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.

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

NASA Astrophysics Data System (ADS)

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

2010-04-01

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

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.

System for estimating fatigue damage

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

LeMonds, Jeffrey; Guzzo, Judith Ann; Liu, Shaopeng

In one aspect, a system for estimating fatigue damage in a riser string is provided. The system includes a plurality of accelerometers which can be deployed along a riser string and a communications link to transmit accelerometer data from the plurality of accelerometers to one or more data processors in real time. With data from a limited number of accelerometers located at sensor locations, the system estimates an optimized current profile along the entire length of the riser including riser locations where no accelerometer is present. The optimized current profile is then used to estimate damage rates to individual risermore » components and to update a total accumulated damage to individual riser components. The number of sensor locations is small relative to the length of a deepwater riser string, and a riser string several miles long can be reliably monitored along its entire length by fewer than twenty sensor locations.« less

Optimizing a Sensor Network with Data from Hazard Mapping Demonstrated in a Heavy-Vehicle Manufacturing Facility.

PubMed

Berman, Jesse D; Peters, Thomas M; Koehler, Kirsten A

2018-05-28

To design a method that uses preliminary hazard mapping data to optimize the number and location of sensors within a network for a long-term assessment of occupational concentrations, while preserving temporal variability, accuracy, and precision of predicted hazards. Particle number concentrations (PNCs) and respirable mass concentrations (RMCs) were measured with direct-reading instruments in a large heavy-vehicle manufacturing facility at 80-82 locations during 7 mapping events, stratified by day and season. Using kriged hazard mapping, a statistical approach identified optimal orders for removing locations to capture temporal variability and high prediction precision of PNC and RMC concentrations. We compared optimal-removal, random-removal, and least-optimal-removal orders to bound prediction performance. The temporal variability of PNC was found to be higher than RMC with low correlation between the two particulate metrics (ρ = 0.30). Optimal-removal orders resulted in more accurate PNC kriged estimates (root mean square error [RMSE] = 49.2) at sample locations compared with random-removal order (RMSE = 55.7). For estimates at locations having concentrations in the upper 10th percentile, the optimal-removal order preserved average estimated concentrations better than random- or least-optimal-removal orders (P < 0.01). However, estimated average concentrations using an optimal-removal were not statistically different than random-removal when averaged over the entire facility. No statistical difference was observed for optimal- and random-removal methods for RMCs that were less variable in time and space than PNCs. Optimized removal performed better than random-removal in preserving high temporal variability and accuracy of hazard map for PNC, but not for the more spatially homogeneous RMC. These results can be used to reduce the number of locations used in a network of static sensors for long-term monitoring of hazards in the workplace, without sacrificing prediction performance.

Choosing Sensor Configuration for a Flexible Structure Using Full Control Synthesis

NASA Technical Reports Server (NTRS)

Lind, Rick; Nalbantoglu, Volkan; Balas, Gary

1997-01-01

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

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

Optical Sensor/Actuator Locations for Active Structural Acoustic Control

NASA Technical Reports Server (NTRS)

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

1998-01-01

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

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

Optimal sensor locations for the backward Lagrangian stochastic technique in measuring lagoon gas emission

USDA-ARS?s Scientific Manuscript database

This study evaluated the impact of gas concentration and wind sensor locations on the accuracy of the backward Lagrangian stochastic inverse-dispersion technique (bLS) for measuring gas emission rates from a typical lagoon environment. Path-integrated concentrations (PICs) and 3-dimensional (3D) wi...

Surveillance versus Reconnaissance: An Entropy Based Model

DTIC Science & Technology

2012-03-22

sensor detection since no new information is received. (Berry, Pontecorvo, & Fogg , Optimal Search, Location and Tracking of Surface Maritime Targets by...by Berry, Pontecorvo and Fogg (Berry, Pontecorvo, & Fogg , July, 2003) facilitates the optimal solutions to dynamically determining the allocation and...region (Berry, Pontecorvo, & Fogg , July, 2003). Phase II: Locate During the locate phase, the objective was to determine the location of the targets

Trip optimization system and method for a train

DOEpatents

Kumar, Ajith Kuttannair; Shaffer, Glenn Robert; Houpt, Paul Kenneth; Movsichoff, Bernardo Adrian; Chan, David So Keung

2017-08-15

A system for operating a train having one or more locomotive consists with each locomotive consist comprising one or more locomotives, the system including a locator element to determine a location of the train, a track characterization element to provide information about a track, a sensor for measuring an operating condition of the locomotive consist, a processor operable to receive information from the locator element, the track characterizing element, and the sensor, and an algorithm embodied within the processor having access to the information to create a trip plan that optimizes performance of the locomotive consist in accordance with one or more operational criteria for the train.

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

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.

Moving target tracking through distributed clustering in directional sensor networks.

PubMed

Enayet, Asma; Razzaque, Md Abdur; Hassan, Mohammad Mehedi; Almogren, Ahmad; Alamri, Atif

2014-12-18

The problem of moving target tracking in directional sensor networks (DSNs) introduces new research challenges, including optimal selection of sensing and communication sectors of the directional sensor nodes, determination of the precise location of the target and an energy-efficient data collection mechanism. Existing solutions allow individual sensor nodes to detect the target's location through collaboration among neighboring nodes, where most of the sensors are activated and communicate with the sink. Therefore, they incur much overhead, loss of energy and reduced target tracking accuracy. In this paper, we have proposed a clustering algorithm, where distributed cluster heads coordinate their member nodes in optimizing the active sensing and communication directions of the nodes, precisely determining the target location by aggregating reported sensing data from multiple nodes and transferring the resultant location information to the sink. Thus, the proposed target tracking mechanism minimizes the sensing redundancy and maximizes the number of sleeping nodes in the network. We have also investigated the dynamic approach of activating sleeping nodes on-demand so that the moving target tracking accuracy can be enhanced while maximizing the network lifetime. We have carried out our extensive simulations in ns-3, and the results show that the proposed mechanism achieves higher performance compared to the state-of-the-art works.

Moving Target Tracking through Distributed Clustering in Directional Sensor Networks

PubMed Central

Enayet, Asma; Razzaque, Md. Abdur; Hassan, Mohammad Mehedi; Almogren, Ahmad; Alamri, Atif

2014-01-01

The problem of moving target tracking in directional sensor networks (DSNs) introduces new research challenges, including optimal selection of sensing and communication sectors of the directional sensor nodes, determination of the precise location of the target and an energy-efficient data collection mechanism. Existing solutions allow individual sensor nodes to detect the target's location through collaboration among neighboring nodes, where most of the sensors are activated and communicate with the sink. Therefore, they incur much overhead, loss of energy and reduced target tracking accuracy. In this paper, we have proposed a clustering algorithm, where distributed cluster heads coordinate their member nodes in optimizing the active sensing and communication directions of the nodes, precisely determining the target location by aggregating reported sensing data from multiple nodes and transferring the resultant location information to the sink. Thus, the proposed target tracking mechanism minimizes the sensing redundancy and maximizes the number of sleeping nodes in the network. We have also investigated the dynamic approach of activating sleeping nodes on-demand so that the moving target tracking accuracy can be enhanced while maximizing the network lifetime. We have carried out our extensive simulations in ns-3, and the results show that the proposed mechanism achieves higher performance compared to the state-of-the-art works. PMID:25529205

An FBG acoustic emission source locating system based on PHAT and GA

NASA Astrophysics Data System (ADS)

Shen, Jing-shi; Zeng, Xiao-dong; Li, Wei; Jiang, Ming-shun

2017-09-01

Using the acoustic emission locating technology to monitor the health of the structure is important for ensuring the continuous and healthy operation of the complex engineering structures and large mechanical equipment. In this paper, four fiber Bragg grating (FBG) sensors are used to establish the sensor array to locate the acoustic emission source. Firstly, the nonlinear locating equations are established based on the principle of acoustic emission, and the solution of these equations is transformed into an optimization problem. Secondly, time difference extraction algorithm based on the phase transform (PHAT) weighted generalized cross correlation provides the necessary conditions for the accurate localization. Finally, the genetic algorithm (GA) is used to solve the optimization model. In this paper, twenty points are tested in the marble plate surface, and the results show that the absolute locating error is within the range of 10 mm, which proves the accuracy of this locating method.

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

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.

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

Ding, Fei; Jiang, Huaiguang; Tan, Jin

This paper proposes an event-driven approach for reconfiguring distribution systems automatically. Specifically, an optimal synchrophasor sensor placement (OSSP) is used to reduce the number of synchrophasor sensors while keeping the whole system observable. Then, a wavelet-based event detection and location approach is used to detect and locate the event, which performs as a trigger for network reconfiguration. With the detected information, the system is then reconfigured using the hierarchical decentralized approach to seek for the new optimal topology. In this manner, whenever an event happens the distribution network can be reconfigured automatically based on the real-time information that is observablemore » and detectable.« less

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.

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.

Operational load estimation of a smart wind turbine rotor blade

NASA Astrophysics Data System (ADS)

White, Jonathan R.; Adams, Douglas E.; Rumsey, Mark A.

