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

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.

Research on the optimal structure configuration of dither RLG used in skewed redundant INS

NASA Astrophysics Data System (ADS)

Gao, Chunfeng; Wang, Qi; Wei, Guo; Long, Xingwu

2016-05-01

The actual combat effectiveness of weapon equipment is restricted by the performance of Inertial Navigation System (INS), especially in high reliability required situations such as fighter, satellite and submarine. Through the use of skewed sensor geometries, redundant technique has been applied to reduce the cost and improve the reliability of the INS. In this paper, the structure configuration and the inertial sensor characteristics of Skewed Redundant Strapdown Inertial Navigation System (SRSINS) using dithered Ring Laser Gyroscope (RLG) are analyzed. For the dither coupling effects of the dither gyro, the system measurement errors can be amplified either the individual gyro dither frequency is near one another or the structure of the SRSINS is unreasonable. Based on the characteristics of RLG, the research on coupled vibration of dithered RLG in SRSINS is carried out. On the principle of optimal navigation performance, optimal reliability and optimal cost-effectiveness, the comprehensive evaluation scheme of the inertial sensor configuration of SRINS is given.

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.

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.

Label-free detection of biomolecules with Ta2O5-based field effect devices

NASA Astrophysics Data System (ADS)

Branquinho, Rita Maria Mourao Salazar

Field-effect-based devices (FEDs) are becoming a basic structural element in a new generation of micro biosensors. Their numerous advantages such as small size, labelfree response and versatility, together with the possibility of on-chip integration of biosensor arrays with a future prospect of low-cost mass production, make their development highly desirable. The present thesis focuses on the study and optimization of tantalum pentoxide (Ta2O5) deposited by rf magnetron sputtering at room temperature, and their application as sensitive layer in biosensors based on field effect devices (BioFEDs). As such, the influence of several deposition parameters and post-processing annealing temperature and surface plasma treatment on the film¡¦s properties was investigated. Electrolyte-insulator-semiconductor (EIS) field-effect-based sensors comprising the optimized Ta2O5 sensitive layer were applied to the development of BioFEDs. Enzyme functionalized sensors (EnFEDs) were produced for penicillin detection. These sensors were also applied to the label free detection of DNA and the monitoring of its amplification via polymerase chain reaction (PCR), real time PCR (RT-PCR) and loop mediated isothermal amplification (LAMP). Ion sensitive field effect transistors (ISFETs) based on semiconductor oxides comprising the optimized Ta2O5 sensitive layer were also fabricated. EIS sensors comprising Ta2O5 films produced with optimized conditions demonstrated near Nernstian pH sensitivity, 58+/-0.3 mV/pH. These sensors were successfully applied to the label-free detection of penicillin and DNA. Penicillinase functionalized sensors showed a 29+/-7 mV/mM sensitivity towards penicillin detection up to 4 mM penicillin concentration. DNA detection was achieved with 30 mV/mugM sensitivity and DNA amplification monitoring with these sensors showed comparable results to those obtained with standard fluorescence based methods. Semiconductor oxides-based ISFETs with Ta2O5 sensitive layer were also produced. Finally, the high quality and sensitivity demonstrated by Ta2O5 thin films produced at low temperature by rf magnetron sputtering allows for their application as sensitive layer in field effect sensors.

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.

Develop Measures of Effectiveness and Deployment Optimization Rules for Networked Ground Micro-Sensors

DTIC Science & Technology

2001-05-01

types and total #) Ø Control of Sensors ( Scheduling ) Ø Coverage (Time & Area) Uncontrollable Inputs ØWeather Ø Atmospheric Effects Ø Equipment...are widely scattered and used to cue or wakeup other higher-level sensors. Trip line sensors consist of some combination of acoustic, seismic and...Employ a mix if different sensor types in order to increase detection probability 4.4.4.2 Minimize Battery Power • Set schedule turn on and off

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.

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.

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

Hybrid swarm intelligence optimization approach for optimal data storage position identification in wireless sensor networks.

PubMed

Mohanasundaram, Ranganathan; Periasamy, Pappampalayam Sanmugam

2015-01-01

The current high profile debate with regard to data storage and its growth have become strategic task in the world of networking. It mainly depends on the sensor nodes called producers, base stations, and also the consumers (users and sensor nodes) to retrieve and use the data. The main concern dealt here is to find an optimal data storage position in wireless sensor networks. The works that have been carried out earlier did not utilize swarm intelligence based optimization approaches to find the optimal data storage positions. To achieve this goal, an efficient swam intelligence approach is used to choose suitable positions for a storage node. Thus, hybrid particle swarm optimization algorithm has been used to find the suitable positions for storage nodes while the total energy cost of data transmission is minimized. Clustering-based distributed data storage is utilized to solve clustering problem using fuzzy-C-means algorithm. This research work also considers the data rates and locations of multiple producers and consumers to find optimal data storage positions. The algorithm is implemented in a network simulator and the experimental results show that the proposed clustering and swarm intelligence based ODS strategy is more effective than the earlier approaches.

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

Optimal Sensor Placement for Measuring Physical Activity with a 3D Accelerometer

PubMed Central

Boerema, Simone T.; van Velsen, Lex; Schaake, Leendert; Tönis, Thijs M.; Hermens, Hermie J.

2014-01-01

Accelerometer-based activity monitors are popular for monitoring physical activity. In this study, we investigated optimal sensor placement for increasing the quality of studies that utilize accelerometer data to assess physical activity. We performed a two-staged study, focused on sensor location and type of mounting. Ten subjects walked at various walking speeds on a treadmill, performed a deskwork protocol, and walked on level ground, while simultaneously wearing five ProMove2 sensors with a snug fit on an elastic waist belt. We found that sensor location, type of activity, and their interaction-effect affected sensor output. The most lateral positions on the waist belt were the least sensitive for interference. The effect of mounting was explored, by making two subjects repeat the experimental protocol with sensors more loosely fitted to the elastic belt. The loose fit resulted in lower sensor output, except for the deskwork protocol, where output was higher. In order to increase the reliability and to reduce the variability of sensor output, researchers should place activity sensors on the most lateral position of a participant's waist belt. If the sensor hampers free movement, it may be positioned slightly more forward on the belt. Finally, sensors should be fitted tightly to the body. PMID:24553085

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.

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.

Underwater Sensor Network Redeployment Algorithm Based on Wolf Search

PubMed Central

Jiang, Peng; Feng, Yang; Wu, Feng

2016-01-01

This study addresses the optimization of node redeployment coverage in underwater wireless sensor networks. Given that nodes could easily become invalid under a poor environment and the large scale of underwater wireless sensor networks, an underwater sensor network redeployment algorithm was developed based on wolf search. This study is to apply the wolf search algorithm combined with crowded degree control in the deployment of underwater wireless sensor networks. The proposed algorithm uses nodes to ensure coverage of the events, and it avoids the prematurity of the nodes. The algorithm has good coverage effects. In addition, considering that obstacles exist in the underwater environment, nodes are prevented from being invalid by imitating the mechanism of avoiding predators. Thus, the energy consumption of the network is reduced. Comparative analysis shows that the algorithm is simple and effective in wireless sensor network deployment. Compared with the optimized artificial fish swarm algorithm, the proposed algorithm exhibits advantages in network coverage, energy conservation, and obstacle avoidance. PMID:27775659

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.

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

Field-Based Optimal Placement of Antennas for Body-Worn Wireless Sensors

PubMed Central

Januszkiewicz, Łukasz; Di Barba, Paolo; Hausman, Sławomir

2016-01-01

We investigate a case of automated energy-budget-aware optimization of the physical position of nodes (sensors) in a Wireless Body Area Network (WBAN). This problem has not been presented in the literature yet, as opposed to antenna and routing optimization, which are relatively well-addressed. In our research, which was inspired by a safety-critical application for firefighters, the sensor network consists of three nodes located on the human body. The nodes communicate over a radio link operating in the 2.4 GHz or 5.8 GHz ISM frequency band. Two sensors have a fixed location: one on the head (earlobe pulse oximetry) and one on the arm (with accelerometers, temperature and humidity sensors, and a GPS receiver), while the position of the third sensor can be adjusted within a predefined region on the wearer’s chest. The path loss between each node pair strongly depends on the location of the nodes and is difficult to predict without performing a full-wave electromagnetic simulation. Our optimization scheme employs evolutionary computing. The novelty of our approach lies not only in the formulation of the problem but also in linking a fully automated optimization procedure with an electromagnetic simulator and a simplified human body model. This combination turns out to be a computationally effective solution, which, depending on the initial placement, has a potential to improve performance of our example sensor network setup by up to about 20 dB with respect to the path loss between selected nodes. PMID:27196911

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.

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.

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.

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.

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

Hybrid Swarm Intelligence Optimization Approach for Optimal Data Storage Position Identification in Wireless Sensor Networks

PubMed Central

Mohanasundaram, Ranganathan; Periasamy, Pappampalayam Sanmugam

2015-01-01

The current high profile debate with regard to data storage and its growth have become strategic task in the world of networking. It mainly depends on the sensor nodes called producers, base stations, and also the consumers (users and sensor nodes) to retrieve and use the data. The main concern dealt here is to find an optimal data storage position in wireless sensor networks. The works that have been carried out earlier did not utilize swarm intelligence based optimization approaches to find the optimal data storage positions. To achieve this goal, an efficient swam intelligence approach is used to choose suitable positions for a storage node. Thus, hybrid particle swarm optimization algorithm has been used to find the suitable positions for storage nodes while the total energy cost of data transmission is minimized. Clustering-based distributed data storage is utilized to solve clustering problem using fuzzy-C-means algorithm. This research work also considers the data rates and locations of multiple producers and consumers to find optimal data storage positions. The algorithm is implemented in a network simulator and the experimental results show that the proposed clustering and swarm intelligence based ODS strategy is more effective than the earlier approaches. PMID:25734182

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

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.

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.

Performance optimization for space-based sensors: simulation and modelling at Fraunhofer IOSB

NASA Astrophysics Data System (ADS)

Schweitzer, Caroline; Stein, Karin

2014-10-01

The prediction of the effectiveness of a space-based sensor for its designated application in space (e.g. special earth surface observations or missile detection) can help to reduce the expenses, especially during the phases of mission planning and instrumentation. In order to optimize the performance of such systems we simulate and analyse the entire operational scenario, including: - optional waveband - various orbit heights and viewing angles - system design characteristics, e. g. pixel size and filter transmission - atmospheric effects, e. g. different cloud types, climate zones and seasons In the following, an evaluation of the appropriate infrared (IR) waveband for the designated sensor application is given. The simulation environment is also capable of simulating moving objects like aircraft or missiles. Therefore, the spectral signature of the object/missile as well as its track along a flight path is implemented. The resulting video sequence is then analysed by a tracking algorithm and an estimation of the effectiveness of the sensor system can be simulated. This paper summarizes the work carried out at Fraunhofer IOSB in the field of simulation and modelling for the performance optimization of space based sensors. The paper is structured as follows: First, an overview of the applied simulation and modelling software is given. Then, the capability of those tools is illustrated by means of a hypothetical threat scenario for space-based early warning (launch of a long-range ballistic missile (BM)).

Developing a reading concentration monitoring system by applying an artificial bee colony algorithm to e-books in an intelligent classroom.

PubMed

Hsu, Chia-Cheng; Chen, Hsin-Chin; Su, Yen-Ning; Huang, Kuo-Kuang; Huang, Yueh-Min

2012-10-22

A growing number of educational studies apply sensors to improve student learning in real classroom settings. However, how can sensors be integrated into classrooms to help instructors find out students' reading concentration rates and thus better increase learning effectiveness? The aim of the current study was to develop a reading concentration monitoring system for use with e-books in an intelligent classroom and to help instructors find out the students' reading concentration rates. The proposed system uses three types of sensor technologies, namely a webcam, heartbeat sensor, and blood oxygen sensor to detect the learning behaviors of students by capturing various physiological signals. An artificial bee colony (ABC) optimization approach is applied to the data gathered from these sensors to help instructors understand their students' reading concentration rates in a classroom learning environment. The results show that the use of the ABC algorithm in the proposed system can effectively obtain near-optimal solutions. The system has a user-friendly graphical interface, making it easy for instructors to clearly understand the reading status of their students.

Developing a Reading Concentration Monitoring System by Applying an Artificial Bee Colony Algorithm to E-Books in an Intelligent Classroom

PubMed Central

Hsu, Chia-Cheng; Chen, Hsin-Chin; Su, Yen-Ning; Huang, Kuo-Kuang; Huang, Yueh-Min

2012-01-01

A growing number of educational studies apply sensors to improve student learning in real classroom settings. However, how can sensors be integrated into classrooms to help instructors find out students' reading concentration rates and thus better increase learning effectiveness? The aim of the current study was to develop a reading concentration monitoring system for use with e-books in an intelligent classroom and to help instructors find out the students' reading concentration rates. The proposed system uses three types of sensor technologies, namely a webcam, heartbeat sensor, and blood oxygen sensor to detect the learning behaviors of students by capturing various physiological signals. An artificial bee colony (ABC) optimization approach is applied to the data gathered from these sensors to help instructors understand their students' reading concentration rates in a classroom learning environment. The results show that the use of the ABC algorithm in the proposed system can effectively obtain near-optimal solutions. The system has a user-friendly graphical interface, making it easy for instructors to clearly understand the reading status of their students. PMID:23202042

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.

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.

High magnetic field test of bismuth Hall sensors for ITER steady state magnetic diagnostic.

PubMed

Ďuran, I; Entler, S; Kohout, M; Kočan, M; Vayakis, G

2016-11-01

Performance of bismuth Hall sensors developed for the ITER steady state magnetic diagnostic was investigated for high magnetic fields in the range ±7 T. Response of the sensors to the magnetic field was found to be nonlinear particularly within the range ±1 T. Significant contribution of the planar Hall effect to the sensors output voltage causing undesirable cross field sensitivity was identified. It was demonstrated that this effect can be minimized by the optimization of the sensor geometry and alignment with the magnetic field and by the application of "current-spinning technique."

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.

The output voltage model and experiment of magnetostrictive displacement sensor based on Weidemann effect

NASA Astrophysics Data System (ADS)

Wang, Bowen; Li, Yuanyuan; Xie, Xinliang; Huang, Wenmei; Weng, Ling; Zhang, Changgeng

2018-05-01

Based on the Wiedemann effect and inverse magnetostritive effect, the output voltage model of a magnetostrictive displacement sensor has been established. The output voltage of the magnetostrictive displacement sensor is calculated in different magnetic fields. It is found that the calculating result is in an agreement with the experimental one. The theoretical and experimental results show that the output voltage of the displacement sensor is linearly related to the magnetostrictive differences, (λl-λt), of waveguide wires. The measured output voltages for Fe-Ga and Fe-Ni wire sensors are 51.5mV and 36.5mV, respectively, and the output voltage of Fe-Ga wire sensor is obviously higher than that of Fe-Ni wire sensor under the same magnetic field. The model can be used to predict the output voltage of the sensor and to provide guidance for the optimization design of the sensor.

Measurement correction method for force sensor used in dynamic pressure calibration based on artificial neural network optimized by genetic algorithm

NASA Astrophysics Data System (ADS)

Gu, Tingwei; Kong, Deren; Shang, Fei; Chen, Jing

2017-12-01

We present an optimization algorithm to obtain low-uncertainty dynamic pressure measurements from a force-transducer-based device. In this paper, the advantages and disadvantages of the methods that are commonly used to measure the propellant powder gas pressure, the applicable scope of dynamic pressure calibration devices, and the shortcomings of the traditional comparison calibration method based on the drop-weight device are firstly analysed in detail. Then, a dynamic calibration method for measuring pressure using a force sensor based on a drop-weight device is introduced. This method can effectively save time when many pressure sensors are calibrated simultaneously and extend the life of expensive reference sensors. However, the force sensor is installed between the drop-weight and the hammerhead by transition pieces through the connection mode of bolt fastening, which causes adverse effects such as additional pretightening and inertia forces. To solve these effects, the influence mechanisms of the pretightening force, the inertia force and other influence factors on the force measurement are theoretically analysed. Then a measurement correction method for the force measurement is proposed based on an artificial neural network optimized by a genetic algorithm. The training and testing data sets are obtained from calibration tests, and the selection criteria for the key parameters of the correction model is discussed. The evaluation results for the test data show that the correction model can effectively improve the force measurement accuracy of the force sensor. Compared with the traditional high-accuracy comparison calibration method, the percentage difference of the impact-force-based measurement is less than 0.6% and the relative uncertainty of the corrected force value is 1.95%, which can meet the requirements of engineering applications.

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

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.

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.

Optimal distance of multi-plane sensor in three-dimensional electrical impedance tomography.

PubMed

Hao, Zhenhua; Yue, Shihong; Sun, Benyuan; Wang, Huaxiang

2017-12-01

Electrical impedance tomography (EIT) is a visual imaging technique for obtaining the conductivity and permittivity distributions in the domain of interest. As an advanced technique, EIT has the potential to be a valuable tool for continuously bedside monitoring of pulmonary function. The EIT applications in any three-dimensional (3 D) field are very limited to the 3 D effects, i.e. the distribution of electric field spreads far beyond the electrode plane. The 3 D effects can result in measurement errors and image distortion. An important way to overcome the 3 D effect is to use the multiple groups of sensors. The aim of this paper is to find the best space resolution of EIT image over various electrode planes and select an optimal plane spacing in a 3 D EIT sensor, and provide guidance for 3 D EIT electrodes placement in monitoring lung function. In simulation and experiment, several typical conductivity distribution models, such as one rod (central, midway and edge), two rods and three rods, are set at different plane spacings between the two electrode planes. A Tikhonov regularization algorithm is utilized for reconstructing the images; the relative error and the correlation coefficient are utilized for evaluating the image quality. Based on numerical simulation and experimental results, the image performance at different spacing conditions is evaluated. The results demonstrate that there exists an optimal plane spacing between the two electrode planes for 3 D EIT sensor. And then the selection of the optimal plane spacing between the electrode planes is suggested for the electrodes placement of multi-plane EIT sensor.

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

Optimality study of a gust alleviation system for light wing-loading STOL aircraft

NASA Technical Reports Server (NTRS)

Komoda, M.

1976-01-01

An analytical study was made of an optimal gust alleviation system that employs a vertical gust sensor mounted forward of an aircraft's center of gravity. Frequency domain optimization techniques were employed to synthesize the optimal filters that process the corrective signals to the flaps and elevator actuators. Special attention was given to evaluating the effectiveness of lead time, that is, the time by which relative wind sensor information should lead the actual encounter of the gust. The resulting filter is expressed as an implicit function of the prescribed control cost. A numerical example for a light wing loading STOL aircraft is included in which the optimal trade-off between performance and control cost is systematically studied.

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.

Magnetoelectric Current Sensors

PubMed Central

Bichurin, Mirza; Petrov, Roman; Leontiev, Viktor; Semenov, Gennadiy; Sokolov, Oleg

2017-01-01

In this work a magnetoelectric (ME) current sensor design based on a magnetoelectric effect is presented and discussed. The resonant and non-resonant type of ME current sensors are considered. Theoretical calculations of the ME current sensors by the equivalent circuit method were conducted. The application of different sensors using the new effects, for example, the ME effect, is made possible with the development of new ME composites. A large number of studies conducted in the field of new composites, allowed us to obtain a high magnetostrictive-piezoelectric laminate sensitivity. An optimal ME structure composition was matched. The characterization of a non-resonant current sensor showed that in the operation range to 5 A, the sensor had a sensitivity of 0.34 V/A, non-linearity less than 1% and for a resonant current sensor in the same operation range, the sensitivity was of 0.53 V/A, non-linearity less than 0.5%. PMID:28574486

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.

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.

Effects of annealing temperature on the H2-sensing properties of Pd-decorated WO3 nanorods

NASA Astrophysics Data System (ADS)

Lee, Sangmin; Lee, Woo Seok; Lee, Jae Kyung; Hyun, Soong Keun; Lee, Chongmu; Choi, Seungbok

2018-03-01

The temperature of the post-annealing treatment carried out after noble metal deposition onto semiconducting metal oxides (SMOs) must be carefully optimized to maximize the sensing performance of the metal-decorated SMO sensors. WO3 nanorods were synthesized by thermal evaporation of WO3 powders and decorated with Pd nanoparticles using a sol-gel method, followed by an annealing process. The effects of the annealing temperature on the hydrogen gas-sensing properties of the Pd-decorated WO3 nanorods were then examined; the optimal annealing temperature, leading to the highest response of the WO3 nanorod sensor to H2, was determined to be 600 °C. Post-annealing at 600 °C resulted in nanorods with the highest surface area-to-volume ratio, as well as in the optimal size and the largest number of deposited Pd nanoparticles, leading to the highest response and the shortest response/recovery times toward H2. The improved H2-sensing performance of the Pd-decorated WO3 nanorod sensor, compared to a sensor based on pristine WO3 nanorods, is attributed to the enhanced catalytic activity, increased surface area-to-volume ratio, and higher amounts of surface defects.

Optimization of pH sensing using silicon nanowire field effect transistors with HfO2 as the sensing surface.

PubMed

Zafar, Sufi; D'Emic, Christopher; Afzali, Ali; Fletcher, Benjamin; Zhu, Y; Ning, Tak

2011-10-07

Silicon nanowire field effect transistor sensors with SiO(2)/HfO(2) as the gate dielectric sensing surface are fabricated using a top down approach. These sensors are optimized for pH sensing with two key characteristics. First, the pH sensitivity is shown to be independent of buffer concentration. Second, the observed pH sensitivity is enhanced and is equal to the Nernst maximum sensitivity limit of 59 mV/pH with a corresponding subthreshold drain current change of ∼ 650%/pH. These two enhanced pH sensing characteristics are attributed to the use of HfO(2) as the sensing surface and an optimized fabrication process compatible with silicon processing technology.

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.

A novel load balanced energy conservation approach in WSN using biogeography based optimization

NASA Astrophysics Data System (ADS)

Kaushik, Ajay; Indu, S.; Gupta, Daya

2017-09-01

Clustering sensor nodes is an effective technique to reduce energy consumption of the sensor nodes and maximize the lifetime of Wireless sensor networks. Balancing load of the cluster head is an important factor in long run operation of WSNs. In this paper we propose a novel load balancing approach using biogeography based optimization (LB-BBO). LB-BBO uses two separate fitness functions to perform load balancing of equal and unequal load respectively. The proposed method is simulated using matlab and compared with existing methods. The proposed method shows better performance than all the previous works implemented for energy conservation in WSN

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.

High Accuracy Passive Magnetic Field-Based Localization for Feedback Control Using Principal Component Analysis.

PubMed

Foong, Shaohui; Sun, Zhenglong

2016-08-12

In this paper, a novel magnetic field-based sensing system employing statistically optimized concurrent multiple sensor outputs for precise field-position association and localization is presented. This method capitalizes on the independence between simultaneous spatial field measurements at multiple locations to induce unique correspondences between field and position. This single-source-multi-sensor configuration is able to achieve accurate and precise localization and tracking of translational motion without contact over large travel distances for feedback control. Principal component analysis (PCA) is used as a pseudo-linear filter to optimally reduce the dimensions of the multi-sensor output space for computationally efficient field-position mapping with artificial neural networks (ANNs). Numerical simulations are employed to investigate the effects of geometric parameters and Gaussian noise corruption on PCA assisted ANN mapping performance. Using a 9-sensor network, the sensing accuracy and closed-loop tracking performance of the proposed optimal field-based sensing system is experimentally evaluated on a linear actuator with a significantly more expensive optical encoder as a comparison.

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

Optimization of Pockels electric field in transverse modulated optical voltage sensor

NASA Astrophysics Data System (ADS)

Huang, Yifan; Xu, Qifeng; Chen, Kun-Long; Zhou, Jie

2018-05-01

This paper investigates the possibilities of optimizing the Pockels electric field in a transverse modulated optical voltage sensor with a spherical electrode structure. The simulations show that due to the edge effect and the electric field concentrations and distortions, the electric field distributions in the crystal are non-uniform. In this case, a tiny variation in the light path leads to an integral error of more than 0.5%. Moreover, a 2D model cannot effectively represent the edge effect, so a 3D model is employed to optimize the electric field distributions. Furthermore, a new method to attach a quartz crystal to the electro-optic crystal along the electric field direction is proposed to improve the non-uniformity of the electric field. The integral error is reduced therefore from 0.5% to 0.015% and less. The proposed method is simple, practical and effective, and it has been validated by numerical simulations and experimental tests.

Performance of Optimized Actuator and Sensor Arrays in an Active Noise Control System

NASA Technical Reports Server (NTRS)

Palumbo, D. L.; Padula, S. L.; Lyle, K. H.; Cline, J. H.; Cabell, R. H.

1996-01-01

Experiments have been conducted in NASA Langley's Acoustics and Dynamics Laboratory to determine the effectiveness of optimized actuator/sensor architectures and controller algorithms for active control of harmonic interior noise. Tests were conducted in a large scale fuselage model - a composite cylinder which simulates a commuter class aircraft fuselage with three sections of trim panel and a floor. Using an optimization technique based on the component transfer functions, combinations of 4 out of 8 piezoceramic actuators and 8 out of 462 microphone locations were evaluated against predicted performance. A combinatorial optimization technique called tabu search was employed to select the optimum transducer arrays. Three test frequencies represent the cases of a strong acoustic and strong structural response, a weak acoustic and strong structural response and a strong acoustic and weak structural response. Noise reduction was obtained using a Time Averaged/Gradient Descent (TAGD) controller. Results indicate that the optimization technique successfully predicted best and worst case performance. An enhancement of the TAGD control algorithm was also evaluated. The principal components of the actuator/sensor transfer functions were used in the PC-TAGD controller. The principal components are shown to be independent of each other while providing control as effective as the standard TAGD.

Preparation and characterization of AuNPs/CNTs-ErGO electrochemical sensors for highly sensitive detection of hydrazine.

PubMed

Zhao, Zhenting; Sun, Yongjiao; Li, Pengwei; Zhang, Wendong; Lian, Kun; Hu, Jie; Chen, Yong

2016-09-01

A highly sensitive electrochemical sensor of hydrazine has been fabricated by Au nanoparticles (AuNPs) coating of carbon nanotubes-electrochemical reduced graphene oxide composite film (CNTs-ErGO) on glassy carbon electrode (GCE). Cyclic voltammetry and potential amperometry have been used to investigate the electrochemical properties of the fabricated sensors for hydrazine detection. The performances of the sensors were optimized by varying the CNTs to ErGO ratio and the quantity of Au nanoparticles. The results show that under optimal conditions, a sensitivity of 9.73μAμM(-1)cm(-2), a short response time of 3s, and a low detection limit of 0.065μM could be achieved with a linear concentration response range from 0.3μM to 319μM. The enhanced electrochemical performances could be attributed to the synergistic effect between AuNPs and CNTs-ErGO film and the outstanding catalytic effect of the Au nanoparticles. Finally, the sensor was successfully used to analyse the tap water, showing high potential for practical applications. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

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.

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

Analysis of power management and system latency in wireless sensor networks

NASA Astrophysics Data System (ADS)

Oswald, Matthew T.; Rohwer, Judd A.; Forman, Michael A.

2004-08-01

Successful power management in a wireless sensor network requires optimization of the protocols which affect energy-consumption on each node and the aggregate effects across the larger network. System optimization for a given deployment scenario requires an analysis and trade off of desired node and network features with their associated costs. The sleep protocol for an energy-efficient wireless sensor network for event detection, target classification, and target tracking developed at Sandia National Laboratories is presented. The dynamic source routing (DSR) algorithm is chosen to reduce network maintenance overhead, while providing a self-configuring and self-healing network architecture. A method for determining the optimal sleep time is developed and presented, providing reference data which spans several orders of magnitude. Message timing diagrams show, that a node in a five-node cluster, employing an optimal cyclic single-radio sleep protocol, consumes 3% more energy and incurs a 16-s increase latency than nodes employing the more complex dual-radio STEM protocol.

Optimal Magnetic Sensor Vests for Cardiac Source Imaging

PubMed Central

Lau, Stephan; Petković, Bojana; Haueisen, Jens

2016-01-01

Magnetocardiography (MCG) non-invasively provides functional information about the heart. New room-temperature magnetic field sensors, specifically magnetoresistive and optically pumped magnetometers, have reached sensitivities in the ultra-low range of cardiac fields while allowing for free placement around the human torso. Our aim is to optimize positions and orientations of such magnetic sensors in a vest-like arrangement for robust reconstruction of the electric current distributions in the heart. We optimized a set of 32 sensors on the surface of a torso model with respect to a 13-dipole cardiac source model under noise-free conditions. The reconstruction robustness was estimated by the condition of the lead field matrix. Optimization improved the condition of the lead field matrix by approximately two orders of magnitude compared to a regular array at the front of the torso. Optimized setups exhibited distributions of sensors over the whole torso with denser sampling above the heart at the front and back of the torso. Sensors close to the heart were arranged predominantly tangential to the body surface. The optimized sensor setup could facilitate the definition of a standard for sensor placement in MCG and the development of a wearable MCG vest for clinical diagnostics. PMID:27231910

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

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

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

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’.

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.

Active control of transient rotordynamic vibration by optimal control methods

NASA Technical Reports Server (NTRS)

Palazzolo, A. B.; Lin, R. R.; Alexander, R. M.; Kascak, A. F.

1988-01-01

Although considerable effort has been put into the study of steady state vibration control, there are few methods applicable to transient vibration control of rotorbearing systems. In this paper optimal control theory has been adopted to minimize rotor vibration due to sudden imbalance, e.g., blade loss. The system gain matrix is obtained by choosing the weighting matrices and solving the Riccati equation. Control forces are applied to the system via a feedback loop. A seven mass rotor system is simulated for illustration. A relationship between the number of sensors and the number of modes used in the optimal control model is investigated. Comparisons of responses are made for various configurations of modes, sensors, and actuators. Furthermore, spillover effect is examined by comparing results from collocated and noncollocated sensor configurations. Results show that shaft vibration is significantly attenuated in the closed loop system.

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

Optimal sensors placement and spillover suppression

NASA Astrophysics Data System (ADS)

Hanis, Tomas; Hromcik, Martin

2012-04-01

A new approach to optimal placement of sensors (OSP) in mechanical structures is presented. In contrast to existing methods, the presented procedure enables a designer to seek for a trade-off between the presence of desirable modes in captured measurements and the elimination of influence of those mode shapes that are not of interest in a given situation. An efficient numerical algorithm is presented, developed from an existing routine based on the Fischer information matrix analysis. We consider two requirements in the optimal sensor placement procedure. On top of the classical EFI approach, the sensors configuration should also minimize spillover of unwanted higher modes. We use the information approach to OSP, based on the effective independent method (EFI), and modify the underlying criterion to meet both of our requirements—to maximize useful signals and minimize spillover of unwanted modes at the same time. Performance of our approach is demonstrated by means of examples, and a flexible Blended Wing Body (BWB) aircraft case study related to a running European-level FP7 research project 'ACFA 2020—Active Control for Flexible Aircraft'.

Deployment-based lifetime optimization for linear wireless sensor networks considering both retransmission and discrete power control.

PubMed

Li, Ruiying; Ma, Wenting; Huang, Ning; Kang, Rui

2017-01-01

A sophisticated method for node deployment can efficiently reduce the energy consumption of a Wireless Sensor Network (WSN) and prolong the corresponding network lifetime. Pioneers have proposed many node deployment based lifetime optimization methods for WSNs, however, the retransmission mechanism and the discrete power control strategy, which are widely used in practice and have large effect on the network energy consumption, are often neglected and assumed as a continuous one, respectively, in the previous studies. In this paper, both retransmission and discrete power control are considered together, and a more realistic energy-consumption-based network lifetime model for linear WSNs is provided. Using this model, we then propose a generic deployment-based optimization model that maximizes network lifetime under coverage, connectivity and transmission rate success constraints. The more accurate lifetime evaluation conduces to a longer optimal network lifetime in the realistic situation. To illustrate the effectiveness of our method, both one-tiered and two-tiered uniformly and non-uniformly distributed linear WSNs are optimized in our case studies, and the comparisons between our optimal results and those based on relatively inaccurate lifetime evaluation show the advantage of our method when investigating WSN lifetime optimization problems.

Weighted Global Artificial Bee Colony Algorithm Makes Gas Sensor Deployment Efficient

PubMed Central

Jiang, Ye; He, Ziqing; Li, Yanhai; Xu, Zhengyi; Wei, Jianming

2016-01-01

This paper proposes an improved artificial bee colony algorithm named Weighted Global ABC (WGABC) algorithm, which is designed to improve the convergence speed in the search stage of solution search equation. The new method not only considers the effect of global factors on the convergence speed in the search phase, but also provides the expression of global factor weights. Experiment on benchmark functions proved that the algorithm can improve the convergence speed greatly. We arrive at the gas diffusion concentration based on the theory of CFD and then simulate the gas diffusion model with the influence of buildings based on the algorithm. Simulation verified the effectiveness of the WGABC algorithm in improving the convergence speed in optimal deployment scheme of gas sensors. Finally, it is verified that the optimal deployment method based on WGABC algorithm can improve the monitoring efficiency of sensors greatly as compared with the conventional deployment methods. PMID:27322262

Open-WiSe: a solar powered wireless sensor network platform.

PubMed

González, Apolinar; Aquino, Raúl; Mata, Walter; Ochoa, Alberto; Saldaña, Pedro; Edwards, Arthur

2012-01-01

Because battery-powered nodes are required in wireless sensor networks and energy consumption represents an important design consideration, alternate energy sources are needed to provide more effective and optimal function. The main goal of this work is to present an energy harvesting wireless sensor network platform, the Open Wireless Sensor node (WiSe). The design and implementation of the solar powered wireless platform is described including the hardware architecture, firmware, and a POSIX Real-Time Kernel. A sleep and wake up strategy was implemented to prolong the lifetime of the wireless sensor network. This platform was developed as a tool for researchers investigating Wireless sensor network or system integrators.

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.

Optimization of Sensor Monitoring Strategies for Emissions

NASA Astrophysics Data System (ADS)

Klise, K. A.; Laird, C. D.; Downey, N.; Baker Hebert, L.; Blewitt, D.; Smith, G. R.

2016-12-01

Continuous or regularly scheduled monitoring has the potential to quickly identify changes in air quality. However, even with low-cost sensors, only a limited number of sensors can be placed to monitor airborne pollutants. The physical placement of these sensors and the sensor technology used can have a large impact on the performance of a monitoring strategy. Furthermore, sensors can be placed for different objectives, including maximum coverage, minimum time to detection or exposure, or to quantify emissions. Different objectives may require different monitoring strategies, which need to be evaluated by stakeholders before sensors are placed in the field. In this presentation, we outline methods to enhance ambient detection programs through optimal design of the monitoring strategy. These methods integrate atmospheric transport models with sensor characteristics, including fixed and mobile sensors, sensor cost and failure rate. The methods use site specific pre-computed scenarios which capture differences in meteorology, terrain, concentration averaging times, gas concentration, and emission characteristics. The pre-computed scenarios become input to a mixed-integer, stochastic programming problem that solves for sensor locations and types that maximize the effectiveness of the detection program. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

Research on a power management system for thermoelectric generators to drive wireless sensors on a spindle unit.

PubMed

Li, Sheng; Yao, Xinhua; Fu, Jianzhong

2014-07-16

Thermoelectric energy harvesting is emerging as a promising alternative energy source to drive wireless sensors in mechanical systems. Typically, the waste heat from spindle units in machine tools creates potential for thermoelectric generation. However, the problem of low and fluctuant ambient temperature differences in spindle units limits the application of thermoelectric generation to drive a wireless sensor. This study is devoted to presenting a transformer-based power management system and its associated control strategy to make the wireless sensor work stably at different speeds of the spindle. The charging/discharging time of capacitors is optimized through this energy-harvesting strategy. A rotating spindle platform is set up to test the performance of the power management system at different speeds. The experimental results show that a longer sampling cycle time will increase the stability of the wireless sensor. The experiments also prove that utilizing the optimal time can make the power management system work more effectively compared with other systems using the same sample cycle.

