteorological networks, thereby replacing traditional instruments, most prominently the Campbell-Stokes (CS) sunshine recorder. Parallel records of automated and traditional SD recording systems are rare. Nevertheless, such records are important to understand the differences/similarities in SD totals obtained with different instruments and how changes in monitoring device type affect the homogeneity of SD records. This study investigates the differences/similarities in parallel SD records obtained with a CS and two automated SD sensors between 2007 and 2016 at the Kanzelhöhe Observatory, Austria. Comparing individual records of daily SD totals, we find differences of both positive and negative sign, with smallest differences between the automated sensors. The larger differences between CS-derived SD totals and those from automated sensors can be attributed (largely) to the higher sensitivity threshold of the CS instrument. Correspondingly, the closest agreement among all sensors is found during summer, the time of year when sensitivity thresholds are least critical. Furthermore, we investigate the performance of various models to create the so-called sensor-type-equivalent (STE) SD records. Our analysis shows that regression models including all available data on daily (or monthly) time scale perform better than simple three- (or four-) point regression models. Despite general good performance, none of the considered regression models (of linear or quadratic form) emerges as the "optimal" model. Although STEs prove useful for relating SD records of individual sensors on daily/monthly time scales, this does not ensure that STE (or joint) records can be used for trend analysis.

Non-traditional Sensor Tasking for SSA: A Case Study

NASA Astrophysics Data System (ADS)

Herz, A.; Herz, E.; Center, K.; Martinez, I.; Favero, N.; Clark, C.; Therien, W.; Jeffries, M.

Industry has recognized that maintaining SSA of the orbital environment going forward is too challenging for the government alone. Consequently there are a significant number of commercial activities in various stages of development standing-up novel sensors and sensor networks to assist in SSA gathering and dissemination. Use of these systems will allow government and military operators to focus on the most sensitive space control issues while allocating routine or lower priority data gathering responsibility to the commercial side. The fact that there will be multiple (perhaps many) commercial sensor capabilities available in this new operational model begets a common access solution. Absent a central access point to assert data needs, optimized use of all commercial sensor resources is not possible and the opportunity for coordinated collections satisfying overarching SSA-elevating objectives is lost. Orbit Logic is maturing its Heimdall Web system - an architecture facilitating “data requestor” perspectives (allowing government operations centers to assert SSA data gathering objectives) and “sensor operator” perspectives (through which multiple sensors of varying phenomenology and capability are integrated via machine -machine interfaces). When requestors submit their needs, Heimdall’s planning engine determines tasking schedules across all sensors, optimizing their use via an SSA-specific figure-of-merit. ExoAnalytic was a key partner in refining the sensor operator interfaces, working with Orbit Logic through specific details of sensor tasking schedule delivery and the return of observation data. Scant preparation on both sides preceded several integration exercises (walk-then-run style), which culminated in successful demonstration of the ability to supply optimized schedules for routine public catalog data collection – then adapt sensor tasking schedules in real-time upon receipt of urgent data collection requests. This paper will provide a narrative of the joint integration process - detailing decision points, compromises, and results obtained on the road toward a set of interoperability standards for commercial sensor accommodation.

Computational design and multivariate optimization of an electrochemical metoprolol sensor based on molecular imprinting in combination with carbon nanotubes.

PubMed

Nezhadali, Azizollah; Mojarrab, Maliheh

2016-06-14

This work describes the development of an electrochemical sensor based on a new molecularly imprinted polymer for detection of metoprolol (MTP) at ultra-trace level. The polypyrrole (PPy) was electrochemically synthesized on the tip of a pencil graphite electrode (PGE) which modified whit functionalized multi-walled carbon nanotubes (MWCNTs). The fabrication process of the sensor was characterized by cyclic voltammetry (CV) and the measurement process was carried out by differential pulse voltammetry (DPV). A computational approach was used to screening functional monomers and polymerization solvent for rational design of molecularly imprinted polymer (MIP). Based on computational results, pyrrole and water were selected as functional monomer and polymerization solvent, respectively. Several significant parameters controlling the performance of the MIP sensor were examined and optimized using multivariate optimization methods such as Plackett-Burman design (PBD) and central composite design (CCD). Under the selected optimal conditions, MIP sensor was showed a linear range from 0.06 to 490 μmol L(-1) MTP, a limit of detection of 2.88 nmol L(-1), a highly reproducible response (RSD 3.9%) and a good selectivity in the presence of structurally related molecules. Furthermore, the applicability of the method was successfully tested with determination of MTP in real samples (tablet, and serum). Copyright © 2016 Elsevier B.V. All rights reserved.