2009-03-01

Rising energy prices and carbon emission standards are driving a fundamental shift from fossil fuels to alternative sources of energy such as biofuel, solar, wind, clean coal and nuclear. In 2008, the U.S. installed 8,358 MW of new wind capacity increasing the total installed wind power by 50% to 25,170 MW. A key technology to improve the efficiency of wind turbines is smart rotor blades that can monitor the physical loads being applied by the wind and then adapt the airfoil for increased energy capture. For extreme wind and gust events, the airfoil could be changed to reduce the loads to prevent excessive fatigue or catastrophic failure. Knowledge of the actual loading to the turbine is also useful for maintenance planning and design improvements. In this work, an array of uniaxial and triaxial accelerometers was integrally manufactured into a 9m smart rotor blade. DC type accelerometers were utilized in order to estimate the loading and deflection from both quasi-steady-state and dynamic events. A method is presented that designs an estimator of the rotor blade static deflection and loading and then optimizes the placement of the sensor(s). Example results show that the method can identify the optimal location for the sensor for both simple example cases and realistic complex loading. The optimal location of a single sensor shifts towards the tip as the curvature of the blade deflection increases with increasingly complex wind loading. The framework developed is practical for the expansion of sensor optimization in more complex blade models and for higher numbers of sensors.

A 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.

Strategy Developed for Selecting Optimal Sensors for Monitoring Engine Health

NASA Technical Reports Server (NTRS)

2004-01-01

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

Design and development of a wireless sensor network to monitor snow depth in multiple catchments in the American River basin, California: hardware selection and sensor placement techniques

NASA Astrophysics Data System (ADS)

Kerkez, B.; Rice, R.; Glaser, S. D.; Bales, R. C.; Saksa, P. C.

2010-12-01

A 100-node wireless sensor network (WSN) was designed for the purpose of monitoring snow depth in two watersheds, spanning 3 km2 in the American River basin, in the central Sierra Nevada of California. The network will be deployed as a prototype project that will become a core element of a larger water information system for the Sierra Nevada. The site conditions range from mid-elevation forested areas to sub-alpine terrain with light forest cover. Extreme temperature and humidity fluctuations, along with heavy rain and snowfall events, create particularly challenging conditions for wireless communications. We show how statistics gathered from a previously deployed 60-node WSN, located in the Southern Sierra Critical Zone Observatory, were used to inform design. We adapted robust network hardware, manufactured by Dust Networks for highly demanding industrial monitoring, and added linear amplifiers to the radios to improve transmission distances. We also designed a custom data-logging board to interface the WSN hardware with snow-depth sensors. Due to the large distance between sensing locations, and complexity of terrain, we analyzed network statistics to select the location of repeater nodes, to create a redundant and reliable mesh. This optimized network topology will maximize transmission distances, while ensuring power-efficient network operations throughout harsh winter conditions. At least 30 of the 100 nodes will actively sense snow depth, while the remainder will act as sensor-ready repeaters in the mesh. Data from a previously conducted snow survey was used to create a Gaussian Process model of snow depth; variance estimates produced by this model were used to suggest near-optimal locations for snow-depth sensors to measure the variability across a 1 km2 grid. We compare the locations selected by the sensor placement algorithm to those made through expert opinion, and offer explanations for differences resulting from each approach.

Image processing occupancy sensor

DOEpatents

Brackney, Larry J.

2016-09-27

A system and method of detecting occupants in a building automation system environment using image based occupancy detection and position determinations. In one example, the system includes an image processing occupancy sensor that detects the number and position of occupants within a space that has controllable building elements such as lighting and ventilation diffusers. Based on the position and location of the occupants, the system can finely control the elements to optimize conditions for the occupants, optimize energy usage, among other advantages.

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.

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.

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.

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.

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

Optimizing placements of ground-based snow sensors for areal snow cover estimation using a machine-learning algorithm and melt-season snow-LiDAR data

NASA Astrophysics Data System (ADS)

Oroza, C.; Zheng, Z.; Glaser, S. D.; Bales, R. C.; Conklin, M. H.

2016-12-01

We present a structured, analytical approach to optimize ground-sensor placements based on time-series remotely sensed (LiDAR) data and machine-learning algorithms. We focused on catchments within the Merced and Tuolumne river basins, covered by the JPL Airborne Snow Observatory LiDAR program. First, we used a Gaussian mixture model to identify representative sensor locations in the space of independent variables for each catchment. Multiple independent variables that govern the distribution of snow depth were used, including elevation, slope, and aspect. Second, we used a Gaussian process to estimate the areal distribution of snow depth from the initial set of measurements. This is a covariance-based model that also estimates the areal distribution of model uncertainty based on the independent variable weights and autocorrelation. The uncertainty raster was used to strategically add sensors to minimize model uncertainty. We assessed the temporal accuracy of the method using LiDAR-derived snow-depth rasters collected in water-year 2014. In each area, optimal sensor placements were determined using the first available snow raster for the year. The accuracy in the remaining LiDAR surveys was compared to 100 configurations of sensors selected at random. We found the accuracy of the model from the proposed placements to be higher and more consistent in each remaining survey than the average random configuration. We found that a relatively small number of sensors can be used to accurately reproduce the spatial patterns of snow depth across the basins, when placed using spatial snow data. Our approach also simplifies sensor placement. At present, field surveys are required to identify representative locations for such networks, a process that is labor intensive and provides limited guarantees on the networks' representation of catchment independent variables.

On localizing a capsule endoscope using magnetic sensors.

PubMed

Moussakhani, Babak; Ramstad, Tor; Flåm, John T; Balasingham, Ilangko

2012-01-01

In this work, localizing a capsule endoscope within the gastrointestinal tract is addressed. It is assumed that the capsule is equipped with a magnet, and that a magnetic sensor network measures the flux from this magnet. We assume no prior knowledge on the source location, and that the measurements collected by the sensors are corrupted by thermal Gaussian noise only. Under these assumptions, we focus on determining the Cramer-Rao Lower Bound (CRLB) for the location of the endoscope. Thus, we are not studying specific estimators, but rather the theoretical performance of an optimal one. It is demonstrated that the CRLB is a function of the distance and angle between the sensor network and the magnet. By studying the CRLB with respect to different sensor array constellations, we are able to indicate favorable constellations.

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.

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.

THREAT ENSEMBLE VULNERABILITY ASSESSMENT ...

EPA Pesticide Factsheets

software and manual TEVA-SPOT is used by water utilities to optimize the number and location of contamination detection sensors so that economic and/or public health consequences are minimized. TEVA-SPOT is interactive, allowing a user to specify the minimization objective (e.g., the number of people exposed, the time to detection, or the extent of pipe length contaminated). It also allows a user to specify constraints. For example, a TEVA-SPOT user can employ expert knowledge during the design process by identifying either existing or unfeasible sensor locations. Installation and maintenance costs for sensor placement can also be factored into the analysis. Python and Java are required to run TEVA-SPOT

Low frequency seismic noise acquisition and analysis with tunable monolithic horizontal sensors

NASA Astrophysics Data System (ADS)

Acernese, Fausto; De Rosa, Rosario; Giordano, Gerardo; Romano, Rocco; Vilasi, Silvia; Barone, Fabrizio

2011-04-01

In this paper we describe the scientific data recorded mechanical monolithic horizontal sensor prototypes located in the Gran Sasso Laboratory of the INFN. The mechanical monolithic sensors, developed at the University of Salerno, are placed, in thermally insulating enclosures, onto concrete slabs connected to the bedrock. The main goal of this experiment is to characterize seismically the sites in the frequency band 10-4 ÷ 10Hz and to get all the necessary information to optimize the sensor.

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

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

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.

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

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.

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.

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.

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

Assessment of water quality monitoring for the optimal sensor placement in lake Yahuarcocha using pattern recognition techniques and geographical information systems.

PubMed

Jácome, Gabriel; Valarezo, Carla; Yoo, Changkyoo

2018-03-30

Pollution and the eutrophication process are increasing in lake Yahuarcocha and constant water quality monitoring is essential for a better understanding of the patterns occurring in this ecosystem. In this study, key sensor locations were determined using spatial and temporal analyses combined with geographical information systems (GIS) to assess the influence of weather features, anthropogenic activities, and other non-point pollution sources. A water quality monitoring network was established to obtain data on 14 physicochemical and microbiological parameters at each of seven sample sites over a period of 13 months. A spatial and temporal statistical approach using pattern recognition techniques, such as cluster analysis (CA) and discriminant analysis (DA), was employed to classify and identify the most important water quality parameters in the lake. The original monitoring network was reduced to four optimal sensor locations based on a fuzzy overlay of the interpolations of concentration variations of the most important parameters.

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

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.