Research on a Power Management System for Thermoelectric Generators to Drive Wireless Sensors on a Spindle Unit

PubMed Central

Li, Sheng; Yao, Xinhua; Fu, Jianzhong

2014-01-01

Thermoelectric energy harvesting is emerging as a promising alternative energy source to drive wireless sensors in mechanical systems. Typically, the waste heat from spindle units in machine tools creates potential for thermoelectric generation. However, the problem of low and fluctuant ambient temperature differences in spindle units limits the application of thermoelectric generation to drive a wireless sensor. This study is devoted to presenting a transformer-based power management system and its associated control strategy to make the wireless sensor work stably at different speeds of the spindle. The charging/discharging time of capacitors is optimized through this energy-harvesting strategy. A rotating spindle platform is set up to test the performance of the power management system at different speeds. The experimental results show that a longer sampling cycle time will increase the stability of the wireless sensor. The experiments also prove that utilizing the optimal time can make the power management system work more effectively compared with other systems using the same sample cycle. PMID:25033189

Statistical-QoS Guaranteed Energy Efficiency Optimization for Energy Harvesting Wireless Sensor Networks

PubMed Central

Cheng, Wenchi; Zhang, Hailin

2017-01-01

Energy harvesting, which offers a never-ending energy supply, has emerged as a prominent technology to prolong the lifetime and reduce costs for the battery-powered wireless sensor networks. However, how to improve the energy efficiency while guaranteeing the quality of service (QoS) for energy harvesting based wireless sensor networks is still an open problem. In this paper, we develop statistical delay-bounded QoS-driven power control policies to maximize the effective energy efficiency (EEE), which is defined as the spectrum efficiency under given specified QoS constraints per unit harvested energy, for energy harvesting based wireless sensor networks. For the battery-infinite wireless sensor networks, our developed QoS-driven power control policy converges to the Energy harvesting Water Filling (E-WF) scheme and the Energy harvesting Channel Inversion (E-CI) scheme under the very loose and stringent QoS constraints, respectively. For the battery-finite wireless sensor networks, our developed QoS-driven power control policy becomes the Truncated energy harvesting Water Filling (T-WF) scheme and the Truncated energy harvesting Channel Inversion (T-CI) scheme under the very loose and stringent QoS constraints, respectively. Furthermore, we evaluate the outage probabilities to theoretically analyze the performance of our developed QoS-driven power control policies. The obtained numerical results validate our analysis and show that our developed optimal power control policies can optimize the EEE over energy harvesting based wireless sensor networks. PMID:28832509

Statistical-QoS Guaranteed Energy Efficiency Optimization for Energy Harvesting Wireless Sensor Networks.

PubMed

Gao, Ya; Cheng, Wenchi; Zhang, Hailin

2017-08-23

Energy harvesting, which offers a never-ending energy supply, has emerged as a prominent technology to prolong the lifetime and reduce costs for the battery-powered wireless sensor networks. However, how to improve the energy efficiency while guaranteeing the quality of service (QoS) for energy harvesting based wireless sensor networks is still an open problem. In this paper, we develop statistical delay-bounded QoS-driven power control policies to maximize the effective energy efficiency (EEE), which is defined as the spectrum efficiency under given specified QoS constraints per unit harvested energy, for energy harvesting based wireless sensor networks. For the battery-infinite wireless sensor networks, our developed QoS-driven power control policy converges to the Energy harvesting Water Filling (E-WF) scheme and the Energy harvesting Channel Inversion (E-CI) scheme under the very loose and stringent QoS constraints, respectively. For the battery-finite wireless sensor networks, our developed QoS-driven power control policy becomes the Truncated energy harvesting Water Filling (T-WF) scheme and the Truncated energy harvesting Channel Inversion (T-CI) scheme under the very loose and stringent QoS constraints, respectively. Furthermore, we evaluate the outage probabilities to theoretically analyze the performance of our developed QoS-driven power control policies. The obtained numerical results validate our analysis and show that our developed optimal power control policies can optimize the EEE over energy harvesting based wireless sensor networks.

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.

A Novel Sensor Selection and Power Allocation Algorithm for Multiple-Target Tracking in an LPI Radar Network

PubMed Central

She, Ji; Wang, Fei; Zhou, Jianjiang

2016-01-01

Radar networks are proven to have numerous advantages over traditional monostatic and bistatic radar. With recent developments, radar networks have become an attractive platform due to their low probability of intercept (LPI) performance for target tracking. In this paper, a joint sensor selection and power allocation algorithm for multiple-target tracking in a radar network based on LPI is proposed. It is found that this algorithm can minimize the total transmitted power of a radar network on the basis of a predetermined mutual information (MI) threshold between the target impulse response and the reflected signal. The MI is required by the radar network system to estimate target parameters, and it can be calculated predictively with the estimation of target state. The optimization problem of sensor selection and power allocation, which contains two variables, is non-convex and it can be solved by separating power allocation problem from sensor selection problem. To be specific, the optimization problem of power allocation can be solved by using the bisection method for each sensor selection scheme. Also, the optimization problem of sensor selection can be solved by a lower complexity algorithm based on the allocated powers. According to the simulation results, it can be found that the proposed algorithm can effectively reduce the total transmitted power of a radar network, which can be conducive to improving LPI performance. PMID:28009819

An Improved High-Sensitivity Airborne Transient Electromagnetic Sensor for Deep Penetration

PubMed Central

Chen, Shudong; Guo, Shuxu; Wang, Haofeng; He, Miao; Liu, Xiaoyan; Qiu, Yu; Zhang, Shuang; Yuan, Zhiwen; Zhang, Haiyang; Fang, Dong; Zhu, Jun

2017-01-01

The investigation depth of transient electromagnetic sensors can be effectively increased by reducing the system noise, which is mainly composed of sensor internal noise, electromagnetic interference (EMI), and environmental noise, etc. A high-sensitivity airborne transient electromagnetic (AEM) sensor with low sensor internal noise and good shielding effectiveness is of great importance for deep penetration. In this article, the design and optimization of such an AEM sensor is described in detail. To reduce sensor internal noise, a noise model with both a damping resistor and a preamplifier is established and analyzed. The results indicate that a sensor with a large diameter, low resonant frequency, and low sampling rate will have lower sensor internal noise. To improve the electromagnetic compatibility of the sensor, an electromagnetic shielding model for a central-tapped coil is established and discussed in detail. Previous studies have shown that unclosed shields with multiple layers and center grounding can effectively suppress EMI and eddy currents. According to these studies, an improved differential AEM sensor is constructed with a diameter, resultant effective area, resonant frequency, and normalized equivalent input noise of 1.1 m, 114 m2, 35.6 kHz, and 13.3 nV/m2, respectively. The accuracy of the noise model and the shielding effectiveness of the sensor have been verified experimentally. The results show a good agreement between calculated and measured results for the sensor internal noise. Additionally, over 20 dB shielding effectiveness is achieved in a complex electromagnetic environment. All of these results show a great improvement in sensor internal noise and shielding effectiveness. PMID:28106718

A Novel Design of an Automatic Lighting Control System for a Wireless Sensor Network with Increased Sensor Lifetime and Reduced Sensor Numbers

PubMed Central

Mohamaddoust, Reza; Haghighat, Abolfazl Toroghi; Sharif, Mohamad Javad Motahari; Capanni, Niccolo

2011-01-01

Wireless sensor networks (WSN) are currently being applied to energy conservation applications such as light control. We propose a design for such a system called a Lighting Automatic Control System (LACS). The LACS system contains a centralized or distributed architecture determined by application requirements and space usage. The system optimizes the calculations and communications for lighting intensity, incorporates user illumination requirements according to their activities and performs adjustments based on external lighting effects in external sensor and external sensor-less architectures. Methods are proposed for reducing the number of sensors required and increasing the lifetime of those used, for considerably reduced energy consumption. Additionally we suggest methods for improving uniformity of illuminance distribution on a workplane’s surface, which improves user satisfaction. Finally simulation results are presented to verify the effectiveness of our design. PMID:22164114

A novel design of an automatic lighting control system for a wireless sensor network with increased sensor lifetime and reduced sensor numbers.

PubMed

Mohamaddoust, Reza; Haghighat, Abolfazl Toroghi; Sharif, Mohamad Javad Motahari; Capanni, Niccolo

2011-01-01

Wireless sensor networks (WSN) are currently being applied to energy conservation applications such as light control. We propose a design for such a system called a lighting automatic control system (LACS). The LACS system contains a centralized or distributed architecture determined by application requirements and space usage. The system optimizes the calculations and communications for lighting intensity, incorporates user illumination requirements according to their activities and performs adjustments based on external lighting effects in external sensor and external sensor-less architectures. Methods are proposed for reducing the number of sensors required and increasing the lifetime of those used, for considerably reduced energy consumption. Additionally we suggest methods for improving uniformity of illuminance distribution on a workplane's surface, which improves user satisfaction. Finally simulation results are presented to verify the effectiveness of our design.

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.

Optimal Deployment of Sensor Nodes Based on Performance Surface of Underwater Acoustic Communication

PubMed Central

Choi, Jee Woong

2017-01-01

The underwater acoustic sensor network (UWASN) is a system that exchanges data between numerous sensor nodes deployed in the sea. The UWASN uses an underwater acoustic communication technique to exchange data. Therefore, it is important to design a robust system that will function even in severely fluctuating underwater communication conditions, along with variations in the ocean environment. In this paper, a new algorithm to find the optimal deployment positions of underwater sensor nodes is proposed. The algorithm uses the communication performance surface, which is a map showing the underwater acoustic communication performance of a targeted area. A virtual force-particle swarm optimization algorithm is then used as an optimization technique to find the optimal deployment positions of the sensor nodes, using the performance surface information to estimate the communication radii of the sensor nodes in each generation. The algorithm is evaluated by comparing simulation results between two different seasons (summer and winter) for an area located off the eastern coast of Korea as the selected targeted area. PMID:29053569

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.

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.

Pyrrole-phenylboronic acid: a novel monomer for dopamine recognition and detection based on imprinted electrochemical sensor.

PubMed

Zhong, Min; Teng, Ying; Pang, Shufen; Yan, Liqin; Kan, Xianwen

2015-02-15

A molecular imprinting polymer (MIP) based electrochemical sensor was successfully prepared for dopamine (DA) recognition and detection using pyrrole-phenylboronic acid (py-PBA) as a novel electropolymerized monomer. py-PBA could form cyclic boronic ester bond with DA, thus endowing a double recognition capacity of the sensor to DA in the combination of the imprinted effect of MIP. Compared with the sensor prepared using pyrrole or phenylboronic acid as electropolymerized monomer, the present sensor exhibited a remarkable high imprinted factor to DA. The influence factors including pH value, the mole ratio between monomer and template molecule, electropolymerization scan rate, and scan cycles of electropolymerization process were investigated and optimized. Under the optimal conditions, the sensor could recognize DA from its analogs and monosaccharides. A linear ranging from 5.0 × 10(-8) to 1.0 × 10(-5) mol/L for the detection of DA was obtained with a detection limit of 3.3 × 10(-8) mol/L (S/N = 3). The sensor has been applied to analyze DA in injection samples with satisfactory results. Copyright © 2014 Elsevier B.V. All rights reserved.

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

Development of self-powered wireless high temperature electrochemical sensor for in situ corrosion monitoring of coal-fired power plant.

PubMed

Aung, Naing Naing; Crowe, Edward; Liu, Xingbo

2015-03-01

Reliable wireless high temperature electrochemical sensor technology is needed to provide in situ corrosion information for optimal predictive maintenance to ensure a high level of operational effectiveness under the harsh conditions present in coal-fired power generation systems. This research highlights the effectiveness of our novel high temperature electrochemical sensor for in situ coal ash hot corrosion monitoring in combination with the application of wireless communication and an energy harvesting thermoelectric generator (TEG). This self-powered sensor demonstrates the successful wireless transmission of both corrosion potential and corrosion current signals to a simulated control room environment. Copyright © 2014 ISA. All rights reserved.

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.

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.

Modelling based on Spatial Impulse Response Model for Optimization of Inter Digital Transducers (SAW Sensors) for Non Destructive Testing

NASA Astrophysics Data System (ADS)

Fall, D.; Duquennoy, M.; Ouaftouh, M.; Piwakowski, B.; Jenot, F.

This study deals with modelling SAW-IDT transducers for their optimization. These sensors are specifically developed to characterize properties of thin layers, coatings and functional surfaces. Among the methods of characterization, the ultrasonic methods using Rayleigh surface waves are particularly interesting because the propagation of these waves is close to the surface of material and the energy is concentrated within a layer under the surface of about one wavelength thick. In order to characterize these coatings and structures, it is necessary to work in high frequencies, this is why in this study, SAW-IDT sensors are realized for surface acoustic wave generation. For optimization of these SAW-IDT sensors, particularly their band-width, it is necessary to study various IDT configurations by varying the number of electrodes, dimensions of the electrodes, their shapes and spacings. Thus it is necessary to implement effective and rapid technique for modelling. The originality of this study is to develop simulation tools based on Spatial Impulse Response model. Therefore it will be possible to reduce considerably computing time and results are obtained in a few seconds, instead of several hours (or days) by using finite element method. In order to validate this method, theoretical and experimental results are compared with finite element method and Interferometric measurements. The results obtained show a good overall concordance and confirm effectiveness of suggested method.

Assessing FPAR Source and Parameter Optimization Scheme in Application of a Diagnostic Carbon Flux Model

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

Turner, D P; Ritts, W D; Wharton, S

2009-02-26

The combination of satellite remote sensing and carbon cycle models provides an opportunity for regional to global scale monitoring of terrestrial gross primary production, ecosystem respiration, and net ecosystem production. FPAR (the fraction of photosynthetically active radiation absorbed by the plant canopy) is a critical input to diagnostic models, however little is known about the relative effectiveness of FPAR products from different satellite sensors nor about the sensitivity of flux estimates to different parameterization approaches. In this study, we used multiyear observations of carbon flux at four eddy covariance flux tower sites within the conifer biome to evaluate these factors.more » FPAR products from the MODIS and SeaWiFS sensors, and the effects of single site vs. cross-site parameter optimization were tested with the CFLUX model. The SeaWiFs FPAR product showed greater dynamic range across sites and resulted in slightly reduced flux estimation errors relative to the MODIS product when using cross-site optimization. With site-specific parameter optimization, the flux model was effective in capturing seasonal and interannual variation in the carbon fluxes at these sites. The cross-site prediction errors were lower when using parameters from a cross-site optimization compared to parameter sets from optimization at single sites. These results support the practice of multisite optimization within a biome for parameterization of diagnostic carbon flux models.« less

Design optimization of an ironless inductive position sensor for the LHC collimators

NASA Astrophysics Data System (ADS)

Danisi, A.; Masi, A.; Losito, R.; Perriard, Y.

2013-09-01

The Ironless Inductive Position Sensor (I2PS) is an air-cored displacement sensor which has been conceived to be totally immune to external DC/slowly-varying magnetic fields. It can thus be used as a valid alternative to Linear Variable Differential Transformers (LVDTs), which can show a position error in magnetic environments. In addition, since it retains the excellent properties of LVDTs, the I2PS can be used in harsh environments, such as nuclear plants, plasma control and particle accelerators. This paper focuses on the design optimization of the sensor, considering the CERN LHC Collimators as application. In particular, the optimization comes after a complete review of the electromagnetic and thermal modeling of the sensor, as well as the proper choice of the reading technique. The design optimization stage is firmly based on these preliminary steps. Therefore, the paper summarises the sensor's complete development, from its modeling to its actual implementation. A set of experimental measurements demonstrates the sensor's performances to be those expected in the design phase.

Dynamic optimization of ISR sensors using a risk-based reward function applied to ground and space surveillance scenarios

NASA Astrophysics Data System (ADS)

DeSena, J. T.; Martin, S. R.; Clarke, J. C.; Dutrow, D. A.; Newman, A. J.

2012-06-01

As the number and diversity of sensing assets available for intelligence, surveillance and reconnaissance (ISR) operations continues to expand, the limited ability of human operators to effectively manage, control and exploit the ISR ensemble is exceeded, leading to reduced operational effectiveness. Automated support both in the processing of voluminous sensor data and sensor asset control can relieve the burden of human operators to support operation of larger ISR ensembles. In dynamic environments it is essential to react quickly to current information to avoid stale, sub-optimal plans. Our approach is to apply the principles of feedback control to ISR operations, "closing the loop" from the sensor collections through automated processing to ISR asset control. Previous work by the authors demonstrated non-myopic multiple platform trajectory control using a receding horizon controller in a closed feedback loop with a multiple hypothesis tracker applied to multi-target search and track simulation scenarios in the ground and space domains. This paper presents extensions in both size and scope of the previous work, demonstrating closed-loop control, involving both platform routing and sensor pointing, of a multisensor, multi-platform ISR ensemble tasked with providing situational awareness and performing search, track and classification of multiple moving ground targets in irregular warfare scenarios. The closed-loop ISR system is fullyrealized using distributed, asynchronous components that communicate over a network. The closed-loop ISR system has been exercised via a networked simulation test bed against a scenario in the Afghanistan theater implemented using high-fidelity terrain and imagery data. In addition, the system has been applied to space surveillance scenarios requiring tracking of space objects where current deliberative, manually intensive processes for managing sensor assets are insufficiently responsive. Simulation experiment results are presented. The algorithm to jointly optimize sensor schedules against search, track, and classify is based on recent work by Papageorgiou and Raykin on risk-based sensor management. It uses a risk-based objective function and attempts to minimize and balance the risks of misclassifying and losing track on an object. It supports the requirement to generate tasking for metric and feature data concurrently and synergistically, and account for both tracking accuracy and object characterization, jointly, in computing reward and cost for optimizing tasking decisions.

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.

Open-WiSe: A Solar Powered Wireless Sensor Network Platform

PubMed Central

González, Apolinar; Aquino, Raúl; Mata, Walter; Ochoa, Alberto; Saldaña, Pedro; Edwards, Arthur

2012-01-01

Because battery-powered nodes are required in wireless sensor networks and energy consumption represents an important design consideration, alternate energy sources are needed to provide more effective and optimal function. The main goal of this work is to present an energy harvesting wireless sensor network platform, the Open Wireless Sensor node (WiSe). The design and implementation of the solar powered wireless platform is described including the hardware architecture, firmware, and a POSIX Real-Time Kernel. A sleep and wake up strategy was implemented to prolong the lifetime of the wireless sensor network. This platform was developed as a tool for researchers investigating Wireless sensor network or system integrators. PMID:22969396

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.

Optimal Sensor Placement with Terrain-Based Constraints and Signal Propagation Effects

DTIC Science & Technology

2008-12-01

example, in optics where the intensities of two inco - herent sources are summed algebraically in contrast to coherent sources (Balanis 1989). Because...5.1M M is the total number of sensors in a network. According to Figure 10, one would need approximately eight full days to process eight sensors. A...Eidenbenz, S. 2002. Approximation algorithms for terrain guarding. Inf Process Lett 82:99–105. Elnagar, A., and L. Lulu. 2005. An art gallery

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.

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

The research of autonomous obstacle avoidance of mobile robot based on multi-sensor integration

NASA Astrophysics Data System (ADS)

Zhao, Ming; Han, Baoling

2016-11-01

The object of this study is the bionic quadruped mobile robot. The study has proposed a system design plan for mobile robot obstacle avoidance with the binocular stereo visual sensor and the self-control 3D Lidar integrated with modified ant colony optimization path planning to realize the reconstruction of the environmental map. Because the working condition of a mobile robot is complex, the result of the 3D reconstruction with a single binocular sensor is undesirable when feature points are few and the light condition is poor. Therefore, this system integrates the stereo vision sensor blumblebee2 and the Lidar sensor together to detect the cloud information of 3D points of environmental obstacles. This paper proposes the sensor information fusion technology to rebuild the environment map. Firstly, according to the Lidar data and visual data on obstacle detection respectively, and then consider two methods respectively to detect the distribution of obstacles. Finally fusing the data to get the more complete, more accurate distribution of obstacles in the scene. Then the thesis introduces ant colony algorithm. It has analyzed advantages and disadvantages of the ant colony optimization and its formation cause deeply, and then improved the system with the help of the ant colony optimization to increase the rate of convergence and precision of the algorithm in robot path planning. Such improvements and integrations overcome the shortcomings of the ant colony optimization like involving into the local optimal solution easily, slow search speed and poor search results. This experiment deals with images and programs the motor drive under the compiling environment of Matlab and Visual Studio and establishes the visual 2.5D grid map. Finally it plans a global path for the mobile robot according to the ant colony algorithm. The feasibility and effectiveness of the system are confirmed by ROS and simulation platform of Linux.

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.

Grating-Coupled Surface Plasmon Resonance (GC-SPR) Optimization for Phase-Interrogation Biosensing in a Microfluidic Chamber.

PubMed

Rossi, Stefano; Gazzola, Enrico; Capaldo, Pietro; Borile, Giulia; Romanato, Filippo

2018-05-18

Surface Plasmon Resonance (SPR)-based sensors have the advantage of being label-free, enzyme-free and real-time. However, their spreading in multidisciplinary research is still mostly limited to prism-coupled devices. Plasmonic gratings, combined with a simple and cost-effective instrumentation, have been poorly developed compared to prism-coupled system mainly due to their lower sensitivity. Here we describe the optimization and signal enhancement of a sensing platform based on phase-interrogation method, which entails the exploitation of a nanostructured sensor. This technique is particularly suitable for integration of the plasmonic sensor in a lab-on-a-chip platform and can be used in a microfluidic chamber to ease the sensing procedures and limit the injected volume. The careful optimization of most suitable experimental parameters by numerical simulations leads to a 30⁻50% enhancement of SPR response, opening new possibilities for applications in the biomedical research field while maintaining the ease and versatility of the configuration.

Grating-Coupled Surface Plasmon Resonance (GC-SPR) Optimization for Phase-Interrogation Biosensing in a Microfluidic Chamber

PubMed Central

Rossi, Stefano; Gazzola, Enrico; Capaldo, Pietro; Borile, Giulia; Romanato, Filippo

2018-01-01

Surface Plasmon Resonance (SPR)-based sensors have the advantage of being label-free, enzyme-free and real-time. However, their spreading in multidisciplinary research is still mostly limited to prism-coupled devices. Plasmonic gratings, combined with a simple and cost-effective instrumentation, have been poorly developed compared to prism-coupled system mainly due to their lower sensitivity. Here we describe the optimization and signal enhancement of a sensing platform based on phase-interrogation method, which entails the exploitation of a nanostructured sensor. This technique is particularly suitable for integration of the plasmonic sensor in a lab-on-a-chip platform and can be used in a microfluidic chamber to ease the sensing procedures and limit the injected volume. The careful optimization of most suitable experimental parameters by numerical simulations leads to a 30–50% enhancement of SPR response, opening new possibilities for applications in the biomedical research field while maintaining the ease and versatility of the configuration. PMID:29783711

Wireless Sensor Network Congestion Control Based on Standard Particle Swarm Optimization and Single Neuron PID

PubMed Central

Yang, Xiaoping; Chen, Xueying; Xia, Riting; Qian, Zhihong

2018-01-01

Aiming at the problem of network congestion caused by the large number of data transmissions in wireless routing nodes of wireless sensor network (WSN), this paper puts forward an algorithm based on standard particle swarm–neural PID congestion control (PNPID). Firstly, PID control theory was applied to the queue management of wireless sensor nodes. Then, the self-learning and self-organizing ability of neurons was used to achieve online adjustment of weights to adjust the proportion, integral and differential parameters of the PID controller. Finally, the standard particle swarm optimization to neural PID (NPID) algorithm of initial values of proportion, integral and differential parameters and neuron learning rates were used for online optimization. This paper describes experiments and simulations which show that the PNPID algorithm effectively stabilized queue length near the expected value. At the same time, network performance, such as throughput and packet loss rate, was greatly improved, which alleviated network congestion and improved network QoS. PMID:29671822

Wireless Sensor Network Congestion Control Based on Standard Particle Swarm Optimization and Single Neuron PID.

PubMed

Yang, Xiaoping; Chen, Xueying; Xia, Riting; Qian, Zhihong

2018-04-19

Aiming at the problem of network congestion caused by the large number of data transmissions in wireless routing nodes of wireless sensor network (WSN), this paper puts forward an algorithm based on standard particle swarm⁻neural PID congestion control (PNPID). Firstly, PID control theory was applied to the queue management of wireless sensor nodes. Then, the self-learning and self-organizing ability of neurons was used to achieve online adjustment of weights to adjust the proportion, integral and differential parameters of the PID controller. Finally, the standard particle swarm optimization to neural PID (NPID) algorithm of initial values of proportion, integral and differential parameters and neuron learning rates were used for online optimization. This paper describes experiments and simulations which show that the PNPID algorithm effectively stabilized queue length near the expected value. At the same time, network performance, such as throughput and packet loss rate, was greatly improved, which alleviated network congestion and improved network QoS.

Dynamic tuning of chemiresistor sensitivity using mechanical strain

DOEpatents

Martin, James E; Read, Douglas H

2014-09-30

The sensitivity of a chemiresistor sensor can be dynamically tuned using mechanical strain. The increase in sensitivity is a smooth, continuous function of the applied strain, and the effect can be reversible. Sensitivity tuning enables the response curve of the sensor to be dynamically optimized for sensing analytes, such as volatile organic compounds, over a wide concentration range.

Optimal space-time attacks on system state estimation under a sparsity constraint

NASA Astrophysics Data System (ADS)

Lu, Jingyang; Niu, Ruixin; Han, Puxiao

2016-05-01

System state estimation in the presence of an adversary that injects false information into sensor readings has attracted much attention in wide application areas, such as target tracking with compromised sensors, secure monitoring of dynamic electric power systems, secure driverless cars, and radar tracking and detection in the presence of jammers. From a malicious adversary's perspective, the optimal strategy for attacking a multi-sensor dynamic system over sensors and over time is investigated. It is assumed that the system defender can perfectly detect the attacks and identify and remove sensor data once they are corrupted by false information injected by the adversary. With this in mind, the adversary's goal is to maximize the covariance matrix of the system state estimate by the end of attack period under a sparse attack constraint such that the adversary can only attack the system a few times over time and over sensors. The sparsity assumption is due to the adversary's limited resources and his/her intention to reduce the chance of being detected by the system defender. This becomes an integer programming problem and its optimal solution, the exhaustive search, is intractable with a prohibitive complexity, especially for a system with a large number of sensors and over a large number of time steps. Several suboptimal solutions, such as those based on greedy search and dynamic programming are proposed to find the attack strategies. Examples and numerical results are provided in order to illustrate the effectiveness and the reduced computational complexities of the proposed attack strategies.

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.

Impact of High Power Interference Sources in Planning and Deployment of Wireless Sensor Networks and Devices in the 2.4 GHz Frequency Band in Heterogeneous Environments

PubMed Central

Iturri, Peio López; Nazábal, Juan Antonio; Azpilicueta, Leire; Rodriguez, Pablo; Beruete, Miguel; Fernández-Valdivielso, Carlos; Falcone, Francisco

2012-01-01

In this work, the impact of radiofrequency radiation leakage from microwave ovens and its effect on 802.15.4 ZigBee-compliant wireless sensor networks operating in the 2.4 GHz Industrial Scientific Medical (ISM) band is analyzed. By means of a novel radioplanning approach, based on electromagnetic field simulation of a microwave oven and determination of equivalent radiation sources applied to an in-house developed 3D ray launching algorithm, estimation of the microwave oven's power leakage is obtained for the complete volume of an indoor scenario. The magnitude and the variable nature of the interference is analyzed and the impact in the radio link quality in operating wireless sensors is estimated and compared with radio channel measurements as well as packet measurements. The measurement results reveal the importance of selecting an adequate 802.15.4 channel, as well as the Wireless Sensor Network deployment strategy within this type of environment, in order to optimize energy consumption and increase the overall network performance. The proposed method enables one to estimate potential interference effects in devices operating within the 2.4 GHz band in the complete scenario, prior to wireless sensor network deployment, which can aid in achieving the most optimal network topology. PMID:23202228

Intelligent Luminance Control of Lighting Systems Based on Imaging Sensor Feedback

PubMed Central

Liu, Haoting; Zhou, Qianxiang; Yang, Jin; Jiang, Ting; Liu, Zhizhen; Li, Jie

2017-01-01

An imaging sensor-based intelligent Light Emitting Diode (LED) lighting system for desk use is proposed. In contrast to the traditional intelligent lighting system, such as the photosensitive resistance sensor-based or the infrared sensor-based system, the imaging sensor can realize a finer perception of the environmental light; thus it can guide a more precise lighting control. Before this system works, first lots of typical imaging lighting data of the desk application are accumulated. Second, a series of subjective and objective Lighting Effect Evaluation Metrics (LEEMs) are defined and assessed for these datasets above. Then the cluster benchmarks of these objective LEEMs can be obtained. Third, both a single LEEM-based control and a multiple LEEMs-based control are developed to realize a kind of optimal luminance tuning. When this system works, first it captures the lighting image using a wearable camera. Then it computes the objective LEEMs of the captured image and compares them with the cluster benchmarks of the objective LEEMs. Finally, the single LEEM-based or the multiple LEEMs-based control can be implemented to get a kind of optimal lighting effect. Many experiment results have shown the proposed system can tune the LED lamp automatically according to environment luminance changes. PMID:28208781

Intelligent Luminance Control of Lighting Systems Based on Imaging Sensor Feedback.

PubMed

Liu, Haoting; Zhou, Qianxiang; Yang, Jin; Jiang, Ting; Liu, Zhizhen; Li, Jie

2017-02-09

An imaging sensor-based intelligent Light Emitting Diode (LED) lighting system for desk use is proposed. In contrast to the traditional intelligent lighting system, such as the photosensitive resistance sensor-based or the infrared sensor-based system, the imaging sensor can realize a finer perception of the environmental light; thus it can guide a more precise lighting control. Before this system works, first lots of typical imaging lighting data of the desk application are accumulated. Second, a series of subjective and objective Lighting Effect Evaluation Metrics (LEEMs) are defined and assessed for these datasets above. Then the cluster benchmarks of these objective LEEMs can be obtained. Third, both a single LEEM-based control and a multiple LEEMs-based control are developed to realize a kind of optimal luminance tuning. When this system works, first it captures the lighting image using a wearable camera. Then it computes the objective LEEMs of the captured image and compares them with the cluster benchmarks of the objective LEEMs. Finally, the single LEEM-based or the multiple LEEMs-based control can be implemented to get a kind of optimal lighting effect. Many experiment results have shown the proposed system can tune the LED lamp automatically according to environment luminance changes.

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

Microwave remote sensing of soil moisture, volume 1. [Guymon, Oklahoma and Dalhart, Texas

NASA Technical Reports Server (NTRS)

Mcfarland, M. J. (Principal Investigator); Theis, S. W.; Rosenthal, W. D.; Jones, C. L.

1982-01-01

Multifrequency sensor data from NASA's C-130 aircraft were used to determine which of the all weather microwave sensors demonstrated the highest correlation to surface soil moisture over optimal bare soil conditions, and to develop and test techniques which use visible/infrared sensors to compensate for the vegetation effect in this sensor's response to soil moisture. The L-band passive microwave radiometer was found to be the most suitable single sensor system to estimate soil moisture over bare fields. The perpendicular vegetation index (PVI) as determined from the visible/infrared sensors was useful as a measure of the vegetation effect on the L-band radiometer response to soil moisture. A linear equation was developed to estimate percent field capacity as a function of L-band emissivity and the vegetation index. The prediction algorithm improves the estimation of moisture significantly over predictions from L-band emissivity alone.

Non-gravimetric contributions to QCR sensor response.

PubMed

Lucklum, Ralf

2005-11-01

Quartz crystal resonator (QCR) sensors are commonly known as mass sensitive devices, usually called QCM (Quartz Crystal Microbalance). This constricted view should not be applied to biosensor applications. In many cases the sensor response is strongly influenced or even governed by non-gravimetric effects; the QCR sensor does not act as a microbalance. For better understanding of the sensor response as well as for sensor optimization a more general description of the sensor principle is required. The Transmission Line Model (TLM) is a powerful tool to describe the transduction scheme of QCR and other acoustic-wave based sensors. It is therefore applied to the analysis of the sensor behavior under several conditions, which can be expected in biochemical experiments. The generalization of acoustic parameters provides a concept to overcome some of the limiting assumptions of the present TLM.

Molecularly Imprinted Sol-Gel-Based QCM Sensor Arrays for the Detection and Recognition of Volatile Aldehydes.

PubMed

Liu, Chuanjun; Wyszynski, Bartosz; Yatabe, Rui; Hayashi, Kenshi; Toko, Kiyoshi

2017-02-16

The detection and recognition of metabolically derived aldehydes, which have been identified as important products of oxidative stress and biomarkers of cancers; are considered as an effective approach for early cancer detection as well as health status monitoring. Quartz crystal microbalance (QCM) sensor arrays based on molecularly imprinted sol-gel (MISG) materials were developed in this work for highly sensitive detection and highly selective recognition of typical aldehyde vapors including hexanal (HAL); nonanal (NAL) and bezaldehyde (BAL). The MISGs were prepared by a sol-gel procedure using two matrix precursors: tetraethyl orthosilicate (TEOS) and tetrabutoxytitanium (TBOT). Aminopropyltriethoxysilane (APT); diethylaminopropyltrimethoxysilane (EAP) and trimethoxy-phenylsilane (TMP) were added as functional monomers to adjust the imprinting effect of the matrix. Hexanoic acid (HA); nonanoic acid (NA) and benzoic acid (BA) were used as psuedotemplates in view of their analogous structure to the target molecules as well as the strong hydrogen-bonding interaction with the matrix. Totally 13 types of MISGs with different components were prepared and coated on QCM electrodes by spin coating. Their sensing characters towards the three aldehyde vapors with different concentrations were investigated qualitatively. The results demonstrated that the response of individual sensors to each target strongly depended on the matrix precursors; functional monomers and template molecules. An optimization of the 13 MISG materials was carried out based on statistical analysis such as principle component analysis (PCA); multivariate analysis of covariance (MANCOVA) and hierarchical cluster analysis (HCA). The optimized sensor array consisting of five channels showed a high discrimination ability on the aldehyde vapors; which was confirmed by quantitative comparison with a randomly selected array. It was suggested that both the molecularly imprinting (MIP) effect and the matrix effect contributed to the sensitivity and selectivity of the optimized sensor array. The developed MISGs were expected to be promising materials for the detection and recognition of volatile aldehydes contained in exhaled breath or human body odor.

Molecularly Imprinted Sol-Gel-Based QCM Sensor Arrays for the Detection and Recognition of Volatile Aldehydes

PubMed Central

Liu, Chuanjun; Wyszynski, Bartosz; Yatabe, Rui; Hayashi, Kenshi; Toko, Kiyoshi

2017-01-01

The detection and recognition of metabolically derived aldehydes, which have been identified as important products of oxidative stress and biomarkers of cancers; are considered as an effective approach for early cancer detection as well as health status monitoring. Quartz crystal microbalance (QCM) sensor arrays based on molecularly imprinted sol-gel (MISG) materials were developed in this work for highly sensitive detection and highly selective recognition of typical aldehyde vapors including hexanal (HAL); nonanal (NAL) and bezaldehyde (BAL). The MISGs were prepared by a sol-gel procedure using two matrix precursors: tetraethyl orthosilicate (TEOS) and tetrabutoxytitanium (TBOT). Aminopropyltriethoxysilane (APT); diethylaminopropyltrimethoxysilane (EAP) and trimethoxy-phenylsilane (TMP) were added as functional monomers to adjust the imprinting effect of the matrix. Hexanoic acid (HA); nonanoic acid (NA) and benzoic acid (BA) were used as psuedotemplates in view of their analogous structure to the target molecules as well as the strong hydrogen-bonding interaction with the matrix. Totally 13 types of MISGs with different components were prepared and coated on QCM electrodes by spin coating. Their sensing characters towards the three aldehyde vapors with different concentrations were investigated qualitatively. The results demonstrated that the response of individual sensors to each target strongly depended on the matrix precursors; functional monomers and template molecules. An optimization of the 13 MISG materials was carried out based on statistical analysis such as principle component analysis (PCA); multivariate analysis of covariance (MANCOVA) and hierarchical cluster analysis (HCA). The optimized sensor array consisting of five channels showed a high discrimination ability on the aldehyde vapors; which was confirmed by quantitative comparison with a randomly selected array. It was suggested that both the molecularly imprinting (MIP) effect and the matrix effect contributed to the sensitivity and selectivity of the optimized sensor array. The developed MISGs were expected to be promising materials for the detection and recognition of volatile aldehydes contained in exhaled breath or human body odor. PMID:28212347

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

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

The effect of rising vs. falling glucose level on amperometric glucose sensor lag and accuracy in Type 1 diabetes.

PubMed

Ward, W K; Engle, J M; Branigan, D; El Youssef, J; Massoud, R G; Castle, J R

2012-08-01

Because declining glucose levels should be detected quickly in persons with Type 1 diabetes, a lag between blood glucose and subcutaneous sensor glucose can be problematic. It is unclear whether the magnitude of sensor lag is lower during falling glucose than during rising glucose. Initially, we analysed 95 data segments during which glucose changed and during which very frequent reference blood glucose monitoring was performed. However, to minimize confounding effects of noise and calibration error, we excluded data segments in which there was substantial sensor error. After these exclusions, and combination of data from duplicate sensors, there were 72 analysable data segments (36 for rising glucose, 36 for falling). We measured lag in two ways: (1) the time delay at the vertical mid-point of the glucose change (regression delay); and (2) determination of the optimal time shift required to minimize the difference between glucose sensor signals and blood glucose values drawn concurrently. Using the regression delay method, the mean sensor lag for rising vs. falling glucose segments was 8.9 min (95%CI 6.1-11.6) vs. 1.5 min (95%CI -2.6 to 5.5, P<0.005). Using the time shift optimization method, results were similar, with a lag that was higher for rising than for falling segments [8.3 (95%CI 5.8-10.7) vs. 1.5 min (95% CI -2.2 to 5.2), P<0.001]. Commensurate with the lag results, sensor accuracy was greater during falling than during rising glucose segments. In Type 1 diabetes, when noise and calibration error are minimized to reduce effects that confound delay measurement, subcutaneous glucose sensors demonstrate a shorter lag duration and greater accuracy when glucose is falling than when rising. © 2011 The Authors. Diabetic Medicine © 2011 Diabetes UK.