Sensors Workshop summary report

NASA Technical Reports Server (NTRS)

1977-01-01

A review of the efforts of three workshops is presented. The presentation describes those technological developments that would contribute most to sensor subsystem optimization and improvement of NASA's data acquisition capabilities, and summarizes the recommendations of the sensor technology panels from the most recent workshops.

Contact position sensor using constant contact force control system

NASA Technical Reports Server (NTRS)

Sturdevant, Jay (Inventor)

1995-01-01

A force control system (50) and method are provided for controlling a position contact sensor (10) so as to produce a constant controlled contact force therewith. The system (50) includes a contact position sensor (10) which has a contact probe (12) for contacting the surface of a target to be measured and an output signal (V.sub.o) for providing a position indication thereof. An actuator (30) is provided for controllably driving the contact position sensor (10) in response to an actuation control signal (I). A controller (52) receives the position indication signal (V.sub.o) and generates in response thereto the actuation control signal (I) so as to provide a substantially constant selective force (F) exerted by the contact probe (12). The actuation drive signal (I) is generated further in response to substantially linear approximation curves based on predetermined force and position data attained from the sensor (10) and the actuator (30).

Dynamically Timed Electric Motor

NASA Technical Reports Server (NTRS)

Casper, Ann M. (Inventor)

1997-01-01

A brushless DC motor including a housing having an end cap secured thereto. The housing encloses a rotor. a stator and a rotationally displaceable commutation board having sensors secured thereon and spaced around the periphery of the rotor. An external rotational force is applied to the commutation board for displacement of the sensors to various positions whereby varying feedback signals are generated by the positioning of the sensors relative to the rotating rotor. The commutation board is secured in a fixed position in response to feedback signals indicative of optimum sensor position being determined. The rotation of the commutation board and the securing of the sensors in the desired fixed position is accomplished without requiring the removal of the end cap and with the DC motor operating.

Method for Vibration Response Simulation and Sensor Placement Optimization of a Machine Tool Spindle System with a Bearing Defect

PubMed Central

Cao, Hongrui; Niu, Linkai; He, Zhengjia

2012-01-01

Bearing defects are one of the most important mechanical sources for vibration and noise generation in machine tool spindles. In this study, an integrated finite element (FE) model is proposed to predict the vibration responses of a spindle bearing system with localized bearing defects and then the sensor placement for better detection of bearing faults is optimized. A nonlinear bearing model is developed based on Jones' bearing theory, while the drawbar, shaft and housing are modeled as Timoshenko's beam. The bearing model is then integrated into the FE model of drawbar/shaft/housing by assembling equations of motion. The Newmark time integration method is used to solve the vibration responses numerically. The FE model of the spindle-bearing system was verified by conducting dynamic tests. Then, the localized bearing defects were modeled and vibration responses generated by the outer ring defect were simulated as an illustration. The optimization scheme of the sensor placement was carried out on the test spindle. The results proved that, the optimal sensor placement depends on the vibration modes under different boundary conditions and the transfer path between the excitation and the response. PMID:23012514

Observability-Based Guidance and Sensor Placement

NASA Astrophysics Data System (ADS)

Hinson, Brian T.

Control system performance is highly dependent on the quality of sensor information available. In a growing number of applications, however, the control task must be accomplished with limited sensing capabilities. This thesis addresses these types of problems from a control-theoretic point-of-view, leveraging system nonlinearities to improve sensing performance. Using measures of observability as an information quality metric, guidance trajectories and sensor distributions are designed to improve the quality of sensor information. An observability-based sensor placement algorithm is developed to compute optimal sensor configurations for a general nonlinear system. The algorithm utilizes a simulation of the nonlinear system as the source of input data, and convex optimization provides a scalable solution method. The sensor placement algorithm is applied to a study of gyroscopic sensing in insect wings. The sensor placement algorithm reveals information-rich areas on flexible insect wings, and a comparison to biological data suggests that insect wings are capable of acting as gyroscopic sensors. An observability-based guidance framework is developed for robotic navigation with limited inertial sensing. Guidance trajectories and algorithms are developed for range-only and bearing-only navigation that improve navigation accuracy. Simulations and experiments with an underwater vehicle demonstrate that the observability measure allows tuning of the navigation uncertainty.