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

A Bayesian Approach for Sensor Optimisation in Impact Identification

PubMed Central

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

2016-01-01

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

Image Processing Occupancy Sensor

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

The Image Processing Occupancy Sensor, or IPOS, is a novel sensor technology developed at the National Renewable Energy Laboratory (NREL). The sensor is based on low-cost embedded microprocessors widely used by the smartphone industry and leverages mature open-source computer vision software libraries. Compared to traditional passive infrared and ultrasonic-based motion sensors currently used for occupancy detection, IPOS has shown the potential for improved accuracy and a richer set of feedback signals for occupant-optimized lighting, daylighting, temperature setback, ventilation control, and other occupancy and location-based uses. Unlike traditional passive infrared (PIR) or ultrasonic occupancy sensors, which infer occupancy based only onmore » motion, IPOS uses digital image-based analysis to detect and classify various aspects of occupancy, including the presence of occupants regardless of motion, their number, location, and activity levels of occupants, as well as the illuminance properties of the monitored space. The IPOS software leverages the recent availability of low-cost embedded computing platforms, computer vision software libraries, and camera elements.« less

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

NASA Astrophysics Data System (ADS)

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

2011-06-01

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

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.

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

PubMed

Luo, Junhai; Fan, Liying

2017-03-30

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

Location identification for indoor instantaneous point contaminant source by probability-based inverse Computational Fluid Dynamics modeling.

PubMed

Liu, X; Zhai, Z

2008-02-01

Indoor pollutions jeopardize human health and welfare and may even cause serious morbidity and mortality under extreme conditions. To effectively control and improve indoor environment quality requires immediate interpretation of pollutant sensor readings and accurate identification of indoor pollution history and source characteristics (e.g. source location and release time). This procedure is complicated by non-uniform and dynamic contaminant indoor dispersion behaviors as well as diverse sensor network distributions. This paper introduces a probability concept based inverse modeling method that is able to identify the source location for an instantaneous point source placed in an enclosed environment with known source release time. The study presents the mathematical models that address three different sensing scenarios: sensors without concentration readings, sensors with spatial concentration readings, and sensors with temporal concentration readings. The paper demonstrates the inverse modeling method and algorithm with two case studies: air pollution in an office space and in an aircraft cabin. The predictions were successfully verified against the forward simulation settings, indicating good capability of the method in finding indoor pollutant sources. The research lays a solid ground for further study of the method for more complicated indoor contamination problems. The method developed can help track indoor contaminant source location with limited sensor outputs. This will ensure an effective and prompt execution of building control strategies and thus achieve a healthy and safe indoor environment. The method can also assist the design of optimal sensor networks.

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

PubMed Central

Luo, Junhai; Fan, Liying

2017-01-01

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

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.

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.

The Optimal Location of GEODSS Sensors in Canada

DTIC Science & Technology

1991-02-01

nteractive procedures for solving multiobjective transportation problems. A transportation problem is a classical linear programming problem where a...product must be transported from each of m sources to any of n destinations such that one or more objectives are optimized (36:96). The first algorithm...0, k - 1,...,L where z, is the fth element of zk The function z’(x) can now be optimized using any efficient, single-objectivc transportation

Localized Temperature Variations in Laser-Irradiated Composites with Embedded Fiber Bragg Grating Sensors.

PubMed

Jenkins, R Brian; Joyce, Peter; Mechtel, Deborah

2017-01-27

Fiber Bragg grating (FBG) temperature sensors are embedded in composites to detect localized temperature gradients resulting from high energy infrared laser radiation. The goal is to detect the presence of radiation on a composite structure as rapidly as possible and to identify its location, much the same way human skin senses heat. A secondary goal is to determine how a network of sensors can be optimized to detect thermal damage in laser-irradiated composite materials or structures. Initial tests are conducted on polymer matrix composites reinforced with either carbon or glass fiber with a single optical fiber embedded into each specimen. As many as three sensors in each optical fiber measure the temporal and spatial thermal response of the composite to high energy radiation incident on the surface. Additional tests use a 2 × 2 × 3 array of 12 sensors embedded in a carbon fiber/epoxy composite to simultaneously measure temperature variations at locations on the composite surface and through the thickness. Results indicate that FBGs can be used to rapidly detect temperature gradients in a composite and their location, even for a direct strike of laser radiation on a sensor, when high temperatures can cause a non-uniform thermal response and FBG decay.

Localized Temperature Variations in Laser-Irradiated Composites with Embedded Fiber Bragg Grating Sensors

PubMed Central

Jenkins, R. Brian; Joyce, Peter; Mechtel, Deborah

2017-01-01

Fiber Bragg grating (FBG) temperature sensors are embedded in composites to detect localized temperature gradients resulting from high energy infrared laser radiation. The goal is to detect the presence of radiation on a composite structure as rapidly as possible and to identify its location, much the same way human skin senses heat. A secondary goal is to determine how a network of sensors can be optimized to detect thermal damage in laser-irradiated composite materials or structures. Initial tests are conducted on polymer matrix composites reinforced with either carbon or glass fiber with a single optical fiber embedded into each specimen. As many as three sensors in each optical fiber measure the temporal and spatial thermal response of the composite to high energy radiation incident on the surface. Additional tests use a 2 × 2 × 3 array of 12 sensors embedded in a carbon fiber/epoxy composite to simultaneously measure temperature variations at locations on the composite surface and through the thickness. Results indicate that FBGs can be used to rapidly detect temperature gradients in a composite and their location, even for a direct strike of laser radiation on a sensor, when high temperatures can cause a non-uniform thermal response and FBG decay. PMID:28134815

Optimizing sensor cover energy for directional sensors

NASA Astrophysics Data System (ADS)

Astorino, Annabella; Gaudioso, Manlio; Miglionico, Giovanna

2016-10-01

The Directional Sensors Continuous Coverage Problem (DSCCP) aims at covering a given set of targets in a plane by means of a set of directional sensors. The location of these sensors is known in advance and they are characterized by a discrete set of possible radii and aperture angles. Decisions to be made are about orientation (which in our approach can vary continuously), radius and aperture angle of each sensor. The objective is to get a minimum cost coverage of all targets, if any. We introduce a MINLP formulation of the problem and define a Lagrangian heuristics based on a dual ascent procedure operating on one multiplier at a time. Finally we report the results of the implementation of the method on a set of test problems.

An Energy-Efficient Target-Tracking Strategy for Mobile Sensor Networks.

PubMed

Mahboubi, Hamid; Masoudimansour, Walid; Aghdam, Amir G; Sayrafian-Pour, Kamran

2017-02-01

In this paper, an energy-efficient strategy is proposed for tracking a moving target in an environment with obstacles, using a network of mobile sensors. Typically, the most dominant sources of energy consumption in a mobile sensor network are sensing, communication, and movement. The proposed algorithm first divides the field into a grid of sufficiently small cells. The grid is then represented by a graph whose edges are properly weighted to reflect the energy consumption of sensors. The proposed technique searches for near-optimal locations for the sensors in different time instants to route information from the target to destination, using a shortest path algorithm. Simulations confirm the efficacy of the proposed algorithm.

Improving the Forecast Accuracy of an Ocean Observation and Prediction System by Adaptive Control of the Sensor Network

NASA Astrophysics Data System (ADS)

Talukder, A.; Panangadan, A. V.; Blumberg, A. F.; Herrington, T.; Georgas, N.

2008-12-01

The New York Harbor Observation and Prediction System (NYHOPS) is a real-time, estuarine and coastal ocean observing and modeling system for the New York Harbor and surrounding waters. Real-time measurements from in-situ mobile and stationary sensors in the NYHOPS networks are assimilated into marine forecasts in order to reduce the discrepancy with ground truth. The forecasts are obtained from the ECOMSED hydrodynamic model, a shallow water derivative of the Princeton Ocean Model. Currently, all sensors in the NYHOPS system are operated in a fixed mode with uniform sampling rates. This technology infusion effort demonstrates the use of Model Predictive Control (MPC) to autonomously adapt the operation of both mobile and stationary sensors in response to changing events that are -automatically detected from the ECOMSED forecasts. The controller focuses sensing resources on those regions that are expected to be impacted by the detected events. The MPC approach involves formulating the problem of calculating the optimal sensor parameters as a constrained multi-objective optimization problem. We have developed an objective function that takes into account the spatiotemporal relationship of the in-situ sensor locations and the locations of events detected by the model. Experiments in simulation were carried out using data collected during a freshwater flooding event. The location of the resulting freshwater plume was calculated from the corresponding model forecasts and was used by the MPC controller to derive control parameters for the sensing assets. The operational parameters that are controlled include the sampling rates of stationary sensors, paths of unmanned underwater vehicles (UUVs), and data transfer routes between sensors and the central modeling computer. The simulation experiments show that MPC-based sensor control reduces the RMS error in the forecast by a factor of 380% as compared to uniform sampling. The paths of multiple UUVs were simultaneously calculated such that measurements from on-board sensors would lead to maximal reduction in the forecast error after data assimilation. The MPC controller also reduces the consumption of system resources such as energy expended in sampling and wireless communication. The MPC-based control approach can be generalized to accept data from remote sensing satellites. This will enable in-situ sensors to be regulated using forecasts generated by assimilating local high resolution in-situ measurements with wide-area observations from remote sensing satellites.