Results in standardization of FOS to support the use of SHM systems

NASA Astrophysics Data System (ADS)

Habel, Wolfgang R.; Krebber, Katerina; Daum, Werner

2016-05-01

Measurement and data recording systems are important parts of a holistic Structural Health Monitoring (SHM) system. New sensor technologies such as fiber-optic sensors are often used; however, standards (or at least guidelines) are not yet available or internationally approved. This lack in standardization makes the acceptance of FOS technologies in complex SHM systems substantially difficult. A standard family for different FOS technologies is therefore being developed that should help to design SHM systems in an optimal way. International standardization activities take place in several standardization bodies such as IEC and ASTM, and within SHM societies such as ISHMII. The paper reports on activities in standardization of fiber-optic sensors, on results already achieved, and on newly started projects. Combined activities of fiber sensor experts and SHM experts from Civil Engineering are presented. These contributions should help owners of structures as well as developers of sensors and monitoring systems to select effective and validated sensing technologies. Using these standards, both parties find recommendations how to proceed in development of SHM systems to evaluate the structural behavior based on e.g. standardized fiber optic sensors, and to derive necessary measures, e.g. the optimal maintenance strategy.

Development of contactless sensors for industrial and automative applications

NASA Astrophysics Data System (ADS)

Heidler, E. A.; Kanbach, H.; Interhoff, H.

1985-04-01

Contactless speed and torque sensors were developed for power measurement and control of motors and for the investigation of their properties for applications in motor vehicle and in industrial domains. For the speed sensor a magnetic bistable wire was developed. The method of wire preparation, efforts to optimize its properties, and data of the prototypes are described. The torque sensor is based on an eddy current measuring head of relatively small dimensions. Changes of permeability at rotating ferromagnetic shafts are detected contactlessly. These changes originate from the inverse magnetostrictive effect as a result of the torsion of the loaded shaft. They are a function of the torque acting at the shaft. The measuring heads and relevant effects are described.

FDTD-based optical simulations methodology for CMOS image sensors pixels architecture and process optimization

NASA Astrophysics Data System (ADS)

Hirigoyen, Flavien; Crocherie, Axel; Vaillant, Jérôme M.; Cazaux, Yvon

2008-02-01

This paper presents a new FDTD-based optical simulation model dedicated to describe the optical performances of CMOS image sensors taking into account diffraction effects. Following market trend and industrialization constraints, CMOS image sensors must be easily embedded into even smaller packages, which are now equipped with auto-focus and short-term coming zoom system. Due to miniaturization, the ray-tracing models used to evaluate pixels optical performances are not accurate anymore to describe the light propagation inside the sensor, because of diffraction effects. Thus we adopt a more fundamental description to take into account these diffraction effects: we chose to use Maxwell-Boltzmann based modeling to compute the propagation of light, and to use a software with an FDTD-based (Finite Difference Time Domain) engine to solve this propagation. We present in this article the complete methodology of this modeling: on one hand incoherent plane waves are propagated to approximate a product-use diffuse-like source, on the other hand we use periodic conditions to limit the size of the simulated model and both memory and computation time. After having presented the correlation of the model with measurements we will illustrate its use in the case of the optimization of a 1.75μm pixel.

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.

A risk-based multi-objective model for optimal placement of sensors in water distribution system

NASA Astrophysics Data System (ADS)

Naserizade, Sareh S.; Nikoo, Mohammad Reza; Montaseri, Hossein

2018-02-01

In this study, a new stochastic model based on Conditional Value at Risk (CVaR) and multi-objective optimization methods is developed for optimal placement of sensors in water distribution system (WDS). This model determines minimization of risk which is caused by simultaneous multi-point contamination injection in WDS using CVaR approach. The CVaR considers uncertainties of contamination injection in the form of probability distribution function and calculates low-probability extreme events. In this approach, extreme losses occur at tail of the losses distribution function. Four-objective optimization model based on NSGA-II algorithm is developed to minimize losses of contamination injection (through CVaR of affected population and detection time) and also minimize the two other main criteria of optimal placement of sensors including probability of undetected events and cost. Finally, to determine the best solution, Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE), as a subgroup of Multi Criteria Decision Making (MCDM) approach, is utilized to rank the alternatives on the trade-off curve among objective functions. Also, sensitivity analysis is done to investigate the importance of each criterion on PROMETHEE results considering three relative weighting scenarios. The effectiveness of the proposed methodology is examined through applying it to Lamerd WDS in the southwestern part of Iran. The PROMETHEE suggests 6 sensors with suitable distribution that approximately cover all regions of WDS. Optimal values related to CVaR of affected population and detection time as well as probability of undetected events for the best optimal solution are equal to 17,055 persons, 31 mins and 0.045%, respectively. The obtained results of the proposed methodology in Lamerd WDS show applicability of CVaR-based multi-objective simulation-optimization model for incorporating the main uncertainties of contamination injection in order to evaluate extreme value of losses in WDS.

Path optimization with limited sensing ability

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

Kang, Sung Ha, E-mail: kang@math.gatech.edu; Kim, Seong Jun, E-mail: skim396@math.gatech.edu; Zhou, Haomin, E-mail: hmzhou@math.gatech.edu

2015-10-15

We propose a computational strategy to find the optimal path for a mobile sensor with limited coverage to traverse a cluttered region. The goal is to find one of the shortest feasible paths to achieve the complete scan of the environment. We pose the problem in the level set framework, and first consider a related question of placing multiple stationary sensors to obtain the full surveillance of the environment. By connecting the stationary locations using the nearest neighbor strategy, we form the initial guess for the path planning problem of the mobile sensor. Then the path is optimized by reducingmore » its length, via solving a system of ordinary differential equations (ODEs), while maintaining the complete scan of the environment. Furthermore, we use intermittent diffusion, which converts the ODEs into stochastic differential equations (SDEs), to find an optimal path whose length is globally minimal. To improve the computation efficiency, we introduce two techniques, one to remove redundant connecting points to reduce the dimension of the system, and the other to deal with the entangled path so the solution can escape the local traps. Numerical examples are shown to illustrate the effectiveness of the proposed method.« less

Flexible Fusion Structure-Based Performance Optimization Learning for Multisensor Target Tracking

PubMed Central

Ge, Quanbo; Wei, Zhongliang; Cheng, Tianfa; Chen, Shaodong; Wang, Xiangfeng

2017-01-01

Compared with the fixed fusion structure, the flexible fusion structure with mixed fusion methods has better adjustment performance for the complex air task network systems, and it can effectively help the system to achieve the goal under the given constraints. Because of the time-varying situation of the task network system induced by moving nodes and non-cooperative target, and limitations such as communication bandwidth and measurement distance, it is necessary to dynamically adjust the system fusion structure including sensors and fusion methods in a given adjustment period. Aiming at this, this paper studies the design of a flexible fusion algorithm by using an optimization learning technology. The purpose is to dynamically determine the sensors’ numbers and the associated sensors to take part in the centralized and distributed fusion processes, respectively, herein termed sensor subsets selection. Firstly, two system performance indexes are introduced. Especially, the survivability index is presented and defined. Secondly, based on the two indexes and considering other conditions such as communication bandwidth and measurement distance, optimization models for both single target tracking and multi-target tracking are established. Correspondingly, solution steps are given for the two optimization models in detail. Simulation examples are demonstrated to validate the proposed algorithms. PMID:28481243

Designing Robust and Resilient Tactical MANETs

DTIC Science & Technology

2014-09-25

Bounds on the Throughput Efficiency of Greedy Maximal Scheduling in Wireless Networks , IEEE/ACM Transactions on Networking , (06 2011): 0. doi: N... Wireless Sensor Networks and Effects of Long Range Dependant Data, Special IWSM Issue of Sequential Analysis, (11 2012): 0. doi: A. D. Dominguez...Bushnell, R. Poovendran. A Convex Optimization Approach for Clone Detection in Wireless Sensor Networks , Pervasive and Mobile Computing, (01 2012

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 Low Power IoT Sensor Node Architecture for Waste Management Within Smart Cities Context.

PubMed

Cerchecci, Matteo; Luti, Francesco; Mecocci, Alessandro; Parrino, Stefano; Peruzzi, Giacomo; Pozzebon, Alessandro

2018-04-21

This paper focuses on the realization of an Internet of Things (IoT) architecture to optimize waste management in the context of Smart Cities. In particular, a novel typology of sensor node based on the use of low cost and low power components is described. This node is provided with a single-chip microcontroller, a sensor able to measure the filling level of trash bins using ultrasounds and a data transmission module based on the LoRa LPWAN (Low Power Wide Area Network) technology. Together with the node, a minimal network architecture was designed, based on a LoRa gateway, with the purpose of testing the IoT node performances. Especially, the paper analyzes in detail the node architecture, focusing on the energy saving technologies and policies, with the purpose of extending the batteries lifetime by reducing power consumption, through hardware and software optimization. Tests on sensor and radio module effectiveness are also presented.

Preparation and Analysis of Platinum Thin Films for High Temperature Sensor Applications

NASA Technical Reports Server (NTRS)

Wrbanek, John D.; Laster, Kimala L. H.

2005-01-01

A study has been made of platinum thin films for application as high temperature resistive sensors. To support NASA Glenn Research Center s high temperature thin film sensor effort, a magnetron sputtering system was installed recently in the GRC Microsystems Fabrication Clean Room Facility. Several samples of platinum films were prepared using various system parameters to establish run conditions. These films were characterized with the intended application of being used as resistive sensing elements, either for temperature or strain measurement. The resistances of several patterned sensors were monitored to document the effect of changes in parameters of deposition and annealing. The parameters were optimized for uniformity and intrinsic strain. The evaporation of platinum via oxidation during annealing over 900 C was documented, and a model for the process developed. The film adhesion was explored on films annealed to 1000 C with various bondcoats on fused quartz and alumina. From this compiled data, a list of optimal parameters and characteristics determined for patterned platinum thin films is given.

A Low Power IoT Sensor Node Architecture for Waste Management Within Smart Cities Context

PubMed Central

Cerchecci, Matteo; Luti, Francesco; Mecocci, Alessandro; Parrino, Stefano; Peruzzi, Giacomo

2018-01-01

This paper focuses on the realization of an Internet of Things (IoT) architecture to optimize waste management in the context of Smart Cities. In particular, a novel typology of sensor node based on the use of low cost and low power components is described. This node is provided with a single-chip microcontroller, a sensor able to measure the filling level of trash bins using ultrasounds and a data transmission module based on the LoRa LPWAN (Low Power Wide Area Network) technology. Together with the node, a minimal network architecture was designed, based on a LoRa gateway, with the purpose of testing the IoT node performances. Especially, the paper analyzes in detail the node architecture, focusing on the energy saving technologies and policies, with the purpose of extending the batteries lifetime by reducing power consumption, through hardware and software optimization. Tests on sensor and radio module effectiveness are also presented. PMID:29690552

Theoretical and experimental investigations of sensor location for optimal aeroelastic system state estimation

NASA Technical Reports Server (NTRS)

Liu, G.

1985-01-01

One of the major concerns in the design of an active control system is obtaining the information needed for effective feedback. This involves the combination of sensing and estimation. A sensor location index is defined as the weighted sum of the mean square estimation errors in which the sensor locations can be regarded as estimator design parameters. The design goal is to choose these locations to minimize the sensor location index. The choice of the number of sensors is a tradeoff between the estimation quality based upon the same performance index and the total costs of installing and maintaining extra sensors. An experimental study for choosing the sensor location was conducted on an aeroelastic system. The system modeling which includes the unsteady aerodynamics model developed by Stephen Rock was improved. Experimental results verify the trend of the theoretical predictions of the sensor location index for different sensor locations at various wind speeds.

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

Anomaly Detection Using Optimally-Placed μPMU Sensors in Distribution Grids

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

Jamei, Mahdi; Scaglione, Anna; Roberts, Ciaran

IEEE As the distribution grid moves toward a tightly-monitored network, it is important to automate the analysis of the enormous amount of data produced by the sensors to increase the operators situational awareness about the system. Here, focusing on Micro-Phasor Measurement Unit (μPMU) data, we propose a hierarchical architecture for monitoring the grid and establish a set of analytics and sensor fusion primitives for the detection of abnormal behavior in the control perimeter. And due to the key role of the μPMU devices in our architecture, a source-constrained optimal μPMU placement is also described that finds the best location ofmore » the devices with respect to our rules. The effectiveness of the proposed methods are tested through the synthetic and real μPMU data.« less

Anomaly Detection Using Optimally-Placed μPMU Sensors in Distribution Grids

DOE PAGES

Jamei, Mahdi; Scaglione, Anna; Roberts, Ciaran; ...

2017-10-25

IEEE As the distribution grid moves toward a tightly-monitored network, it is important to automate the analysis of the enormous amount of data produced by the sensors to increase the operators situational awareness about the system. Here, focusing on Micro-Phasor Measurement Unit (μPMU) data, we propose a hierarchical architecture for monitoring the grid and establish a set of analytics and sensor fusion primitives for the detection of abnormal behavior in the control perimeter. And due to the key role of the μPMU devices in our architecture, a source-constrained optimal μPMU placement is also described that finds the best location ofmore » the devices with respect to our rules. The effectiveness of the proposed methods are tested through the synthetic and real μPMU data.« less

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.

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

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.

Markovian Search Games in Heterogeneous Spaces

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

Griffin, Christopher H

2009-01-01

We consider how to search for a mobile evader in a large heterogeneous region when sensors are used for detection. Sensors are modeled using probability of detection. Due to environmental effects, this probability will not be constant over the entire region. We map this problem to a graph search problem and, even though deterministic graph search is NP-complete, we derive a tractable, optimal, probabilistic search strategy. We do this by defining the problem as a differential game played on a Markov chain. We prove that this strategy is optimal in the sense of Nash. Simulations of an example problem illustratemore » our approach and verify our claims.« less

Integrated approach for automatic target recognition using a network of collaborative sensors.

PubMed

Mahalanobis, Abhijit; Van Nevel, Alan

2006-10-01

We introduce what is believed to be a novel concept by which several sensors with automatic target recognition (ATR) capability collaborate to recognize objects. Such an approach would be suitable for netted systems in which the sensors and platforms can coordinate to optimize end-to-end performance. We use correlation filtering techniques to facilitate the development of the concept, although other ATR algorithms may be easily substituted. Essentially, a self-configuring geometry of netted platforms is proposed that positions the sensors optimally with respect to each other, and takes into account the interactions among the sensor, the recognition algorithms, and the classes of the objects to be recognized. We show how such a paradigm optimizes overall performance, and illustrate the collaborative ATR scheme for recognizing targets in synthetic aperture radar imagery by using viewing position as a sensor parameter.

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.

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

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.

Smart Elasto-Magneto-Electric (EME) Sensors for Stress Monitoring of Steel Cables: Design Theory and Experimental Validation

PubMed Central

Zhang, Ru; Duan, Yuanfeng; Or, Siu Wing; Zhao, Yang

2014-01-01

An elasto-magnetic (EM) and magneto-electric (ME) effect based elasto-magneto-electric (EME) sensor has been proposed recently by the authors for stress monitoring of steel cables with obvious superiorities over traditional elasto-magnetic sensors. For design optimization and engineering application of the EME sensor, the design theory is interpreted with a developed model taking into account the EM coupling effect and ME coupling effect. This model is able to approximate the magnetization changes that a steel structural component undergoes when subjected to excitation magnetic field and external stress, and to simulate the induced ME voltages of the ME sensing unit located in the magnetization area. A full-scale experiment is then carried out to verify the model and to calibrate the EME sensor as a non-destructive evaluation (NDE) tool to monitor the cable stress. The experimental results agree well with the simulation results using the developed model. The proposed EME sensor proves to be feasible for stress monitoring of steel cables with high sensitivity, fast response, and ease of installation. PMID:25072348

Smart elasto-magneto-electric (EME) sensors for stress monitoring of steel cables: design theory and experimental validation.

PubMed

Zhang, Ru; Duan, Yuanfeng; Or, Siu Wing; Zhao, Yang

2014-07-28

An elasto-magnetic (EM) and magneto-electric (ME) effect based elasto-magneto-electric (EME) sensor has been proposed recently by the authors for stress monitoring of steel cables with obvious superiorities over traditional elasto-magnetic sensors. For design optimization and engineering application of the EME sensor, the design theory is interpreted with a developed model taking into account the EM coupling effect and ME coupling effect. This model is able to approximate the magnetization changes that a steel structural component undergoes when subjected to excitation magnetic field and external stress, and to simulate the induced ME voltages of the ME sensing unit located in the magnetization area. A full-scale experiment is then carried out to verify the model and to calibrate the EME sensor as a non-destructive evaluation (NDE) tool to monitor the cable stress. The experimental results agree well with the simulation results using the developed model. The proposed EME sensor proves to be feasible for stress monitoring of steel cables with high sensitivity, fast response, and ease of installation.

Response analysis of holography-based modal wavefront sensor.

PubMed

Dong, Shihao; Haist, Tobias; Osten, Wolfgang; Ruppel, Thomas; Sawodny, Oliver

2012-03-20

The crosstalk problem of holography-based modal wavefront sensing (HMWS) becomes more severe with increasing aberration. In this paper, crosstalk effects on the sensor response are analyzed statistically for typical aberrations due to atmospheric turbulence. For specific turbulence strength, we optimized the sensor by adjusting the detector radius and the encoded phase bias for each Zernike mode. Calibrated response curves of low-order Zernike modes were further utilized to improve the sensor accuracy. The simulation results validated our strategy. The number of iterations for obtaining a residual RMS wavefront error of 0.1λ is reduced from 18 to 3. © 2012 Optical Society of America

A Single Polyaniline Nanofiber Field Effect Transistor and Its Gas Sensing Mechanisms

PubMed Central

Chen, Dajing; Lei, Sheng; Chen, Yuquan

2011-01-01

A single polyaniline nanofiber field effect transistor (FET) gas sensor fabricated by means of electrospinning was investigated to understand its sensing mechanisms and optimize its performance. We studied the morphology, field effect characteristics and gas sensitivity of conductive nanofibers. The fibers showed Schottky and Ohmic contacts based on different electrode materials. Higher applied gate voltage contributes to an increase in gas sensitivity. The nanofiber transistor showed a 7% reversible resistance change to 1 ppm NH3 with 10 V gate voltage. The FET characteristics of the sensor when exposed to different gas concentrations indicate that adsorption of NH3 molecules reduces the carrier mobility in the polyaniline nanofiber. As such, nanofiber-based sensors could be promising for environmental and industrial applications. PMID:22163969

A triaxial accelerometer monkey algorithm for optimal sensor placement in structural health monitoring

NASA Astrophysics Data System (ADS)

Jia, Jingqing; Feng, Shuo; Liu, Wei

2015-06-01

Optimal sensor placement (OSP) technique is a vital part of the field of structural health monitoring (SHM). Triaxial accelerometers have been widely used in the SHM of large-scale structures in recent years. Triaxial accelerometers must be placed in such a way that all of the important dynamic information is obtained. At the same time, the sensor configuration must be optimal, so that the test resources are conserved. The recommended practice is to select proper degrees of freedom (DOF) based upon several criteria and the triaxial accelerometers are placed at the nodes corresponding to these DOFs. This results in non-optimal placement of many accelerometers. A ‘triaxial accelerometer monkey algorithm’ (TAMA) is presented in this paper to solve OSP problems of triaxial accelerometers. The EFI3 measurement theory is modified and involved in the objective function to make it more adaptable in the OSP technique of triaxial accelerometers. A method of calculating the threshold value based on probability theory is proposed to improve the healthy rate of monkeys in a troop generation process. Meanwhile, the processes of harmony ladder climb and scanning watch jump are proposed and given in detail. Finally, Xinghai NO.1 Bridge in Dalian is implemented to demonstrate the effectiveness of TAMA. The final results obtained by TAMA are compared with those of the original monkey algorithm and EFI3 measurement, which show that TAMA can improve computational efficiency and get a better sensor configuration.

Evaluation and optimization of quartz resonant-frequency retuned fork force sensors with high Q factors, and the associated electric circuits, for non-contact atomic force microscopy.

PubMed

Ooe, Hiroaki; Fujii, Mikihiro; Tomitori, Masahiko; Arai, Toyoko

2016-02-01

High-Q factor retuned fork (RTF) force sensors made from quartz tuning forks, and the electric circuits for the sensors, were evaluated and optimized to improve the performance of non-contact atomic force microscopy (nc-AFM) performed under ultrahigh vacuum (UHV) conditions. To exploit the high Q factor of the RTF sensor, the oscillation of the RTF sensor was excited at its resonant frequency, using a stray capacitance compensation circuit to cancel the excitation signal leaked through the stray capacitor of the sensor. To improve the signal-to-noise (S/N) ratio in the detected signal, a small capacitor was inserted before the input of an operational (OP) amplifier placed in an UHV chamber, which reduced the output noise from the amplifier. A low-noise, wideband OP amplifier produced a superior S/N ratio, compared with a precision OP amplifier. The thermal vibrational density spectra of the RTF sensors were evaluated using the circuit. The RTF sensor with an effective spring constant value as low as 1000 N/m provided a lower minimum detection limit for force differentiation. A nc-AFM image of a Si(111)-7 × 7 surface was produced with atomic resolution using the RTF sensor in a constant frequency shift mode; tunneling current and energy dissipation images with atomic resolution were also simultaneously produced. The high-Q factor RTF sensor showed potential for the high sensitivity of energy dissipation as small as 1 meV/cycle and the high-resolution analysis of non-conservative force interactions.

Multisensor fusion with non-optimal decision rules: the challenges of open world sensing

NASA Astrophysics Data System (ADS)

Minor, Christian; Johnson, Kevin

2014-05-01

In this work, simple, generic models of chemical sensing are used to simulate sensor array data and to illustrate the impact on overall system performance that specific design choices impart. The ability of multisensor systems to perform multianalyte detection (i.e., distinguish multiple targets) is explored by examining the distinction between fundamental design-related limitations stemming from mismatching of mixture composition to fused sensor measurement spaces, and limitations that arise from measurement uncertainty. Insight on the limits and potential of sensor fusion to robustly address detection tasks in realistic field conditions can be gained through an examination of a) the underlying geometry of both the composition space of sources one hopes to elucidate and the measurement space a fused sensor system is capable of generating, and b) the informational impact of uncertainty on both of these spaces. For instance, what is the potential impact on sensor fusion in an open world scenario where unknown interferants may contaminate target signals? Under complex and dynamic backgrounds, decision rules may implicitly become non-optimal and adding sensors may increase the amount of conflicting information observed. This suggests that the manner in which a decision rule handles sensor conflict can be critical in leveraging sensor fusion for effective open world sensing, and becomes exponentially more important as more sensors are added. Results and design considerations for handling conflicting evidence in Bayes and Dempster-Shafer fusion frameworks are presented. Bayesian decision theory is used to provide an upper limit on detector performance of simulated sensor systems.

A near-optimal low complexity sensor fusion technique for accurate indoor localization based on ultrasound time of arrival measurements from low-quality sensors

NASA Astrophysics Data System (ADS)

Mitilineos, Stelios A.; Argyreas, Nick D.; Thomopoulos, Stelios C. A.

2009-05-01

A fusion-based localization technique for location-based services in indoor environments is introduced herein, based on ultrasound time-of-arrival measurements from multiple off-the-shelf range estimating sensors which are used in a market-available localization system. In-situ field measurements results indicated that the respective off-the-shelf system was unable to estimate position in most of the cases, while the underlying sensors are of low-quality and yield highly inaccurate range and position estimates. An extensive analysis is performed and a model of the sensor-performance characteristics is established. A low-complexity but accurate sensor fusion and localization technique is then developed, which consists inof evaluating multiple sensor measurements and selecting the one that is considered most-accurate based on the underlying sensor model. Optimality, in the sense of a genie selecting the optimum sensor, is subsequently evaluated and compared to the proposed technique. The experimental results indicate that the proposed fusion method exhibits near-optimal performance and, albeit being theoretically suboptimal, it largely overcomes most flaws of the underlying single-sensor system resulting in a localization system of increased accuracy, robustness and availability.

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.

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.

A new aptameric biosensor for cocaine based on surface-enhanced Raman scattering spectroscopy.

PubMed

Chen, Jiwei; Jiang, Jianhui; Gao, Xing; Liu, Guokun; Shen, Guoli; Yu, Ruqin

2008-01-01

The present study reports the proof of principle of a reagentless aptameric sensor based on surface-enhanced Raman scattering (SERS) spectroscopy with "signal-on" architecture using a model target of cocaine. This new aptameric sensor is based on the conformational change of the surface-tethered aptamer on a binding target that draws a certain Raman reporter in close proximity to the SERS substrate, thereby increasing the Raman scattering signal due to the local enhancement effect of SERS. To improve the response performance, the sensor is fabricated from a cocaine-templated mixed self-assembly of a 3'-terminal tetramethylrhodamine (TMR)-labeled DNA aptamer on a silver colloid film by means of an alkanethiol moiety at the 5' end. This immobilization strategy optimizes the orientation of the aptamer on the surface and facilitates the folding on the binding target. Under optimized assay conditions, one can determine cocaine at a concentration of 1 muM, which compares favorably with analogous aptameric sensors based on electrochemical and fluorescence techniques. The sensor can be readily regenerated by being washed with a buffer. These results suggest that the SERS-based transducer might create a new dimension for future development of aptameric sensors for sensitive determination in biochemical and biomedical studies.

Wireless Sensor Networks - Node Localization for Various Industry Problems

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

Derr, Kurt; Manic, Milos

Fast, effective monitoring following airborne releases of toxic substances is critical to mitigate risks to threatened population areas. Wireless sensor nodes at fixed predetermined locations may monitor such airborne releases and provide early warnings to the public. A challenging algorithmic problem is determining the locations to place these sensor nodes while meeting several criteria: 1) provide complete coverage of the domain, and 2) create a topology with problem dependent node densities, while 3) minimizing the number of sensor nodes. This manuscript presents a novel approach to determining optimal sensor placement, Advancing Front mEsh generation with Constrained dElaunay Triangulation and Smoothingmore » (AFECETS) that addresses these criteria. A unique aspect of AFECETS is the ability to determine wireless sensor node locations for areas of high interest (hospitals, schools, high population density areas) that require higher density of nodes for monitoring environmental conditions, a feature that is difficult to find in other research work. The AFECETS algorithm was tested on several arbitrary shaped domains. AFECETS simulation results show that the algorithm 1) provides significant reduction in the number of nodes, in some cases over 40%, compared to an advancing front mesh generation algorithm, 2) maintains and improves optimal spacing between nodes, and 3) produces simulation run times suitable for real-time applications.« less

Wireless Sensor Networks - Node Localization for Various Industry Problems

DOE PAGES

Derr, Kurt; Manic, Milos

2015-06-01

Fast, effective monitoring following airborne releases of toxic substances is critical to mitigate risks to threatened population areas. Wireless sensor nodes at fixed predetermined locations may monitor such airborne releases and provide early warnings to the public. A challenging algorithmic problem is determining the locations to place these sensor nodes while meeting several criteria: 1) provide complete coverage of the domain, and 2) create a topology with problem dependent node densities, while 3) minimizing the number of sensor nodes. This manuscript presents a novel approach to determining optimal sensor placement, Advancing Front mEsh generation with Constrained dElaunay Triangulation and Smoothingmore » (AFECETS) that addresses these criteria. A unique aspect of AFECETS is the ability to determine wireless sensor node locations for areas of high interest (hospitals, schools, high population density areas) that require higher density of nodes for monitoring environmental conditions, a feature that is difficult to find in other research work. The AFECETS algorithm was tested on several arbitrary shaped domains. AFECETS simulation results show that the algorithm 1) provides significant reduction in the number of nodes, in some cases over 40%, compared to an advancing front mesh generation algorithm, 2) maintains and improves optimal spacing between nodes, and 3) produces simulation run times suitable for real-time applications.« less

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.

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.

A Game Theoretic Approach for Balancing Energy Consumption in Clustered Wireless Sensor Networks.

PubMed

Yang, Liu; Lu, Yinzhi; Xiong, Lian; Tao, Yang; Zhong, Yuanchang

2017-11-17

Clustering is an effective topology control method in wireless sensor networks (WSNs), since it can enhance the network lifetime and scalability. To prolong the network lifetime in clustered WSNs, an efficient cluster head (CH) optimization policy is essential to distribute the energy among sensor nodes. Recently, game theory has been introduced to model clustering. Each sensor node is considered as a rational and selfish player which will play a clustering game with an equilibrium strategy. Then it decides whether to act as the CH according to this strategy for a tradeoff between providing required services and energy conservation. However, how to get the equilibrium strategy while maximizing the payoff of sensor nodes has rarely been addressed to date. In this paper, we present a game theoretic approach for balancing energy consumption in clustered WSNs. With our novel payoff function, realistic sensor behaviors can be captured well. The energy heterogeneity of nodes is considered by incorporating a penalty mechanism in the payoff function, so the nodes with more energy will compete for CHs more actively. We have obtained the Nash equilibrium (NE) strategy of the clustering game through convex optimization. Specifically, each sensor node can achieve its own maximal payoff when it makes the decision according to this strategy. Through plenty of simulations, our proposed game theoretic clustering is proved to have a good energy balancing performance and consequently the network lifetime is greatly enhanced.

A Fault Tolerance Mechanism for On-Road Sensor Networks

PubMed Central

Feng, Lei; Guo, Shaoyong; Sun, Jialu; Yu, Peng; Li, Wenjing

2016-01-01

On-Road Sensor Networks (ORSNs) play an important role in capturing traffic flow data for predicting short-term traffic patterns, driving assistance and self-driving vehicles. However, this kind of network is prone to large-scale communication failure if a few sensors physically fail. In this paper, to ensure that the network works normally, an effective fault-tolerance mechanism for ORSNs which mainly consists of backup on-road sensor deployment, redundant cluster head deployment and an adaptive failure detection and recovery method is proposed. Firstly, based on the N − x principle and the sensors’ failure rate, this paper formulates the backup sensor deployment problem in the form of a two-objective optimization, which explains the trade-off between the cost and fault resumption. In consideration of improving the network resilience further, this paper introduces a redundant cluster head deployment model according to the coverage constraint. Then a common solving method combining integer-continuing and sequential quadratic programming is explored to determine the optimal location of these two deployment problems. Moreover, an Adaptive Detection and Resume (ADR) protocol is deigned to recover the system communication through route and cluster adjustment if there is a backup on-road sensor mismatch. The final experiments show that our proposed mechanism can achieve an average 90% recovery rate and reduce the average number of failed sensors at most by 35.7%. PMID:27918483

Noise activated bistable sensor based on chaotic system with output defined by temporal coding and firing rate

NASA Astrophysics Data System (ADS)

Korneta, Wojciech; Gomes, Iacyel

2017-11-01

Traditional bistable sensors use external bias signal to drive its response between states and their detection strategy is based on the output power spectral density or the residence time difference (RTD) in two sensor states. Recently, the noise activated nonlinear dynamic sensors driven only by noise based on RTD technique have been proposed. Here, we present experimental results of dc voltage measurements by noise-driven bistable sensor based on electronic Chua's circuit operating in a chaotic regime where two single scroll attractors coexist. The output of the sensor is quantified by the proportion of the time the sensor stays in one state to the total observation time and by the spike-count rate with spikes defined by crossings between attractors. The relationship between the stimuli and particular observable for different noise intensities is obtained, the usefulness of each coding scheme is discussed, and the optimal noise intensity for detection is indicated. It is shown that the obtained relationship is the same for any observation time when population coding is used. The optimal time window for both detection and the number of units in population coding is found. Our results may be useful for analyses and understanding of the neural activity and in designing bistable storage elements at length scales where thermal fluctuations drastically increase and the effect of noise must be taken into consideration.

A photonic crystal fiber glucose sensor filled with silver nanowires

NASA Astrophysics Data System (ADS)

Yang, X. C.; Lu, Y.; Wang, M. T.; Yao, J. Q.

2016-01-01

We report a photonic crystal fiber glucose sensor filled with silver nanowires in this paper. The proposed sensor is both analyzed by COMSOL multiphysics software and demonstrated by experiments. The extremely high average spectral sensitivity 19009.17 nm/RIU for experimental measurement is obtained, equivalent to 44.25 mg/dL of glucose in water, which is lower than 70 mg/dL for efficient detection of hypoglycemia episodes. The silver nanowires diameter which may affect the sensor's spectral sensitivity is also discussed and an optimal range of silver nanowires diameter 90-120 nm is obtained. We expect that the sensor can provide an effective platform for glucose sensing and potentially leading to a further development towards minimal-invasive glucose measurement.

Development of solution-gated graphene transistor model for biosensors

NASA Astrophysics Data System (ADS)

Karimi, Hediyeh; Yusof, Rubiyah; Rahmani, Rasoul; Hosseinpour, Hoda; Ahmadi, Mohammad T.

2014-02-01

The distinctive properties of graphene, characterized by its high carrier mobility and biocompatibility, have stimulated extreme scientific interest as a promising nanomaterial for future nanoelectronic applications. In particular, graphene-based transistors have been developed rapidly and are considered as an option for DNA sensing applications. Recent findings in the field of DNA biosensors have led to a renewed interest in the identification of genetic risk factors associated with complex human diseases for diagnosis of cancers or hereditary diseases. In this paper, an analytical model of graphene-based solution gated field effect transistors (SGFET) is proposed to constitute an important step towards development of DNA biosensors with high sensitivity and selectivity. Inspired by this fact, a novel strategy for a DNA sensor model with capability of single-nucleotide polymorphism detection is proposed and extensively explained. First of all, graphene-based DNA sensor model is optimized using particle swarm optimization algorithm. Based on the sensing mechanism of DNA sensors, detective parameters ( I ds and V gmin) are suggested to facilitate the decision making process. Finally, the behaviour of graphene-based SGFET is predicted in the presence of single-nucleotide polymorphism with an accuracy of more than 98% which guarantees the reliability of the optimized model for any application of the graphene-based DNA sensor. It is expected to achieve the rapid, quick and economical detection of DNA hybridization which could speed up the realization of the next generation of the homecare sensor system.

Development of solution-gated graphene transistor model for biosensors

PubMed Central

2014-01-01

The distinctive properties of graphene, characterized by its high carrier mobility and biocompatibility, have stimulated extreme scientific interest as a promising nanomaterial for future nanoelectronic applications. In particular, graphene-based transistors have been developed rapidly and are considered as an option for DNA sensing applications. Recent findings in the field of DNA biosensors have led to a renewed interest in the identification of genetic risk factors associated with complex human diseases for diagnosis of cancers or hereditary diseases. In this paper, an analytical model of graphene-based solution gated field effect transistors (SGFET) is proposed to constitute an important step towards development of DNA biosensors with high sensitivity and selectivity. Inspired by this fact, a novel strategy for a DNA sensor model with capability of single-nucleotide polymorphism detection is proposed and extensively explained. First of all, graphene-based DNA sensor model is optimized using particle swarm optimization algorithm. Based on the sensing mechanism of DNA sensors, detective parameters (Ids and Vgmin) are suggested to facilitate the decision making process. Finally, the behaviour of graphene-based SGFET is predicted in the presence of single-nucleotide polymorphism with an accuracy of more than 98% which guarantees the reliability of the optimized model for any application of the graphene-based DNA sensor. It is expected to achieve the rapid, quick and economical detection of DNA hybridization which could speed up the realization of the next generation of the homecare sensor system. PMID:24517158

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.

Design and Field Test of a WSN Platform Prototype for Long-Term Environmental Monitoring

PubMed Central

Lazarescu, Mihai T.

2015-01-01

Long-term wildfire monitoring using distributed in situ temperature sensors is an accurate, yet demanding environmental monitoring application, which requires long-life, low-maintenance, low-cost sensors and a simple, fast, error-proof deployment procedure. We present in this paper the most important design considerations and optimizations of all elements of a low-cost WSN platform prototype for long-term, low-maintenance pervasive wildfire monitoring, its preparation for a nearly three-month field test, the analysis of the causes of failure during the test and the lessons learned for platform improvement. The main components of the total cost of the platform (nodes, deployment and maintenance) are carefully analyzed and optimized for this application. The gateways are designed to operate with resources that are generally used for sensor nodes, while the requirements and cost of the sensor nodes are significantly lower. We define and test in simulation and in the field experiment a simple, but effective communication protocol for this application. It helps to lower the cost of the nodes and field deployment procedure, while extending the theoretical lifetime of the sensor nodes to over 16 years on a single 1 Ah lithium battery. PMID:25912349

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.