Optimizing Cluster Heads for Energy Efficiency in Large-Scale Heterogeneous Wireless Sensor Networks

DOE PAGES

Gu, Yi; Wu, Qishi; Rao, Nageswara S. V.

2010-01-01

Many complex sensor network applications require deploying a large number of inexpensive and small sensors in a vast geographical region to achieve quality through quantity. Hierarchical clustering is generally considered as an efficient and scalable way to facilitate the management and operation of such large-scale networks and minimize the total energy consumption for prolonged lifetime. Judicious selection of cluster heads for data integration and communication is critical to the success of applications based on hierarchical sensor networks organized as layered clusters. We investigate the problem of selecting sensor nodes in a predeployed sensor network to be the cluster heads tomore » minimize the total energy needed for data gathering. We rigorously derive an analytical formula to optimize the number of cluster heads in sensor networks under uniform node distribution, and propose a Distance-based Crowdedness Clustering algorithm to determine the cluster heads in sensor networks under general node distribution. The results from an extensive set of experiments on a large number of simulated sensor networks illustrate the performance superiority of the proposed solution over the clustering schemes based on k -means algorithm.« less

Robust Operation of Tendon-Driven Robot Fingers Using Force and Position-Based Control Laws

NASA Technical Reports Server (NTRS)

Hargrave, Brian (Inventor); Abdallah, Muhammad E (Inventor); Reiland, Matthew J (Inventor); Diftler, Myron A (Inventor); Strawser, Philip A (Inventor); Platt, Jr., Robert J. (Inventor); Ihrke, Chris A. (Inventor)

2013-01-01

A robotic system includes a tendon-driven finger and a control system. The system controls the finger via a force-based control law when a tension sensor is available, and via a position-based control law when a sensor is not available. Multiple tendons may each have a corresponding sensor. The system selectively injects a compliance value into the position-based control law when only some sensors are available. A control system includes a host machine and a non-transitory computer-readable medium having a control process, which is executed by the host machine to control the finger via the force- or position-based control law. A method for controlling the finger includes determining the availability of a tension sensor(s), and selectively controlling the finger, using the control system, via the force or position-based control law. The position control law allows the control system to resist disturbances while nominally maintaining the initial state of internal tendon tensions.

Operational load estimation of a smart wind turbine rotor blade

NASA Astrophysics Data System (ADS)

White, Jonathan R.; Adams, Douglas E.; Rumsey, Mark A.

2009-03-01

Rising energy prices and carbon emission standards are driving a fundamental shift from fossil fuels to alternative sources of energy such as biofuel, solar, wind, clean coal and nuclear. In 2008, the U.S. installed 8,358 MW of new wind capacity increasing the total installed wind power by 50% to 25,170 MW. A key technology to improve the efficiency of wind turbines is smart rotor blades that can monitor the physical loads being applied by the wind and then adapt the airfoil for increased energy capture. For extreme wind and gust events, the airfoil could be changed to reduce the loads to prevent excessive fatigue or catastrophic failure. Knowledge of the actual loading to the turbine is also useful for maintenance planning and design improvements. In this work, an array of uniaxial and triaxial accelerometers was integrally manufactured into a 9m smart rotor blade. DC type accelerometers were utilized in order to estimate the loading and deflection from both quasi-steady-state and dynamic events. A method is presented that designs an estimator of the rotor blade static deflection and loading and then optimizes the placement of the sensor(s). Example results show that the method can identify the optimal location for the sensor for both simple example cases and realistic complex loading. The optimal location of a single sensor shifts towards the tip as the curvature of the blade deflection increases with increasingly complex wind loading. The framework developed is practical for the expansion of sensor optimization in more complex blade models and for higher numbers of sensors.