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.

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.

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

Estimating Snow Water Equivalent over the American River in the Sierra Nevada Basin Using Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Welch, S. C.; Kerkez, B.; Glaser, S. D.; Bales, R. C.; Rice, R.

2011-12-01

We have designed a basin-scale (>2000 km2) instrument cluster, made up of 20 local-scale (1-km footprint) wireless sensor networks (WSNs), to measure patterns of snow depth and snow water equivalent (SWE) across the main snowmelt producing area within the American River basin. Each of the 20 WSNs has on the order of 25 wireless nodes, with over 10 nodes actively sensing snow depth, and thus snow accumulation and melt. When combined with existing snow density measurements and full-basin satellite snowcover data, these measurements are designed to provide dense ground-truth snow properties for research and real-time SWE for water management. The design of this large-scale network is based on rigorous testing of previous, smaller-scale studies, permitting for the development of methods to significantly, and efficiently scale up network operations. Recent advances in WSN technology have resulted in a modularized strategy that permits rapid future network deployment. To select network and sensor locations, various sensor placement approaches were compared, including random placement, placement of WSNs in locations that have captured the historical basin mean, as well as a placement algorithm leveraging the covariance structure of the SWE distribution. We show that that the optimal network locations do not exhibit a uniform grid, but rather follow strategic patterns based on physiographic terrain parameters. Uncertainty estimates are also provided to assess the confidence in the placement approach. To ensure near-optimal coverage of the full basin, we validated each placement approach with a multi-year record of SWE derived from reconstruction of historical satellite measurements.

The Impact of Model Uncertainty on Spatial Compensation in Active Structural Acoustic Control

NASA Technical Reports Server (NTRS)

Cabell, Randolph H.; Gibbs, Gary P.; Sprofera, Joseph D.; Clark, Robert L.

2004-01-01

Turbulent boundary layer (TBL) noise is considered a primary factor in the interior noise experienced by passengers aboard commercial airliners. There have been numerous investigations of interior noise control devoted to aircraft panels; however, practical realization is a challenge since the physical boundary conditions are uncertain at best. In most prior studies, pinned or clamped boundary conditions have been assumed; however, realistic panels likely display a range of varying boundary conditions between these two limits. Uncertainty in boundary conditions is a challenge for control system designers, both in terms of the compensator implemented and the location of actuators and sensors required to achieve the desired control. The impact of model uncertainties, uncertain boundary conditions in particular, on the selection of actuator and sensor locations for structural acoustic control are considered herein. Results from this research effort indicate that it is possible to optimize the design of actuator and sensor location and aperture, which minimizes the impact of boundary conditions on the desired structural acoustic control.

Optimization of the Hartmann-Shack microlens array

NASA Astrophysics Data System (ADS)

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

2011-04-01

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

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.

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.

Global Radius of Curvature Estimation and Control System for Segmented Mirrors

NASA Technical Reports Server (NTRS)

Rakoczy, John M. (Inventor)

2006-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

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

NASA Technical Reports Server (NTRS)

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

1984-01-01

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

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

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.

Using Impact Modulation to Identify Loose Bolts on a Satellite

DTIC Science & Technology

2011-10-21

for public release; distribution is unlimited the literature to be an effective damage detection method for cracks, delamination, and fatigue in...to identify loose bolts and fatigue damage using optimized sensor locations using a Support Vector Machines algorithm to classify the dam- age. Finally...48] did preliminary work which showed that VM is effective in detecting fatigue cracks in engineering components despite changes in actuator location

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

Experimental and theoretical investigation of the precise transduction mechanism in giant magnetoresistive biosensors

PubMed Central

Lee, Jung-Rok; Sato, Noriyuki; Bechstein, Daniel J. B.; Osterfeld, Sebastian J.; Wang, Junyi; Gani, Adi Wijaya; Hall, Drew A.; Wang, Shan X.

2016-01-01

Giant magnetoresistive (GMR) biosensors consisting of many rectangular stripes are being developed for high sensitivity medical diagnostics of diseases at early stages, but many aspects of the sensing mechanism remain to be clarified. Using e-beam patterned masks on the sensors, we showed that the magnetic nanoparticles with a diameter of 50 nm located between the stripes predominantly determine the sensor signals over those located on the sensor stripes. Based on computational analysis, it was confirmed that the particles in the trench, particularly those near the edges of the stripes, mainly affect the sensor signals due to additional field from the stripe under an applied field. We also demonstrated that the direction of the average magnetic field from the particles that contributes to the signal is indeed the same as that of the applied field, indicating that the particles in the trench are pivotal to produce sensor signal. Importantly, the same detection principle was validated with a duplex protein assay. Also, 8 different types of sensor stripes were fabricated and design parameters were explored. According to the detection principle uncovered, GMR biosensors can be further optimized to improve their sensitivity, which is highly desirable for early diagnosis of diseases. PMID:26728870

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.

Robustness properties of LQG optimized compensators for collocated rate sensors

NASA Technical Reports Server (NTRS)

Balakrishnan, A. V.

1994-01-01

In this paper we study the robustness with respect to stability of the closed-loop system with collocated rate sensor using LQG (mean square rate) optimized compensators. Our main result is that the transmission zeros of the compensator are precisely the structure modes when the actuator/sensor locations are 'pinned' and/or 'clamped': i.e., motion in the direction sensed is not allowed. We have stability even under parameter mismatch, except in the unlikely situation where such a mode frequency of the assumed system coincides with an undamped mode frequency of the real system and the corresponding mode shape is an eigenvector of the compensator transfer function matrix at that frequency. For a truncated modal model - such as that of the NASA LaRC Phase Zero Evolutionary model - the transmission zeros of the corresponding compensator transfer function can be interpreted as the structure modes when motion in the directions sensed is prohibited.

FLASH X-RAY (FXR) LINEAR INDUCTION ACCELERATOR (LIA) OPTIMIZATION Sensor Delay Correction

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

Ong, M M; Houck, T L; Kreitzer, B R

2006-05-01

The radiographic goal of the FXR Optimization Project is to generate an x-ray pulse with peak energy of 19 MeV, spot-size of 1.5 mm, a dose of 500 rad, and duration of 60 ns. The electrical objectives are to generate a 3 kA electron-beam and refine our 16 MV accelerator so that the voltage does not vary more than 1%-rms. In a multi-cell linear induction accelerator, like FXR, the timing of the acceleration pulses relative to the beam is critical. The pulses must be timed optimally so that a cell is at full voltage before the beam arrives and doesmore » not drop until the beam passes. In order to stay within the energy-variation budget, the synchronization between the cells and beam arrival must be controlled to a couple of nanoseconds. Therefore, temporal measurements must be accurate to a fraction of a nanosecond. FXR Optimization Project developed a one-giga-sample per second (gs/s) data acquisition system to record beam sensor data. Signal processing algorithms were written to determine cell timing with an uncertainty of a fraction of a nanosecond. However, the uncertainty in the sensor delay was still a few nanoseconds. This error had to be reduced if we are to improve the quality of the electron beam. Two types of sensors are used to align the cell voltage pulse against the beam current. The beam current is measured with resistive-wall sensors. The cell voltages are read with capacitive voltage monitors. Sensor delays can be traced to two mechanisms: (1) the sensors are not co-located at the beam and cell interaction points, and (2) the sensors have different length jumper cables and other components that connect them to the standard-length coaxial cables of the data acquisition system. Using the physical locations and dimensions of the sensor components, and the dielectric constant of the materials, delay times were computed. Relative to the cell voltage, the beam current was theoretically reporting late by 7.7 ns. Two experiments were performed to verify and refine the sensor delay correction. In the first experiment, the beam was allowed to drift through a cell that was not pulsed. The beam induces a potential into the cell that is read by the voltage monitor. Analysis of the data indicated that the beam sensor signal was likely 7.1 ns late. In the second experiment, the beam current is calculated from the injector diode voltage that is the sum of the cell voltages. A 7 ns correction produced a very good match between the signals from the two types of sensors. For simplicity, we selected a correction factor that advanced the current signals by 7 ns. This should reduce the uncertainty in the temporal measurements to less than 1 ns.« less

Active sensing in the categorization of visual patterns

PubMed Central

Yang, Scott Cheng-Hsin; Lengyel, Máté; Wolpert, Daniel M

2016-01-01

Interpreting visual scenes typically requires us to accumulate information from multiple locations in a scene. Using a novel gaze-contingent paradigm in a visual categorization task, we show that participants' scan paths follow an active sensing strategy that incorporates information already acquired about the scene and knowledge of the statistical structure of patterns. Intriguingly, categorization performance was markedly improved when locations were revealed to participants by an optimal Bayesian active sensor algorithm. By using a combination of a Bayesian ideal observer and the active sensor algorithm, we estimate that a major portion of this apparent suboptimality of fixation locations arises from prior biases, perceptual noise and inaccuracies in eye movements, and the central process of selecting fixation locations is around 70% efficient in our task. Our results suggest that participants select eye movements with the goal of maximizing information about abstract categories that require the integration of information from multiple locations. DOI: http://dx.doi.org/10.7554/eLife.12215.001 PMID:26880546

Pollution source localization in an urban water supply network based on dynamic water demand.