An Effective Cuckoo Search Algorithm for Node Localization in Wireless Sensor Network.

PubMed

Cheng, Jing; Xia, Linyuan

2016-08-31

Localization is an essential requirement in the increasing prevalence of wireless sensor network (WSN) applications. Reducing the computational complexity, communication overhead in WSN localization is of paramount importance in order to prolong the lifetime of the energy-limited sensor nodes and improve localization performance. This paper proposes an effective Cuckoo Search (CS) algorithm for node localization. Based on the modification of step size, this approach enables the population to approach global optimal solution rapidly, and the fitness of each solution is employed to build mutation probability for avoiding local convergence. Further, the approach restricts the population in the certain range so that it can prevent the energy consumption caused by insignificant search. Extensive experiments were conducted to study the effects of parameters like anchor density, node density and communication range on the proposed algorithm with respect to average localization error and localization success ratio. In addition, a comparative study was conducted to realize the same localization task using the same network deployment. Experimental results prove that the proposed CS algorithm can not only increase convergence rate but also reduce average localization error compared with standard CS algorithm and Particle Swarm Optimization (PSO) algorithm.

An Effective Cuckoo Search Algorithm for Node Localization in Wireless Sensor Network

PubMed Central

Cheng, Jing; Xia, Linyuan

2016-01-01

Localization is an essential requirement in the increasing prevalence of wireless sensor network (WSN) applications. Reducing the computational complexity, communication overhead in WSN localization is of paramount importance in order to prolong the lifetime of the energy-limited sensor nodes and improve localization performance. This paper proposes an effective Cuckoo Search (CS) algorithm for node localization. Based on the modification of step size, this approach enables the population to approach global optimal solution rapidly, and the fitness of each solution is employed to build mutation probability for avoiding local convergence. Further, the approach restricts the population in the certain range so that it can prevent the energy consumption caused by insignificant search. Extensive experiments were conducted to study the effects of parameters like anchor density, node density and communication range on the proposed algorithm with respect to average localization error and localization success ratio. In addition, a comparative study was conducted to realize the same localization task using the same network deployment. Experimental results prove that the proposed CS algorithm can not only increase convergence rate but also reduce average localization error compared with standard CS algorithm and Particle Swarm Optimization (PSO) algorithm. PMID:27589756

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

Secure Multiuser Communications in Wireless Sensor Networks with TAS and Cooperative Jamming

PubMed Central

Yang, Maoqiang; Zhang, Bangning; Huang, Yuzhen; Yang, Nan; Guo, Daoxing; Gao, Bin

2016-01-01

In this paper, we investigate the secure transmission in wireless sensor networks (WSNs) consisting of one multiple-antenna base station (BS), multiple single-antenna legitimate users, one single-antenna eavesdropper and one multiple-antenna cooperative jammer. In an effort to reduce the scheduling complexity and extend the battery lifetime of the sensor nodes, the switch-and-stay combining (SSC) scheduling scheme is exploited over the sensor nodes. Meanwhile, transmit antenna selection (TAS) is employed at the BS and cooperative jamming (CJ) is adopted at the jammer node, aiming at achieving a satisfactory secrecy performance. Moreover, depending on whether the jammer node has the global channel state information (CSI) of both the legitimate channel and the eavesdropper’s channel, it explores a zero-forcing beamforming (ZFB) scheme or a null-space artificial noise (NAN) scheme to confound the eavesdropper while avoiding the interference to the legitimate user. Building on this, we propose two novel hybrid secure transmission schemes, termed TAS-SSC-ZFB and TAS-SSC-NAN, for WSNs. We then derive the exact closed-form expressions for the secrecy outage probability and the effective secrecy throughput of both schemes to characterize the secrecy performance. Using these closed-form expressions, we further determine the optimal switching threshold and obtain the optimal power allocation factor between the BS and jammer node for both schemes to minimize the secrecy outage probability, while the optimal secrecy rate is decided to maximize the effective secrecy throughput for both schemes. Numerical results are provided to verify the theoretical analysis and illustrate the impact of key system parameters on the secrecy performance. PMID:27845753

General solution of undersampling frequency conversion and its optimization for parallel photodisplacement imaging.

PubMed

Nakata, Toshihiko; Ninomiya, Takanori

2006-10-10

A general solution of undersampling frequency conversion and its optimization for parallel photodisplacement imaging is presented. Phase-modulated heterodyne interference light generated by a linear region of periodic displacement is captured by a charge-coupled device image sensor, in which the interference light is sampled at a sampling rate lower than the Nyquist frequency. The frequencies of the components of the light, such as the sideband and carrier (which include photodisplacement and topography information, respectively), are downconverted and sampled simultaneously based on the integration and sampling effects of the sensor. A general solution of frequency and amplitude in this downconversion is derived by Fourier analysis of the sampling procedure. The optimal frequency condition for the heterodyne beat signal, modulation signal, and sensor gate pulse is derived such that undesirable components are eliminated and each information component is converted into an orthogonal function, allowing each to be discretely reproduced from the Fourier coefficients. The optimal frequency parameters that maximize the sideband-to-carrier amplitude ratio are determined, theoretically demonstrating its high selectivity over 80 dB. Preliminary experiments demonstrate that this technique is capable of simultaneous imaging of reflectivity, topography, and photodisplacement for the detection of subsurface lattice defects at a speed corresponding to an acquisition time of only 0.26 s per 256 x 256 pixel area.

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.

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

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.

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

Multiple sensor fault diagnosis for dynamic processes.

PubMed

Li, Cheng-Chih; Jeng, Jyh-Cheng

2010-10-01

Modern industrial plants are usually large scaled and contain a great amount of sensors. Sensor fault diagnosis is crucial and necessary to process safety and optimal operation. This paper proposes a systematic approach to detect, isolate and identify multiple sensor faults for multivariate dynamic systems. The current work first defines deviation vectors for sensor observations, and further defines and derives the basic sensor fault matrix (BSFM), consisting of the normalized basic fault vectors, by several different methods. By projecting a process deviation vector to the space spanned by BSFM, this research uses a vector with the resulted weights on each direction for multiple sensor fault diagnosis. This study also proposes a novel monitoring index and derives corresponding sensor fault detectability. The study also utilizes that vector to isolate and identify multiple sensor faults, and discusses the isolatability and identifiability. Simulation examples and comparison with two conventional PCA-based contribution plots are presented to demonstrate the effectiveness of the proposed methodology. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.

High speed demodulation systems for fiber optic grating sensors

NASA Technical Reports Server (NTRS)

Udd, Eric (Inventor); Weisshaar, Andreas (Inventor)

2002-01-01

Fiber optic grating sensor demodulation systems are described that offer high speed and multiplexing options for both single and multiple parameter fiber optic grating sensors. To attain very high speeds for single parameter fiber grating sensors ratio techniques are used that allow a series of sensors to be placed in a single fiber while retaining high speed capability. These methods can be extended to multiparameter fiber grating sensors. Optimization of speeds can be obtained by minimizing the number of spectral peaks that must be processed and it is shown that two or three spectral peak measurements may in specific multiparameter applications offer comparable or better performance than processing four spectral peaks. Combining the ratio methods with minimization of peak measurements allows very high speed measurement of such important environmental effects as transverse strain and pressure.

Intelligent Tires Based on Measurement of Tire Deformation

NASA Astrophysics Data System (ADS)

Matsuzaki, Ryosuke; Todoroki, Akira

From a traffic safety point-of-view, there is an urgent need for intelligent tires as a warning system for road conditions, for optimized braking control on poor road surfaces and as a tire fault detection system. Intelligent tires, equipped with sensors for monitoring applied strain, are effective in improving reliability and control systems such as anti-lock braking systems (ABSs). In previous studies, we developed a direct tire deformation or strain measurement system with sufficiently low stiffness and high elongation for practical use, and a wireless communication system between tires and vehicle that operates without a battery. The present study investigates the application of strain data for an optimized braking control and road condition warning system. The relationships between strain sensor outputs and tire mechanical parameters, including braking torque, effective radius and contact patch length, are calculated using finite element analysis. Finally, we suggested the possibility of optimized braking control and road condition warning systems. Optimized braking control can be achieved by keeping the slip ratio constant. The road condition warning would be actuated if the recorded friction coefficient at a certain slip ratio is lower than a ‘safe’ reference value.

Intelligent tires for improved tire safety using wireless strain measurement

NASA Astrophysics Data System (ADS)

Matsuzaki, Ryosuke; Todoroki, Akira

2008-03-01

From a traffic safety point-of-view, there is an urgent need for intelligent tires as a warning system for road conditions, for optimized braking control on poor road surfaces and as a tire fault detection system. Intelligent tires, equipped with sensors for monitoring applied strain, are effective in improving reliability and control systems such as anti-lock braking systems (ABSs). In previous studies, we developed a direct tire deformation or strain measurement system with sufficiently low stiffness and high elongation for practical use, and a wireless communication system between tires and vehicle that operates without a battery. The present study investigates the application of strain data for an optimized braking control and road condition warning system. The relationships between strain sensor outputs and tire mechanical parameters, including braking torque, effective radius and contact patch length, are calculated using finite element analysis. Finally, we suggested the possibility of optimized braking control and road condition warning systems. Optimized braking control can be achieved by keeping the slip ratio constant. The road condition warning would be actuated if the recorded friction coefficient at a certain slip ratio is lower than a 'safe' reference value.

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

Short-Term Distribution System State Forecast Based on Optimal Synchrophasor Sensor Placement and Extreme Learning Machine

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

Jiang, Huaiguang; Zhang, Yingchen

This paper proposes an approach for distribution system state forecasting, which aims to provide an accurate and high speed state forecasting with an optimal synchrophasor sensor placement (OSSP) based state estimator and an extreme learning machine (ELM) based forecaster. Specifically, considering the sensor installation cost and measurement error, an OSSP algorithm is proposed to reduce the number of synchrophasor sensor and keep the whole distribution system numerically and topologically observable. Then, the weighted least square (WLS) based system state estimator is used to produce the training data for the proposed forecaster. Traditionally, the artificial neural network (ANN) and support vectormore » regression (SVR) are widely used in forecasting due to their nonlinear modeling capabilities. However, the ANN contains heavy computation load and the best parameters for SVR are difficult to obtain. In this paper, the ELM, which overcomes these drawbacks, is used to forecast the future system states with the historical system states. The proposed approach is effective and accurate based on the testing results.« less

Matrix Completion Optimization for Localization in Wireless Sensor Networks for Intelligent IoT

PubMed Central

Nguyen, Thu L. N.; Shin, Yoan

2016-01-01

Localization in wireless sensor networks (WSNs) is one of the primary functions of the intelligent Internet of Things (IoT) that offers automatically discoverable services, while the localization accuracy is a key issue to evaluate the quality of those services. In this paper, we develop a framework to solve the Euclidean distance matrix completion problem, which is an important technical problem for distance-based localization in WSNs. The sensor network localization problem is described as a low-rank dimensional Euclidean distance completion problem with known nodes. The task is to find the sensor locations through recovery of missing entries of a squared distance matrix when the dimension of the data is small compared to the number of data points. We solve a relaxation optimization problem using a modification of Newton’s method, where the cost function depends on the squared distance matrix. The solution obtained in our scheme achieves a lower complexity and can perform better if we use it as an initial guess for an interactive local search of other higher precision localization scheme. Simulation results show the effectiveness of our approach. PMID:27213378

Distributed Event-Based Set-Membership Filtering for a Class of Nonlinear Systems With Sensor Saturations Over Sensor Networks.

PubMed

Ma, Lifeng; Wang, Zidong; Lam, Hak-Keung; Kyriakoulis, Nikos

2017-11-01

In this paper, the distributed set-membership filtering problem is investigated for a class of discrete time-varying system with an event-based communication mechanism over sensor networks. The system under consideration is subject to sector-bounded nonlinearity, unknown but bounded noises and sensor saturations. Each intelligent sensing node transmits the data to its neighbors only when certain triggering condition is violated. By means of a set of recursive matrix inequalities, sufficient conditions are derived for the existence of the desired distributed event-based filter which is capable of confining the system state in certain ellipsoidal regions centered at the estimates. Within the established theoretical framework, two additional optimization problems are formulated: one is to seek the minimal ellipsoids (in the sense of matrix trace) for the best filtering performance, and the other is to maximize the triggering threshold so as to reduce the triggering frequency with satisfactory filtering performance. A numerically attractive chaos algorithm is employed to solve the optimization problems. Finally, an illustrative example is presented to demonstrate the effectiveness and applicability of the proposed algorithm.

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.

Energy-efficient hierarchical processing in the network of wireless intelligent sensors (WISE)

NASA Astrophysics Data System (ADS)

Raskovic, Dejan

Sensor network nodes have benefited from technological advances in the field of wireless communication, processing, and power sources. However, the processing power of microcontrollers is often not sufficient to perform sophisticated processing, while the power requirements of digital signal processing boards or handheld computers are usually too demanding for prolonged system use. We are matching the intrinsic hierarchical nature of many digital signal-processing applications with the natural hierarchy in distributed wireless networks, and building the hierarchical system of wireless intelligent sensors. Our goal is to build a system that will exploit the hierarchical organization to optimize the power consumption and extend battery life for the given time and memory constraints, while providing real-time processing of sensor signals. In addition, we are designing our system to be able to adapt to the current state of the environment, by dynamically changing the algorithm through procedure replacement. This dissertation presents the analysis of hierarchical environment and methods for energy profiling used to evaluate different system design strategies, and to optimize time-effective and energy-efficient processing.

Synergistic electron transfer effect-based signal amplification strategy for the ultrasensitive detection of dopamine.

PubMed

Lu, Qiujun; Chen, Xiaogen; Liu, Dan; Wu, Cuiyan; Liu, Meiling; Li, Haitao; Zhang, Youyu; Yao, Shouzhuo

2018-05-15

The selective and sensitive detection of dopamine (DA) is of great significance for the identification of schizophrenia, Huntington's disease, and Parkinson's disease from the perspective of molecular diagnostics. So far, most of DA fluorescence sensors are based on the electron transfer from the fluorescence nanomaterials to DA-quinone. However, the limited electron transfer ability of the DA-quinone affects the level of detection sensitivity of these sensors. In this work, based on the DA can reduce Ag + into AgNPs followed by oxidized to DA-quinone, we developed a novel silicon nanoparticles-based electron transfer fluorescent sensor for the detection of DA. As electron transfer acceptor, the AgNPs and DA-quinone can quench the fluorescence of silicon nanoparticles effectively through the synergistic electron transfer effect. Compared with traditional fluorescence DA sensors, the proposed synergistic electron transfer-based sensor improves the detection sensitivity to a great extent (at least 10-fold improvement). The proposed sensor shows a low detection limit of DA, which is as low as 0.1 nM under the optimal conditions. This sensor has potential applicability for the detection of DA in practical sample. This work has been demonstrated to contribute to a substantial improvement in the sensitivity of the sensors. It also gives new insight into design electron transfer-based sensors. Copyright © 2018. Published by Elsevier B.V.

An Effective Hybrid Routing Algorithm in WSN: Ant Colony Optimization in combination with Hop Count Minimization.

PubMed

Jiang, Ailian; Zheng, Lihong

2018-03-29

Low cost, high reliability and easy maintenance are key criteria in the design of routing protocols for wireless sensor networks (WSNs). This paper investigates the existing ant colony optimization (ACO)-based WSN routing algorithms and the minimum hop count WSN routing algorithms by reviewing their strengths and weaknesses. We also consider the critical factors of WSNs, such as energy constraint of sensor nodes, network load balancing and dynamic network topology. Then we propose a hybrid routing algorithm that integrates ACO and a minimum hop count scheme. The proposed algorithm is able to find the optimal routing path with minimal total energy consumption and balanced energy consumption on each node. The algorithm has unique superiority in terms of searching for the optimal path, balancing the network load and the network topology maintenance. The WSN model and the proposed algorithm have been implemented using C++. Extensive simulation experimental results have shown that our algorithm outperforms several other WSN routing algorithms on such aspects that include the rate of convergence, the success rate in searching for global optimal solution, and the network lifetime.

An Effective Hybrid Routing Algorithm in WSN: Ant Colony Optimization in combination with Hop Count Minimization

PubMed Central

2018-01-01

Low cost, high reliability and easy maintenance are key criteria in the design of routing protocols for wireless sensor networks (WSNs). This paper investigates the existing ant colony optimization (ACO)-based WSN routing algorithms and the minimum hop count WSN routing algorithms by reviewing their strengths and weaknesses. We also consider the critical factors of WSNs, such as energy constraint of sensor nodes, network load balancing and dynamic network topology. Then we propose a hybrid routing algorithm that integrates ACO and a minimum hop count scheme. The proposed algorithm is able to find the optimal routing path with minimal total energy consumption and balanced energy consumption on each node. The algorithm has unique superiority in terms of searching for the optimal path, balancing the network load and the network topology maintenance. The WSN model and the proposed algorithm have been implemented using C++. Extensive simulation experimental results have shown that our algorithm outperforms several other WSN routing algorithms on such aspects that include the rate of convergence, the success rate in searching for global optimal solution, and the network lifetime. PMID:29596336

Multifrequency remote sensing of soil moisture. [Guymon, Oklahoma and Dalhart, Texas

NASA Technical Reports Server (NTRS)

Theis, S. W.; Mcfarland, M. J.; Rosenthal, W. D.; Jones, C. L. (Principal Investigator)

1982-01-01

Multifrequency sensor data collected at Guymon, Oklahoma and Dalhart, Texas using NASA's C-130 aircraft were used to determine which of the all-weather microwave sensors demonstrated the highest correlation to surface soil moisture over optimal bare soil conditions, and to develop and test techniques which use visible/infrared sensors to compensate for the vegetation effect in this sensor's response to soil moisture. The L-band passive microwave radiometer was found to be the most suitable single sensor system to estimate soil moisture over bare fields. In comparison to other active and passive microwave sensors the L-band radiometer (1) was influenced least by ranges in surface roughness; (2) demonstrated the most sensitivity to soil moisture differences in terms of the range of return from the full range of soil moisture; and (3) was less sensitive to errors in measurement in relation to the range of sensor response. L-band emissivity related more strongly to soil moisture when moisture was expressed as percent of field capacity. The perpendicular vegetation index as determined from the visible/infrared sensors was useful as a measure of the vegetation effect on the L-band radiometer response to soil moisture.

Fugitive Methane Gas Emission Monitoring in oil and gas industry

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

Klein, Levente

Identifying fugitive methane leaks allow optimization of the extraction process, can extend gas extraction equipment lifetime, and eliminate hazardous work conditions. We demonstrate a wireless sensor network based on cost effective and robust chemi-resistive methane sensors combined with real time analytics to identify leaks from 2 scfh to 10000 scfh. The chemi-resistive sensors were validated for sensitivity better than 1 ppm of methane plume detection. The real time chemical sensor and wind data is integrated into an inversion models to identify the location and the magnitude of the methane leak. This integrated solution can be deployed in outdoor environment formore » long term monitoring of chemical plumes.« less

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.

Design, optimization and characterization of the light concentrators of the single-mirror small size telescopes of the Cherenkov Telescope Array

NASA Astrophysics Data System (ADS)

Aguilar, J. A.; Basili, A.; Boccone, V.; Cadoux, F.; Christov, A.; della Volpe, D.; Montaruli, T.; Płatos, Ł.; Rameez, M.

2015-01-01

The focal-plane cameras of γ -ray telescopes frequently use light concentrators in front of the light sensors. The purpose of these concentrators is to increase the effective area of the camera as well as to reduce the stray light coming at large incident angles. These light concentrators are usually based on the Winston cone design. In this contribution we present the design of a hexagonal hollow light concentrator with a lateral profile optimized using a cubic Bézier function to achieve a higher collection efficiency in the angular region of interest. The design presented here is optimized for a Davies-Cotton telescope with a primary mirror of about 4 m in diameter and a focal length of 5.6 m. The described concentrators are part of an innovative camera made up of silicon-photomultiplier sensors, although a similar approach can be used for other sizes of single-mirror telescopes with different camera sensors, including photomultipliers. The challenge of our approach is to achieve a cost-effective design suitable for standard industrial production of both the plastic concentrator substrate and the reflective coating. At the same time we maximize the optical performance. In this paper we also describe the optical set-up to measure the absolute collection efficiency of the light concentrators and demonstrate our good understanding of the measured data using a professional ray-tracing simulation.

Stochastic optimal preview control of a vehicle suspension

NASA Astrophysics Data System (ADS)

Marzbanrad, Javad; Ahmadi, Goodarz; Zohoor, Hassan; Hojjat, Yousef

2004-08-01

Stochastic optimal control of a vehicle suspension on a random road is studied. The road roughness height is modelled as a filtered white noise stochastic process and a four-degree-of-freedom half-car model is used in the analysis. It is assumed that a sensor is mounted in the front bumper that measures the road irregularity at some distances in the front of the vehicle. Two other sensors also measure relative velocities of the vehicle body with respect to the unsprung masses in the vehicle suspension spaces. All measurements are assumed to be conducted in a noisy environment. The state variables of the vehicle system are estimated using a method similar to the Kalman filter. The suspension system is optimized by minimizing the performance index containing the mean-square values of body accelerations (including effects of heave and pitch), tire deflections and front and rear suspension rattle spaces. The effect of delay between front and rear wheels is included in the analysis. For stochastic active control with and without preview, the suspension performance and the power demand are evaluated and compared with those of the passive system. The results show that the inclusion of time delay between the front and rear axles and the preview information measured by the sensor mounted on the vehicle improves all aspects of the suspension performance, while reducing the energy consumption.

Advanced Taste Sensors Based on Artificial Lipids with Global Selectivity to Basic Taste Qualities and High Correlation to Sensory Scores

PubMed Central

Kobayashi, Yoshikazu; Habara, Masaaki; Ikezazki, Hidekazu; Chen, Ronggang; Naito, Yoshinobu; Toko, Kiyoshi

2010-01-01

Effective R&D and strict quality control of a broad range of foods, beverages, and pharmaceutical products require objective taste evaluation. Advanced taste sensors using artificial-lipid membranes have been developed based on concepts of global selectivity and high correlation with human sensory score. These sensors respond similarly to similar basic tastes, which they quantify with high correlations to sensory score. Using these unique properties, these sensors can quantify the basic tastes of saltiness, sourness, bitterness, umami, astringency and richness without multivariate analysis or artificial neural networks. This review describes all aspects of these taste sensors based on artificial lipid, ranging from the response principle and optimal design methods to applications in the food, beverage, and pharmaceutical markets. PMID:22319306

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.

Piezoresistive silicon pressure sensors in cryogenic environment

NASA Technical Reports Server (NTRS)

Kahng, Seun K.; Chapman, John J.

1989-01-01

This paper presents data on low-temperature measurements of silicon pressure sensors. It was found that both the piezoresistance coefficients and the charge-carrier mobility increase with decreasing temperature. For lightly doped semiconductor materials, the density of free charge carriers decreases with temperature and can freeze out eventually. However, the effect of carrier freeze-out can be minimized by increasing the impurity content to higher levels, at which the temperature dependency of piezoresistance coefficients is reduced. An impurity density of 1 x 10 to the 19th/cu cm was found to be optimal for cryogenic applications of pressure sensor dies.

Ferroelectric Zinc Oxide Nanowire Embedded Flexible Sensor for Motion and Temperature Sensing.

PubMed

Shin, Sung-Ho; Park, Dae Hoon; Jung, Joo-Yun; Lee, Min Hyung; Nah, Junghyo

2017-03-22

We report a simple method to realize multifunctional flexible motion sensor using ferroelectric lithium-doped ZnO-PDMS. The ferroelectric layer enables piezoelectric dynamic sensing and provides additional motion information to more precisely discriminate different motions. The PEDOT:PSS-functionalized AgNWs, working as electrode layers for the piezoelectric sensing layer, resistively detect a change of both movement or temperature. Thus, through the optimal integration of both elements, the sensing limit, accuracy, and functionality can be further expanded. The method introduced here is a simple and effective route to realize a high-performance flexible motion sensor with integrated multifunctionalities.

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

Optimization of Perovskite Gas Sensor Performance: Characterization, Measurement and Experimental Design.

PubMed

Bertocci, Francesco; Fort, Ada; Vignoli, Valerio; Mugnaini, Marco; Berni, Rossella

2017-06-10

Eight different types of nanostructured perovskites based on YCoO 3 with different chemical compositions are prepared as gas sensor materials, and they are studied with two target gases NO 2 and CO. Moreover, a statistical approach is adopted to optimize their performance. The innovative contribution is carried out through a split-plot design planning and modeling, also involving random effects, for studying Metal Oxide Semiconductors (MOX) sensors in a robust design context. The statistical results prove the validity of the proposed approach; in fact, for each material type, the variation of the electrical resistance achieves a satisfactory optimized value conditional to the working temperature and by controlling for the gas concentration variability. Just to mention some results, the sensing material YCo 0 . 9 Pd 0 . 1 O 3 (Mt1) achieved excellent solutions during the optimization procedure. In particular, Mt1 resulted in being useful and feasible for the detection of both gases, with optimal response equal to +10.23% and working temperature at 312 ∘ C for CO (284 ppm, from design) and response equal to -14.17% at 185 ∘ C for NO 2 (16 ppm, from design). Analogously, for NO 2 (16 ppm, from design), the material type YCo 0 . 9 O 2 . 85 + 1 % Pd (Mt8) allows for optimizing the response value at - 15 . 39 % with a working temperature at 181 . 0 ∘ C, whereas for YCo 0 . 95 Pd 0 . 05 O 3 (Mt3), the best response value is achieved at - 15 . 40 % with the temperature equal to 204 ∘ C.

Optimization of Perovskite Gas Sensor Performance: Characterization, Measurement and Experimental Design

PubMed Central

Bertocci, Francesco; Fort, Ada; Vignoli, Valerio; Mugnaini, Marco; Berni, Rossella

2017-01-01

Eight different types of nanostructured perovskites based on YCoO3 with different chemical compositions are prepared as gas sensor materials, and they are studied with two target gases NO2 and CO. Moreover, a statistical approach is adopted to optimize their performance. The innovative contribution is carried out through a split-plot design planning and modeling, also involving random effects, for studying Metal Oxide Semiconductors (MOX) sensors in a robust design context. The statistical results prove the validity of the proposed approach; in fact, for each material type, the variation of the electrical resistance achieves a satisfactory optimized value conditional to the working temperature and by controlling for the gas concentration variability. Just to mention some results, the sensing material YCo0.9Pd0.1O3 (Mt1) achieved excellent solutions during the optimization procedure. In particular, Mt1 resulted in being useful and feasible for the detection of both gases, with optimal response equal to +10.23% and working temperature at 312∘C for CO (284 ppm, from design) and response equal to −14.17% at 185∘C for NO2 (16 ppm, from design). Analogously, for NO2 (16 ppm, from design), the material type YCo0.9O2.85+1%Pd (Mt8) allows for optimizing the response value at −15.39% with a working temperature at 181.0∘C, whereas for YCo0.95Pd0.05O3 (Mt3), the best response value is achieved at −15.40% with the temperature equal to 204∘C. PMID:28604587

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.

Perspectives on MEMS in bioengineering: a novel capacitive position microsensor.

PubMed

Pedrocchi, A; Hoen, S; Ferrigno, G; Pedotti, A

2000-01-01

We describe a novel capacitive position sensor using micromachining to achieve high sensitivity and large range of motion. These sensors require a new theoretical framework to describe and optimize their performance. Employing a complete description of the electrical fields, the sensor should deviate from the standard geometries used for capacitive sensors. By this optimization, the sensor gains a twofold increase in sensitivity. Results on a PC board 10x model imply that the micromachined sensor should achieve a sensitivity of less than 10 nm over 500-micron range of travel. Some bioengineering applications are addressed, including positioning of micromirrors for laser surgery and dose control for implantable drug delivery systems.

Inverse modeling of rainfall infiltration with a dual permeability approach using different matrix-fracture coupling variants.

NASA Astrophysics Data System (ADS)

Blöcher, Johanna; Kuraz, Michal

2017-04-01

In this contribution we propose implementations of the dual permeability model with different inter-domain exchange descriptions and metaheuristic optimization algorithms for parameter identification and mesh optimization. We compare variants of the coupling term with different numbers of parameters to test if a reduction of parameters is feasible. This can reduce parameter uncertainty in inverse modeling, but also allow for different conceptual models of the domain and matrix coupling. The different variants of the dual permeability model are implemented in the open-source objective library DRUtES written in FORTRAN 2003/2008 in 1D and 2D. For parameter identification we use adaptations of the particle swarm optimization (PSO) and Teaching-learning-based optimization (TLBO), which are population-based metaheuristics with different learning strategies. These are high-level stochastic-based search algorithms that don't require gradient information or a convex search space. Despite increasing computing power and parallel processing, an overly fine mesh is not feasible for parameter identification. This creates the need to find a mesh that optimizes both accuracy and simulation time. We use a bi-objective PSO algorithm to generate a Pareto front of optimal meshes to account for both objectives. The dual permeability model and the optimization algorithms were tested on virtual data and field TDR sensor readings. The TDR sensor readings showed a very steep increase during rapid rainfall events and a subsequent steep decrease. This was theorized to be an effect of artificial macroporous envelopes surrounding TDR sensors creating an anomalous region with distinct local soil hydraulic properties. One of our objectives is to test how well the dual permeability model can describe this infiltration behavior and what coupling term would be most suitable.

Frontside-micromachined planar piezoresistive vibration sensor: Evaluating performance in the low frequency test range

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

Zhang, Lan; Lu, Jian, E-mail: jian-lu@aist.go.jp; Takagi, Hideki

2014-01-15

Using a surface piezoresistor diffusion method and front-side only micromachining process, a planar piezoresistive vibration sensor was successfully developed with a simple structure, lower processing cost and fewer packaging difficulties. The vibration sensor had a large sector proof mass attached to a narrow flexure. Optimization of the boron diffusion piezoresistor placed on the edge of the narrow flexure greatly improved the sensitivity. Planar vibration sensors were fabricated and measured in order to analyze the effects of the sensor dimensions on performance, including the values of flexure width and the included angle of the sector. Sensitivities of fabricated planar sensors ofmore » 0.09–0.46 mV/V/g were measured up to a test frequency of 60 Hz. The sensor functioned at low voltages (<3 V) and currents (<1 mA) with a high sensitivity and low drift. At low background noise levels, the sensor had performance comparable to a commercial device.« less

Application of zonal model on indoor air sensor network design

NASA Astrophysics Data System (ADS)

Chen, Y. Lisa; Wen, Jin

2007-04-01

Growing concerns over the safety of the indoor environment have made the use of sensors ubiquitous. Sensors that detect chemical and biological warfare agents can offer early warning of dangerous contaminants. However, current sensor system design is more informed by intuition and experience rather by systematic design. To develop a sensor system design methodology, a proper indoor airflow modeling approach is needed. Various indoor airflow modeling techniques, from complicated computational fluid dynamics approaches to simplified multi-zone approaches, exist in the literature. In this study, the effects of two airflow modeling techniques, multi-zone modeling technique and zonal modeling technique, on indoor air protection sensor system design are discussed. Common building attack scenarios, using a typical CBW agent, are simulated. Both multi-zone and zonal models are used to predict airflows and contaminant dispersion. Genetic Algorithm is then applied to optimize the sensor location and quantity. Differences in the sensor system design resulting from the two airflow models are discussed for a typical office environment and a large hall environment.

A Game Theoretic Approach for Balancing Energy Consumption in Clustered Wireless Sensor Networks

PubMed Central

Lu, Yinzhi; Xiong, Lian; Tao, Yang; Zhong, Yuanchang

2017-01-01

Clustering is an effective topology control method in wireless sensor networks (WSNs), since it can enhance the network lifetime and scalability. To prolong the network lifetime in clustered WSNs, an efficient cluster head (CH) optimization policy is essential to distribute the energy among sensor nodes. Recently, game theory has been introduced to model clustering. Each sensor node is considered as a rational and selfish player which will play a clustering game with an equilibrium strategy. Then it decides whether to act as the CH according to this strategy for a tradeoff between providing required services and energy conservation. However, how to get the equilibrium strategy while maximizing the payoff of sensor nodes has rarely been addressed to date. In this paper, we present a game theoretic approach for balancing energy consumption in clustered WSNs. With our novel payoff function, realistic sensor behaviors can be captured well. The energy heterogeneity of nodes is considered by incorporating a penalty mechanism in the payoff function, so the nodes with more energy will compete for CHs more actively. We have obtained the Nash equilibrium (NE) strategy of the clustering game through convex optimization. Specifically, each sensor node can achieve its own maximal payoff when it makes the decision according to this strategy. Through plenty of simulations, our proposed game theoretic clustering is proved to have a good energy balancing performance and consequently the network lifetime is greatly enhanced. PMID:29149075

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.

[INVITED] Porphyrin-nanoassembled fiber-optic gas sensor fabrication: Optimization of parameters for sensitive ammonia gas detection

NASA Astrophysics Data System (ADS)

Korposh, Sergiy; Kodaira, Suguru; Selyanchyn, Roman; Ledezma, Francisco H.; James, Stephen W.; Lee, Seung-Woo

2018-05-01

Highly sensitive fiber-optic ammonia gas sensors were fabricated via layer-by-layer deposition of poly(diallyldimethylammonium chloride) (PDDA) and tetrakis(4-sulfophenyl)porphine (TSPP) onto the surface of the core of a hard-clad multimode fiber that was stripped of its polymer cladding. The effects of film thickness, length of sensing area, and depth of evanescent wave penetration were investigated to clearly understand the sensor performance. The sensitivity of the fiber-optic sensor to ammonia was linear in the concentration range of 0.5-50 ppm and the response and recovery times were less than 3 min, with a limit of detection of 0.5 ppm, when a ten-cycle PDDA/TSPP film was assembled on the surface of the core along a 1 cm-long stripped section of the fiber. The sensor's response towards ammonia was also checked under different relative humidity conditions and a simple statistical data treatment approach, principal component analysis, demonstrated the feasibility of ammonia sensing in environmental relative humidity ranging from dry 7% to highly saturated 80%. Penetration depths of the evanescent wave for the optimal sensor configuration were estimated to be 30 and 33 nm at wavelengths of 420 and 706 nm, which are in a good agreement with the thickness of the 10-cycle deposited film (ca. 30 nm).

A novel integrated multifunction micro-sensor for three-dimensional micro-force measurements.

PubMed

Wang, Weizhong; Zhao, Yulong; Qin, Yafei

2012-01-01

An integrated multifunction micro-sensor for three-dimensional micro-force precision measurement under different pressure and temperature conditions is introduced in this paper. The integrated sensor consists of three kinds of sensors: a three-dimensional micro-force sensor, an absolute pressure sensor and a temperature sensor. The integrated multifunction micro-sensor is fabricated on silicon wafers by micromachining technology. Different doping doses of boron ion, placement and structure of resistors are tested for the force sensor, pressure sensor and temperature sensor to minimize the cross interference and optimize the properties. A glass optical fiber, with a ladder structure and sharp tip etched by buffer oxide etch solution, is glued on the micro-force sensor chip as the tactile probe. Experimental results show that the minimum force that can be detected by the force sensor is 300 nN; the lateral sensitivity of the force sensor is 0.4582 mV/μN; the probe length is linearly proportional to sensitivity of the micro-force sensor in lateral; the sensitivity of the pressure sensor is 0.11 mv/KPa; the sensitivity of the temperature sensor is 5.836 × 10(-3) KΩ/°C. Thus it is a cost-effective method to fabricate integrated multifunction micro-sensors with different measurement ranges that could be used in many fields.

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.

A Multi-Attribute Pheromone Ant Secure Routing Algorithm Based on Reputation Value for Sensor Networks

PubMed Central

Zhang, Lin; Yin, Na; Fu, Xiong; Lin, Qiaomin; Wang, Ruchuan

2017-01-01

With the development of wireless sensor networks, certain network problems have become more prominent, such as limited node resources, low data transmission security, and short network life cycles. To solve these problems effectively, it is important to design an efficient and trusted secure routing algorithm for wireless sensor networks. Traditional ant-colony optimization algorithms exhibit only local convergence, without considering the residual energy of the nodes and many other problems. This paper introduces a multi-attribute pheromone ant secure routing algorithm based on reputation value (MPASR). This algorithm can reduce the energy consumption of a network and improve the reliability of the nodes’ reputations by filtering nodes with higher coincidence rates and improving the method used to update the nodes’ communication behaviors. At the same time, the node reputation value, the residual node energy and the transmission delay are combined to formulate a synthetic pheromone that is used in the formula for calculating the random proportion rule in traditional ant-colony optimization to select the optimal data transmission path. Simulation results show that the improved algorithm can increase both the security of data transmission and the quality of routing service. PMID:28282894

Achieving Crossed Strong Barrier Coverage in Wireless Sensor Network.