A Game Theoretic Optimization Method for Energy Efficient Global Connectivity in Hybrid Wireless Sensor Networks

PubMed Central

Lee, JongHyup; Pak, Dohyun

2016-01-01

For practical deployment of wireless sensor networks (WSN), WSNs construct clusters, where a sensor node communicates with other nodes in its cluster, and a cluster head support connectivity between the sensor nodes and a sink node. In hybrid WSNs, cluster heads have cellular network interfaces for global connectivity. However, when WSNs are active and the load of cellular networks is high, the optimal assignment of cluster heads to base stations becomes critical. Therefore, in this paper, we propose a game theoretic model to find the optimal assignment of base stations for hybrid WSNs. Since the communication and energy cost is different according to cellular systems, we devise two game models for TDMA/FDMA and CDMA systems employing power prices to adapt to the varying efficiency of recent wireless technologies. The proposed model is defined on the assumptions of the ideal sensing field, but our evaluation shows that the proposed model is more adaptive and energy efficient than local selections. PMID:27589743

A MEMS-based Benzene Gas Sensor with a Self-heating WO3 Sensing Layer

PubMed Central

Ke, Ming-Tsun; Lee, Mu-Tsun; Lee, Chia-Yen; Fu, Lung-Ming

2009-01-01

In the study, a MEMS-based benzene gas sensor is presented, consisting of a quartz substrate, a thin-film WO3 sensing layer, an integrated Pt micro-heater, and Pt interdigitated electrodes (IDEs). When benzene is present in the atmosphere, oxidation occurs on the heated WO3 sensing layer. This causes a change in the electrical conductivity of the WO3 film, and hence changes the resistance between the IDEs. The benzene concentration is then computed from the change in the measured resistance. A specific orientation of the WO3 layer is obtained by optimizing the sputtering process parameters. It is found that the sensitivity of the gas sensor is optimized at a working temperature of 300 °C. At the optimal working temperature, the experimental results show that the sensor has a high degree of sensitivity (1.0 KΩ ppm−1), a low detection limit (0.2 ppm) and a rapid response time (35 s). PMID:22574052

Self-Learning Variable Structure Control for a Class of Sensor-Actuator Systems

PubMed Central

Chen, Sanfeng; Li, Shuai; Liu, Bo; Lou, Yuesheng; Liang, Yongsheng

2012-01-01

Variable structure strategy is widely used for the control of sensor-actuator systems modeled by Euler-Lagrange equations. However, accurate knowledge on the model structure and model parameters are often required for the control design. In this paper, we consider model-free variable structure control of a class of sensor-actuator systems, where only the online input and output of the system are available while the mathematic model of the system is unknown. The problem is formulated from an optimal control perspective and the implicit form of the control law are analytically obtained by using the principle of optimality. The control law and the optimal cost function are explicitly solved iteratively. Simulations demonstrate the effectiveness and the efficiency of the proposed method. PMID:22778633

Energy aware swarm optimization with intercluster search for wireless sensor network.

PubMed

Thilagavathi, Shanmugasundaram; Geetha, Bhavani Gnanasambandan

2015-01-01

Wireless sensor networks (WSNs) are emerging as a low cost popular solution for many real-world challenges. The low cost ensures deployment of large sensor arrays to perform military and civilian tasks. Generally, WSNs are power constrained due to their unique deployment method which makes replacement of battery source difficult. Challenges in WSN include a well-organized communication platform for the network with negligible power utilization. In this work, an improved binary particle swarm optimization (PSO) algorithm with modified connected dominating set (CDS) based on residual energy is proposed for discovery of optimal number of clusters and cluster head (CH). Simulations show that the proposed BPSO-T and BPSO-EADS perform better than LEACH- and PSO-based system in terms of energy savings and QOS.

A transmission power optimization with a minimum node degree for energy-efficient wireless sensor networks with full-reachability.

PubMed

Chen, Yi-Ting; Horng, Mong-Fong; Lo, Chih-Cheng; Chu, Shu-Chuan; Pan, Jeng-Shyang; Liao, Bin-Yih

2013-03-20

Transmission power optimization is the most significant factor in prolonging the lifetime and maintaining the connection quality of wireless sensor networks. Un-optimized transmission power of nodes either interferes with or fails to link neighboring nodes. The optimization of transmission power depends on the expected node degree and node distribution. In this study, an optimization approach to an energy-efficient and full reachability wireless sensor network is proposed. In the proposed approach, an adjustment model of the transmission range with a minimum node degree is proposed that focuses on topology control and optimization of the transmission range according to node degree and node density. The model adjusts the tradeoff between energy efficiency and full reachability to obtain an ideal transmission range. In addition, connectivity and reachability are used as performance indices to evaluate the connection quality of a network. The two indices are compared to demonstrate the practicability of framework through simulation results. Furthermore, the relationship between the indices under the conditions of various node degrees is analyzed to generalize the characteristics of node densities. The research results on the reliability and feasibility of the proposed approach will benefit the future real deployments.