PubMed

Yan, Xuesong; Zhu, Zhixin; Li, Tian

2017-10-27

Urban water supply networks are susceptible to intentional, accidental chemical, and biological pollution, which pose a threat to the health of consumers. In recent years, drinking-water pollution incidents have occurred frequently, seriously endangering social stability and security. The real-time monitoring for water quality can be effectively implemented by placing sensors in the water supply network. However, locating the source of pollution through the data detection obtained by water quality sensors is a challenging problem. The difficulty lies in the limited number of sensors, large number of water supply network nodes, and dynamic user demand for water, which leads the pollution source localization problem to an uncertainty, large-scale, and dynamic optimization problem. In this paper, we mainly study the dynamics of the pollution source localization problem. Previous studies of pollution source localization assume that hydraulic inputs (e.g., water demand of consumers) are known. However, because of the inherent variability of urban water demand, the problem is essentially a fluctuating dynamic problem of consumer's water demand. In this paper, the water demand is considered to be stochastic in nature and can be described using Gaussian model or autoregressive model. On this basis, an optimization algorithm is proposed based on these two dynamic water demand change models to locate the pollution source. The objective of the proposed algorithm is to find the locations and concentrations of pollution sources that meet the minimum between the analogue and detection values of the sensor. Simulation experiments were conducted using two different sizes of urban water supply network data, and the experimental results were compared with those of the standard genetic algorithm.

Long term seismic noise acquisition and analysis with tunable monolithic horizontal sensors at the INFN Gran Sasso National Laboratory

NASA Astrophysics Data System (ADS)

Acernese, F.; De Rosa, R.; Giordano, G.; Romano, R.; Barone, F.

2012-04-01

In this paper we present the scientific data recorded by tunable mechanical monolithic horizontal seismometers located in the Gran Sasso National Laboratory of the INFN, within thermally insulating enclosures onto concrete slabs connected to the bedrock. The main goals of this long term test are a preliminary seismic characterization of the site in the frequency band 10-5÷1Hz and the acquisition of all the relevant information for the optimization of the sensors.

Long term seismic noise acquisition and analysis with tunable monolithic horizontal sensors at the INFN Gran Sasso National Laboratory

NASA Astrophysics Data System (ADS)

Acernese, F.; Canonico, R.; De Rosa, R.; Giordano, G.; Romano, R.; Barone, F.

2012-10-01

In this paper we present the scientific data recorded by tunable mechanical monolithic horizontal seismometers located in the Gran Sasso National Laboratory of the INFN, within thermally insulating enclosures onto concrete slabs connected to the bedrock. The main goals of this long term test are a preliminary seismic characterization of the site in the frequency band 10-7÷1Hz and the acquisition of all the relevant information for the optimization of the sensors.

An Optimal Set of Flesh Points on Tongue and Lips for Speech-Movement Classification

PubMed Central

Samal, Ashok; Rong, Panying; Green, Jordan R.

2016-01-01

Purpose The authors sought to determine an optimal set of flesh points on the tongue and lips for classifying speech movements. Method The authors used electromagnetic articulographs (Carstens AG500 and NDI Wave) to record tongue and lip movements from 13 healthy talkers who articulated 8 vowels, 11 consonants, a phonetically balanced set of words, and a set of short phrases during the recording. We used a machine-learning classifier (support-vector machine) to classify the speech stimuli on the basis of articulatory movements. We then compared classification accuracies of the flesh-point combinations to determine an optimal set of sensors. Results When data from the 4 sensors (T1: the vicinity between the tongue tip and tongue blade; T4: the tongue-body back; UL: the upper lip; and LL: the lower lip) were combined, phoneme and word classifications were most accurate and were comparable with the full set (including T2: the tongue-body front; and T3: the tongue-body front). Conclusion We identified a 4-sensor set—that is, T1, T4, UL, LL—that yielded a classification accuracy (91%–95%) equivalent to that using all 6 sensors. These findings provide an empirical basis for selecting sensors and their locations for scientific and emerging clinical applications that incorporate articulatory movements. PMID:26564030

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.

Hand-arm vibration exposure monitoring with wearable sensor module.

PubMed

Austad, Hanne O; Røed, Morten H; Liverud, Anders E; Dalgard, Steffen; Seeberg, Trine M

2013-01-01

Vibration exposure is a serious risk within work physiology for several work groups. Combined with cold artic climate, the risk for permanent harm is even higher. Equipment that can monitor the vibration exposure and warn the user when at risk will provide a safer work environment for these work groups. This study evaluates whether data from a wearable wireless multi-parameter sensor module can be used to estimate vibration exposure and exposure time. This work has been focused on the characterization of the response from the accelerometer in the sensor module and the optimal location of the module in the hand-arm configuration.

Remotely detected high-field MRI of porous samples

NASA Astrophysics Data System (ADS)

Seeley, Juliette A.; Han, Song-I.; Pines, Alexander

2004-04-01

Remote detection of NMR is a novel technique in which an NMR-active sensor surveys an environment of interest and retains memory of that environment to be recovered at a later time in a different location. The NMR or MRI information about the sensor nucleus is encoded and stored as spin polarization at the first location and subsequently moved to a different physical location for optimized detection. A dedicated probe incorporating two separate radio frequency (RF)—circuits was built for this purpose. The encoding solenoid coil was large enough to fit around the bulky sample matrix, while the smaller detection solenoid coil had not only a higher quality factor, but also an enhanced filling factor since the coil volume comprised purely the sensor nuclei. We obtained two-dimensional (2D) void space images of two model porous samples with resolution less than 1.4 mm 2. The remotely reconstructed images demonstrate the ability to determine fine structure with image quality superior to their directly detected counterparts and show the great potential of NMR remote detection for imaging applications that suffer from low sensitivity due to low concentrations and filling factor.

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.

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

Shunt-Enhanced, Lead-Driven Bifurcation of Epilayer GaAs based EEC Sensor Responsivity

NASA Astrophysics Data System (ADS)

Solin, Stuart; Werner, Fletcher

2015-03-01

The results reported here explore the geometric optimization of room-temperature EEC sensor responsivity to applied bias by exploring contact geometry and location. The EEC sensor structure resembles that of a MESFET, but the measurement technique and operation distinguish the EEC sensor significantly; the EEC sensor employs a four-point resistance measurement as opposed to a two-point source-drain measurement and is operated under both forward and reverse bias. Under direct forward bias, the sensor distinguishes itself from a traditional FET by allowing current to be injected from the gate, referred to as a shunt, into the active layer. We show that the observed bifurcation in EEC sensor response to direct reverse bias depends critically on measurement lead location. A dramatic enhancement in responsivity is achieved via a modification of the shunt geometry. A maximum percent change of 130,856% of the four-point resistance was achieved under a direct reverse bias of -1V using an enhanced shunt design, a 325 fold increase over the conventional EEC square shunt design. This result was accompanied by an observed bifurcation in sensor response, driven by a rotation of the four-point measurement leads. S. A. S is a co-founder of and has a financial interest in PixelEXX, a start-up company whose mission is to market imaging arrays.

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

An Optimized Hidden Node Detection Paradigm for Improving the Coverage and Network Efficiency in Wireless Multimedia Sensor Networks

PubMed Central

Alanazi, Adwan; Elleithy, Khaled

2016-01-01

Successful transmission of online multimedia streams in wireless multimedia sensor networks (WMSNs) is a big challenge due to their limited bandwidth and power resources. The existing WSN protocols are not completely appropriate for multimedia communication. The effectiveness of WMSNs varies, and it depends on the correct location of its sensor nodes in the field. Thus, maximizing the multimedia coverage is the most important issue in the delivery of multimedia contents. The nodes in WMSNs are either static or mobile. Thus, the node connections change continuously due to the mobility in wireless multimedia communication that causes an additional energy consumption, and synchronization loss between neighboring nodes. In this paper, we introduce an Optimized Hidden Node Detection (OHND) paradigm. The OHND consists of three phases: hidden node detection, message exchange, and location detection. These three phases aim to maximize the multimedia node coverage, and improve energy efficiency, hidden node detection capacity, and packet delivery ratio. OHND helps multimedia sensor nodes to compute the directional coverage. Furthermore, an OHND is used to maintain a continuous node– continuous neighbor discovery process in order to handle the mobility of the nodes. We implement our proposed algorithms by using a network simulator (NS2). The simulation results demonstrate that nodes are capable of maintaining direct coverage and detecting hidden nodes in order to maximize coverage and multimedia node mobility. To evaluate the performance of our proposed algorithms, we compared our results with other known approaches. PMID:27618048

An Optimized Hidden Node Detection Paradigm for Improving the Coverage and Network Efficiency in Wireless Multimedia Sensor Networks.