PubMed

Han, Ruisong; Yang, Wei; Zhang, Li

2018-02-10

Barrier coverage has been widely used to detect intrusions in wireless sensor networks (WSNs). It can fulfill the monitoring task while extending the lifetime of the network. Though barrier coverage in WSNs has been intensively studied in recent years, previous research failed to consider the problem of intrusion in transversal directions. If an intruder knows the deployment configuration of sensor nodes, then there is a high probability that it may traverse the whole target region from particular directions, without being detected. In this paper, we introduce the concept of crossed barrier coverage that can overcome this defect. We prove that the problem of finding the maximum number of crossed barriers is NP-hard and integer linear programming (ILP) is used to formulate the optimization problem. The branch-and-bound algorithm is adopted to determine the maximum number of crossed barriers. In addition, we also propose a multi-round shortest path algorithm (MSPA) to solve the optimization problem, which works heuristically to guarantee efficiency while maintaining near-optimal solutions. Several conventional algorithms for finding the maximum number of disjoint strong barriers are also modified to solve the crossed barrier problem and for the purpose of comparison. Extensive simulation studies demonstrate the effectiveness of MSPA.

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.

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

PubMed Central

Zhang, Guangzhi; Cai, Shaobin; Xiong, Naixue

2018-01-01

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

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

PubMed

Zhang, Guangzhi; Cai, Shaobin; Xiong, Naixue

2018-02-03

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

Refractive index sensor based on lateral-offset of coreless silica interferometer

NASA Astrophysics Data System (ADS)

Baharin, Nur Faizzah; Azmi, Asrul Izam; Abdullah, Ahmad Sharmi; Mohd Noor, Muhammad Yusof

2018-02-01

A compact, cost-effective and high sensitivity fiber interferometer refractive index (RI) sensor based on symmetrical offset coreless silica fiber (CSF) configuration is proposed, optimized and demonstrated. The sensor is formed by splicing a section of CSF between two CSF sections in an offset manner. Thus, two distinct optical paths are created with large index difference, the first path through the connecting CSF sections and the second path is outside the CSF through the surrounding media. RI sensing is established from direct interaction of light with surrounding media, hence high sensitivity can be achieved with a relatively compact sensor length. In the experimental work, a 1.5 mm sensor demonstrates RI sensitivity of 750 nm/RIU for RI range between 1.33 and 1.345. With the main attributes of high sensitivity and compact size, the proposed sensor can be further developed for related applications including blood diagnosis, water quality control and food industries.

A high-performance nonenzymatic glucose sensor made of CuO-SWCNT nanocomposites.

PubMed

Quoc Dung, Nguyen; Patil, Dewyani; Jung, Hyuck; Kim, Dojin

2013-04-15

Nanocomposites of CuO and single-wall carbon nanotubes (SWCNTs) were synthesized using an arc-discharging graphite rod that contained copper wires. Simultaneous arc discharges produced a CuO-SWCNT composite network. The crystalline structure and morphology of the CuO-SWCNT composite films were investigated using XRD, Raman spectroscopy, FE-SEM and TEM. The electrochemical properties were investigated by cyclic voltammogram and amperometric measurements in a 0.1 M NaOH solution. The CuO content in the CuO-SWCNT nanocomposites was optimized for nonenzymatic glucose detection. The glucose sensing properties of the optimized CuO-SWCNT electrode showed good stability, selectivity, and linear glucose detection that ranged from 0.05 to 1800 μM with a higher sensitivity of 1610 μA cm⁻² mM⁻¹, a quick response time of 1-2 s, and the lowest limit of detection at 50 nM. The sensing performance was better than the pure CuO and SWCNT sensors, and the synergetic effect of the composite sensor was attributed to the high conductivity network of highly porous nanowires. The sensor also showed a good response in a human serum sample, which proves its high potential towards a commercial nonenzymatic glucose sensor. Copyright © 2012 Elsevier B.V. All rights reserved.

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.

Development of a TiO2/SiO2 waveguide-mode chip for an ultraviolet near-field fluorescence sensor.

PubMed

Kuroda, Chiaki; Nakai, Midori; Fujimaki, Makoto; Ohki, Yoshimichi

2018-03-19

Aimed at detecting fluorescent-labeled biological substances sensitively, a sensor that utilizes near-field light has attracted much attention. According to our calculations, a planar structure composed of two dielectric layers can enhance the electric field of UV near-field light effectively by inducing waveguide-mode (WM) resonance. The fluorescence intensity obtainable by a WM chip with an optimized structure is 5.5 times that obtainable by an optimized surface plasmon resonance chip. We confirmed the above by making a WM chip consisting of TiO 2 and SiO 2 layers on a silica glass substrate and by measuring the fluorescence intensity of a solution of quantum dots dropped on the chip.

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

Polymer nanocomposite nanomechanical cantilever sensors: material characterization, device development and application in explosive vapour detection.

PubMed

Seena, V; Fernandes, Avil; Pant, Prita; Mukherji, Soumyo; Rao, V Ramgopal

2011-07-22

This paper reports an optimized and highly sensitive piezoresistive SU-8 nanocomposite microcantilever sensor and its application for detection of explosives in vapour phase. The optimization has been in improving its electrical, mechanical and transduction characteristics. We have achieved a better dispersion of carbon black (CB) in the SU-8/CB nanocomposite piezoresistor and arrived at an optimal range of 8-9 vol% CB concentration by performing a systematic mechanical and electrical characterization of polymer nanocomposites. Mechanical characterization of SU-8/CB nanocomposite thin films was performed using the nanoindentation technique with an appropriate substrate effect analysis. Piezoresistive microcantilevers having an optimum carbon black concentration were fabricated using a design aimed at surface stress measurements with reduced fabrication process complexity. The optimal range of 8-9 vol% CB concentration has resulted in an improved sensitivity, low device variability and low noise level. The resonant frequency and spring constant of the microcantilever were found to be 22 kHz and 0.4 N m(-1) respectively. The devices exhibited a surface stress sensitivity of 7.6 ppm (mN m(-1))(-1) and the noise characterization results support their suitability for biochemical sensing applications. This paper also reports the ability of the sensor in detecting TNT vapour concentration down to less than six parts per billion with a sensitivity of 1 mV/ppb.

Low-Cost Sensor System Design for In-Home Physical Activity Tracking.

PubMed

Nambiar, Siddhartha; Nikolaev, Alexander; Greene, Melissa; Cavuoto, Lora; Bisantz, Ann

2016-01-01

An aging and more sedentary population requires interventions aimed at monitoring physical activity, particularly within the home. This research uses simulation, optimization, and regression analyses to assess the feasibility of using a small number of sensors to track movement and infer physical activity levels of older adults. Based on activity data from the American Time Use Survey and assisted living apartment layouts, we determined that using three to four doorway sensors can be used to effectively capture a sufficient amount of movements in order to estimate activity. The research also identified preferred approaches for assigning sensor locations, evaluated the error magnitude inherent in the approach, and developed a methodology to identify which apartment layouts would be best suited for these technologies.

Fuel sensor-less control of a liquid feed fuel cell system under steady load for portable applications

NASA Astrophysics Data System (ADS)

Chang, C. L.; Chen, C. Y.; Sung, C. C.; Liou, D. H.

This study presents a novel fuel sensor-less control scheme for a liquid feed fuel cell system that does not rely on a fuel concentration sensor. The proposed approach simplifies the design and reduces the cost and complexity of a liquid feed fuel cell system, and is especially suited to portable power sources, of which the volume and weight are important. During the reaction of a fuel cell, the cell's operating characteristics, such as potential, current and power are measured to control the supply of fuel and regulate its concentration to optimize performance. Experiments were conducted to verify that the fuel sensor-less control algorithm is effective in the liquid feed fuel cell system.

Low-Cost Sensor System Design for In-Home Physical Activity Tracking

PubMed Central

Nikolaev, Alexander; Greene, Melissa; Cavuoto, Lora; Bisantz, Ann

2016-01-01

An aging and more sedentary population requires interventions aimed at monitoring physical activity, particularly within the home. This research uses simulation, optimization, and regression analyses to assess the feasibility of using a small number of sensors to track movement and infer physical activity levels of older adults. Based on activity data from the American Time Use Survey and assisted living apartment layouts, we determined that using three to four doorway sensors can be used to effectively capture a sufficient amount of movements in order to estimate activity. The research also identified preferred approaches for assigning sensor locations, evaluated the error magnitude inherent in the approach, and developed a methodology to identify which apartment layouts would be best suited for these technologies. PMID:28560118

Optimization of Microelectronic Devices for Sensor Applications

NASA Technical Reports Server (NTRS)

Cwik, Tom; Klimeck, Gerhard

2000-01-01

The NASA/JPL goal to reduce payload in future space missions while increasing mission capability demands miniaturization of active and passive sensors, analytical instruments and communication systems among others. Currently, typical system requirements include the detection of particular spectral lines, associated data processing, and communication of the acquired data to other systems. Advances in lithography and deposition methods result in more advanced devices for space application, while the sub-micron resolution currently available opens a vast design space. Though an experimental exploration of this widening design space-searching for optimized performance by repeated fabrication efforts-is unfeasible, it does motivate the development of reliable software design tools. These tools necessitate models based on fundamental physics and mathematics of the device to accurately model effects such as diffraction and scattering in opto-electronic devices, or bandstructure and scattering in heterostructure devices. The software tools must have convenient turn-around times and interfaces that allow effective usage. The first issue is addressed by the application of high-performance computers and the second by the development of graphical user interfaces driven by properly developed data structures. These tools can then be integrated into an optimization environment, and with the available memory capacity and computational speed of high performance parallel platforms, simulation of optimized components can proceed. In this paper, specific applications of the electromagnetic modeling of infrared filtering, as well as heterostructure device design will be presented using genetic algorithm global optimization methods.

Heterogeneous Multi-Metric Learning for Multi-Sensor Fusion

DTIC Science & Technology

2011-07-01

distance”. One of the most widely used methods is the k-nearest neighbor ( KNN ) method [4], which labels an input data sample to be the class with majority...despite of its simplicity, it can be an effective candidate and can be easily extended to handle multiple sensors. Distance based method such as KNN relies...Neighbor (LMNN) method [21] which will be briefly reviewed in the sequel. LMNN method tries to learn an optimal metric specifically for KNN classifier. The

Fabrication and optimization of a conducting polymer sensor array using stored grain model volatiles.

PubMed

Hossain, Md Eftekhar; Rahman, G M Aminur; Freund, Michael S; Jayas, Digvir S; White, Noel D G; Shafai, Cyrus; Thomson, Douglas J

2012-03-21

During storage, grain can experience significant degradation in quality due to a variety of physical, chemical, and biological interactions. Most commonly, these losses are associated with insects or fungi. Continuous monitoring and an ability to differentiate between sources of spoilage are critical for rapid and effective intervention to minimize deterioration or losses. Therefore, there is a keen interest in developing a straightforward, cost-effective, and efficient method for monitoring of stored grain. Sensor arrays are currently used for classifying liquors, perfumes, and the quality of food products by mimicking the mammalian olfactory system. The use of this technology for monitoring of stored grain and identification of the source of spoilage is a new application, which has the potential for broad impact. The main focus of the work described herein is on the fabrication and optimization of a carbon black (CB) polymer sensor array to monitor stored grain model volatiles associated with insect secretions (benzene derivatives) and fungi (aliphatic hydrocarbon derivatives). Various methods of statistical analysis (RSD, PCA, LDA, t test) were used to select polymers for the array that were optimum for distinguishing between important compound classes (quinones, alcohols) and to minimize the sensitivity for other parameters such as humidity. The performance of the developed sensor array was satisfactory to demonstrate identification and separation of stored grain model volatiles at ambient conditions.

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

An Effective Massive Sensor Network Data Access Scheme Based on Topology Control for the Internet of Things.

PubMed

Yi, Meng; Chen, Qingkui; Xiong, Neal N

2016-11-03

This paper considers the distributed access and control problem of massive wireless sensor networks' data access center for the Internet of Things, which is an extension of wireless sensor networks and an element of its topology structure. In the context of the arrival of massive service access requests at a virtual data center, this paper designs a massive sensing data access and control mechanism to improve the access efficiency of service requests and makes full use of the available resources at the data access center for the Internet of things. Firstly, this paper proposes a synergistically distributed buffer access model, which separates the information of resource and location. Secondly, the paper divides the service access requests into multiple virtual groups based on their characteristics and locations using an optimized self-organizing feature map neural network. Furthermore, this paper designs an optimal scheduling algorithm of group migration based on the combination scheme between the artificial bee colony algorithm and chaos searching theory. Finally, the experimental results demonstrate that this mechanism outperforms the existing schemes in terms of enhancing the accessibility of service requests effectively, reducing network delay, and has higher load balancing capacity and higher resource utility rate.

Reduced signal crosstalk multi neurotransmitter image sensor by microhole array structure

NASA Astrophysics Data System (ADS)

Ogaeri, Yuta; Lee, You-Na; Mitsudome, Masato; Iwata, Tatsuya; Takahashi, Kazuhiro; Sawada, Kazuaki

2018-06-01

A microhole array structure combined with an enzyme immobilization method using magnetic beads can enhance the target discernment capability of a multi neurotransmitter image sensor. Here we report the fabrication and evaluation of the H+-diffusion-preventing capability of the sensor with the array structure. The structure with an SU-8 photoresist has holes with a size of 24.5 × 31.6 µm2. Sensors were prepared with the array structure of three different heights: 0, 15, and 60 µm. When the sensor has the structure of 60 µm height, 48% reduced output voltage is measured at a H+-sensitive null pixel that is located 75 µm from the acetylcholinesterase (AChE)-immobilized pixel, which is the starting point of H+ diffusion. The suppressed H+ immigration is shown in a two-dimensional (2D) image in real time. The sensor parameters, such as height of the array structure and measuring time, are optimized experimentally. The sensor is expected to effectively distinguish various neurotransmitters in biological samples.

Preparation of a novel pH optical sensor using orange (II) based on agarose membrane as support.

PubMed

Heydari, Rouhollah; Hosseini, Mohammad; Amraei, Ahmadreza; Mohammadzadeh, Ali

2016-04-01

A novel and cost effective optical pH sensor was prepared using covalent immobilization of orange (II) indicator on the agarose membrane as solid support. The fabricated optical sensor was fixed into a sample holder of a spectrophotometer instrument for pH monitoring. Variables affecting sensor performance including pH of dye bonding to agarose membrane and dye concentration were optimized. The sensor responds to the pH changes in the range of 3.0-10.0 with a response time of 2.0 min and appropriate reproducibility (RSD ≤ 0.9%). No significant variation was observed on sensor response after increasing the ionic strength in the range of 0.0-0.5M of sodium chloride. Determination of pH using the proposed optical sensor is quick, simple, inexpensive, selective and sensitive in the pH range of 3.0-10.0. Copyright © 2015 Elsevier B.V. All rights reserved.

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.

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.

A Method for Application of Classification Tree Models to Map Aquatic Vegetation Using Remotely Sensed Images from Different Sensors and Dates

PubMed Central

Jiang, Hao; Zhao, Dehua; Cai, Ying; An, Shuqing

2012-01-01

In previous attempts to identify aquatic vegetation from remotely-sensed images using classification trees (CT), the images used to apply CT models to different times or locations necessarily originated from the same satellite sensor as that from which the original images used in model development came, greatly limiting the application of CT. We have developed an effective normalization method to improve the robustness of CT models when applied to images originating from different sensors and dates. A total of 965 ground-truth samples of aquatic vegetation types were obtained in 2009 and 2010 in Taihu Lake, China. Using relevant spectral indices (SI) as classifiers, we manually developed a stable CT model structure and then applied a standard CT algorithm to obtain quantitative (optimal) thresholds from 2009 ground-truth data and images from Landsat7-ETM+, HJ-1B-CCD, Landsat5-TM and ALOS-AVNIR-2 sensors. Optimal CT thresholds produced average classification accuracies of 78.1%, 84.7% and 74.0% for emergent vegetation, floating-leaf vegetation and submerged vegetation, respectively. However, the optimal CT thresholds for different sensor images differed from each other, with an average relative variation (RV) of 6.40%. We developed and evaluated three new approaches to normalizing the images. The best-performing method (Method of 0.1% index scaling) normalized the SI images using tailored percentages of extreme pixel values. Using the images normalized by Method of 0.1% index scaling, CT models for a particular sensor in which thresholds were replaced by those from the models developed for images originating from other sensors provided average classification accuracies of 76.0%, 82.8% and 68.9% for emergent vegetation, floating-leaf vegetation and submerged vegetation, respectively. Applying the CT models developed for normalized 2009 images to 2010 images resulted in high classification (78.0%–93.3%) and overall (92.0%–93.1%) accuracies. Our results suggest that Method of 0.1% index scaling provides a feasible way to apply CT models directly to images from sensors or time periods that differ from those of the images used to develop the original models.

Modeling and Validation of Performance Limitations for the Optimal Design of Interferometric and Intensity-Modulated Fiber Optic Displacement Sensors

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

Moro, Erik A.

Optical fiber sensors offer advantages over traditional electromechanical sensors, making them particularly well-suited for certain measurement applications. Generally speaking, optical fiber sensors respond to a desired measurand through modulation of an optical signal's intensity, phase, or wavelength. Practically, non-contacting fiber optic displacement sensors are limited to intensity-modulated and interferometric (or phase-modulated) methodologies. Intensity-modulated fiber optic displacement sensors relate target displacement to a power measurement. The simplest intensity-modulated sensor architectures are not robust to environmental and hardware fluctuations, since such variability may cause changes in the measured power level that falsely indicate target displacement. Differential intensity-modulated sensors have been implemented, offeringmore » robustness to such intensity fluctuations, and the speed of these sensors is limited only by the combined speed of the photodetection hardware and the data acquisition system (kHz-MHz). The primary disadvantages of intensity-modulated sensing are the relatively low accuracy (?m-mm for low-power sensors) and the lack of robustness, which consequently must be designed, often with great difficulty, into the sensor's architecture. White light interferometric displacement sensors, on the other hand, offer increased accuracy and robustness. Unlike their monochromatic-interferometer counterparts, white light interferometric sensors offer absolute, unambiguous displacement measurements over large displacement ranges (cm for low-power, 5 mW, sources), necessitating no initial calibration, and requiring no environmental or feedback control. The primary disadvantage of white light interferometric displacement sensors is that their utility in dynamic testing scenarios is limited, both by hardware bandwidth and by their inherent high-sensitivity to Doppler-effects. The decision of whether to use either an intensity-modulated interferometric sensor depends on an appropriate performance function (e.g., desired displacement range, accuracy, robustness, etc.). In this dissertation, the performance limitations of a bundled differential intensity-modulated displacement sensor are analyzed, where the bundling configuration has been designed to optimize performance. The performance limitations of a white light Fabry-Perot displacement sensor are also analyzed. Both these sensors are non-contacting, but they have access to different regions of the performance-space. Further, both these sensors have different degrees of sensitivity to experimental uncertainty. Made in conjunction with careful analysis, the decision of which sensor to deploy need not be an uninformed one.« less

CMOS image sensors: State-of-the-art

NASA Astrophysics Data System (ADS)

Theuwissen, Albert J. P.

2008-09-01

This paper gives an overview of the state-of-the-art of CMOS image sensors. The main focus is put on the shrinkage of the pixels : what is the effect on the performance characteristics of the imagers and on the various physical parameters of the camera ? How is the CMOS pixel architecture optimized to cope with the negative performance effects of the ever-shrinking pixel size ? On the other hand, the smaller dimensions in CMOS technology allow further integration on column level and even on pixel level. This will make CMOS imagers even smarter that they are already.

Building Extraction Based on an Optimized Stacked Sparse Autoencoder of Structure and Training Samples Using LIDAR DSM and Optical Images.

PubMed

Yan, Yiming; Tan, Zhichao; Su, Nan; Zhao, Chunhui

2017-08-24

In this paper, a building extraction method is proposed based on a stacked sparse autoencoder with an optimized structure and training samples. Building extraction plays an important role in urban construction and planning. However, some negative effects will reduce the accuracy of extraction, such as exceeding resolution, bad correction and terrain influence. Data collected by multiple sensors, as light detection and ranging (LIDAR), optical sensor etc., are used to improve the extraction. Using digital surface model (DSM) obtained from LIDAR data and optical images, traditional method can improve the extraction effect to a certain extent, but there are some defects in feature extraction. Since stacked sparse autoencoder (SSAE) neural network can learn the essential characteristics of the data in depth, SSAE was employed to extract buildings from the combined DSM data and optical image. A better setting strategy of SSAE network structure is given, and an idea of setting the number and proportion of training samples for better training of SSAE was presented. The optical data and DSM were combined as input of the optimized SSAE, and after training by an optimized samples, the appropriate network structure can extract buildings with great accuracy and has good robustness.

Magnetic Field Dependence of the Critical Current in S-N Bilayer Thin Films

NASA Technical Reports Server (NTRS)

Sadleir, John E.; Lee, Sang-Jun; Smith, Stephen James; Bandler, Simon; Chervenak, James; Kilbourne, Caroline A.; Finkbeiner, Fred M.; Porter, Frederick S.; Kelley, Richard L.; Adams, Joseph S.;

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

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.

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

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.

Optimizing Wastewater Reuse in Agricultural Fields via Merging of Embedded Network Sensor Data and Flow and Transport Models Using Data Assimilation

NASA Astrophysics Data System (ADS)

Wu, C.; Margulis, S. A.

2007-12-01

Wastewater re-use via crop irrigation has the potential to be an effective means of wastewater disposal. However, nitrate in wastewater may contaminate groundwater if it does not decay before reaching the groundwater table. In order to dispose of wastewater while preventing long-term groundwater pollution, irrigation rates need to be optimized based on the current and predicted states of the soil, such as soil moisture content and/or nitrate concentration. A real-time soil states estimation system using the Ensemble Kalman Filter (EnKF) has been developed for application to a test bed for wastewater re-use in Palmdale, CA. This test bed, covered with alfalfa, is a 30-acre irrigation plot with a 200-meter long rotating pivot arm that irrigates the area with reclaimed wastewater. A sensor network is deployed in the soil near the surface. The data assimilation system has shown the ability to characterize soil states and fluxes from sparse measurements. The real-time estimation system will then be used to explore the potential feedback for optimizing the sprinkler operation (i.e. maximizing the magnitude of wastewater release while minimizing the ultimate groundwater pollution). In optimization models, soil states and fluxes can be regarded as functions of irrigation rate. Through optimization, the irrigation rate in a finite horizon can be maximized while still satisfying all criteria in soil states and fluxes to ensure the safety of groundwater. Since the data assimilation system provides reliable estimation of soil states and fluxes, it is expected to define the optimal irrigation rate with higher confidence compared to using models or sensors only.

An efficient multi-objective optimization method for water quality sensor placement within water distribution systems considering contamination probability variations.

PubMed

He, Guilin; Zhang, Tuqiao; Zheng, Feifei; Zhang, Qingzhou

2018-06-20

Water quality security within water distribution systems (WDSs) has been an important issue due to their inherent vulnerability associated with contamination intrusion. This motivates intensive studies to identify optimal water quality sensor placement (WQSP) strategies, aimed to timely/effectively detect (un)intentional intrusion events. However, these available WQSP optimization methods have consistently presumed that each WDS node has an equal contamination probability. While being simple in implementation, this assumption may do not conform to the fact that the nodal contamination probability may be significantly regionally varied owing to variations in population density and user properties. Furthermore, the low computational efficiency is another important factor that has seriously hampered the practical applications of the currently available WQSP optimization approaches. To address these two issues, this paper proposes an efficient multi-objective WQSP optimization method to explicitly account for contamination probability variations. Four different contamination probability functions (CPFs) are proposed to represent the potential variations of nodal contamination probabilities within the WDS. Two real-world WDSs are used to demonstrate the utility of the proposed method. Results show that WQSP strategies can be significantly affected by the choice of the CPF. For example, when the proposed method is applied to the large case study with the CPF accounting for user properties, the event detection probabilities of the resultant solutions are approximately 65%, while these values are around 25% for the traditional approach, and such design solutions are achieved approximately 10,000 times faster than the traditional method. This paper provides an alternative method to identify optimal WQSP solutions for the WDS, and also builds knowledge regarding the impacts of different CPFs on sensor deployments. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

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.

Angular rate optimal design for the rotary strapdown inertial navigation system.

PubMed

Yu, Fei; Sun, Qian

2014-04-22

Due to the characteristics of high precision for a long duration, the rotary strapdown inertial navigation system (RSINS) has been widely used in submarines and surface ships. Nowadays, the core technology, the rotating scheme, has been studied by numerous researchers. It is well known that as one of the key technologies, the rotating angular rate seriously influences the effectiveness of the error modulating. In order to design the optimal rotating angular rate of the RSINS, the relationship between the rotating angular rate and the velocity error of the RSINS was analyzed in detail based on the Laplace transform and the inverse Laplace transform in this paper. The analysis results showed that the velocity error of the RSINS depends on not only the sensor error, but also the rotating angular rate. In order to minimize the velocity error, the rotating angular rate of the RSINS should match the sensor error. One optimal design method for the rotating rate of the RSINS was also proposed in this paper. Simulation and experimental results verified the validity and superiority of this optimal design method for the rotating rate of the RSINS.

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.

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.

Construction of a novel peptide nucleic acid piezoelectric gene sensor microarray detection system.

PubMed

Chen, Ming; Liu, Minghua; Yu, Lili; Cai, Guoru; Chen, Qinghai; Wu, Rong; Wang, Feng; Zhang, Bo; Jiang, Tianlun; Fu, Welling

2005-08-01

A novel 2 x 5 clamped style piezoelectric gene sensor microarray has been successfully constructed. Every crystal unit of the fabricated gene sensor can oscillate independently without interfering with each other. The bis-peptide nucleic acid (bis-PNA) probe, which can combine with target DNA or RNA sequences more effectively and specifically than a DNA probe, was designed and immobilized on the surface of the gene sensor microarray to substitute the conventional DNA probe for direct detection of the hepatitis B virus (HBV) genomic DNA. Detection conditions were then explored and optimized. Results showed that PBS buffer of pH 6.8, an ion concentration of 20 mmol/liter, and a probe concentration of 1.5 micromol/liter were optimal for the detection system. Under such optimized experimental conditions, the specificity of bis-PNA was proved much higher than that of DNA probe. The relationship between quantity of target and decrease of frequency showed a typical saturation curve when concentrations of target HBV DNA varied from 10 pg/liter to 100 microg/liter, and 10 microg/liter was the watershed, with a statistic linear regression equation of I gC = -2.7455 + 0.0691 deltaF and the correlating coefficient of 0.9923. Fortunately, this is exactly the most ordinary variant range of the HBV virus concentration in clinical hepatitis samples. So, a good technical platform is successfully constructed and it will be applied to detect HBV quantitatively in clinical samples.

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

Balance Improvement Effects of Biofeedback Systems with State-of-the-Art Wearable Sensors: A Systematic Review.

PubMed

Ma, Christina Zong-Hao; Wong, Duo Wai-Chi; Lam, Wing Kai; Wan, Anson Hong-Ping; Lee, Winson Chiu-Chun

2016-03-25

Falls and fall-induced injuries are major global public health problems. Balance and gait disorders have been the second leading cause of falls. Inertial motion sensors and force sensors have been widely used to monitor both static and dynamic balance performance. Based on the detected performance, instant visual, auditory, electrotactile and vibrotactile biofeedback could be provided to augment the somatosensory input and enhance balance control. This review aims to synthesize the research examining the effect of biofeedback systems, with wearable inertial motion sensors and force sensors, on balance performance. Randomized and non-randomized clinical trials were included in this review. All studies were evaluated based on the methodological quality. Sample characteristics, device design and study characteristics were summarized. Most previous studies suggested that biofeedback devices were effective in enhancing static and dynamic balance in healthy young and older adults, and patients with balance and gait disorders. Attention should be paid to the choice of appropriate types of sensors and biofeedback for different intended purposes. Maximizing the computing capacity of the micro-processer, while minimizing the size of the electronic components, appears to be the future direction of optimizing the devices. Wearable balance-improving devices have their potential of serving as balance aids in daily life, which can be used indoors and outdoors.

Recent progress in millimeter-wave sensor system capabilities for enhanced (synthetic) vision

NASA Astrophysics Data System (ADS)

Hellemann, Karlheinz; Zachai, Reinhard

1999-07-01

Weather- and daylight independent operation of modern traffic systems is strongly required for an optimized and economic availability. Mainly helicopters, small aircraft and military transport aircraft operating frequently close to the ground have a need for effective and cost-effective Enhanced Vision sensors. The technical progress in sensor technology and processing speed offer today the possibility for new concepts to be realized. Derived from this background the paper reports on the improvements which are under development within the HiVision program at DaimlerChrysler Aerospace. A sensor demonstrator based on FMCW radar technology with high information update-rate and operating in the mm-wave band, has been up-graded to improve performance and fitted to fly on an experimental base. The results achieved so far demonstrate the capability to produce a weather independent enhanced vision. In addition the demonstrator has been tested on board a high- speed ferry at the Baltic sea, because fast vessels have a similar need for weather-independent operation and anti- collision measures. In the future one sensor type may serve both 'worlds' and help ease and save traffic. The described demonstrator fills up the technology gap between optical sensors (Infrared) and standard pulse radars with its specific features such as high speed scanning and weather penetration with the additional benefit of cost-effectiveness.

Balance Improvement Effects of Biofeedback Systems with State-of-the-Art Wearable Sensors: A Systematic Review

PubMed Central

Ma, Christina Zong-Hao; Wong, Duo Wai-Chi; Lam, Wing Kai; Wan, Anson Hong-Ping; Lee, Winson Chiu-Chun

2016-01-01

Falls and fall-induced injuries are major global public health problems. Balance and gait disorders have been the second leading cause of falls. Inertial motion sensors and force sensors have been widely used to monitor both static and dynamic balance performance. Based on the detected performance, instant visual, auditory, electrotactile and vibrotactile biofeedback could be provided to augment the somatosensory input and enhance balance control. This review aims to synthesize the research examining the effect of biofeedback systems, with wearable inertial motion sensors and force sensors, on balance performance. Randomized and non-randomized clinical trials were included in this review. All studies were evaluated based on the methodological quality. Sample characteristics, device design and study characteristics were summarized. Most previous studies suggested that biofeedback devices were effective in enhancing static and dynamic balance in healthy young and older adults, and patients with balance and gait disorders. Attention should be paid to the choice of appropriate types of sensors and biofeedback for different intended purposes. Maximizing the computing capacity of the micro-processer, while minimizing the size of the electronic components, appears to be the future direction of optimizing the devices. Wearable balance-improving devices have their potential of serving as balance aids in daily life, which can be used indoors and outdoors. PMID:27023558

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.

Optimized extreme learning machine for urban land cover classification using hyperspectral imagery

NASA Astrophysics Data System (ADS)

Su, Hongjun; Tian, Shufang; Cai, Yue; Sheng, Yehua; Chen, Chen; Najafian, Maryam

2017-12-01

This work presents a new urban land cover classification framework using the firefly algorithm (FA) optimized extreme learning machine (ELM). FA is adopted to optimize the regularization coefficient C and Gaussian kernel σ for kernel ELM. Additionally, effectiveness of spectral features derived from an FA-based band selection algorithm is studied for the proposed classification task. Three sets of hyperspectral databases were recorded using different sensors, namely HYDICE, HyMap, and AVIRIS. Our study shows that the proposed method outperforms traditional classification algorithms such as SVM and reduces computational cost significantly.

Optimization of sensor introduction into laminated composite materials

NASA Astrophysics Data System (ADS)

Schaaf, Kristin; Nemat-Nasser, Sia

2008-03-01

This work seeks to extend the functionality of the composite material beyond that of simply load-bearing and to enable in situ sensing, without compromising the structural integrity of the host composite material. Essential to the application of smart composites is the issue of the mechanical coupling of the sensor to the host material. Here we present various methods of embedding sensors within the host composite material. In this study, quasi-static three-point bending (short beam) and fatigue three-point bending (short beam) tests are conducted in order to characterize the effects of introducing the sensors into the host composite material. The sensors that are examined include three types of polyvinylidene fluoride (PVDF) thin film sensors: silver ink with a protective coating of urethane, silver ink without a protective coating, and nickel-copper alloy without a protective coating. The methods of sensor integration include placement at the midplane between the layers of prepreg material as well as a sandwich configuration in which a PVDF thin film sensor is placed between the first and second and nineteenth and twentieth layers of prepreg. Each PVDF sensor is continuous and occupies the entire layer, lying in the plane normal to the thickness direction in laminated composites. The work described here is part of an ongoing effort to understand the structural effects of integrating microsensor networks into a host composite material.

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.

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

The Genetic-Algorithm-Based Normal Boundary Intersection (GANBI) Method; An Efficient Approach to Pareto Multiobjective Optimization for Engineering Design

DTIC Science & Technology

2006-05-15

alarm performance in a cost-effective manner is the use of track - before - detect strategies, in which multiple sensor detections must occur within the...corresponding to the traditional sensor coverage problem. Also, in the track - before - detect context, reference is made to the field-level functions of...detection and false alarm as successful search and false search, respectively, because the track - before - detect process serves as a searching function

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.

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.

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.

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.

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

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.

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.

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.

Analysis and optimization of Love wave liquid sensors.

PubMed

Jakoby, B; Vellekoop, M J

1998-01-01

Love wave sensors are highly sensitive microacoustic devices, which are well suited for liquid sensing applications thanks to the shear polarization of the wave. The sensing mechanism thereby relies on the mechanical (or acoustic) interaction of the device with the liquid. The successful utilization of Love wave devices for this purpose requires proper shielding to avoid unwanted electric interaction of the liquid with the wave and the transducers. In this work we describe the effects of this electric interaction and the proper design of a shield to prevent it. We present analysis methods, which illustrate the impact of the interaction and which help to obtain an optimized design of the proposed shield. We also present experimental results for devices that have been fabricated according to these design rules.

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.

Selective Detection of Formaldehyde Gas Using a Cd-Doped TiO2-SnO2 Sensor

PubMed Central

Zeng, Wen; Liu, Tianmo; Wang, Zhongchang; Tsukimoto, Susumu; Saito, Mitsuhiro; Ikuhara, Yuichi

2009-01-01

We report the microstructure and gas-sensing properties of a nonequilibrium TiO2-SnO2 solid solution prepared by the sol-gel method. In particular, we focus on the effect of Cd doping on the sensing behavior of the TiO2-SnO2 sensor. Of all volatile organic compound gases examined, the sensor with Cd doping exhibits exclusive selectivity as well as high sensitivity to formaldehyde, a main harmful indoor gas. The key gas-sensing quantities, maximum sensitivity, optimal working temperature, and response and recovery time, are found to meet the basic industrial needs. This makes the Cd-doped TiO2-SnO2 composite a promising sensor material for detecting the formaldehyde gas. PMID:22291551

Low-complexity piecewise-affine virtual sensors: theory and design

NASA Astrophysics Data System (ADS)

Rubagotti, Matteo; Poggi, Tomaso; Oliveri, Alberto; Pascucci, Carlo Alberto; Bemporad, Alberto; Storace, Marco

2014-03-01

This paper is focused on the theoretical development and the hardware implementation of low-complexity piecewise-affine direct virtual sensors for the estimation of unmeasured variables of interest of nonlinear systems. The direct virtual sensor is designed directly from measured inputs and outputs of the system and does not require a dynamical model. The proposed approach allows one to design estimators which mitigate the effect of the so-called 'curse of dimensionality' of simplicial piecewise-affine functions, and can be therefore applied to relatively high-order systems, enjoying convergence and optimality properties. An automatic toolchain is also presented to generate the VHDL code describing the digital circuit implementing the virtual sensor, starting from the set of measured input and output data. The proposed methodology is applied to generate an FPGA implementation of the virtual sensor for the estimation of vehicle lateral velocity, using a hardware-in-the-loop setting.

A highly sensitive CMOS digital Hall sensor for low magnetic field applications.

PubMed

Xu, Yue; Pan, Hong-Bin; He, Shu-Zhuan; Li, Li

2012-01-01

Integrated CMOS Hall sensors have been widely used to measure magnetic fields. However, they are difficult to work with in a low magnetic field environment due to their low sensitivity and large offset. This paper describes a highly sensitive digital Hall sensor fabricated in 0.18 μm high voltage CMOS technology for low field applications. The sensor consists of a switched cross-shaped Hall plate and a novel signal conditioner. It effectively eliminates offset and low frequency 1/f noise by applying a dynamic quadrature offset cancellation technique. The measured results show the optimal Hall plate achieves a high current related sensitivity of about 310 V/AT. The whole sensor has a remarkable ability to measure a minimum ± 2 mT magnetic field and output a digital Hall signal in a wide temperature range from -40 °C to 120 °C.