A Transmission Power Optimization with a Minimum Node Degree for Energy-Efficient Wireless Sensor Networks with Full-Reachability

PubMed Central

Chen, Yi-Ting; Horng, Mong-Fong; Lo, Chih-Cheng; Chu, Shu-Chuan; Pan, Jeng-Shyang; Liao, Bin-Yih

2013-01-01

Transmission power optimization is the most significant factor in prolonging the lifetime and maintaining the connection quality of wireless sensor networks. Un-optimized transmission power of nodes either interferes with or fails to link neighboring nodes. The optimization of transmission power depends on the expected node degree and node distribution. In this study, an optimization approach to an energy-efficient and full reachability wireless sensor network is proposed. In the proposed approach, an adjustment model of the transmission range with a minimum node degree is proposed that focuses on topology control and optimization of the transmission range according to node degree and node density. The model adjusts the tradeoff between energy efficiency and full reachability to obtain an ideal transmission range. In addition, connectivity and reachability are used as performance indices to evaluate the connection quality of a network. The two indices are compared to demonstrate the practicability of framework through simulation results. Furthermore, the relationship between the indices under the conditions of various node degrees is analyzed to generalize the characteristics of node densities. The research results on the reliability and feasibility of the proposed approach will benefit the future real deployments. PMID:23519351

Localizing on-scalp MEG sensors using an array of magnetic dipole coils.

PubMed

Pfeiffer, Christoph; Andersen, Lau M; Lundqvist, Daniel; Hämäläinen, Matti; Schneiderman, Justin F; Oostenveld, Robert

2018-01-01

Accurate estimation of the neural activity underlying magnetoencephalography (MEG) signals requires co-registration i.e., determination of the position and orientation of the sensors with respect to the head. In modern MEG systems, an array of hundreds of low-Tc SQUID sensors is used to localize a set of small, magnetic dipole-like (head-position indicator, HPI) coils that are attached to the subject's head. With accurate prior knowledge of the positions and orientations of the sensors with respect to one another, the HPI coils can be localized with high precision, and thereby the positions of the sensors in relation to the head. With advances in magnetic field sensing technologies, e.g., high-Tc SQUIDs and optically pumped magnetometers (OPM), that require less extreme operating temperatures than low-Tc SQUID sensors, on-scalp MEG is on the horizon. To utilize the full potential of on-scalp MEG, flexible sensor arrays are preferable. Conventional co-registration is impractical for such systems as the relative positions and orientations of the sensors to each other are subject-specific and hence not known a priori. Herein, we present a method for co-registration of on-scalp MEG sensors. We propose to invert the conventional co-registration approach and localize the sensors relative to an array of HPI coils on the subject's head. We show that given accurate prior knowledge of the positions of the HPI coils with respect to one another, the sensors can be localized with high precision. We simulated our method with realistic parameters and layouts for sensor and coil arrays. Results indicate co-registration is possible with sub-millimeter accuracy, but the performance strongly depends upon a number of factors. Accurate calibration of the coils and precise determination of the positions and orientations of the coils with respect to one another are crucial. Finally, we propose methods to tackle practical challenges to further improve the method.

Localizing on-scalp MEG sensors using an array of magnetic dipole coils

PubMed Central

Andersen, Lau M.; Lundqvist, Daniel; Hämäläinen, Matti; Schneiderman, Justin F.; Oostenveld, Robert