PubMed

Alanazi, Adwan; Elleithy, Khaled

2016-09-07

Successful transmission of online multimedia streams in wireless multimedia sensor networks (WMSNs) is a big challenge due to their limited bandwidth and power resources. The existing WSN protocols are not completely appropriate for multimedia communication. The effectiveness of WMSNs varies, and it depends on the correct location of its sensor nodes in the field. Thus, maximizing the multimedia coverage is the most important issue in the delivery of multimedia contents. The nodes in WMSNs are either static or mobile. Thus, the node connections change continuously due to the mobility in wireless multimedia communication that causes an additional energy consumption, and synchronization loss between neighboring nodes. In this paper, we introduce an Optimized Hidden Node Detection (OHND) paradigm. The OHND consists of three phases: hidden node detection, message exchange, and location detection. These three phases aim to maximize the multimedia node coverage, and improve energy efficiency, hidden node detection capacity, and packet delivery ratio. OHND helps multimedia sensor nodes to compute the directional coverage. Furthermore, an OHND is used to maintain a continuous node- continuous neighbor discovery process in order to handle the mobility of the nodes. We implement our proposed algorithms by using a network simulator (NS2). The simulation results demonstrate that nodes are capable of maintaining direct coverage and detecting hidden nodes in order to maximize coverage and multimedia node mobility. To evaluate the performance of our proposed algorithms, we compared our results with other known approaches.

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

NASA Astrophysics Data System (ADS)

Jacobs, Bryan C.; Nelson, Carl V.

2001-08-01

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

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

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

PubMed Central

Nefti-Meziani, Samia; Carbonaro, Nicola

2017-01-01

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

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

PubMed

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

2017-08-31

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

Leak Detection and Location of Water Pipes Using Vibration Sensors and Modified ML Prefilter.

PubMed

Choi, Jihoon; Shin, Joonho; Song, Choonggeun; Han, Suyong; Park, Doo Il

2017-09-13

This paper proposes a new leak detection and location method based on vibration sensors and generalised cross-correlation techniques. Considering the estimation errors of the power spectral densities (PSDs) and the cross-spectral density (CSD), the proposed method employs a modified maximum-likelihood (ML) prefilter with a regularisation factor. We derive a theoretical variance of the time difference estimation error through summation in the discrete-frequency domain, and find the optimal regularisation factor that minimises the theoretical variance in practical water pipe channels. The proposed method is compared with conventional correlation-based techniques via numerical simulations using a water pipe channel model, and it is shown through field measurement that the proposed modified ML prefilter outperforms conventional prefilters for the generalised cross-correlation. In addition, we provide a formula to calculate the leak location using the time difference estimate when different types of pipes are connected.

Mitigation of the consequence of seismically induced damage on a utility water network by means of next generation SCADA

NASA Astrophysics Data System (ADS)

Robertson, Jamie; Shinozuka, Masanobu; Wu, Felix

2011-04-01

When a lifeline system such as a water delivery network is damaged due to a severe earthquake, it is critical to identify its location and extent of the damage in real time in order to minimize the potentially disastrous consequence such damage could otherwise entail. This paper demonstrates how the degree of such minimization can be estimated qualitatively by using the water delivery system of Irvine Water Ranch District (IRWD) as testbed, when it is subjected to magnitude 6.6 San Joaquin Hills Earthquake. In this demonstration, we consider two cases when the IRWD system is equipped or not equipped with a next generation SCADA which consists of a network of MEMS acceleration sensors densely populated and optimally located. These sensors are capable of identifying the location and extent of the damage as well as transmitting the data to the SCADA center for monitoring and control.

Leak Detection and Location of Water Pipes Using Vibration Sensors and Modified ML Prefilter

PubMed Central

Shin, Joonho; Song, Choonggeun; Han, Suyong; Park, Doo Il

2017-01-01

This paper proposes a new leak detection and location method based on vibration sensors and generalised cross-correlation techniques. Considering the estimation errors of the power spectral densities (PSDs) and the cross-spectral density (CSD), the proposed method employs a modified maximum-likelihood (ML) prefilter with a regularisation factor. We derive a theoretical variance of the time difference estimation error through summation in the discrete-frequency domain, and find the optimal regularisation factor that minimises the theoretical variance in practical water pipe channels. The proposed method is compared with conventional correlation-based techniques via numerical simulations using a water pipe channel model, and it is shown through field measurement that the proposed modified ML prefilter outperforms conventional prefilters for the generalised cross-correlation. In addition, we provide a formula to calculate the leak location using the time difference estimate when different types of pipes are connected. PMID:28902154

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.

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

PubMed

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

2010-09-01

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

On Location Estimation Technique Based of the Time of Flight in Low-power Wireless Systems

NASA Astrophysics Data System (ADS)

Botta, Miroslav; Simek, Milan; Krajsa, Ondrej; Cervenka, Vladimir; Pal, Tamas

2015-04-01

This study deals with the distance estimation issue in low-power wireless systems being usually used for sensor networking and interconnecting the Internet of Things. There is an effort to locate or track these sensor entities for different needs the radio signal time of flight principle from the theoretical and practical side of application research is evaluated. Since these sensor devices are mainly targeted for low power consumption appliances, there is always need for optimization of any aspects needed for regular sensor operation. For the distance estimation we benefit from IEEE 802.15.4a technology, which offers the precise ranging capabilities. There is no need for additional hardware to be used for the ranging task and all fundamental measurements are acquired within the 15.4a standard compliant hardware in the real environment. The proposed work examines the problems and the solutions for implementation of distance estimation algorithms for WSN devices. The main contribution of the article is seen in this real testbed evaluation of the ranging technology.

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

Locating single-point sources from arrival times containing large picking errors (LPEs): the virtual field optimization method (VFOM)

NASA Astrophysics Data System (ADS)

Li, Xi-Bing; Wang, Ze-Wei; Dong, Long-Jun

2016-01-01

Microseismic monitoring systems using local location techniques tend to be timely, automatic and stable. One basic requirement of these systems is the automatic picking of arrival times. However, arrival times generated by automated techniques always contain large picking errors (LPEs), which may make the location solution unreliable and cause the integrated system to be unstable. To overcome the LPE issue, we propose the virtual field optimization method (VFOM) for locating single-point sources. In contrast to existing approaches, the VFOM optimizes a continuous and virtually established objective function to search the space for the common intersection of the hyperboloids, which is determined by sensor pairs other than the least residual between the model-calculated and measured arrivals. The results of numerical examples and in-site blasts show that the VFOM can obtain more precise and stable solutions than traditional methods when the input data contain LPEs. Furthermore, we discuss the impact of LPEs on objective functions to determine the LPE-tolerant mechanism, velocity sensitivity and stopping criteria of the VFOM. The proposed method is also capable of locating acoustic sources using passive techniques such as passive sonar detection and acoustic emission.

Calibration and assessment of electrochemical air quality sensors by co-location with regulatory-grade instruments

NASA Astrophysics Data System (ADS)

Hagan, David H.; Isaacman-VanWertz, Gabriel; Franklin, Jonathan P.; Wallace, Lisa M. M.; Kocar, Benjamin D.; Heald, Colette L.; Kroll, Jesse H.

2018-01-01

The use of low-cost air quality sensors for air pollution research has outpaced our understanding of their capabilities and limitations under real-world conditions, and there is thus a critical need for understanding and optimizing the performance of such sensors in the field. Here we describe the deployment, calibration, and evaluation of electrochemical sensors on the island of Hawai`i, which is an ideal test bed for characterizing such sensors due to its large and variable sulfur dioxide (SO2) levels and lack of other co-pollutants. Nine custom-built SO2 sensors were co-located with two Hawaii Department of Health Air Quality stations over the course of 5 months, enabling comparison of sensor output with regulatory-grade instruments under a range of realistic environmental conditions. Calibration using a nonparametric algorithm (k nearest neighbors) was found to have excellent performance (RMSE < 7 ppb, MAE < 4 ppb, r2 > 0.997) across a wide dynamic range in SO2 (< 1 ppb, > 2 ppm). However, since nonparametric algorithms generally cannot extrapolate to conditions beyond those outside the training set, we introduce a new hybrid linear-nonparametric algorithm, enabling accurate measurements even when pollutant levels are higher than encountered during calibration. We find no significant change in instrument sensitivity toward SO2 after 18 weeks and demonstrate that calibration accuracy remains high when a sensor is calibrated at one location and then moved to another. The performance of electrochemical SO2 sensors is also strong at lower SO2 mixing ratios (< 25 ppb), for which they exhibit an error of less than 2.5 ppb. While some specific results of this study (calibration accuracy, performance of the various algorithms, etc.) may differ for measurements of other pollutant species in other areas (e.g., polluted urban regions), the calibration and validation approaches described here should be widely applicable to a range of pollutants, sensors, and environments.

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.

Optimal design of the absolute positioning sensor for a high-speed maglev train and research on its fault diagnosis.

PubMed

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

2012-01-01

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

Selection of optimal spectral sensitivity functions for color filter arrays.