Multianalyte biosensor based on pH-sensitive ZnO electrolyte–insulator–semiconductor structures

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

Haur Kao, Chyuan; Chun Liu, Che; Ueng, Herng-Yih

2014-05-14

Multianalyte electrolyte–insulator–semiconductor (EIS) sensors with a ZnO sensing membrane annealed on silicon substrate for use in pH sensing were fabricated. Material analyses were conducted using X-ray diffraction and atomic force microscopy to identify optimal treatment conditions. Sensing performance for various ions of Na{sup +}, K{sup +}, urea, and glucose was also tested. Results indicate that an EIS sensor with a ZnO membrane annealed at 600 °C exhibited good performance with high sensitivity and a low drift rate compared with all other reported ZnO-based pH sensors. Furthermore, based on well-established pH sensing properties, pH-ion-sensitive field-effect transistor sensors have also been developed formore » use in detecting urea and glucose ions. ZnO-based EIS sensors show promise for future industrial biosensing applications.« less

Formaldehyde sensor based on Ni-doped tetrapod-shaped ZnO nanopowder induced by external magnetic field

NASA Astrophysics Data System (ADS)

Bai, Zikui; Xie, Changsheng; Hu, Mulin; Zhang, Shunping

2008-12-01

The sensors based on Ni-doped ZnO nanopowder with tetrapod-shape (T-ZnO) were fabricated by screen-printing technique with external magnetic field in different direction. The morphologies and crystal structures of the thick film were characterized by X-ray diffraction (XRD) and field-emission scanning electron microscopy (FE-SEM), respectively. Gas-sensing property of sensors responded to 100 ppm formaldehyde was also detected. The results show that the direction of magnetic field has crucial effect on the sensor sensitivity. The sensors based on 5 wt% Ni-doped T-ZnO induced by magnetic field in parallel direction to the thick film surface, has the optimization sensitivity, the shortest response and recovery time, which are 10.6, 16 and 15 s, respectively. The magnetic-field induction model and the gas-sensing mechanism of the Ni-doped T-ZnO are proposed.

Design Optimisation of a Magnetic Field Based Soft Tactile Sensor

PubMed Central

Raske, Nicholas; Kow, Junwai; Alazmani, Ali; Ghajari, Mazdak; Culmer, Peter; Hewson, Robert

2017-01-01

This paper investigates the design optimisation of a magnetic field based soft tactile sensor, comprised of a magnet and Hall effect module separated by an elastomer. The aim was to minimise sensitivity of the output force with respect to the input magnetic field; this was achieved by varying the geometry and material properties. Finite element simulations determined the magnetic field and structural behaviour under load. Genetic programming produced phenomenological expressions describing these responses. Optimisation studies constrained by a measurable force and stable loading conditions were conducted; these produced Pareto sets of designs from which the optimal sensor characteristics were selected. The optimisation demonstrated a compromise between sensitivity and the measurable force, a fabricated version of the optimised sensor validated the improvements made using this methodology. The approach presented can be applied in general for optimising soft tactile sensor designs over a range of applications and sensing modes. PMID:29099787

An enhanced data visualization method for diesel engine malfunction classification using multi-sensor signals.

PubMed

Li, Yiqing; Wang, Yu; Zi, Yanyang; Zhang, Mingquan

2015-10-21

The various multi-sensor signal features from a diesel engine constitute a complex high-dimensional dataset. The non-linear dimensionality reduction method, t-distributed stochastic neighbor embedding (t-SNE), provides an effective way to implement data visualization for complex high-dimensional data. However, irrelevant features can deteriorate the performance of data visualization, and thus, should be eliminated a priori. This paper proposes a feature subset score based t-SNE (FSS-t-SNE) data visualization method to deal with the high-dimensional data that are collected from multi-sensor signals. In this method, the optimal feature subset is constructed by a feature subset score criterion. Then the high-dimensional data are visualized in 2-dimension space. According to the UCI dataset test, FSS-t-SNE can effectively improve the classification accuracy. An experiment was performed with a large power marine diesel engine to validate the proposed method for diesel engine malfunction classification. Multi-sensor signals were collected by a cylinder vibration sensor and a cylinder pressure sensor. Compared with other conventional data visualization methods, the proposed method shows good visualization performance and high classification accuracy in multi-malfunction classification of a diesel engine.

An Enhanced Data Visualization Method for Diesel Engine Malfunction Classification Using Multi-Sensor Signals

PubMed Central

Li, Yiqing; Wang, Yu; Zi, Yanyang; Zhang, Mingquan

2015-01-01

The various multi-sensor signal features from a diesel engine constitute a complex high-dimensional dataset. The non-linear dimensionality reduction method, t-distributed stochastic neighbor embedding (t-SNE), provides an effective way to implement data visualization for complex high-dimensional data. However, irrelevant features can deteriorate the performance of data visualization, and thus, should be eliminated a priori. This paper proposes a feature subset score based t-SNE (FSS-t-SNE) data visualization method to deal with the high-dimensional data that are collected from multi-sensor signals. In this method, the optimal feature subset is constructed by a feature subset score criterion. Then the high-dimensional data are visualized in 2-dimension space. According to the UCI dataset test, FSS-t-SNE can effectively improve the classification accuracy. An experiment was performed with a large power marine diesel engine to validate the proposed method for diesel engine malfunction classification. Multi-sensor signals were collected by a cylinder vibration sensor and a cylinder pressure sensor. Compared with other conventional data visualization methods, the proposed method shows good visualization performance and high classification accuracy in multi-malfunction classification of a diesel engine. PMID:26506347

Effect of Molecular Crowding on the Response of an Electrochemical DNA Sensor

PubMed Central

Ricci, Francesco; Lai, Rebecca Y.; Heeger, Alan J.; Plaxco, Kevin W.; Sumner, James J.

2009-01-01

E-DNA sensors, the electrochemical equivalent of molecular beacons, appear to be a promising means of detecting oligonucleotides. E-DNA sensors are comprised of a redox-modified (here, methylene blue or ferrocene) DNA stem-loop covalently attached to an interrogating electrode. Because E-DNA signaling arises due to binding-induced changes in the conformation of the stem-loop probe, it is likely sensitive to the nature of the molecular packing on the electrode surface. Here we detail the effects of probe density, target length, and other aspects of molecular crowding on the signaling properties, specificity, and response time of a model E-DNA sensor. We find that the highest signal suppression is obtained at the highest probe densities investigated, and that greater suppression is observed with longer and bulkier targets. In contrast, sensor equilibration time slows monotonically with increasing probe density, and the specificity of hybridization is not significantly affected. In addition to providing insight into the optimization of electrochemical DNA sensors, these results suggest that E-DNA signaling arises due to hybridization-linked changes in the rate, and thus efficiency, with which the redox moiety collides with the electrode and transfers electrons. PMID:17488132

Real-time CO2 sensor for the optimal control of electronic EGR system

NASA Astrophysics Data System (ADS)

Kim, Gwang-jung; Choi, Byungchul; Choi, Inchul

2013-12-01

In modern diesel engines, EGR (Exhaust Gas Recirculation) is an important technique used in nitrogen oxide (NOx) emission reduction. This paper describes the development and experimental results of a fiber-optical sensor using a 2.7 μm wavelength absorption to quantify the simultaneous CO2 concentration which is the primary variable of EGR rate (CO2 in the exhaust gas versus CO2 in the intake gas, %). A real-time laser absorption method was developed using a DFB (distributed feedback) diode laser and waveguide to make optimal design and control of electronic EGR system required for `Euro-6' and `Tier 4 Final' NOx emission regulations. While EGR is effective to reduce NOx significantly, the amount of HC and CO is increased in the exhaust gas if EGR rate is not controlled based on driving conditions. Therefore, it is important to recirculate an appropriate amount of exhaust gas in the operation condition generating high volume of NOx. In this study, we evaluated basic characteristics and functions of our optical sensor and studied basically in order to find out optimal design condition. We demonstrated CO2 measurement speed, accuracy and linearity as making a condition similar to real engine through the bench-scale experiment.

Computer-Guided Deep Brain Stimulation Programming for Parkinson's Disease.

PubMed

Heldman, Dustin A; Pulliam, Christopher L; Urrea Mendoza, Enrique; Gartner, Maureen; Giuffrida, Joseph P; Montgomery, Erwin B; Espay, Alberto J; Revilla, Fredy J

2016-02-01

Pilot study to evaluate computer-guided deep brain stimulation (DBS) programming designed to optimize stimulation settings using objective motion sensor-based motor assessments. Seven subjects (five males; 54-71 years) with Parkinson's disease (PD) and recently implanted DBS systems participated in this pilot study. Within two months of lead implantation, the subject returned to the clinic to undergo computer-guided programming and parameter selection. A motion sensor was placed on the index finger of the more affected hand. Software guided a monopolar survey during which monopolar stimulation on each contact was iteratively increased followed by an automated assessment of tremor and bradykinesia. After completing assessments at each setting, a software algorithm determined stimulation settings designed to minimize symptom severities, side effects, and battery usage. Optimal DBS settings were chosen based on average severity of motor symptoms measured by the motion sensor. Settings chosen by the software algorithm identified a therapeutic window and improved tremor and bradykinesia by an average of 35.7% compared with baseline in the "off" state (p < 0.01). Motion sensor-based computer-guided DBS programming identified stimulation parameters that significantly improved tremor and bradykinesia with minimal clinician involvement. Automated motion sensor-based mapping is worthy of further investigation and may one day serve to extend programming to populations without access to specialized DBS centers. © 2015 International Neuromodulation Society.

Accurate Natural Trail Detection Using a Combination of a Deep Neural Network and Dynamic Programming.

PubMed

Adhikari, Shyam Prasad; Yang, Changju; Slot, Krzysztof; Kim, Hyongsuk

2018-01-10

This paper presents a vision sensor-based solution to the challenging problem of detecting and following trails in highly unstructured natural environments like forests, rural areas and mountains, using a combination of a deep neural network and dynamic programming. The deep neural network (DNN) concept has recently emerged as a very effective tool for processing vision sensor signals. A patch-based DNN is trained with supervised data to classify fixed-size image patches into "trail" and "non-trail" categories, and reshaped to a fully convolutional architecture to produce trail segmentation map for arbitrary-sized input images. As trail and non-trail patches do not exhibit clearly defined shapes or forms, the patch-based classifier is prone to misclassification, and produces sub-optimal trail segmentation maps. Dynamic programming is introduced to find an optimal trail on the sub-optimal DNN output map. Experimental results showing accurate trail detection for real-world trail datasets captured with a head mounted vision system are presented.

A Novel High Sensitivity Sensor for Remote Field Eddy Current Non-Destructive Testing Based on Orthogonal Magnetic Field

PubMed Central

Xu, Xiaojie; Liu, Ming; Zhang, Zhanbin; Jia, Yueling

2014-01-01

Remote field eddy current is an effective non-destructive testing method for ferromagnetic tubular structures. In view of conventional sensors' disadvantages such as low signal-to-noise ratio and poor sensitivity to axial cracks, a novel high sensitivity sensor based on orthogonal magnetic field excitation is proposed. Firstly, through a three-dimensional finite element simulation, the remote field effect under orthogonal magnetic field excitation is determined, and an appropriate configuration which can generate an orthogonal magnetic field for a tubular structure is developed. Secondly, optimized selection of key parameters such as frequency, exciting currents and shielding modes is analyzed in detail, and different types of pick-up coils, including a new self-differential mode pick-up coil, are designed and analyzed. Lastly, the proposed sensor is verified experimentally by various types of defects manufactured on a section of a ferromagnetic tube. Experimental results show that the proposed novel sensor can largely improve the sensitivity of defect detection, especially for axial crack whose depth is less than 40% wall thickness, which are very difficult to detect and identify by conventional sensors. Another noteworthy advantage of the proposed sensor is that it has almost equal sensitivity to various types of defects, when a self-differential mode pick-up coil is adopted. PMID:25615738

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.

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

Automated Image Intelligence Adaptive Sensor Management System for High Altitude Long Endurance UAVs in a Dynamic and Anti-Access Area Denial Environment

NASA Astrophysics Data System (ADS)

Kim, Gi Young

The problem we investigate deals with an Image Intelligence (IMINT) sensor allocation schedule for High Altitude Long Endurance UAVs in a dynamic and Anti-Access Area Denial (A2AD) environment. The objective is to maximize the Situational Awareness (SA) of decision makers. The value of SA can be improved in two different ways. First, if a sensor allocated to an Areas of Interest (AOI) detects target activity, then the SA value will be increased. Second, the SA value increases if an AOI is monitored for a certain period of time, regardless of target detections. These values are functions of the sensor allocation time, sensor type and mode. Relatively few studies in the archival literature have been devoted to an analytic, detailed explanation of the target detection process, and AOI monitoring value dynamics. These two values are the fundamental criteria used to choose the most judicious sensor allocation schedule. This research presents mathematical expressions for target detection processes, and shows the monitoring value dynamics. Furthermore, the dynamics of target detection is the result of combined processes between belligerent behavior (target activity) and friendly behavior (sensor allocation). We investigate these combined processes and derive mathematical expressions for simplified cases. These closed form mathematical models can be used for Measures of Effectiveness (MOEs), i.e., target activity detection to evaluate sensor allocation schedules. We also verify these models with discrete event simulations which can also be used to describe more complex systems. We introduce several methodologies to achieve a judicious sensor allocation schedule focusing on the AOI monitoring value. The first methodology is a discrete time integer programming model which provides an optimal solution but is impractical for real world scenarios due to its computation time. Thus, it is necessary to trade off the quality of solution with computation time. The Myopic Greedy Procedure (MGP) is a heuristic which chooses the largest immediate unit time return at each decision epoch. This reduces computation time significantly, but the quality of the solution may be only 95% of optimal (for small size problems). Another alternative is a multi-start random constructive Hybrid Myopic Greedy Procedure (H-MGP), which incorporates stochastic variation in choosing an action at each stage, and repeats it a predetermined number of times (roughly 99.3% of optimal with 1000 repetitions). Finally, the One Stage Look Ahead (OSLA) procedure considers all the 'top choices' at each stage for a temporary time horizon and chooses the best action (roughly 98.8% of optimal with no repetition). Using OSLA procedure, we can have ameliorated solutions within a reasonable computation time. Other important issues discussed in this research are methodologies for the development of input parameters for real world applications.

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.

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.

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

Sensor networks for optimal target localization with bearings-only measurements in constrained three-dimensional scenarios.

PubMed

Moreno-Salinas, David; Pascoal, Antonio; Aranda, Joaquin

2013-08-12

In this paper, we address the problem of determining the optimal geometric configuration of an acoustic sensor network that will maximize the angle-related information available for underwater target positioning. In the set-up adopted, a set of autonomous vehicles carries a network of acoustic units that measure the elevation and azimuth angles between a target and each of the receivers on board the vehicles. It is assumed that the angle measurements are corrupted by white Gaussian noise, the variance of which is distance-dependent. Using tools from estimation theory, the problem is converted into that of minimizing, by proper choice of the sensor positions, the trace of the inverse of the Fisher Information Matrix (also called the Cramer-Rao Bound matrix) to determine the sensor configuration that yields the minimum possible covariance of any unbiased target estimator. It is shown that the optimal configuration of the sensors depends explicitly on the intensity of the measurement noise, the constraints imposed on the sensor configuration, the target depth and the probabilistic distribution that defines the prior uncertainty in the target position. Simulation examples illustrate the key results derived.

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 actuators 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.

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.

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.

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.

Energy Efficient Real-Time Scheduling Using DPM on Mobile Sensors with a Uniform Multi-Cores

PubMed Central

Kim, Youngmin; Lee, Chan-Gun

2017-01-01

In wireless sensor networks (WSNs), sensor nodes are deployed for collecting and analyzing data. These nodes use limited energy batteries for easy deployment and low cost. The use of limited energy batteries is closely related to the lifetime of the sensor nodes when using wireless sensor networks. Efficient-energy management is important to extending the lifetime of the sensor nodes. Most effort for improving power efficiency in tiny sensor nodes has focused mainly on reducing the power consumed during data transmission. However, recent emergence of sensor nodes equipped with multi-cores strongly requires attention to be given to the problem of reducing power consumption in multi-cores. In this paper, we propose an energy efficient scheduling method for sensor nodes supporting a uniform multi-cores. We extend the proposed T-Ler plane based scheduling for global optimal scheduling of a uniform multi-cores and multi-processors to enable power management using dynamic power management. In the proposed approach, processor selection for a scheduling and mapping method between the tasks and processors is proposed to efficiently utilize dynamic power management. Experiments show the effectiveness of the proposed approach compared to other existing methods. PMID:29240695

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.

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.

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.

Grating-patterned FeCo coated surface acoustic wave device for sensing magnetic field

NASA Astrophysics Data System (ADS)

Wang, Wen; Jia, Yana; Xue, Xufeng; Liang, Yong; Du, Zhaofu

2018-01-01

This study addresses the theoretical and experimental investigations of grating-patterned magnetostrictive FeCo coated surface acoustic wave (SAW) device for sensing magnetic field. The proposed sensor is composed of a configuration of differential dual-delay-line oscillators, and a magnetostrictive FeCo grating array deposited along the SAW propagation path of the sensing device, which suppresses effectively the hysteresis effect by releasing the internal binding force in FeCo. The magnetostrictive strain and ΔE effect from the FeCo coating modulates the SAW propagation characteristic, and the corresponding shift in differential oscillation frequency was utilized to evaluate the measurant. A theoretical model is performed to investigate the wave propagation in layered structure of FeCo/LiNbO3 in the effect of magnetostrictive, and allowing determining the optimal structure. The experimental results indicate that higher sensitivity, excellent linearity, and lower hysteresis error over the typical FeCo thin-film coated sensor were achieved from the grating-patterned FeCo coated sensor successfully.

Community Sewage Sensors towards Evaluation of Drug Use Trends: Detection of Cocaine in Wastewater with DNA-Directed Immobilization Aptamer Sensors

PubMed Central

Yang, Zhugen; Castrignanò, Erika; Estrela, Pedro; Frost, Christopher G.; Kasprzyk-Hordern, Barbara

2016-01-01

Illicit drug use has a global concern and effective monitoring and interventions are highly required to combat drug abuse. Wastewater-based epidemiology (WBE) is an innovative and cost-effective approach to evaluate community-wide drug use trends, compared to traditional population surveys. Here we report for the first time, a novel quantitative community sewage sensor (namely DNA-directed immobilization of aptamer sensors, DDIAS) for rapid and cost-effective estimation of cocaine use trends via WBE. Thiolated single-stranded DNA (ssDNA) probe was hybridized with aptamer ssDNA in solution, followed by co-immobilization with 6-mercapto-hexane onto the gold electrodes to control the surface density to effectively bind with cocaine. DDIAS was optimized to detect cocaine at as low as 10 nM with a dynamic range from 10 nM to 5 μM, which were further employed for the quantification of cocaine in wastewater samples collected from a wastewater treatment plant in seven consecutive days. The concentration pattern of the sampling week is comparable with that from mass spectrometry. Our results demonstrate that the developed DDIAS can be used as community sewage sensors for rapid and cost-effective evaluation of drug use trends, and potentially implemented as a powerful tool for on-site and real-time monitoring of wastewater by un-skilled personnel. PMID:26876971

Community Sewage Sensors towards Evaluation of Drug Use Trends: Detection of Cocaine in Wastewater with DNA-Directed Immobilization Aptamer Sensors

NASA Astrophysics Data System (ADS)

Yang, Zhugen; Castrignanò, Erika; Estrela, Pedro; Frost, Christopher G.; Kasprzyk-Hordern, Barbara

2016-02-01

Illicit drug use has a global concern and effective monitoring and interventions are highly required to combat drug abuse. Wastewater-based epidemiology (WBE) is an innovative and cost-effective approach to evaluate community-wide drug use trends, compared to traditional population surveys. Here we report for the first time, a novel quantitative community sewage sensor (namely DNA-directed immobilization of aptamer sensors, DDIAS) for rapid and cost-effective estimation of cocaine use trends via WBE. Thiolated single-stranded DNA (ssDNA) probe was hybridized with aptamer ssDNA in solution, followed by co-immobilization with 6-mercapto-hexane onto the gold electrodes to control the surface density to effectively bind with cocaine. DDIAS was optimized to detect cocaine at as low as 10 nM with a dynamic range from 10 nM to 5 μM, which were further employed for the quantification of cocaine in wastewater samples collected from a wastewater treatment plant in seven consecutive days. The concentration pattern of the sampling week is comparable with that from mass spectrometry. Our results demonstrate that the developed DDIAS can be used as community sewage sensors for rapid and cost-effective evaluation of drug use trends, and potentially implemented as a powerful tool for on-site and real-time monitoring of wastewater by un-skilled personnel.

A new optimal sliding mode controller design using scalar sign function.

PubMed

Singla, Mithun; Shieh, Leang-San; Song, Gangbing; Xie, Linbo; Zhang, Yongpeng

2014-03-01

This paper presents a new optimal sliding mode controller using the scalar sign function method. A smooth, continuous-time scalar sign function is used to replace the discontinuous switching function in the design of a sliding mode controller. The proposed sliding mode controller is designed using an optimal Linear Quadratic Regulator (LQR) approach. The sliding surface of the system is designed using stable eigenvectors and the scalar sign function. Controller simulations are compared with another existing optimal sliding mode controller. To test the effectiveness of the proposed controller, the controller is implemented on an aluminum beam with piezoceramic sensor and actuator for vibration control. This paper includes the control design and stability analysis of the new optimal sliding mode controller, followed by simulation and experimental results. The simulation and experimental results show that the proposed approach is very effective. © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Reduction of skylight reflection effects in the above-water measurement of diffuse marine reflectance: comment.

PubMed

Krotkov, N A; Vasilkov, A P

2000-03-20

Use of a vertical polarizer has been suggested to reduce the effects of surface reflection in the above-water measurements of marine reflectance. We suggest using a similar technique for airborne or spaceborne sensors when atmospheric scattering adds its own polarization signature to the upwelling radiance. Our own theoretical sensitivity study supports the recommendation of Fougnie et al. [Appl. Opt. 38, 3844 (1999)] (40-50 degrees vertical angle and azimuth angle near 135 degrees, polarizer parallel to the viewing plane) for above-water measurements. However, the optimal viewing directions (and the optimal orientation of the polarizer) change with altitude above the sea surface, solar angle, and atmospheric vertical optical structure. A polarization efficiency function is introduced, which shows the maximal possible polarization discrimination of the background radiation for an arbitrary altitude above the sea surface, viewing direction, and solar angle. Our comment is meant to encourage broader application of airborne and spaceborne polarization sensors in remote sensing of water and sea surface properties.

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

Direct protein detection with a nano-interdigitated array gate MOSFET.

PubMed

Tang, Xiaohui; Jonas, Alain M; Nysten, Bernard; Demoustier-Champagne, Sophie; Blondeau, Franoise; Prévot, Pierre-Paul; Pampin, Rémi; Godfroid, Edmond; Iñiguez, Benjamin; Colinge, Jean-Pierre; Raskin, Jean-Pierre; Flandre, Denis; Bayot, Vincent

2009-08-15

A new protein sensor is demonstrated by replacing the gate of a metal oxide semiconductor field effect transistor (MOSFET) with a nano-interdigitated array (nIDA). The sensor is able to detect the binding reaction of a typical antibody Ixodes ricinus immunosuppressor (anti-Iris) protein at a concentration lower than 1 ng/ml. The sensor exhibits a high selectivity and reproducible specific detection. We provide a simple model that describes the behavior of the sensor and explains the origin of its high sensitivity. The simulated and experimental results indicate that the drain current of nIDA-gate MOSFET sensor is significantly increased with the successive binding of the thiol layer, Iris and anti-Iris protein layers. It is found that the sensor detection limit can be improved by well optimizing the geometrical parameters of nIDA-gate MOSFET. This nanobiosensor, with real-time and label-free capabilities, can easily be used for the detection of other proteins, DNA, virus and cancer markers. Moreover, an on-chip associated electronics nearby the sensor can be integrated since its fabrication is compatible with complementary metal oxide semiconductor (CMOS) technology.

Characteristics research of pressure sensor based on nanopolysilicon thin films resistors

NASA Astrophysics Data System (ADS)

Zhao, Xiaofeng; Li, Dandan; Wen, Dianzhong

2017-10-01

To further improve the sensitivity temperature characteristics of pressure sensor, a kind of pressure sensor taking nanopolysilicon thin films as piezoresistors is proposed in this paper. On the basis of the microstructure analysis by X-ray diffraction (XRD) and scanning electron microscope (SEM) tests, the preparing process of nanopolysilicon thin films is optimized. The effects of film thickness and annealing temperature on the micro-structure of nanopolysilicon thin films were studied, respectively. In order to realize the measurement of external pressure, four nanopolysilicon thin films resistors were arranged at the edges of square silicon diaphragm connected to a Wheatstone bridge, and the chip of the sensor was designed and fabricated on a 〈100〉 orientation silicon wafer by microelectromechanical system (MEMS) technology. Experimental result shows that when I = 6.80 mA, the sensitivity of the sensor PS-1 is 0.308 mV/kPa, and the temperature coefficient of sensitivity (TCS) is about -1742 ppm/∘C in the range of -40-140∘C. It is possible to obviously improve the sensitivity temperature characteristics of pressure sensor by the proposed sensors.

Memetic Algorithm-Based Multi-Objective Coverage Optimization for Wireless Sensor Networks

PubMed Central

Chen, Zhi; Li, Shuai; Yue, Wenjing

2014-01-01

Maintaining effective coverage and extending the network lifetime as much as possible has become one of the most critical issues in the coverage of WSNs. In this paper, we propose a multi-objective coverage optimization algorithm for WSNs, namely MOCADMA, which models the coverage control of WSNs as the multi-objective optimization problem. MOCADMA uses a memetic algorithm with a dynamic local search strategy to optimize the coverage of WSNs and achieve the objectives such as high network coverage, effective node utilization and more residual energy. In MOCADMA, the alternative solutions are represented as the chromosomes in matrix form, and the optimal solutions are selected through numerous iterations of the evolution process, including selection, crossover, mutation, local enhancement, and fitness evaluation. The experiment and evaluation results show MOCADMA can have good capabilities in maintaining the sensing coverage, achieve higher network coverage while improving the energy efficiency and effectively prolonging the network lifetime, and have a significant improvement over some existing algorithms. PMID:25360579

Memetic algorithm-based multi-objective coverage optimization for wireless sensor networks.

PubMed

Chen, Zhi; Li, Shuai; Yue, Wenjing

2014-10-30

Maintaining effective coverage and extending the network lifetime as much as possible has become one of the most critical issues in the coverage of WSNs. In this paper, we propose a multi-objective coverage optimization algorithm for WSNs, namely MOCADMA, which models the coverage control of WSNs as the multi-objective optimization problem. MOCADMA uses a memetic algorithm with a dynamic local search strategy to optimize the coverage of WSNs and achieve the objectives such as high network coverage, effective node utilization and more residual energy. In MOCADMA, the alternative solutions are represented as the chromosomes in matrix form, and the optimal solutions are selected through numerous iterations of the evolution process, including selection, crossover, mutation, local enhancement, and fitness evaluation. The experiment and evaluation results show MOCADMA can have good capabilities in maintaining the sensing coverage, achieve higher network coverage while improving the energy efficiency and effectively prolonging the network lifetime, and have a significant improvement over some existing algorithms.

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

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.

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.

An Effective Massive Sensor Network Data Access Scheme Based on Topology Control for the Internet of Things

PubMed Central

Yi, Meng; Chen, Qingkui; Xiong, Neal N.

2016-01-01

This paper considers the distributed access and control problem of massive wireless sensor networks’ data access center for the Internet of Things, which is an extension of wireless sensor networks and an element of its topology structure. In the context of the arrival of massive service access requests at a virtual data center, this paper designs a massive sensing data access and control mechanism to improve the access efficiency of service requests and makes full use of the available resources at the data access center for the Internet of things. Firstly, this paper proposes a synergistically distributed buffer access model, which separates the information of resource and location. Secondly, the paper divides the service access requests into multiple virtual groups based on their characteristics and locations using an optimized self-organizing feature map neural network. Furthermore, this paper designs an optimal scheduling algorithm of group migration based on the combination scheme between the artificial bee colony algorithm and chaos searching theory. Finally, the experimental results demonstrate that this mechanism outperforms the existing schemes in terms of enhancing the accessibility of service requests effectively, reducing network delay, and has higher load balancing capacity and higher resource utility rate. PMID:27827878

In-situ growth of AuNPs on WS2@U-bent optical fiber for evanescent wave absorption sensor

NASA Astrophysics Data System (ADS)

Zhang, Suzhen; Zhao, Yuefeng; Zhang, Chao; Jiang, Shouzhen; Yang, Cheng; Xiu, Xianwu; Li, Chonghui; Li, Zhen; Zhao, Xiaofei; Man, Baoyuan

2018-05-01

The sensitivity of the evanescent wave absorption sensor is always a hot topic which has been attracted researchers' discussion. It is still a challenge for developing the effective sensor to sensitively detect some biochemical molecules solution in a simple and low-cost way. In this paper, an evanescent wave absorption (EWA) sensor has been presented based on the U-bent multimode fiber coated with tungsten disulfide (WS2) film and in-situ growth of gold nanoparticles (AuNPs) for the detection of ethanol solution and sodium chloride (NaCl) solution. Benefitted from the effective light coupling produced between U-bent probe and AuNPs, we attained the optimal size of the AuNPs by changing the reaction time between WS2 and tetrachloroauric acid (HAuCl4). With the AuNPs/WS2@U-bent optical fiber, we discussed the behaviors of EWA sensor, such as sensitivity, reproducibility, fast response-recovery time and stability. The sensitivity (△A/△C) of the proposed AuNPs/WS2@U-bent optical fiber EWA sensor is 0.65 for the detection of the ethanol solution. Besides, the AuNPs/WS2@U-bent optical fiber EWA sensor exhibits high sensitivity in detection of the sodium chloride (NaCl), which can reach 1.5 when the proposed sensor was immersed into NaCl solution. Our work demonstrates that the U-bent optical fiber EWA sensor may have promising applications in testing the solution of concentration.

PIYAS-proceeding to intelligent service oriented memory allocation for flash based data centric sensor devices in wireless sensor networks.

PubMed

Rizvi, Sanam Shahla; Chung, Tae-Sun

2010-01-01

Flash memory has become a more widespread storage medium for modern wireless devices because of its effective characteristics like non-volatility, small size, light weight, fast access speed, shock resistance, high reliability and low power consumption. Sensor nodes are highly resource constrained in terms of limited processing speed, runtime memory, persistent storage, communication bandwidth and finite energy. Therefore, for wireless sensor networks supporting sense, store, merge and send schemes, an efficient and reliable file system is highly required with consideration of sensor node constraints. In this paper, we propose a novel log structured external NAND flash memory based file system, called Proceeding to Intelligent service oriented memorY Allocation for flash based data centric Sensor devices in wireless sensor networks (PIYAS). This is the extended version of our previously proposed PIYA [1]. The main goals of the PIYAS scheme are to achieve instant mounting and reduced SRAM space by keeping memory mapping information to a very low size of and to provide high query response throughput by allocation of memory to the sensor data by network business rules. The scheme intelligently samples and stores the raw data and provides high in-network data availability by keeping the aggregate data for a longer period of time than any other scheme has done before. We propose effective garbage collection and wear-leveling schemes as well. The experimental results show that PIYAS is an optimized memory management scheme allowing high performance for wireless sensor networks.

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.

Flammable and noxious gas sensing using a microtripolar electrode sensor with diameter and chirality sorted single-walled carbon nanotubes

NASA Astrophysics Data System (ADS)

Cai, Shengbing; Duan, Zhe min; Zhang, Yong

2013-08-01

We report on the utilization of densely packed (˜10 SWCNTs µm-1), well-aligned arrays of single-chirality single-walled carbon nanotubes (SWCNTs) as an effective thin-film for integration into a gas sensor with a microtripolar electrode, based on field ionization by dielectrophoretic assembly from a monodisperse SWCNTs solution obtained by polymer-mediated sorting. The sensor is characterized as a field ionization electrode with sorted SWCNTs acting as both the sensing material and transducer gas concentrated directly into an electrical signal, an extractor serving to improve electric field uniformity and a collector electrode completing the current path. The gas sensing properties toward flammable and noxious gases, such as CO and H2, were investigated at room temperature. Besides the high sensitivity, the as-fabricated sensor exhibited attractive behaviors in terms of both the detection limit and a fast response, suggesting that our sensor could be used to partly circumvent the low sensing selectivity, long recovery time or irreversibility and allow for a preferential identification of the selected flammable and noxious analytes. Interestingly, the excellent sensing behaviors of the sensors based on the field ionization effect derive directly from the combined effects of the high-quality, low defect SWCNTs arrays, which leads to a small device-to-device variation in the properties and the optimization of electrode fabrication, highlighting the sensor as an appealing candidate in view of nanotube electronics.

Conjugated polyelectrolyte based real-time fluorescence assay for phospholipase C.

PubMed

Liu, Yan; Ogawa, Katsu; Schanze, Kirk S

2008-01-01

A fluorescence turnoff assay for phospholipase C (PLC) from Clostridium perfringens is developed based on the reversible interaction between the natural substrate, phosphatidylcholine, and a fluorescent, water-soluble conjugated polyelectrolyte (CPE). The fluorescence intensity of the CPE in water is increased substantially by the addition of the phospholipid due to the formation of a CPE-lipid complex. Incubation of the CPE-lipid complex with the enzyme PLC causes the fluorescence intensity to decrease (turnoff sensor); the response arises due to PLC-catalyzed hydrolysis of the phosphatidylcholine, which effectively disrupts the CPE-lipid complex. The PLC assay operates with phospholipid substrate concentrations in the micromolar range, and the analytical detection limit for PLC is <1 nM. The optimized assay provides a convenient, rapid, and real-time sensor for PLC activity. The real-time fluorescence intensity from the CPE can be converted to substrate concentration by using an ex situ calibration curve, allowing PLC-catalyzed reaction rates and kinetic parameters to be determined. PLC activation by Ca2+ and inhibition by EDTA and fluoride ion are demonstrated using the optimized sensor.

Analysis of electrical tomography sensitive field based on multi-terminal network and electric field

NASA Astrophysics Data System (ADS)

He, Yongbo; Su, Xingguo; Xu, Meng; Wang, Huaxiang

2010-08-01

Electrical tomography (ET) aims at the study of the conductivity/permittivity distribution of the interested field non-intrusively via the boundary voltage/current. The sensor is usually regarded as an electric field, and finite element method (FEM) is commonly used to calculate the sensitivity matrix and to optimize the sensor architecture. However, only the lumped circuit parameters can be measured by the data acquisition electronics, it's very meaningful to treat the sensor as a multi terminal network. Two types of multi terminal network with common node and common loop topologies are introduced. Getting more independent measurements and making more uniform current distribution are the two main ways to minimize the inherent ill-posed effect. By exploring the relationships of network matrixes, a general formula is proposed for the first time to calculate the number of the independent measurements. Additionally, the sensitivity distribution is analyzed with FEM. As a result, quasi opposite mode, an optimal single source excitation mode, that has the advantages of more uniform sensitivity distribution and more independent measurements, is proposed.

Immobilization, stabilization and patterning techniques for enzyme based sensor systems.

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

Flounders, A.W.; Carichner, S.C.; Singh, A.K.

1997-01-01

Sandia National Laboratories has recently opened the Chemical and Radiation Detection Laboratory (CRDL) in Livermore CA to address the detection needs of a variety of government agencies (e.g., Department of Energy, Environmental Protection Agency, Department of Agriculture) as well as provide a fertile environment for the cooperative development of new industrial technologies. This laboratory consolidates a variety of existing chemical and radiation detection efforts and enables Sandia to expand into the novel area of biochemically based sensors. One aspect of this biosensor effort is further development and optimization of enzyme modified field effect transistors (EnFETs). Recent work has focused uponmore » covalent attachment of enzymes to silicon dioxide and silicon nitride surfaces for EnFET fabrication. They are also investigating methods to pattern immobilized proteins; a critical component for development of array-based sensor systems. Novel enzyme stabilization procedures are key to patterning immobilized enzyme layers while maintaining enzyme activity. Results related to maximized enzyme loading, optimized enzyme activity and fluorescent imaging of patterned surfaces will be presented.« less

Number and placement of control system components considering possible failures. [for large space structures

NASA Technical Reports Server (NTRS)

Vander Velde, W. E.; Carignan, C. R.

1984-01-01

One of the first questions facing the designer of the control system for a large space structure is how many components actuators and sensors - to specify and where to place them on the structure. This paper presents a methodology which is intended to assist the designer in making these choices. A measure of controllability is defined which is a quantitative indication of how well the system can be controlled with a given set of actuators. Similarly, a measure of observability is defined which is a quantitative indication of how well the system can be observed with a given set of sensors. Then the effect of component unreliability is introduced by computing the average expected degree of controllability (observability) over the operating lifetime of the system accounting for the likelihood of various combinations of component failures. The problem of component location is resolved by optimizing this performance measure over the admissible set of locations. The variation of this optimized performance measure with number of actuators (sensors) is helpful in deciding how many components to use.