2018-01-01

Accurate estimation of the neural activity underlying magnetoencephalography (MEG) signals requires co-registration i.e., determination of the position and orientation of the sensors with respect to the head. In modern MEG systems, an array of hundreds of low-Tc SQUID sensors is used to localize a set of small, magnetic dipole-like (head-position indicator, HPI) coils that are attached to the subject’s head. With accurate prior knowledge of the positions and orientations of the sensors with respect to one another, the HPI coils can be localized with high precision, and thereby the positions of the sensors in relation to the head. With advances in magnetic field sensing technologies, e.g., high-Tc SQUIDs and optically pumped magnetometers (OPM), that require less extreme operating temperatures than low-Tc SQUID sensors, on-scalp MEG is on the horizon. To utilize the full potential of on-scalp MEG, flexible sensor arrays are preferable. Conventional co-registration is impractical for such systems as the relative positions and orientations of the sensors to each other are subject-specific and hence not known a priori. Herein, we present a method for co-registration of on-scalp MEG sensors. We propose to invert the conventional co-registration approach and localize the sensors relative to an array of HPI coils on the subject’s head. We show that given accurate prior knowledge of the positions of the HPI coils with respect to one another, the sensors can be localized with high precision. We simulated our method with realistic parameters and layouts for sensor and coil arrays. Results indicate co-registration is possible with sub-millimeter accuracy, but the performance strongly depends upon a number of factors. Accurate calibration of the coils and precise determination of the positions and orientations of the coils with respect to one another are crucial. Finally, we propose methods to tackle practical challenges to further improve the method. PMID:29746486

Relative Navigation for Formation Flying of Spacecraft

NASA Technical Reports Server (NTRS)

Alonso, Roberto; Du, Ju-Young; Hughes, Declan; Junkins, John L.; Crassidis, John L.

2001-01-01

This paper presents a robust and efficient approach for relative navigation and attitude estimation of spacecraft flying in formation. This approach uses measurements from a new optical sensor that provides a line of sight vector from the master spacecraft to the secondary satellite. The overall system provides a novel, reliable, and autonomous relative navigation and attitude determination system, employing relatively simple electronic circuits with modest digital signal processing requirements and is fully independent of any external systems. Experimental calibration results are presented, which are used to achieve accurate line of sight measurements. State estimation for formation flying is achieved through an optimal observer design. Also, because the rotational and translational motions are coupled through the observation vectors, three approaches are suggested to separate both signals just for stability analysis. Simulation and experimental results indicate that the combined sensor/estimator approach provides accurate relative position and attitude estimates.

Power Maximization Control of Variable Speed Wind Generation System Using Permanent Magnet Synchronous Generator

NASA Astrophysics Data System (ADS)

Morimoto, Shigeo; Nakamura, Tomohiko; Takeda, Yoji

This paper proposes the sensorless output power maximization control of the wind generation system. A permanent magnet synchronous generator (PMSG) is used as a variable speed generator in the proposed system. The generator torque is suitably controlled according to the generator speed and thus the power from a wind turbine settles down on the maximum power point by the proposed MPPT control method, where the information of wind velocity is not required. Moreover, the maximum available generated power is obtained by the optimum current vector control. The current vector of PMSG is optimally controlled according to the generator speed and the required torque in order to minimize the losses of PMSG considering the voltage and current constraints. The proposed wind power generation system can be achieved without mechanical sensors such as a wind velocity detector and a position sensor. Several experimental results show the effectiveness of the proposed control method.

Constructive Engineering of Simulations

NASA Technical Reports Server (NTRS)

Snyder, Daniel R.; Barsness, Brendan

2011-01-01

Joint experimentation that investigates sensor optimization, re-tasking and management has far reaching implications for Department of Defense, Interagency and multinational partners. An adaption of traditional human in the loop (HITL) Modeling and Simulation (M&S) was one approach used to generate the findings necessary to derive and support these implications. Here an entity-based simulation was re-engineered to run on USJFCOM's High Performance Computer (HPC). The HPC was used to support the vast number of constructive runs necessary to produce statistically significant data in a timely manner. Then from the resulting sensitivity analysis, event designers blended the necessary visualization and decision making components into a synthetic environment for the HITL simulations trials. These trials focused on areas where human decision making had the greatest impact on the sensor investigations. Thus, this paper discusses how re-engineering existing M&S for constructive applications can positively influence the design of an associated HITL experiment.

Assessment of navigation cues with proximal force sensing during endovascular catheterization.