PubMed

Parmar, Manu; Reeves, Stanley J

2010-12-01

A color image meant for human consumption can be appropriately displayed only if at least three distinct color channels are present. Typical digital cameras acquire three-color images with only one sensor. A color filter array (CFA) is placed on the sensor such that only one color is sampled at a particular spatial location. This sparsely sampled signal is then reconstructed to form a color image with information about all three colors at each location. In this paper, we show that the wavelength sensitivity functions of the CFA color filters affect both the color reproduction ability and the spatial reconstruction quality of recovered images. We present a method to select perceptually optimal color filter sensitivity functions based upon a unified spatial-chromatic sampling framework. A cost function independent of particular scenes is defined that expresses the error between a scene viewed by the human visual system and the reconstructed image that represents the scene. A constrained minimization of the cost function is used to obtain optimal values of color-filter sensitivity functions for several periodic CFAs. The sensitivity functions are shown to perform better than typical RGB and CMY color filters in terms of both the s-CIELAB ∆E error metric and a qualitative assessment.

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.

On Deployment of Multiple Base Stations for Energy-Efficient Communication in Wireless Sensor Networks

DOE PAGES

Lin, Yunyue; Wu, Qishi; Cai, Xiaoshan; ...

2010-01-01

Data transmission from sensor nodes to a base station or a sink node often incurs significant energy consumption, which critically affects network lifetime. We generalize and solve the problem of deploying multiple base stations to maximize network lifetime in terms of two different metrics under one-hop and multihop communication models. In the one-hop communication model, the sensors far away from base stations always deplete their energy much faster than others. We propose an optimal solution and a heuristic approach based on the minimal enclosing circle algorithm to deploy a base station at the geometric center of each cluster. In themore » multihop communication model, both base station location and data routing mechanism need to be considered in maximizing network lifetime. We propose an iterative algorithm based on rigorous mathematical derivations and use linear programming to compute the optimal routing paths for data transmission. Simulation results show the distinguished performance of the proposed deployment algorithms in maximizing network lifetime.« less

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

PubMed Central

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

2016-01-01

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

Satellite telemetry: performance of animal-tracking systems

USGS Publications Warehouse

Keating, Kim A.; Brewster, Wayne G.; Key, Carl H.

1991-01-01

t: We used 10 Telonics ST-3 platform transmitter terminals (PTT's) configured for wolves and ungulates to examine the performance of the Argos satellite telemetry system. Under near-optimal conditions, 68 percentile errors for location qualities (NQ) 1, 2, and 3 were 1,188, 903, and 361 m, respectively. Errors (rE) exceeded expected values for NQ = 2 and 3, varied greatly among PTT's, increased as the difference (HE) between the estimated and actual PTT elevations increased, and were correlated nonlinearly with maximum satellite pass height (P,). We present a model of the relationships among rE, HE, and PH. Errors were bimodally distributed along the east-west axis and tended to occur away from the satellite when HE was positive. A southeasterly bias increased with HE, probably due to the particular distribution of satellite passes and effects of HE on rE. Under near-optimal conditions, 21 sensor message was received for up to 64% of available (PH, 50) satellite passes, and a location (NQ 2 1) was calculated for up to 63% of such passes. Sampling frequencies of sensor and location data declined 13 and 70%, respectively, for PTT's in a valley bottom and 65 and 86%, respectively, for PTT's on animals that were in valley bottoms. Sampling frequencies were greater for ungulate than for wolf collars.

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.

A global stochastic programming approach for the optimal placement of gas detectors with nonuniform unavailabilities

DOE PAGES

Liu, Jianfeng; Laird, Carl Damon

2017-09-22

Optimal design of a gas detection systems is challenging because of the numerous sources of uncertainty, including weather and environmental conditions, leak location and characteristics, and process conditions. Rigorous CFD simulations of dispersion scenarios combined with stochastic programming techniques have been successfully applied to the problem of optimal gas detector placement; however, rigorous treatment of sensor failure and nonuniform unavailability has received less attention. To improve reliability of the design, this paper proposes a problem formulation that explicitly considers nonuniform unavailabilities and all backup detection levels. The resulting sensor placement problem is a large-scale mixed-integer nonlinear programming (MINLP) problem thatmore » requires a tailored solution approach for efficient solution. We have developed a multitree method which depends on iteratively solving a sequence of upper-bounding master problems and lower-bounding subproblems. The tailored global solution strategy is tested on a real data problem and the encouraging numerical results indicate that our solution framework is promising in solving sensor placement problems. This study was selected for the special issue in JLPPI from the 2016 International Symposium of the MKO Process Safety Center.« less

A global stochastic programming approach for the optimal placement of gas detectors with nonuniform unavailabilities

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

Liu, Jianfeng; Laird, Carl Damon

Optimal design of a gas detection systems is challenging because of the numerous sources of uncertainty, including weather and environmental conditions, leak location and characteristics, and process conditions. Rigorous CFD simulations of dispersion scenarios combined with stochastic programming techniques have been successfully applied to the problem of optimal gas detector placement; however, rigorous treatment of sensor failure and nonuniform unavailability has received less attention. To improve reliability of the design, this paper proposes a problem formulation that explicitly considers nonuniform unavailabilities and all backup detection levels. The resulting sensor placement problem is a large-scale mixed-integer nonlinear programming (MINLP) problem thatmore » requires a tailored solution approach for efficient solution. We have developed a multitree method which depends on iteratively solving a sequence of upper-bounding master problems and lower-bounding subproblems. The tailored global solution strategy is tested on a real data problem and the encouraging numerical results indicate that our solution framework is promising in solving sensor placement problems. This study was selected for the special issue in JLPPI from the 2016 International Symposium of the MKO Process Safety Center.« less

Optimum parameters of image preprocessing method for Shack-Hartmann wavefront sensor in different SNR condition

NASA Astrophysics Data System (ADS)

Wei, Ping; Li, Xinyang; Luo, Xi; Li, Jianfeng

2018-02-01

The centroid method is commonly adopted to locate the spot in the sub-apertures in the Shack-Hartmann wavefront sensor (SH-WFS), in which preprocessing image is required before calculating the spot location due to that the centroid method is extremely sensitive to noises. In this paper, the SH-WFS image was simulated according to the characteristics of the noises, background and intensity distribution. The Optimal parameters of SH-WFS image preprocessing method were put forward, in different signal-to-noise ratio (SNR) conditions, where the wavefront reconstruction error was considered as the evaluation index. Two methods of image preprocessing, thresholding method and windowing combing with thresholding method, were compared by studying the applicable range of SNR and analyzing the stability of the two methods, respectively.

Autonomous In-Situ Resources Prospector

NASA Technical Reports Server (NTRS)

Dissly, R. W.; Buehler, M. G.; Schaap, M. G.; Nicks, D.; Taylor, G. J.; Castano, R.; Suarez, D.

2004-01-01

This presentation will describe the concept of an autonomous, intelligent, rover-based rapid surveying system to identify and map several key lunar resources to optimize their ISRU (In Situ Resource Utilization) extraction potential. Prior to an extraction phase for any target resource, ground-based surveys are needed to provide confirmation of remote observation, to quantify and map their 3-D distribution, and to locate optimal extraction sites (e.g. ore bodies) with precision to maximize their economic benefit. The system will search for and quantify optimal minerals for oxygen production feedstock, water ice, and high glass-content regolith that can be used for building materials. These are targeted because of their utility and because they are, or are likely to be, variable in quantity over spatial scales accessible to a rover (i.e., few km). Oxygen has benefits for life support systems and as an oxidizer for propellants. Water is a key resource for sustainable exploration, with utility for life support, propellants, and other industrial processes. High glass-content regolith has utility as a feedstock for building materials as it readily sinters upon heating into a cohesive matrix more readily than other regolith materials or crystalline basalts. Lunar glasses are also a potential feedstock for oxygen production, as many are rich in iron and titanium oxides that are optimal for oxygen extraction. To accomplish this task, a system of sensors and decision-making algorithms for an autonomous prospecting rover is described. One set of sensors will be located in the wheel tread of the robotic search vehicle providing contact sensor data on regolith composition. Another set of instruments will be housed on the platform of the rover, including VIS-NIR imagers and spectrometers, both for far-field context and near-field characterization of the regolith in the immediate vicinity of the rover. Also included in the sensor suite are a neutron spectrometer, ground-penetrating radar, and an instrumented cone penetrometer for subsurface assessment. Output from these sensors will be evaluated autonomously in real-time by decision-making software to evaluate if any of the targeted resources has been detected, and if so, to quantify their abundance. Algorithms for optimizing the mapping strategy based on target resource abundance and distribution are also included in the autonomous software. This approach emphasizes on-the-fly survey measurements to enable efficient and rapid prospecting of large areas, which will improve the economics of ISRU system approaches. The mature technology will enable autonomous rovers to create in-situ resource maps of lunar or other planetary surfaces, which will facilitate human and robotic exploration.