A Zinc Oxide Nanoflower-Based Electrochemical Sensor for Trace Detection of Sunset Yellow

PubMed Central

Ya, Yu; Jiang, Cuiwen; Li, Tao; Liao, Jie; Fan, Yegeng; Wei, Yuning; Yan, Feiyan; Xie, Liping

2017-01-01

Zinc oxide nanoflower (ZnONF) was synthesized by a simple process and was used to construct a highly sensitive electrochemical sensor for the detection of sunset yellow (SY). Due to the large surface area and high accumulation efficiency of ZnONF, the ZnONF-modified carbon paste electrode (ZnONF/CPE) showed a strong enhancement effect on the electrochemical oxidation of SY. The electrochemical behaviors of SY were investigated using voltammetry with the ZnONF-based sensor. The optimized parameters included the amount of ZnONF, the accumulation time, and the pH value. Under optimal conditions, the oxidation peak current was linearly proportional to SY concentration in the range of 0.50–10 μg/L and 10–70 μg/L, while the detection limit was 0.10 μg/L (signal-to-noise ratio = 3). The proposed method was used to determine the amount of SY in soft drinks with recoveries of 97.5%–103%, and the results were in good agreement with the results obtained by high-performance liquid chromatography. PMID:28282900

Adaptive Self-Tuning Networks

NASA Astrophysics Data System (ADS)

Knox, H. A.; Draelos, T.; Young, C. J.; Lawry, B.; Chael, E. P.; Faust, A.; Peterson, M. G.

2015-12-01

The quality of automatic detections from seismic sensor networks depends on a large number of data processing parameters that interact in complex ways. The largely manual process of identifying effective parameters is painstaking and does not guarantee that the resulting controls are the optimal configuration settings. Yet, achieving superior automatic detection of seismic events is closely related to these parameters. We present an automated sensor tuning (AST) system that learns near-optimal parameter settings for each event type using neuro-dynamic programming (reinforcement learning) trained with historic data. AST learns to test the raw signal against all event-settings and automatically self-tunes to an emerging event in real-time. The overall goal is to reduce the number of missed legitimate event detections and the number of false event detections. Reducing false alarms early in the seismic pipeline processing will have a significant impact on this goal. Applicable both for existing sensor performance boosting and new sensor deployment, this system provides an important new method to automatically tune complex remote sensing systems. Systems tuned in this way will achieve better performance than is currently possible by manual tuning, and with much less time and effort devoted to the tuning process. With ground truth on detections in seismic waveforms from a network of stations, we show that AST increases the probability of detection while decreasing false alarms.

Enhanced compressed sensing for visual target tracking in wireless visual sensor networks

NASA Astrophysics Data System (ADS)

Qiang, Guo

2017-11-01

Moving object tracking in wireless sensor networks (WSNs) has been widely applied in various fields. Designing low-power WSNs for the limited resources of the sensor, such as energy limitation, energy restriction, and bandwidth constraints, is of high priority. However, most existing works focus on only single conflicting optimization criteria. An efficient compressive sensing technique based on a customized memory gradient pursuit algorithm with early termination in WSNs is presented, which strikes compelling trade-offs among energy dissipation for wireless transmission, certain types of bandwidth, and minimum storage. Then, the proposed approach adopts an unscented particle filter to predict the location of the target. The experimental results with a theoretical analysis demonstrate the substantially superior effectiveness of the proposed model and framework in regard to the energy and speed under the resource limitation of a visual sensor node.

Cooperative Search and Rescue with Artificial Fishes Based on Fish-Swarm Algorithm for Underwater Wireless Sensor Networks

PubMed Central

Zhao, Wei; Tang, Zhenmin; Yang, Yuwang; Wang, Lei; Lan, Shaohua

2014-01-01

This paper presents a searching control approach for cooperating mobile sensor networks. We use a density function to represent the frequency of distress signals issued by victims. The mobile nodes' moving in mission space is similar to the behaviors of fish-swarm in water. So, we take the mobile node as artificial fish node and define its operations by a probabilistic model over a limited range. A fish-swarm based algorithm is designed requiring local information at each fish node and maximizing the joint detection probabilities of distress signals. Optimization of formation is also considered for the searching control approach and is optimized by fish-swarm algorithm. Simulation results include two schemes: preset route and random walks, and it is showed that the control scheme has adaptive and effective properties. PMID:24741341

Cooperative search and rescue with artificial fishes based on fish-swarm algorithm for underwater wireless sensor networks.

PubMed

Zhao, Wei; Tang, Zhenmin; Yang, Yuwang; Wang, Lei; Lan, Shaohua

2014-01-01

This paper presents a searching control approach for cooperating mobile sensor networks. We use a density function to represent the frequency of distress signals issued by victims. The mobile nodes' moving in mission space is similar to the behaviors of fish-swarm in water. So, we take the mobile node as artificial fish node and define its operations by a probabilistic model over a limited range. A fish-swarm based algorithm is designed requiring local information at each fish node and maximizing the joint detection probabilities of distress signals. Optimization of formation is also considered for the searching control approach and is optimized by fish-swarm algorithm. Simulation results include two schemes: preset route and random walks, and it is showed that the control scheme has adaptive and effective properties.

Charge transfer efficiency improvement of 4T pixel for high speed CMOS image sensor

NASA Astrophysics Data System (ADS)

Jin, Xiangliang; Liu, Weihui; Yang, Hongjiao; Tang, Lizhen; Yang, Jia

2015-03-01

The charge transfer efficiency improvement method is proposed by optimizing the electrical potential distribution along the transfer path from the PPD to the FD. In this work, we present a non-uniform doped transfer transistor channel, with the adjustments to the overlap length between the CPIA layer and the transfer gate, and the overlap length between the SEN layer and transfer gate. Theory analysis and TCAD simulation results show that the density of the residual charge reduces from 1e11 /cm3 to 1e9 /cm3, and the transfer time reduces from 500 ns to 143 ns, and the charge transfer efficiency is about 77 e-/ns. This optimizing design effectively improves the charge transfer efficiency of 4T pixel and the performance of 4T high speed CMOS image sensor.

Sensor-Based Optimized Control of the Full Load Instability in Large Hydraulic Turbines

PubMed Central

Presas, Alexandre; Valero, Carme; Egusquiza, Eduard

2018-01-01

Hydropower plants are of paramount importance for the integration of intermittent renewable energy sources in the power grid. In order to match the energy generated and consumed, Large hydraulic turbines have to work under off-design conditions, which may lead to dangerous unstable operating points involving the hydraulic, mechanical and electrical system. Under these conditions, the stability of the grid and the safety of the power plant itself can be compromised. For many Francis Turbines one of these critical points, that usually limits the maximum output power, is the full load instability. Therefore, these machines usually work far away from this unstable point, reducing the effective operating range of the unit. In order to extend the operating range of the machine, working closer to this point with a reasonable safety margin, it is of paramount importance to monitor and to control relevant parameters of the unit, which have to be obtained with an accurate sensor acquisition strategy. Within the framework of a large EU project, field tests in a large Francis Turbine located in Canada (rated power of 444 MW) have been performed. Many different sensors were used to monitor several working parameters of the unit for all its operating range. Particularly for these tests, more than 80 signals, including ten type of different sensors and several operating signals that define the operating point of the unit, were simultaneously acquired. The present study, focuses on the optimization of the acquisition strategy, which includes type, number, location, acquisition frequency of the sensors and corresponding signal analysis to detect the full load instability and to prevent the unit from reaching this point. A systematic approach to determine this strategy has been followed. It has been found that some indicators obtained with different types of sensors are linearly correlated with the oscillating power. The optimized strategy has been determined based on the correlation characteristics (linearity, sensitivity and reactivity), the simplicity of the installation and the acquisition frequency necessary. Finally, an economic and easy implementable protection system based on the resulting optimized acquisition strategy is proposed. This system, which can be used in a generic Francis turbine with a similar full load instability, permits one to extend the operating range of the unit by working close to the instability with a reasonable safety margin. PMID:29601512

Sensor-Based Optimized Control of the Full Load Instability in Large Hydraulic Turbines.

PubMed

Presas, Alexandre; Valentin, David; Egusquiza, Mònica; Valero, Carme; Egusquiza, Eduard

2018-03-30

Hydropower plants are of paramount importance for the integration of intermittent renewable energy sources in the power grid. In order to match the energy generated and consumed, Large hydraulic turbines have to work under off-design conditions, which may lead to dangerous unstable operating points involving the hydraulic, mechanical and electrical system. Under these conditions, the stability of the grid and the safety of the power plant itself can be compromised. For many Francis Turbines one of these critical points, that usually limits the maximum output power, is the full load instability. Therefore, these machines usually work far away from this unstable point, reducing the effective operating range of the unit. In order to extend the operating range of the machine, working closer to this point with a reasonable safety margin, it is of paramount importance to monitor and to control relevant parameters of the unit, which have to be obtained with an accurate sensor acquisition strategy. Within the framework of a large EU project, field tests in a large Francis Turbine located in Canada (rated power of 444 MW) have been performed. Many different sensors were used to monitor several working parameters of the unit for all its operating range. Particularly for these tests, more than 80 signals, including ten type of different sensors and several operating signals that define the operating point of the unit, were simultaneously acquired. The present study, focuses on the optimization of the acquisition strategy, which includes type, number, location, acquisition frequency of the sensors and corresponding signal analysis to detect the full load instability and to prevent the unit from reaching this point. A systematic approach to determine this strategy has been followed. It has been found that some indicators obtained with different types of sensors are linearly correlated with the oscillating power. The optimized strategy has been determined based on the correlation characteristics (linearity, sensitivity and reactivity), the simplicity of the installation and the acquisition frequency necessary. Finally, an economic and easy implementable protection system based on the resulting optimized acquisition strategy is proposed. This system, which can be used in a generic Francis turbine with a similar full load instability, permits one to extend the operating range of the unit by working close to the instability with a reasonable safety margin.

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.

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...

Solar rejection for an orbiting telescope

NASA Technical Reports Server (NTRS)

Rehnberg, J. D.

1975-01-01

The present work discusses some of the constraints that the optical designer must deal with in optimizing spaceborne sensors that must look at or near the sun. Analytical techniques are described for predicting the effects of stray radiation from sources such as mirror scatter, baffle scatter, diffraction, and ghost images. In addition, the paper describes a sensor design that has been flown on the Apollo Telescope Mount (Skylab) to aid astronauts in locating solar flares. In addition to keeping stray radiation to a minimum, the design had to be nondegradable by the direct solar heat load.

Optimizing the Attitude Control of Small Satellite Constellations for Rapid Response Imaging

NASA Astrophysics Data System (ADS)

Nag, S.; Li, A.

2016-12-01

Distributed Space Missions (DSMs) such as formation flight and constellations, are being recognized as important solutions to increase measurement samples over space and time. Given the increasingly accurate attitude control systems emerging in the commercial market, small spacecraft now have the ability to slew and point within few minutes of notice. In spite of hardware development in CubeSats at the payload (e.g. NASA InVEST) and subsystems (e.g. Blue Canyon Technologies), software development for tradespace analysis in constellation design (e.g. Goddard's TAT-C), planning and scheduling development in single spacecraft (e.g. GEO-CAPE) and aerial flight path optimizations for UAVs (e.g. NASA Sensor Web), there is a gap in open-source, open-access software tools for planning and scheduling distributed satellite operations in terms of pointing and observing targets. This paper will demonstrate results from a tool being developed for scheduling pointing operations of narrow field-of-view (FOV) sensors over mission lifetime to maximize metrics such as global coverage and revisit statistics. Past research has shown the need for at least fourteen satellites to cover the Earth globally everyday using a LandSat-like sensor. Increasing the FOV three times reduces the need to four satellites, however adds image distortion and BRDF complexities to the observed reflectance. If narrow FOV sensors on a small satellite constellation were commanded using robust algorithms to slew their sensor dynamically, they would be able to coordinately cover the global landmass much faster without compensating for spatial resolution or BRDF effects. Our algorithm to optimize constellation satellite pointing is based on a dynamic programming approach under the constraints of orbital mechanics and existing attitude control systems for small satellites. As a case study for our algorithm, we minimize the time required to cover the 17000 Landsat images with maximum signal to noise ratio fall-off and minimum image distortion among the satellites, using Landsat's specifications. Attitude-specific constraints such as power consumption, response time, and stability were factored into the optimality computations. The algorithm can integrate cloud cover predictions, specific ground and air assets and angular constraints.

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 Power-Optimized Cooperative MAC Protocol for Lifetime Extension in Wireless Sensor Networks.

PubMed

Liu, Kai; Wu, Shan; Huang, Bo; Liu, Feng; Xu, Zhen

2016-10-01

In wireless sensor networks, in order to satisfy the requirement of long working time of energy-limited nodes, we need to design an energy-efficient and lifetime-extended medium access control (MAC) protocol. In this paper, a node cooperation mechanism that one or multiple nodes with higher channel gain and sufficient residual energy help a sender relay its data packets to its recipient is employed to achieve this objective. We first propose a transmission power optimization algorithm to prolong network lifetime by optimizing the transmission powers of the sender and its cooperative nodes to maximize their minimum residual energy after their data packet transmissions. Based on it, we propose a corresponding power-optimized cooperative MAC protocol. A cooperative node contention mechanism is designed to ensure that the sender can effectively select a group of cooperative nodes with the lowest energy consumption and the best channel quality for cooperative transmissions, thus further improving the energy efficiency. Simulation results show that compared to typical MAC protocol with direct transmissions and energy-efficient cooperative MAC protocol, the proposed cooperative MAC protocol can efficiently improve the energy efficiency and extend the network lifetime.

A Power-Optimized Cooperative MAC Protocol for Lifetime Extension in Wireless Sensor Networks

PubMed Central

Liu, Kai; Wu, Shan; Huang, Bo; Liu, Feng; Xu, Zhen

2016-01-01

In wireless sensor networks, in order to satisfy the requirement of long working time of energy-limited nodes, we need to design an energy-efficient and lifetime-extended medium access control (MAC) protocol. In this paper, a node cooperation mechanism that one or multiple nodes with higher channel gain and sufficient residual energy help a sender relay its data packets to its recipient is employed to achieve this objective. We first propose a transmission power optimization algorithm to prolong network lifetime by optimizing the transmission powers of the sender and its cooperative nodes to maximize their minimum residual energy after their data packet transmissions. Based on it, we propose a corresponding power-optimized cooperative MAC protocol. A cooperative node contention mechanism is designed to ensure that the sender can effectively select a group of cooperative nodes with the lowest energy consumption and the best channel quality for cooperative transmissions, thus further improving the energy efficiency. Simulation results show that compared to typical MAC protocol with direct transmissions and energy-efficient cooperative MAC protocol, the proposed cooperative MAC protocol can efficiently improve the energy efficiency and extend the network lifetime. PMID:27706079

Angular Rate Optimal Design for the Rotary Strapdown Inertial Navigation System

PubMed Central

Yu, Fei; Sun, Qian

2014-01-01

Due to the characteristics of high precision for a long duration, the rotary strapdown inertial navigation system (RSINS) has been widely used in submarines and surface ships. Nowadays, the core technology, the rotating scheme, has been studied by numerous researchers. It is well known that as one of the key technologies, the rotating angular rate seriously influences the effectiveness of the error modulating. In order to design the optimal rotating angular rate of the RSINS, the relationship between the rotating angular rate and the velocity error of the RSINS was analyzed in detail based on the Laplace transform and the inverse Laplace transform in this paper. The analysis results showed that the velocity error of the RSINS depends on not only the sensor error, but also the rotating angular rate. In order to minimize the velocity error, the rotating angular rate of the RSINS should match the sensor error. One optimal design method for the rotating rate of the RSINS was also proposed in this paper. Simulation and experimental results verified the validity and superiority of this optimal design method for the rotating rate of the RSINS. PMID:24759115

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.

Motion Artifact Quantification and Sensor Fusion for Unobtrusive Health Monitoring.

PubMed

Hoog Antink, Christoph; Schulz, Florian; Leonhardt, Steffen; Walter, Marian

2017-12-25

Sensors integrated into objects of everyday life potentially allow unobtrusive health monitoring at home. However, since the coupling of sensors and subject is not as well-defined as compared to a clinical setting, the signal quality is much more variable and can be disturbed significantly by motion artifacts. One way of tackling this challenge is the combined evaluation of multiple channels via sensor fusion. For robust and accurate sensor fusion, analyzing the influence of motion on different modalities is crucial. In this work, a multimodal sensor setup integrated into an armchair is presented that combines capacitively coupled electrocardiography, reflective photoplethysmography, two high-frequency impedance sensors and two types of ballistocardiography sensors. To quantify motion artifacts, a motion protocol performed by healthy volunteers is recorded with a motion capture system, and reference sensors perform cardiorespiratory monitoring. The shape-based signal-to-noise ratio SNR S is introduced and used to quantify the effect on motion on different sensing modalities. Based on this analysis, an optimal combination of sensors and fusion methodology is developed and evaluated. Using the proposed approach, beat-to-beat heart-rate is estimated with a coverage of 99.5% and a mean absolute error of 7.9 ms on 425 min of data from seven volunteers in a proof-of-concept measurement scenario.

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.

A Novel Energy Efficient Topology Control Scheme Based on a Coverage-Preserving and Sleep Scheduling Model for Sensor Networks

PubMed Central

Shi, Binbin; Wei, Wei; Wang, Yihuai; Shu, Wanneng

2016-01-01

In high-density sensor networks, scheduling some sensor nodes to be in the sleep mode while other sensor nodes remain active for monitoring or forwarding packets is an effective control scheme to conserve energy. In this paper, a Coverage-Preserving Control Scheduling Scheme (CPCSS) based on a cloud model and redundancy degree in sensor networks is proposed. Firstly, the normal cloud model is adopted for calculating the similarity degree between the sensor nodes in terms of their historical data, and then all nodes in each grid of the target area can be classified into several categories. Secondly, the redundancy degree of a node is calculated according to its sensing area being covered by the neighboring sensors. Finally, a centralized approximation algorithm based on the partition of the target area is designed to obtain the approximate minimum set of nodes, which can retain the sufficient coverage of the target region and ensure the connectivity of the network at the same time. The simulation results show that the proposed CPCSS can balance the energy consumption and optimize the coverage performance of the sensor network. PMID:27754405

A Novel Energy Efficient Topology Control Scheme Based on a Coverage-Preserving and Sleep Scheduling Model for Sensor Networks.

PubMed

Shi, Binbin; Wei, Wei; Wang, Yihuai; Shu, Wanneng

2016-10-14

In high-density sensor networks, scheduling some sensor nodes to be in the sleep mode while other sensor nodes remain active for monitoring or forwarding packets is an effective control scheme to conserve energy. In this paper, a Coverage-Preserving Control Scheduling Scheme (CPCSS) based on a cloud model and redundancy degree in sensor networks is proposed. Firstly, the normal cloud model is adopted for calculating the similarity degree between the sensor nodes in terms of their historical data, and then all nodes in each grid of the target area can be classified into several categories. Secondly, the redundancy degree of a node is calculated according to its sensing area being covered by the neighboring sensors. Finally, a centralized approximation algorithm based on the partition of the target area is designed to obtain the approximate minimum set of nodes, which can retain the sufficient coverage of the target region and ensure the connectivity of the network at the same time. The simulation results show that the proposed CPCSS can balance the energy consumption and optimize the coverage performance of the sensor network.

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.

Efficient Skin Temperature Sensor and Stable Gel-Less Sticky ECG Sensor for a Wearable Flexible Healthcare Patch.

PubMed

Yamamoto, Yuki; Yamamoto, Daisuke; Takada, Makoto; Naito, Hiroyoshi; Arie, Takayuki; Akita, Seiji; Takei, Kuniharu

2017-09-01

Wearable, flexible healthcare devices, which can monitor health data to predict and diagnose disease in advance, benefit society. Toward this future, various flexible and stretchable sensors as well as other components are demonstrated by arranging materials, structures, and processes. Although there are many sensor demonstrations, the fundamental characteristics such as the dependence of a temperature sensor on film thickness and the impact of adhesive for an electrocardiogram (ECG) sensor are yet to be explored in detail. In this study, the effect of film thickness for skin temperature measurements, adhesive force, and reliability of gel-less ECG sensors as well as an integrated real-time demonstration is reported. Depending on the ambient conditions, film thickness strongly affects the precision of skin temperature measurements, resulting in a thin flexible film suitable for a temperature sensor in wearable device applications. Furthermore, by arranging the material composition, stable gel-less sticky ECG electrodes are realized. Finally, real-time simultaneous skin temperature and ECG signal recordings are demonstrated by attaching an optimized device onto a volunteer's chest. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Three-Dimensional Venturi Sensor for Measuring Extreme Winds

NASA Technical Reports Server (NTRS)

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

2003-01-01

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

Novel nanostructured oxygen sensor

NASA Astrophysics Data System (ADS)

Boardman, Alan James

New government regulations and industry requirements for medical oxygen sensors require the development of alternate materials and process optimization of primary sensor components. Current oxygen sensors are not compliant with the Restriction of Hazardous Substances (RoHS) Directive. This work focused on two areas. First, was finding suitable readily available materials for the sensor anodes. Second was optimizing the processing of the sensor cathode membrane for reduced delamination. Oxygen sensors were made using tin (Sn) and bismuth (Bi) electrodes, potassium hydroxide (KOH) and acetic acid (CH3COOH) electrolytes with platinum (Pt) and gold (Au) reference electrodes. Bi electrodes were fabricated by casting and pressing processes. Electrochemical characterization of the Sn and Bi electrodes was performed by Cyclic Voltammetry (CV), Electrochemical Impedance Spectroscopy (EIS) and sensing characterization per BSEN ISO 21647:2009 at various oxygen percentages, 0%, 20.9% and 100% oxygen levels with an automated test apparatus. The Sn anode with both electrolyte solutions showed good oxygen sensing properties and performance in a sensor. This system shows promise for replacement of Pb electrodes as required by the RoHS Directive. The Bi anode with Au cathode in both KOH and CH3COOH electrolytes showed acceptable performance and oxygen sensing properties. The Bi anodes fabricated by separate manufacturing methods demonstrated effectiveness for use in medical oxygen sensors. Gold thin films were prepared by magnetron sputtering on Flouroethylene Polymer (FEP) films. The FEP substrate temperature ranged from -77°C to 50°C. X-Ray Diffraction (XRD) and 4-point resistivity characterized the effects of substrate temperature to Au thin film particle size. XRD peak broadening and resistivity measurements showed a strong correlation of particle size to FEP substrate temperature. Particle size at 50°C was 594A and the -77°C particle size was 2.4 x 103A. Substrate temperature exhibited a strong correlation to adhesion of the Au thin film to the FEP. Adhesion of the Au thin film with a FEP temperature of 50°C was rated a 3B per the ASTM D3359-02 peel test standard. At FEP substrate temperature of -77°C it was rated at 1B. The morphology of the deposited Au thin films was observed using optical microscopy and Scanning Electron Microscopy (SEM).

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...

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.

Nanoporous gold film based SPR sensors for trace chemical detection

NASA Astrophysics Data System (ADS)

Wang, Li; Gong, Xiaoqing; Wan, Xiumei; Lu, Dan-feng; Qi, Zhi-mei

2017-02-01

Thin films of nanoporous gold (NPG) have both localized and propagating surface plasmon resonance (SPR) effects. The propagating SPR effect of NPG film combined with its huge internal surface area makes it applicable as an evanescent wave sensor with high sensitivity. In this work, NPG films with controlled thicknesses were fabricated on glass substrates by sputtering deposition of AuAg films followed by dealloying in nitric acid. By using of the NPG films as the sensing layer, a broadband wavelength-interrogated SPR sensor was prepared for chemical and biological detection. The propagating SPR absorption band in the visible-near infrared region was clearly observed upon exposure of the NPG film to air, and this band was detected to move to longer wavelengths in response to adsorption of molecules within the NPG film. Simulations based on Fresnel equations combined with Bruggeman approximation were carried out for optimizing the propagating SPR property of NPG film. The sensor's performance was investigated using both bisphenol A (BPA) and lead (II) ions as analytes. According to the experimental results, the detection limits of the sensor are 5 nmol·L-1 for BPA and 1 nmol·L-1 for lead (II) ions. The work demonstrated the outstanding applicability of the NPG film based SPR sensor for sensitive environmental monitoring.

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

The study of concentration effects of target hybridization on cervical cancer detection using interdigitated electrodes (IDE)

NASA Astrophysics Data System (ADS)

Noriani, C.; Hashim, U.; Azizah, N.

2016-07-01

Human Papilloma Virus (HPV) is a virus from the Papilloma virus family that affects human skin and the moist membranes that line the body, such as the throat, mouth, feet, fingers, nails, anus and cervix [1]. There are over 100 types, of which 40 can affect the genital area. Most known HPV types cause no symptoms to humans. Some, however, can cause verrucae (warts), while a small number can increase the risk of developing several cancers, such as that of the cervix, penis, vagina, anus and oropharynx (oral part of the pharynx - throat cancer). HPV strand 16 and 18 are well known for causing the advanced of Cervical Cancer (CC). Currently, integrated electrodes (IDEs) are implemented in various sensing devices including surface acoustic wave (SAW) sensors, chemical sensors as well as current MEMS biosensors. IDEs have been optimized for a variety of sensing applications including biosensors sensors, acoustic sensors, and chemical sensors. However, optimization for cancer cell detection has yet to be reported. The output signal strength of IDEs is controlled through careful design of the active area, width, and spacing of the electrode fingers the efficiency of DNA nanochip depends mainly on the sequence of the capture probes and the way they are attached to the support [2]. This strategy presented a simple, rapid and sensitive platform for HPV detection and would become a powerful tool for pathogenic microorganisms screening in clinical diagnosis. The coupling procedure must be quick, covalent, and reproducible.

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.

Tactile Sensory Supplementation of Gravitational References to Optimize Sensorimotor Recovery

NASA Technical Reports Server (NTRS)

Black, F. O.; Paloski, W. H.; Bloomberg, J. J.; Wood, S. J.

2007-01-01

Integration of multi-sensory inputs to detect tilts relative to gravity is critical for sensorimotor control of upright orientation. Displaying body orientation using electrotactile feedback to the tongue has been developed by Bach-y- Rita and colleagues as a sensory aid to maintain upright stance with impaired vestibular feedback. This investigation has explored the effects of Tongue Elecrotactile Feedback (TEF) for control of posture and movement as a sensorimotor countermeasure, specifically addressing the optimal location of movement sensors.

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

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.

Research and Experiments on a Unipolar Capacitive Voltage Sensor

PubMed Central

Zhou, Qiang; He, Wei; Li, Songnong; Hou, Xingzhe

2015-01-01

Voltage sensors are an important part of the electric system. In service, traditional voltage sensors need to directly contact a high-voltage charged body. Sensors involve a large volume, complex insulation structures, and high design costs. Typically an iron core structure is adopted. As a result, ferromagnetic resonance can occur easily during practical application. Moreover, owing to the multilevel capacitor divider, the sensor cannot reflect the changes of measured voltage in time. Based on the electric field coupling principle, this paper designs a new voltage sensor; the unipolar structure design solves many problems of traditional voltage sensors like the great insulation design difficulty and high costs caused by grounding electrodes. A differential signal input structure is adopted for the detection circuit, which effectively restrains the influence of the common-mode interference signal. Through sensor modeling, simulation and calculations, the structural design of the sensor electrode was optimized, miniaturization of the sensor was realized, the voltage division ratio of the sensor was enhanced, and the phase difference of sensor measurement was weakened. The voltage sensor is applied to a single-phase voltage class line of 10 kV for testing. According to the test results, the designed sensor is able to meet the requirements of accurate and real-time measurement for voltage of the charged conductor as well as to provide a new method for electricity larceny prevention and on-line monitoring of the power grid in an electric system. Therefore, it can satisfy the development demands of the smart power grid. PMID:26307992

Ammonia and ammonium hydroxide sensors for ammonia/water absorption machines: Literature review and data compilation

NASA Astrophysics Data System (ADS)

Anheier, N. C., Jr.; McDonald, C. E.; Cuta, J. M.; Cuta, F. M.; Olsen, K. B.

1995-05-01

This report describes an evaluation of various sensing techniques for determining the ammonia concentration in the working fluid of ammonia/water absorption cycle systems. The purpose was to determine if any existing sensor technology or instrumentation could provide an accurate, reliable, and cost-effective continuous measure of ammonia concentration in water. The resulting information will be used for design optimization and cycle control in an ammonia-absorption heat pump. Pacific Northwest Laboratory (PNL) researchers evaluated each sensing technology against a set of general requirements characterizing the potential operating conditions within the absorption cycle. The criteria included the physical constraints for in situ operation, sensor characteristics, and sensor application. PNL performed an extensive literature search, which uncovered several promising sensing technologies that might be applicable to this problem. Sixty-two references were investigated, and 33 commercial vendors were identified as having ammonia sensors. The technologies for ammonia sensing are acoustic wave, refractive index, electrode, thermal, ion-selective field-effect transistor (ISFET), electrical conductivity, pH/colormetric, and optical absorption. Based on information acquired in the literature search, PNL recommends that follow-on activities focus on ISFET devices and a fiber optic evanescent sensor with a colormetric indicator. The ISFET and fiber optic evanescent sensor are inherently microminiature and capable of in situ measurements. Further, both techniques have been demonstrated selective to the ammonium ion (NH4(+)). The primary issue remaining is how to make the sensors sufficiently corrosion-resistant to be useful in practice.

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

Competitive Swarm Optimizer Based Gateway Deployment Algorithm in Cyber-Physical Systems.

PubMed

Huang, Shuqiang; Tao, Ming

2017-01-22

Wireless sensor network topology optimization is a highly important issue, and topology control through node selection can improve the efficiency of data forwarding, while saving energy and prolonging lifetime of the network. To address the problem of connecting a wireless sensor network to the Internet in cyber-physical systems, here we propose a geometric gateway deployment based on a competitive swarm optimizer algorithm. The particle swarm optimization (PSO) algorithm has a continuous search feature in the solution space, which makes it suitable for finding the geometric center of gateway deployment; however, its search mechanism is limited to the individual optimum (pbest) and the population optimum (gbest); thus, it easily falls into local optima. In order to improve the particle search mechanism and enhance the search efficiency of the algorithm, we introduce a new competitive swarm optimizer (CSO) algorithm. The CSO search algorithm is based on an inter-particle competition mechanism and can effectively avoid trapping of the population falling into a local optimum. With the improvement of an adaptive opposition-based search and its ability to dynamically parameter adjustments, this algorithm can maintain the diversity of the entire swarm to solve geometric K -center gateway deployment problems. The simulation results show that this CSO algorithm has a good global explorative ability as well as convergence speed and can improve the network quality of service (QoS) level of cyber-physical systems by obtaining a minimum network coverage radius. We also find that the CSO algorithm is more stable, robust and effective in solving the problem of geometric gateway deployment as compared to the PSO or Kmedoids algorithms.

Recent advances in integrated photonic sensors.

PubMed

Passaro, Vittorio M N; de Tullio, Corrado; Troia, Benedetto; La Notte, Mario; Giannoccaro, Giovanni; De Leonardis, Francesco

2012-11-09

Nowadays, optical devices and circuits are becoming fundamental components in several application fields such as medicine, biotechnology, automotive, aerospace, food quality control, chemistry, to name a few. In this context, we propose a complete review on integrated photonic sensors, with specific attention to materials, technologies, architectures and optical sensing principles. To this aim, sensing principles commonly used in optical detection are presented, focusing on sensor performance features such as sensitivity, selectivity and rangeability. Since photonic sensors provide substantial benefits regarding compatibility with CMOS technology and integration on chips characterized by micrometric footprints, design and optimization strategies of photonic devices are widely discussed for sensing applications. In addition, several numerical methods employed in photonic circuits and devices, simulations and design are presented, focusing on their advantages and drawbacks. Finally, recent developments in the field of photonic sensing are reviewed, considering advanced photonic sensor architectures based on linear and non-linear optical effects and to be employed in chemical/biochemical sensing, angular velocity and electric field detection.

Noninvasive, three-dimensional full-field body sensor for surface deformation monitoring of human body in vivo

NASA Astrophysics Data System (ADS)

Chen, Zhenning; Shao, Xinxing; He, Xiaoyuan; Wu, Jialin; Xu, Xiangyang; Zhang, Jinlin

2017-09-01

Noninvasive, three-dimensional (3-D), full-field surface deformation measurements of the human body are important for biomedical investigations. We proposed a 3-D noninvasive, full-field body sensor based on stereo digital image correlation (stereo-DIC) for surface deformation monitoring of the human body in vivo. First, by applying an improved water-transfer printing (WTP) technique to transfer optimized speckle patterns onto the skin, the body sensor was conveniently and harmlessly fabricated directly onto the human body. Then, stereo-DIC was used to achieve 3-D noncontact and noninvasive surface deformation measurements. The accuracy and efficiency of the proposed body sensor were verified and discussed by considering different complexions. Moreover, the fabrication of speckle patterns on human skin, which has always been considered a challenging problem, was shown to be feasible, effective, and harmless as a result of the improved WTP technique. An application of the proposed stereo-DIC-based body sensor was demonstrated by measuring the pulse wave velocity of human carotid artery.

Recent Advances in Integrated Photonic Sensors

PubMed Central

Passaro, Vittorio M. N.; de Tullio, Corrado; Troia, Benedetto; La Notte, Mario; Giannoccaro, Giovanni; De Leonardis, Francesco

2012-01-01

Nowadays, optical devices and circuits are becoming fundamental components in several application fields such as medicine, biotechnology, automotive, aerospace, food quality control, chemistry, to name a few. In this context, we propose a complete review on integrated photonic sensors, with specific attention to materials, technologies, architectures and optical sensing principles. To this aim, sensing principles commonly used in optical detection are presented, focusing on sensor performance features such as sensitivity, selectivity and rangeability. Since photonic sensors provide substantial benefits regarding compatibility with CMOS technology and integration on chips characterized by micrometric footprints, design and optimization strategies of photonic devices are widely discussed for sensing applications. In addition, several numerical methods employed in photonic circuits and devices, simulations and design are presented, focusing on their advantages and drawbacks. Finally, recent developments in the field of photonic sensing are reviewed, considering advanced photonic sensor architectures based on linear and non-linear optical effects and to be employed in chemical/biochemical sensing, angular velocity and electric field detection. PMID:23202223

Robust Multivariable Estimation of the Relevant Information Coming from a Wheel Speed Sensor and an Accelerometer Embedded in a Car under Performance Tests

PubMed Central

Hernandez, Wilmar

2005-01-01

In the present paper, in order to estimate the response of both a wheel speed sensor and an accelerometer placed in a car under performance tests, robust and optimal multivariable estimation techniques are used. In this case, the disturbances and noises corrupting the relevant information coming from the sensors' outputs are so dangerous that their negative influence on the electrical systems impoverish the general performance of the car. In short, the solution to this problem is a safety related problem that deserves our full attention. Therefore, in order to diminish the negative effects of the disturbances and noises on the car's electrical and electromechanical systems, an optimum observer is used. The experimental results show a satisfactory improvement in the signal-to-noise ratio of the relevant signals and demonstrate the importance of the fusion of several intelligent sensor design techniques when designing the intelligent sensors that today's cars need.

Compound Event Barrier Coverage in Wireless Sensor Networks under Multi-Constraint Conditions.

PubMed

Zhuang, Yaoming; Wu, Chengdong; Zhang, Yunzhou; Jia, Zixi

2016-12-24

It is important to monitor compound event by barrier coverage issues in wireless sensor networks (WSNs). Compound event barrier coverage (CEBC) is a novel coverage problem. Unlike traditional ones, the data of compound event barrier coverage comes from different types of sensors. It will be subject to multiple constraints under complex conditions in real-world applications. The main objective of this paper is to design an efficient algorithm for complex conditions that can combine the compound event confidence. Moreover, a multiplier method based on an active-set strategy (ASMP) is proposed to optimize the multiple constraints in compound event barrier coverage. The algorithm can calculate the coverage ratio efficiently and allocate the sensor resources reasonably in compound event barrier coverage. The proposed algorithm can simplify complex problems to reduce the computational load of the network and improve the network efficiency. The simulation results demonstrate that the proposed algorithm is more effective and efficient than existing methods, especially in the allocation of sensor resources.

Square array photonic crystal fiber-based surface plasmon resonance refractive index sensor

NASA Astrophysics Data System (ADS)

Liu, Min; Yang, Xu; Zhao, Bingyue; Hou, Jingyun; Shum, Ping

2017-12-01

Based on surface plasmon resonance (SPR), a novel refractive index (RI) sensor comprising a square photonic crystal fiber (PCF) is proposed to realize the detection of the annular analyte. Instead of hexagon structure, four large air-holes in a square array are introduced to enhance the sensitivity by allowing two polarization directions of the core mode to be more sensitive. The gold is used as the only plasmonic material. The design purpose is to reduce the difficulty in gold deposition and enhance the RI sensitivity. The guiding properties and the effects of the parameters on the performance of the sensor are numerically investigated by the Finite Element Method (FEM). By optimizing the structure, the sensor can exhibit remarkable sensitivity up to 7250 nm/RIU and resolution of 1.0638 × 10-5 RIU with only one plasmonic material, which is very competitive compared with the other reported externally coated and single-layer coated PCF-based SPR (PCF-SPR) sensors, to our best knowledge.