PubMed

Rafii-Taril, Hedyeh; Payne, Christopher J; Riga, Celia; Bicknell, Colin; Lee, Su-Lin; Yang, Guang-Zhong

2012-01-01

Despite increased use of robotic catheter navigation systems for endovascular intervention procedures, current master-slave platforms have not yet taken into account dexterous manipulation skill used in traditional catheterization procedures. Information on tool forces applied by operators is often limited. A novel force/torque sensor is developed in this paper to obtain behavioural data across different experience levels and identify underlying factors that affect overall operator performance. The miniature device can be attached to any part of the proximal end of the catheter, together with a position sensor attached to the catheter tip, for relating tool forces to catheter dynamics and overall performance. The results show clear differences in manipulation skills between experience groups, thus providing insights into different patterns and range of forces applied during routine endovascular procedures. They also provide important design specifications for ergonomically optimized catheter manipulation platforms with added haptic feedback while maintaining natural skills of the operators.

Optimization of Emissions Sensor Networks Incorporating Tradeoffs Between Different Sensor Technologies

NASA Astrophysics Data System (ADS)

Nicholson, B.; Klise, K. A.; Laird, C. D.; Ravikumar, A. P.; Brandt, A. R.

2017-12-01

In order to comply with current and future methane emissions regulations, natural gas producers must develop emissions monitoring strategies for their facilities. In addition, regulators must develop air monitoring strategies over wide areas incorporating multiple facilities. However, in both of these cases, only a limited number of sensors can be deployed. With a wide variety of sensors to choose from in terms of cost, precision, accuracy, spatial coverage, location, orientation, and sampling frequency, it is difficult to design robust monitoring strategies for different scenarios while systematically considering the tradeoffs between different sensor technologies. In addition, the geography, weather, and other site specific conditions can have a large impact on the performance of a sensor network. In this work, we demonstrate methods for calculating optimal sensor networks. Our approach can incorporate tradeoffs between vastly different sensor technologies, optimize over typical wind conditions for a particular area, and consider different objectives such as time to detection or geographic coverage. We do this by pre-computing site specific scenarios and using them as input to a mixed-integer, stochastic programming problem that solves for a sensor network that maximizes the effectiveness of the detection program. Our methods and approach have been incorporated within an open source Python package called Chama with the goal of providing facility operators and regulators with tools for designing more effective and efficient monitoring systems. Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energys National Nuclear Security Administration under contract DE-NA0003525.

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.

Development of a Hydrogen Peroxide Sensor Based on Screen-Printed Electrodes Modified with Inkjet-Printed Prussian Blue Nanoparticles

PubMed Central

Cinti, Stefano; Arduini, Fabiana; Moscone, Danila; Palleschi, Giuseppe; Killard, Anthony J.

2014-01-01

A sensor for the simple and sensitive measurement of hydrogen peroxide has been developed which is based on screen printed electrodes (SPEs) modified with Prussian blue nanoparticles (PBNPs) deposited using piezoelectric inkjet printing. PBNP-modified SPEs were characterized using physical and electrochemical techniques to optimize the PBNP layer thickness and electroanalytical conditions for optimum measurement of hydrogen peroxide. Sensor optimization resulted in a limit of detection of 2 × 10−7 M, a linear range from 0 to 4.5 mM and a sensitivity of 762 μA·mM−1·cm−2 which was achieved using 20 layers of printed PBNPs. Sensors also demonstrated excellent reproducibility (<5% rsd). PMID:25093348

Development of a novel pH sensor based upon Janus Green B immobilized on triacetyl cellulose membrane: Experimental design and optimization.

PubMed

Chamkouri, Narges; Niazi, Ali; Zare-Shahabadi, Vali

2016-03-05

A novel pH optical sensor was prepared by immobilizing an azo dye called Janus Green B on the triacetylcellulose membrane. Condition of the dye solution used in the immobilization step, including concentration of the dye, pH, and duration were considered and optimized using the Box-Behnken design. The proposed sensor showed good behavior and precision (RSD<5%) in the pH range of 2.0-10.0. Advantages of this optical sensor include on-line applicability, no leakage, long-term stability (more than 6 months), fast response time (less than 1 min), high selectivity and sensitivity as well as good reversibility and reproducibility. Copyright © 2015. Published by Elsevier B.V.