Compound Event Barrier Coverage in Wireless Sensor Networks under Multi-Constraint Conditions

PubMed Central

Zhuang, Yaoming; Wu, Chengdong; Zhang, Yunzhou; Jia, Zixi

2016-01-01

It is important to monitor compound event by barrier coverage issues in wireless sensor networks (WSNs). Compound event barrier coverage (CEBC) is a novel coverage problem. Unlike traditional ones, the data of compound event barrier coverage comes from different types of sensors. It will be subject to multiple constraints under complex conditions in real-world applications. The main objective of this paper is to design an efficient algorithm for complex conditions that can combine the compound event confidence. Moreover, a multiplier method based on an active-set strategy (ASMP) is proposed to optimize the multiple constraints in compound event barrier coverage. The algorithm can calculate the coverage ratio efficiently and allocate the sensor resources reasonably in compound event barrier coverage. The proposed algorithm can simplify complex problems to reduce the computational load of the network and improve the network efficiency. The simulation results demonstrate that the proposed algorithm is more effective and efficient than existing methods, especially in the allocation of sensor resources. PMID:28029118

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.

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.

Optimizing Energy Consumption in Vehicular Sensor Networks by Clustering Using Fuzzy C-Means and Fuzzy Subtractive Algorithms

NASA Astrophysics Data System (ADS)

Ebrahimi, A.; Pahlavani, P.; Masoumi, Z.

2017-09-01

Traffic monitoring and managing in urban intelligent transportation systems (ITS) can be carried out based on vehicular sensor networks. In a vehicular sensor network, vehicles equipped with sensors such as GPS, can act as mobile sensors for sensing the urban traffic and sending the reports to a traffic monitoring center (TMC) for traffic estimation. The energy consumption by the sensor nodes is a main problem in the wireless sensor networks (WSNs); moreover, it is the most important feature in designing these networks. Clustering the sensor nodes is considered as an effective solution to reduce the energy consumption of WSNs. Each cluster should have a Cluster Head (CH), and a number of nodes located within its supervision area. The cluster heads are responsible for gathering and aggregating the information of clusters. Then, it transmits the information to the data collection center. Hence, the use of clustering decreases the volume of transmitting information, and, consequently, reduces the energy consumption of network. In this paper, Fuzzy C-Means (FCM) and Fuzzy Subtractive algorithms are employed to cluster sensors and investigate their performance on the energy consumption of sensors. It can be seen that the FCM algorithm and Fuzzy Subtractive have been reduced energy consumption of vehicle sensors up to 90.68% and 92.18%, respectively. Comparing the performance of the algorithms implies the 1.5 percent improvement in Fuzzy Subtractive algorithm in comparison.

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

Optimized star sensors laboratory calibration method using a regularization neural network.

PubMed

Zhang, Chengfen; Niu, Yanxiong; Zhang, Hao; Lu, Jiazhen

2018-02-10

High-precision ground calibration is essential to ensure the performance of star sensors. However, the complex distortion and multi-error coupling have brought great difficulties to traditional calibration methods, especially for large field of view (FOV) star sensors. Although increasing the complexity of models is an effective way to improve the calibration accuracy, it significantly increases the demand for calibration data. In order to achieve high-precision calibration of star sensors with large FOV, a novel laboratory calibration method based on a regularization neural network is proposed. A multi-layer structure neural network is designed to represent the mapping of the star vector and the corresponding star point coordinate directly. To ensure the generalization performance of the network, regularization strategies are incorporated into the net structure and the training algorithm. Simulation and experiment results demonstrate that the proposed method can achieve high precision with less calibration data and without any other priori information. Compared with traditional methods, the calibration error of the star sensor decreased by about 30%. The proposed method can satisfy the precision requirement for large FOV star sensors.

An Experimental Study on the Fabrication of Glass-based Acceleration Sensor Body Using Micro Powder Blasting Method

PubMed Central

Park, Dong-Sam; Yun, Dae-Jin; Cho, Myeong-Woo; Shin, Bong-Cheol

2007-01-01

This study investigated the feasibility of the micro powder blasting technique for the micro fabrication of sensor structures using the Pyrex glass to replace the existing silicon-based acceleration sensor fabrication processes. As the preliminary experiments, the effects of the blasting pressure, the mass flow rate of abrasive and the number of nozzle scanning times on erosion depth of the Pyrex and the soda lime glasses were examined. From the experimental results, optimal blasting conditions were selected for the Pyrex glass machining. The dimensions of the designed glass sensor was 1.7×1.7×0.6mm for the vibrating mass, and 2.9×0.7×0.2mm for the cantilever beam. The machining results showed that the dimensional errors of the machined glass sensor ranged from 3 μm in minimum to 20 μm in maximum. These results imply that the micro powder blasting method can be applied for the micromachining of glass-based acceleration sensors to replace the exiting method.

Enhanced Sensitivity of a Surface Acoustic Wave Gyroscope

NASA Astrophysics Data System (ADS)

Zhang, Yanhua; Wang, Wen

2009-10-01

In this paper, we present an optimal design and performance evaluation of a surface acoustic wave (SAW) gyroscope. It consists of a two-port SAW resonator (SAWR) and a SAW sensor (SAWS) structured using a delay line pattern. The SAW resonator provides a stable reference vibration and creates a standing wave, and the vibrating metallic dot array at antinodes of the standing wave induces the second SAW in the normal direction by the Coriolis force, and the SAW sensor is used to detect the secondary SAW. By using the coupling of modes (COM), the SAW resonator was simulated, and the effects of the design parameters on the frequency response of the device were investigated. Also, a theoretical analysis was performed to investigate the effect of metallic dots on the frequency response of the SAW device. The measured frequency response S21 of the fabricated 80 MHz two-port SAW resonator agrees well with the simulated result, that is, a low insertion loss (˜5 dB) and a single steep resonance peak were observed. In the gyroscopic experiments using a rate table, optimal metallic dot thickness was determined, and the sensitivity of the fabricated SAW gyroscope with an optimal metallic dot thickness of ˜350 nm was determined to be 3.2 µV deg-1 s-1.

Design and analysis on fume exhaust system of blackbody cavity sensor for continuously measuring molten steel temperature

NASA Astrophysics Data System (ADS)

Mei, Guohui; Zhang, Jiu; Zhao, Shumao; Xie, Zhi

2017-03-01

Fume exhaust system is the main component of the novel blackbody cavity sensor with a single layer tube, which removes the fume by gas flow along the exhaust pipe to keep the light path clean. However, the gas flow may break the conditions of blackbody cavity and results in the poor measurement accuracy. In this paper, we analyzed the influence of the gas flow on the temperature distribution of the measuring cavity, and then calculated the integrated effective emissivity of the non-isothermal cavity based on Monte-Carlo method, accordingly evaluated the sensor measurement accuracy, finally obtained the maximum allowable flow rate for various length of the exhaust pipe to meet the measurement accuracy. These results will help optimize the novel blackbody cavity sensor design and use it better for measuring the temperature of molten steel.

A Web of Things-Based Emerging Sensor Network Architecture for Smart Control Systems.

PubMed

Khan, Murad; Silva, Bhagya Nathali; Han, Kijun

2017-02-09

The Web of Things (WoT) plays an important role in the representation of the objects connected to the Internet of Things in a more transparent and effective way. Thus, it enables seamless and ubiquitous web communication between users and the smart things. Considering the importance of WoT, we propose a WoT-based emerging sensor network (WoT-ESN), which collects data from sensors, routes sensor data to the web, and integrate smart things into the web employing a representational state transfer (REST) architecture. A smart home scenario is introduced to evaluate the proposed WoT-ESN architecture. The smart home scenario is tested through computer simulation of the energy consumption of various household appliances, device discovery, and response time performance. The simulation results show that the proposed scheme significantly optimizes the energy consumption of the household appliances and the response time of the appliances.

T-L Plane Abstraction-Based Energy-Efficient Real-Time Scheduling for Multi-Core Wireless Sensors.

PubMed

Kim, Youngmin; Lee, Ki-Seong; Pham, Ngoc-Son; Lee, Sun-Ro; Lee, Chan-Gun

2016-07-08

Energy efficiency is considered as a critical requirement for wireless sensor networks. As more wireless sensor nodes are equipped with multi-cores, there are emerging needs for energy-efficient real-time scheduling algorithms. The T-L plane-based scheme is known to be an optimal global scheduling technique for periodic real-time tasks on multi-cores. Unfortunately, there has been a scarcity of studies on extending T-L plane-based scheduling algorithms to exploit energy-saving techniques. In this paper, we propose a new T-L plane-based algorithm enabling energy-efficient real-time scheduling on multi-core sensor nodes with dynamic power management (DPM). Our approach addresses the overhead of processor mode transitions and reduces fragmentations of the idle time, which are inherent in T-L plane-based algorithms. Our experimental results show the effectiveness of the proposed algorithm compared to other energy-aware scheduling methods on T-L plane abstraction.

Fiber optic Raman sensor to monitor the concentration ratio of nitrogen and oxygen in a cryogenic mixture

NASA Astrophysics Data System (ADS)

Tiwari, Vidhu S.; Kalluru, Rajamohan R.; Yueh, Fang Y.; Singh, Jagdish P.; St. Cyr, William; Khijwania, Sunil K.

2007-06-01

A spontaneous Raman scattering optical fiber sensor was developed for a specific need of the National Aeronautics and Space Administration (NASA) for long-term detection and monitoring of the purity of liquid oxygen (LO2) in the oxidizer feed line during ground testing of rocket engines. The Raman peak intensity ratios for liquid nitrogen (LN2) and LO2 with varied weight ratios (LN2/LO2) were analyzed for their applicability to impurity sensing. The study of the sensor performance with different excitation light sources has helped to design a miniaturized, cost-effective system for this application. The optimal system response time of this miniaturized sensor for LN2/LO2 measurement was found to be in the range of a few seconds. It will need to be further reduced to the millisecond range for real-time, quantitative monitoring of the quality of cryogenic fluids in a harsh envioronment.

Analytic Confusion Matrix Bounds for Fault Detection and Isolation Using a Sum-of-Squared- Residuals Approach

NASA Technical Reports Server (NTRS)

Simon, Dan; Simon, Donald L.

2009-01-01

Given a system which can fail in 1 or n different ways, a fault detection and isolation (FDI) algorithm uses sensor data in order to determine which fault is the most likely to have occurred. The effectiveness of an FDI algorithm can be quantified by a confusion matrix, which i ndicates the probability that each fault is isolated given that each fault has occurred. Confusion matrices are often generated with simulation data, particularly for complex systems. In this paper we perform FDI using sums of squares of sensor residuals (SSRs). We assume that the sensor residuals are Gaussian, which gives the SSRs a chi-squared distribution. We then generate analytic lower and upper bounds on the confusion matrix elements. This allows for the generation of optimal sensor sets without numerical simulations. The confusion matrix bound s are verified with simulated aircraft engine data.

A Web of Things-Based Emerging Sensor Network Architecture for Smart Control Systems

PubMed Central

Khan, Murad; Silva, Bhagya Nathali; Han, Kijun

2017-01-01

The Web of Things (WoT) plays an important role in the representation of the objects connected to the Internet of Things in a more transparent and effective way. Thus, it enables seamless and ubiquitous web communication between users and the smart things. Considering the importance of WoT, we propose a WoT-based emerging sensor network (WoT-ESN), which collects data from sensors, routes sensor data to the web, and integrate smart things into the web employing a representational state transfer (REST) architecture. A smart home scenario is introduced to evaluate the proposed WoT-ESN architecture. The smart home scenario is tested through computer simulation of the energy consumption of various household appliances, device discovery, and response time performance. The simulation results show that the proposed scheme significantly optimizes the energy consumption of the household appliances and the response time of the appliances.  PMID:28208787

Design of a surface-scanning coil detector for direct bacteria detection on food surfaces using a magnetoelastic biosensor

NASA Astrophysics Data System (ADS)

Chai, Yating; Wikle, Howard C.; Wang, Zhenyu; Horikawa, Shin; Best, Steve; Cheng, Zhongyang; Dyer, Dave F.; Chin, Bryan A.

2013-09-01

The real-time, in-situ bacteria detection on food surfaces was achieved by using a magnetoelastic biosensor combined with a surface-scanning coil detector. This paper focuses on the coil design for signal optimization. The coil was used to excite the sensor's vibration and detect its resonant frequency signal. The vibrating sensor creates a magnetic flux change around the coil, which then produces a mutual inductance. In order to enhance the signal amplitude, a theory of the sensor's mutual inductance with the measurement coil is proposed. Both theoretical calculations and experimental data showed that the working length of the coil has a significant effect on the signal amplitude. For a 1 mm-long sensor, a coil with a working length of 1.3 mm showed the best signal amplitude. The real-time detection of Salmonella bacteria on a fresh food surface was demonstrated using this new technology.

Sensitivity optimization of ZnO clad-modified optical fiber humidity sensor by means of tuning the optical fiber waist diameter

NASA Astrophysics Data System (ADS)

Azad, Saeed; Sadeghi, Ebrahim; Parvizi, Roghaieh; Mazaheri, Azardokht; Yousefi, M.

2017-05-01

In this work, the multimode optical fiber size effects on the performances of the clad-modified fiber with ZnO nanorods relative humidity (RH) sensor were experimentally investigated. Simple and controlled chemical etching method through on line monitoring was used to prepare different fiber waist diameter with long length of 15 mm. More precisely, the competition behavior of sensor performances with varying fiber waist diameter was studied to find appropriate size of maximizing evanescent fields. The obtained results revealed that evanescent wave absorption coefficient (γ) enhanced more than 10 times compare to bare fiber at the proposed optimum fiber diameter of 28 μm. Also, high linearity and fast recovery time about 7 s was obtained at the proposed fiber waist diameter. Applicable features of the proposed sensor allow this device to be used for humidity sensing applications, especially to be applied in remote sensing technologies.

QCM gas phase detection with ceramic materials--VOCs and oil vapors.

PubMed

Latif, Usman; Rohrer, Andreas; Lieberzeit, Peter A; Dickert, Franz L

2011-06-01

Titanate sol-gel layers imprinted with carbonic acids were used as sensitive layers on quartz crystal microbalance. These functionalized ceramics enable us detection of volatile organic compounds such as ethanol, n-propanol, n-butanol, n-hexane, n-heptane, n-/iso-octane, and n-decane. Variation of the precursors (i.e., tetrabutoxy titanium, tetrapropoxy titanium, tetraethoxy titanium) allows us to tune the sensitivity of the material by a factor of 7. Sensitivity as a function of precursors leads to selective inclusion of n-butanol vapors down to 1 ppm. The selectivity of materials is optimized to differentiate between isomers, e.g., n- and iso-octane. The results can be rationalized by correlating the sensor effects of hydrocarbons with the Wiener index. A mass-sensitive sensor based on titanate layer was also developed for monitoring emanation of degraded engine oil. Heating the sensor by a meander avoids vapor condensation. Thus, a continuously working oil quality sensor was designed.

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).

Tailoring plasmonic properties of gold nanohole arrays for surface-enhanced Raman scattering

PubMed Central

Zheng, Peng; Cushing, Scott K.; Suri, Savan; Wu, Nianqiang

2015-01-01

The wide plasmonic tuning range of nanotriangle and nanohole array patterns fabricated by nanosphere lithography makes them promising in surface-enhanced Raman scattering (SERS) sensors. Unfortunately, it is challenging to optimize these patterns for SERS sensing because their optical response is a complex mixture of localized and propagating surface plasmons. In this paper, transmission and reflection measurements are combined with finite difference time domain simulations to identify and separate each plasmonic mode, discerning which resonance leads to the electromagnetic field enhancement. The SERS enhancement is found to be dominated by the absorption, which is shifted from the transmission and reflection dips usually used as tuning points, and by the ‘gap’ defects formed within the pattern. These effects have different spectral and geometric dependences, forming two optimization curves which can be used to predict the best performance for a given excitation wavelength. The developed model is verified with experimental SERS measurements for several nanohole sizes and periodicities, and then used to give optimal fabrication parameters for a range of measurement conditions. The results will promote the application of two-dimensional plasmonic nanoarrays in SERS sensors. PMID:25586930

An Optimal Image-Based Method for Identification of Acoustic Emission (AE) Sources in Plate-Like Structures Using a Lead Zirconium Titanate (PZT) Sensor Array.

PubMed

Yan, Gang; Zhou, Li

2018-02-21

This paper proposes an innovative method for identifying the locations of multiple simultaneous acoustic emission (AE) events in plate-like structures from the view of image processing. By using a linear lead zirconium titanate (PZT) sensor array to record the AE wave signals, a reverse-time frequency-wavenumber (f-k) migration is employed to produce images displaying the locations of AE sources by back-propagating the AE waves. Lamb wave theory is included in the f-k migration to consider the dispersive property of the AE waves. Since the exact occurrence time of the AE events is usually unknown when recording the AE wave signals, a heuristic artificial bee colony (ABC) algorithm combined with an optimal criterion using minimum Shannon entropy is used to find the image with the identified AE source locations and occurrence time that mostly approximate the actual ones. Experimental studies on an aluminum plate with AE events simulated by PZT actuators are performed to validate the applicability and effectiveness of the proposed optimal image-based AE source identification method.

An Optimal Image-Based Method for Identification of Acoustic Emission (AE) Sources in Plate-Like Structures Using a Lead Zirconium Titanate (PZT) Sensor Array

PubMed Central

Zhou, Li

2018-01-01

This paper proposes an innovative method for identifying the locations of multiple simultaneous acoustic emission (AE) events in plate-like structures from the view of image processing. By using a linear lead zirconium titanate (PZT) sensor array to record the AE wave signals, a reverse-time frequency-wavenumber (f-k) migration is employed to produce images displaying the locations of AE sources by back-propagating the AE waves. Lamb wave theory is included in the f-k migration to consider the dispersive property of the AE waves. Since the exact occurrence time of the AE events is usually unknown when recording the AE wave signals, a heuristic artificial bee colony (ABC) algorithm combined with an optimal criterion using minimum Shannon entropy is used to find the image with the identified AE source locations and occurrence time that mostly approximate the actual ones. Experimental studies on an aluminum plate with AE events simulated by PZT actuators are performed to validate the applicability and effectiveness of the proposed optimal image-based AE source identification method. PMID:29466310

Active stabilization of thin-wall structures under compressive loading

NASA Astrophysics Data System (ADS)

Welham, Jared; Calius, Emilio P.; Chase, J. Geoffrey

2003-08-01

The active suppression of elastic buckling instability has the potential to significantly increase the effective strength of thin-wall structures. Despite all the interest in smart structures, the active suppression of buckling has received comparatively little attention. This paper addresses the effects of embedded actuation on the compression buckling strength of laminated composite plates through analysis and simulation. Numerical models are formulated that include the influence of essential features such as sensor uncertainty and noise, actuator saturation and control architecture on the buckling process. Silicon-based strain sensors and diffuse laser distance sensors are both considered for use in the detection of incipient buckling behavior due to their increased sensitivity. Actuation is provided by paired distributions of piezo-electric material incorporated into both sides of the laminate. Optimal controllers are designed to command the structure to deform in ways that interfere with the development of buckling mode shapes. Commercial software packages are used to solve the resulting non-linear equations, and some of the tradeoffs are enumerated. Overall, the results show that active buckling control can considerably enhance resistance to instability under compressive loads. These buckling load predictions demonstrate the viability of optimal control and piezo-electric actuation for implementing active buckling control. Due to the importance of early detection, the relative effectiveness of active buckling control is shown to be strongly dependent on the performance of the sensing scheme, as well as on the characteristics of the structure.

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.

Control and optimization system and method for chemical looping processes

DOEpatents

Lou, Xinsheng; Joshi, Abhinaya; Lei, Hao

2014-06-24

A control system for optimizing a chemical loop system includes one or more sensors for measuring one or more parameters in a chemical loop. The sensors are disposed on or in a conduit positioned in the chemical loop. The sensors generate one or more data signals representative of an amount of solids in the conduit. The control system includes a data acquisition system in communication with the sensors and a controller in communication with the data acquisition system. The data acquisition system receives the data signals and the controller generates the control signals. The controller is in communication with one or more valves positioned in the chemical loop. The valves are configured to regulate a flow of the solids through the chemical loop.

Control and optimization system and method for chemical looping processes

DOEpatents

Lou, Xinsheng; Joshi, Abhinaya; Lei, Hao

2015-02-17

A control system for optimizing a chemical loop system includes one or more sensors for measuring one or more parameters in a chemical loop. The sensors are disposed on or in a conduit positioned in the chemical loop. The sensors generate one or more data signals representative of an amount of solids in the conduit. The control system includes a data acquisition system in communication with the sensors and a controller in communication with the data acquisition system. The data acquisition system receives the data signals and the controller generates the control signals. The controller is in communication with one or more valves positioned in the chemical loop. The valves are configured to regulate a flow of the solids through the chemical loop.

On Efficient Deployment of Wireless Sensors for Coverage and Connectivity in Constrained 3D Space.

PubMed

Wu, Chase Q; Wang, Li

2017-10-10

Sensor networks have been used in a rapidly increasing number of applications in many fields. This work generalizes a sensor deployment problem to place a minimum set of wireless sensors at candidate locations in constrained 3D space to k -cover a given set of target objects. By exhausting the combinations of discreteness/continuousness constraints on either sensor locations or target objects, we formulate four classes of sensor deployment problems in 3D space: deploy sensors at Discrete/Continuous Locations (D/CL) to cover Discrete/Continuous Targets (D/CT). We begin with the design of an approximate algorithm for DLDT and then reduce DLCT, CLDT, and CLCT to DLDT by discretizing continuous sensor locations or target objects into a set of divisions without sacrificing sensing precision. Furthermore, we consider a connected version of each problem where the deployed sensors must form a connected network, and design an approximation algorithm to minimize the number of deployed sensors with connectivity guarantee. For performance comparison, we design and implement an optimal solution and a genetic algorithm (GA)-based approach. Extensive simulation results show that the proposed deployment algorithms consistently outperform the GA-based heuristic and achieve a close-to-optimal performance in small-scale problem instances and a significantly superior overall performance than the theoretical upper bound.

Simulating optoelectronic systems for remote sensing with SENSOR

NASA Astrophysics Data System (ADS)

Boerner, Anko

2003-04-01

The consistent end-to-end simulation of airborne and spaceborne remote sensing systems is an important task and sometimes the only way for the adaptation and optimization of a sensor and its observation conditions, the choice and test of algorithms for data processing, error estimation and the evaluation of the capabilities of the whole sensor system. The presented software simulator SENSOR (Software ENvironment for the Simulation of Optical Remote sensing systems) includes a full model of the sensor hardware, the observed scene, and the atmosphere in between. It allows the simulation of a wide range of optoelectronic systems for remote sensing. The simulator consists of three parts. The first part describes the geometrical relations between scene, sun, and the remote sensing system using a ray tracing algorithm. The second part of the simulation environment considers the radiometry. It calculates the at-sensor radiance using a pre-calculated multidimensional lookup-table taking the atmospheric influence on the radiation into account. Part three consists of an optical and an electronic sensor model for the generation of digital images. Using SENSOR for an optimization requires the additional application of task-specific data processing algorithms. The principle of the end-to-end-simulation approach is explained, all relevant concepts of SENSOR are discussed, and examples of its use are given. The verification of SENSOR is demonstrated.

Design, fabrication, and optimization of photo acoustic gas sensor for the trace level detection of NO2 in the atmosphere.

PubMed

Gondal, Mohammed A; Dastageer, Mohamed A

2010-09-01

Photoacoustic (PA) gas sensor for the detection of hazardous NO(2) with detection limit as low as few part per billion by volume (ppbV) has been designed and tested with pulsed UV laser. Some design optimization factors such as the optimum cell geometry, buffer gas etc has been proposed. It was found that a cylindrical cell with many acoustic filters considerably dampens the noise level and also argon as a buffer gas improves the photoacoustic signal level and this combination substantially improved the signal to noise ratio and the limit of detection. Ambiguous decline of photo acoustic signal at higher NO(2) concentration due to the adsorption of NO(2) on the walls of the photoacoustic cells and the dependence of this effect on the buffer gases are also discussed. The PA signal dependence on incident laser energy for three cells was also investigated.

Study on Silicon Microstructure Processing Technology Based on Porous Silicon

NASA Astrophysics Data System (ADS)

Shang, Yingqi; Zhang, Linchao; Qi, Hong; Wu, Yalin; Zhang, Yan; Chen, Jing

2018-03-01

Aiming at the heterogeneity of micro - sealed cavity in silicon microstructure processing technology, the technique of preparing micro - sealed cavity of porous silicon is proposed. The effects of different solutions, different substrate doping concentrations, different current densities, and different etching times on the rate, porosity, thickness and morphology of the prepared porous silicon were studied. The porous silicon was prepared by different process parameters and the prepared porous silicon was tested and analyzed. For the test results, optimize the process parameters and experiments. The experimental results show that the porous silicon can be controlled by optimizing the parameters of the etching solution and the doping concentration of the substrate, and the preparation of porous silicon with different porosity can be realized by different doping concentration, so as to realize the preparation of silicon micro-sealed cavity, to solve the sensor sensitive micro-sealed cavity structure heterogeneous problem, greatly increasing the application of the sensor.

Piezoresistive Cantilever Performance—Part II: Optimization

PubMed Central

Park, Sung-Jin; Doll, Joseph C.; Rastegar, Ali J.; Pruitt, Beth L.

2010-01-01

Piezoresistive silicon cantilevers fabricated by ion implantation are frequently used for force, displacement, and chemical sensors due to their low cost and electronic readout. However, the design of piezoresistive cantilevers is not a straightforward problem due to coupling between the design parameters, constraints, process conditions, and performance. We systematically analyzed the effect of design and process parameters on force resolution and then developed an optimization approach to improve force resolution while satisfying various design constraints using simulation results. The combined simulation and optimization approach is extensible to other doping methods beyond ion implantation in principle. The optimization results were validated by fabricating cantilevers with the optimized conditions and characterizing their performance. The measurement results demonstrate that the analytical model accurately predicts force and displacement resolution, and sensitivity and noise tradeoff in optimal cantilever performance. We also performed a comparison between our optimization technique and existing models and demonstrated eight times improvement in force resolution over simplified models. PMID:20333323

The effects of optical sensor-tissue separation in endocavitary photoplethysmography.

PubMed

Patel, Zaibaa; Thaha, Mohamed A; Kyriacou, Panayiotis A

2018-06-12

<i>Objective:</i> Intestinal anastomotic failure that occurs mainly due to ischaemia is a serious risk in colorectal cancer patients undergoing surgery. Surgeons continue to rely on subjective methods such as visual inspection to assess intestinal viability during surgery and there are no clinical tools to directly monitor viability postoperatively. A dual wavelength, reflectance optical sensor has been developed for continuous and dynamic monitoring of intestinal viability via the intestinal lumen. Maintaining direct contact between the sensor and the inner intestinal wall can be difficult in an intraluminal design, therefore impacting on signal acquisition and quality. This paper investigates the effect of direct contact versus variable distances between the sensor and the tissue surface of the buccal mucosa as a surrogate. <i>Approach:</i> The <i>in-vivo</i> study involved 20 healthy volunteers to measure the effect of optical sensor-tissue distances on the ability to acquire photoplethysmography signals and their quality. Signals were acquired from the buccal mucosa at five optical sensor-tissue distances. <i>Main results:</i> Distances between 0 mm (contact) to 5 mm were the most optimal, producing signals of high quality and signal-to-noise ratio, resulting in reliable estimations of the blood oxygen saturation. Distances exceeding 5 mm compromised the acquired signals, and were of poor quality, thereby unreliably estimating the blood oxygen saturation. <i>Significance:</i> The developed optical sensor proved to be reliable for acquiring photoplethysmography signals for cases where distances between the optical sensor-tissue may arise during the assessment of intraluminal intestinal viability. © 2018 Institute of Physics and Engineering in Medicine.

Optimal placement of excitations and sensors for verification of large dynamical systems

NASA Technical Reports Server (NTRS)

Salama, M.; Rose, T.; Garba, J.

1987-01-01

The computationally difficult problem of the optimal placement of excitations and sensors to maximize the observed measurements is studied within the framework of combinatorial optimization, and is solved numerically using a variation of the simulated annealing heuristic algorithm. Results of numerical experiments including a square plate and a 960 degrees-of-freedom Control of Flexible Structure (COFS) truss structure, are presented. Though the algorithm produces suboptimal solutions, its generality and simplicity allow the treatment of complex dynamical systems which would otherwise be difficult to handle.

A facile electrochemical sensor for nonylphenol determination based on the enhancement effect of cetyltrimethylammonium bromide.

PubMed

Lu, Qing; Zhang, Weina; Wang, Zhihui; Yu, Guangxia; Yuan, Yuan; Zhou, Yikai

2013-01-07

A facile electrochemical sensor for the determination of nonylphenol (NP) was fabricated in this work. Cetyltrimethylammonium bromide (CTAB), which formed a bilayer on the surface of the carbon paste (CP) electrode, displayed a remarkable enhancement effect for the electrochemical oxidation of NP. Moreover, the oxidation peak current of NP at the CTAB/CP electrode demonstrated a linear relationship with NP concentration, which could be applied in the direct determination of NP. Some experimental parameters were investigated, such as external solution pH, mode and time of accumulation, concentration and modification time of CTAB and so on. Under optimized conditions, a wide linear range from 1.0 × 10(-7) mol·L(-1) to 2.5 × 10(-5) mol·L(-1) was obtained for the sensor, with a low limit of detection at 1.0 × 10(-8) mol·L(-1). Several distinguishing advantages of the as-prepared sensor, including facile fabrication, easy operation, low cost and so on, suggest a great potential for its practical applications.

Optimization-based channel constrained data aggregation routing algorithms in multi-radio wireless sensor networks.

PubMed

Yen, Hong-Hsu

2009-01-01

In wireless sensor networks, data aggregation routing could reduce the number of data transmissions so as to achieve energy efficient transmission. However, data aggregation introduces data retransmission that is caused by co-channel interference from neighboring sensor nodes. This kind of co-channel interference could result in extra energy consumption and significant latency from retransmission. This will jeopardize the benefits of data aggregation. One possible solution to circumvent data retransmission caused by co-channel interference is to assign different channels to every sensor node that is within each other's interference range on the data aggregation tree. By associating each radio with a different channel, a sensor node could receive data from all the children nodes on the data aggregation tree simultaneously. This could reduce the latency from the data source nodes back to the sink so as to meet the user's delay QoS. Since the number of radios on each sensor node and the number of non-overlapping channels are all limited resources in wireless sensor networks, a challenging question here is to minimize the total transmission cost under limited number of non-overlapping channels in multi-radio wireless sensor networks. This channel constrained data aggregation routing problem in multi-radio wireless sensor networks is an NP-hard problem. I first model this problem as a mixed integer and linear programming problem where the objective is to minimize the total transmission subject to the data aggregation routing, channel and radio resources constraints. The solution approach is based on the Lagrangean relaxation technique to relax some constraints into the objective function and then to derive a set of independent subproblems. By optimally solving these subproblems, it can not only calculate the lower bound of the original primal problem but also provide useful information to get the primal feasible solutions. By incorporating these Lagrangean multipliers as the link arc weight, the optimization-based heuristics are proposed to get energy-efficient data aggregation tree with better resource (channel and radio) utilization. From the computational experiments, the proposed optimization-based approach is superior to existing heuristics under all tested cases.

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.

Plenoptic camera wavefront sensing with extended sources

NASA Astrophysics Data System (ADS)

Jiang, Pengzhi; Xu, Jieping; Liang, Yonghui; Mao, Hongjun

2016-09-01

The wavefront sensor is used in adaptive optics to detect the atmospheric distortion, which feeds back to the deformable mirror to compensate for this distortion. Different from the Shack-Hartmann sensor that has been widely used with point sources, the plenoptic camera wavefront sensor has been proposed as an alternative wavefront sensor adequate for extended objects in recent years. In this paper, the plenoptic camera wavefront sensing with extended sources is discussed systematically. Simulations are performed to investigate the wavefront measurement error and the closed-loop performance of the plenoptic sensor. The results show that there are an optimal lenslet size and an optimal number of pixels to make the best performance. The RMS of the resulting corrected wavefront in closed-loop adaptive optics system is less than 108 nm (0.2λ) when D/r0 ≤ 10 and the magnitude M ≤ 5. Our investigation indicates that the plenoptic sensor is efficient to operate on extended sources in the closed-loop adaptive optics system.

Optimal active vibration absorber: Design and experimental results

NASA Technical Reports Server (NTRS)

Lee-Glauser, Gina; Juang, Jer-Nan; Sulla, Jeffrey L.

1992-01-01

An optimal active vibration absorber can provide guaranteed closed-loop stability and control for large flexible space structures with collocated sensors/actuators. The active vibration absorber is a second-order dynamic system which is designed to suppress any unwanted structural vibration. This can be designed with minimum knowledge of the controlled system. Two methods for optimizing the active vibration absorber parameters are illustrated: minimum resonant amplitude and frequency matched active controllers. The Controls-Structures Interaction Phase-1 Evolutionary Model at NASA LaRC is used to demonstrate the effectiveness of the active vibration absorber for vibration suppression. Performance is compared numerically and experimentally using acceleration feedback.

Non-destructive evaluation of laminated composite plates using dielectrometry sensors

NASA Astrophysics Data System (ADS)

Nassr, Amr A.; El-Dakhakhni, Wael W.

2009-05-01

The use of composite materials in marine, aerospace and automotive applications is increasing; however, several kinds of damages of composite materials may influence its durability and future applications. In this paper, a methodology was presented for damage detection of laminated composite plates using dielectrometry sensors. The presence of damage in the laminated composite plate leads to changes in its dielectric characteristics, causing variation in the measured capacitance by the sensors. An analytical model was used to analyse the influence of different sensor parameters on the output signals and to optimize sensor design. Two-dimensional finite element (FE) simulations were performed to assess the validity of the analytical results and to evaluate other sensor design-related parameters. To experimentally verify the model, the dielectric permittivity of the composite plate was measured. In addition, a glass fibre reinforced polymer (GFRP) laminated plate containing pre-fabricated slots through its thickness to simulate delamination and water intrusion defects was inspected in a laboratory setting. Excellent agreements were found between the experimental capacitance response signals and those predicated from the FE simulations. This cost-effective technique can be used for rapid damage screening, regular scheduled inspection, or as a permanent sensor network within the composite system.

Sensor Placement Optimization using Chama

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

Klise, Katherine A.; Nicholson, Bethany L.; Laird, Carl Damon

Continuous or regularly scheduled monitoring has the potential to quickly identify changes in the environment. However, even with low - cost sensors, only a limited number of sensors can be deployed. The physical placement of these sensors, along with the sensor technology and operating conditions, can have a large impact on the performance of a monitoring strategy. Chama is an open source Python package which includes mixed - integer, stochastic programming formulations to determine sensor locations and technology that maximize monitoring effectiveness. The methods in Chama are general and can be applied to a wide range of applications. Chama ismore » currently being used to design sensor networks to monitor airborne pollutants and to monitor water quality in water distribution systems. The following documentation includes installation instructions and examples, description of software features, and software license. The software is intended to be used by regulatory agencies, industry, and the research community. It is assumed that the reader is familiar with the Python Programming Language. References are included for addit ional background on software components. Online documentation, hosted at http://chama.readthedocs.io/, will be updated as new features are added. The online version includes API documentation .« less

Methods and Piezoelectric Imbedded Sensors for Damage Detection in Composite Plates Under Ambient and Cryogenic Conditions

NASA Technical Reports Server (NTRS)

Engberg, Robert; Ooi, Teng K.

2004-01-01

New methods for structural health monitoring are being assessed, especially in high-performance, extreme environment, safety-critical applications. One such application is for composite cryogenic fuel tanks. The work presented here attempts to characterize and investigate the feasibility of using imbedded piezoelectric sensors to detect cracks and delaminations under cryogenic and ambient conditions. A variety of damage detection methods and different Sensors are employed in the different composite plate samples to aid in determining an optimal algorithm, sensor placement strategy, and type of imbedded sensor to use. Variations of frequency, impedance measurements, and pulse echoing techniques of the sensors are employed and compared. Statistical and analytic techniques are then used to determine which method is most desirable for a specific type of damage. These results are furthermore compared with previous work using externally mounted sensors. Results and optimized methods from this work can then be incorporated into a larger composite structure to validate and assess its structural health. This could prove to be important in the development and qualification of any 2" generation reusable launch vehicle using composites as a structural element.