Parallel multi-join query optimization algorithm for distributed sensor network in the internet of things

NASA Astrophysics Data System (ADS)

Zheng, Yan

2015-03-01

Internet of things (IoT), focusing on providing users with information exchange and intelligent control, attracts a lot of attention of researchers from all over the world since the beginning of this century. IoT is consisted of large scale of sensor nodes and data processing units, and the most important features of IoT can be illustrated as energy confinement, efficient communication and high redundancy. With the sensor nodes increment, the communication efficiency and the available communication band width become bottle necks. Many research work is based on the instance which the number of joins is less. However, it is not proper to the increasing multi-join query in whole internet of things. To improve the communication efficiency between parallel units in the distributed sensor network, this paper proposed parallel query optimization algorithm based on distribution attributes cost graph. The storage information relations and the network communication cost are considered in this algorithm, and an optimized information changing rule is established. The experimental result shows that the algorithm has good performance, and it would effectively use the resource of each node in the distributed sensor network. Therefore, executive efficiency of multi-join query between different nodes could be improved.

Celestial Object Imaging Model and Parameter Optimization for an Optical Navigation Sensor Based on the Well Capacity Adjusting Scheme.

PubMed

Wang, Hao; Jiang, Jie; Zhang, Guangjun

2017-04-21

The simultaneous extraction of optical navigation measurements from a target celestial body and star images is essential for autonomous optical navigation. Generally, a single optical navigation sensor cannot simultaneously image the target celestial body and stars well-exposed because their irradiance difference is generally large. Multi-sensor integration or complex image processing algorithms are commonly utilized to solve the said problem. This study analyzes and demonstrates the feasibility of simultaneously imaging the target celestial body and stars well-exposed within a single exposure through a single field of view (FOV) optical navigation sensor using the well capacity adjusting (WCA) scheme. First, the irradiance characteristics of the celestial body are analyzed. Then, the celestial body edge model and star spot imaging model are established when the WCA scheme is applied. Furthermore, the effect of exposure parameters on the accuracy of star centroiding and edge extraction is analyzed using the proposed model. Optimal exposure parameters are also derived by conducting Monte Carlo simulation to obtain the best performance of the navigation sensor. Finally, laboratorial and night sky experiments are performed to validate the correctness of the proposed model and optimal exposure parameters.

Celestial Object Imaging Model and Parameter Optimization for an Optical Navigation Sensor Based on the Well Capacity Adjusting Scheme

PubMed Central

Wang, Hao; Jiang, Jie; Zhang, Guangjun

2017-01-01

The simultaneous extraction of optical navigation measurements from a target celestial body and star images is essential for autonomous optical navigation. Generally, a single optical navigation sensor cannot simultaneously image the target celestial body and stars well-exposed because their irradiance difference is generally large. Multi-sensor integration or complex image processing algorithms are commonly utilized to solve the said problem. This study analyzes and demonstrates the feasibility of simultaneously imaging the target celestial body and stars well-exposed within a single exposure through a single field of view (FOV) optical navigation sensor using the well capacity adjusting (WCA) scheme. First, the irradiance characteristics of the celestial body are analyzed. Then, the celestial body edge model and star spot imaging model are established when the WCA scheme is applied. Furthermore, the effect of exposure parameters on the accuracy of star centroiding and edge extraction is analyzed using the proposed model. Optimal exposure parameters are also derived by conducting Monte Carlo simulation to obtain the best performance of the navigation sensor. Finally, laboratorial and night sky experiments are performed to validate the correctness of the proposed model and optimal exposure parameters. PMID:28430132

Activity Recognition Invariant to Sensor Orientation with Wearable Motion Sensors.

PubMed

Yurtman, Aras; Barshan, Billur

2017-08-09

Most activity recognition studies that employ wearable sensors assume that the sensors are attached at pre-determined positions and orientations that do not change over time. Since this is not the case in practice, it is of interest to develop wearable systems that operate invariantly to sensor position and orientation. We focus on invariance to sensor orientation and develop two alternative transformations to remove the effect of absolute sensor orientation from the raw sensor data. We test the proposed methodology in activity recognition with four state-of-the-art classifiers using five publicly available datasets containing various types of human activities acquired by different sensor configurations. While the ordinary activity recognition system cannot handle incorrectly oriented sensors, the proposed transformations allow the sensors to be worn at any orientation at a given position on the body, and achieve nearly the same activity recognition performance as the ordinary system for which the sensor units are not rotatable. The proposed techniques can be applied to existing wearable systems without much effort, by simply transforming the time-domain sensor data at the pre-processing stage.