Distributed wireless sensing for methane leak detection technology

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

Klein, Levente; van Kesse, Theodor

Large scale environmental monitoring requires dynamic optimization of data transmission, power management, and distribution of the computational load. In this work, we demonstrate the use of a wireless sensor network for detection of chemical leaks on gas oil well pads. The sensor network consist of chemi-resistive and wind sensors and aggregates all the data and transmits it to the cloud for further analytics processing. The sensor network data is integrated with an inversion model to identify leak location and quantify leak rates. We characterize the sensitivity and accuracy of such system under multiple well controlled methane release experiments. It ismore » demonstrated that even 1 hour measurement with 10 sensors localizes leaks within 1 m and determines leak rate with an accuracy of 40%. This integrated sensing and analytics solution is currently refined to be a robust system for long term remote monitoring of methane leaks, generation of alarms, and tracking regulatory compliance.« less

Distributed wireless sensing for fugitive methane leak detection

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

Klein, Levente J.; van Kessel, Theodore; Nair, Dhruv

Large scale environmental monitoring requires dynamic optimization of data transmission, power management, and distribution of the computational load. In this work, we demonstrate the use of a wireless sensor network for detection of chemical leaks on gas oil well pads. The sensor network consist of chemi-resistive and wind sensors and aggregates all the data and transmits it to the cloud for further analytics processing. The sensor network data is integrated with an inversion model to identify leak location and quantify leak rates. We characterize the sensitivity and accuracy of such system under multiple well controlled methane release experiments. It ismore » demonstrated that even 1 hour measurement with 10 sensors localizes leaks within 1 m and determines leak rate with an accuracy of 40%. This integrated sensing and analytics solution is currently refined to be a robust system for long term remote monitoring of methane leaks, generation of alarms, and tracking regulatory compliance.« less

Distributed wireless sensing for fugitive methane leak detection

DOE PAGES

Klein, Levente J.; van Kessel, Theodore; Nair, Dhruv; ...

2017-12-11

Large scale environmental monitoring requires dynamic optimization of data transmission, power management, and distribution of the computational load. In this work, we demonstrate the use of a wireless sensor network for detection of chemical leaks on gas oil well pads. The sensor network consist of chemi-resistive and wind sensors and aggregates all the data and transmits it to the cloud for further analytics processing. The sensor network data is integrated with an inversion model to identify leak location and quantify leak rates. We characterize the sensitivity and accuracy of such system under multiple well controlled methane release experiments. It ismore » demonstrated that even 1 hour measurement with 10 sensors localizes leaks within 1 m and determines leak rate with an accuracy of 40%. This integrated sensing and analytics solution is currently refined to be a robust system for long term remote monitoring of methane leaks, generation of alarms, and tracking regulatory compliance.« less

A Real-Time De-Noising Algorithm for E-Noses in a Wireless Sensor Network

PubMed Central

Qu, Jianfeng; Chai, Yi; Yang, Simon X.

2009-01-01

A wireless e-nose network system is developed for the special purpose of monitoring odorant gases and accurately estimating odor strength in and around livestock farms. This system is to simultaneously acquire accurate odor strength values remotely at various locations, where each node is an e-nose that includes four metal-oxide semiconductor (MOS) gas sensors. A modified Kalman filtering technique is proposed for collecting raw data and de-noising based on the output noise characteristics of those gas sensors. The measurement noise variance is obtained in real time by data analysis using the proposed slip windows average method. The optimal system noise variance of the filter is obtained by using the experiments data. The Kalman filter theory on how to acquire MOS gas sensors data is discussed. Simulation results demonstrate that the proposed method can adjust the Kalman filter parameters and significantly reduce the noise from the gas sensors. PMID:22399946

Developing Fast Fluorescent Protein Voltage Sensors by Optimizing FRET Interactions

PubMed Central

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

2015-01-01

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

Model development and system performance optimization for staring infrared search and track (IRST) sensors

NASA Astrophysics Data System (ADS)

Olson, Craig; Theisen, Michael; Pace, Teresa; Halford, Carl; Driggers, Ronald

2016-05-01

The mission of an Infrared Search and Track (IRST) system is to detect and locate (sometimes called find and fix) enemy aircraft at significant ranges. Two extreme opposite examples of IRST applications are 1) long range offensive aircraft detection when electronic warfare equipment is jammed, compromised, or intentionally turned off, and 2) distributed aperture systems where enemy aircraft may be in the proximity of the host aircraft. Past IRST systems have been primarily long range offensive systems that were based on the LWIR second generation thermal imager. The new IRST systems are primarily based on staring infrared focal planes and sensors. In the same manner that FLIR92 did not work well in the design of staring infrared cameras (NVTherm was developed to address staring infrared sensor performance), current modeling techniques do not adequately describe the performance of a staring IRST sensor. There are no standard military IRST models (per AFRL and NAVAIR), and each program appears to perform their own modeling. For this reason, L-3 has decided to develop a corporate model, working with AFRL and NAVAIR, for the analysis, design, and evaluation of IRST concepts, programs, and solutions. This paper provides some of the first analyses in the L-3 IRST model development program for the optimization of staring IRST sensors.

Multi-Parameter Aerosol Scattering Sensor

NASA Technical Reports Server (NTRS)

Greenberg, Paul S.; Fischer, David G.

2011-01-01

This work relates to the development of sensors that measure specific aerosol properties. These properties are in the form of integrated moment distributions, i.e., total surface area, total mass, etc., or mathematical combinations of these moment distributions. Specifically, the innovation involves two fundamental features: a computational tool to design and optimize such sensors and the embodiment of these sensors in actual practice. The measurement of aerosol properties is a problem of general interest. Applications include, but are not limited to, environmental monitoring, assessment of human respiratory health, fire detection, emission characterization and control, and pollutant monitoring. The objectives for sensor development include increased accuracy and/or dynamic range, the inclusion in a single sensor of the ability to measure multiple aerosol properties, and developing an overall physical package that is rugged, compact, and low in power consumption, so as to enable deployment in harsh or confined field applications, and as distributed sensor networks. Existing instruments for this purpose include scattering photometers, direct-reading mass instruments, Beta absorption devices, differential mobility analyzers, and gravitational samplers. The family of sensors reported here is predicated on the interaction of light and matter; specifically, the scattering of light from distributions of aerosol particles. The particular arrangement of the sensor, e.g. the wavelength(s) of incident radiation, the number and location of optical detectors, etc., can be derived so as to optimize the sensor response to aerosol properties of practical interest. A key feature of the design is the potential embodiment as an extremely compact, integrated microsensor package. This is of fundamental importance, as it enables numerous previously inaccessible applications. The embodiment of these sensors is inherently low maintenance and high reliability by design. The novel and unique features include the underlying computational underpinning that allows the optimization for specific applications, and the physical embodiment that affords the construction of a compact, durable, and reliable integrated package. The advantage appears in the form of increased accuracy relative to existing instruments, and the applications enabled by the physical attributes of the resulting configuration

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.

WE-AB-BRA-11: Improved Imaging of Permanent Prostate Brachytherapy Seed Implants by Combining an Endorectal X-Ray Sensor with a CT Scanner

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

Steiner, J; Matthews, K; Jia, G

Purpose: To test feasibility of the use of a digital endorectal x-ray sensor for improved image resolution of permanent brachytherapy seed implants compared to conventional CT. Methods: Two phantoms simulating the male pelvic region were used to test the capabilities of a digital endorectal x-ray sensor for imaging permanent brachytherapy seed implants. Phantom 1 was constructed from acrylic plastic with cavities milled in the locations of the prostate and the rectum. The prostate cavity was filled a Styrofoam plug implanted with 10 training seeds. Phantom 2 was constructed from tissue-equivalent gelatins and contained a prostate phantom implanted with 18 strandsmore » of training seeds. For both phantoms, an intraoral digital dental x-ray sensor was placed in the rectum within 2 cm of the seed implants. Scout scans were taken of the phantoms over a limited arc angle using a CT scanner (80 kV, 120–200 mA). The dental sensor was removed from the phantoms and normal helical CT and scout (0 degree) scans using typical parameters for pelvic CT (120 kV, auto-mA) were collected. A shift-and add tomosynthesis algorithm was developed to localize seed plane location normal to detector face. Results: The endorectal sensor produced images with improved resolution compared to CT scans. Seed clusters and individual seed geometry were more discernable using the endorectal sensor. Seed 3D locations, including seeds that were not located in every projection image, were discernable using the shift and add algorithm. Conclusion: This work shows that digital endorectal x-ray sensors are a feasible method for improving imaging of permanent brachytherapy seed implants. Future work will consist of optimizing the tomosynthesis technique to produce higher resolution, lower dose images of 1) permanent brachytherapy seed implants for post-implant dosimetry and 2) fine anatomic details for imaging and managing prostatic disease compared to CT images. Funding: LSU Faculty Start-up Funding. Disclosure: XDR Radiography has loaned our research group the digital x-ray detector used in this work. CoI: None.« less

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

NASA Astrophysics Data System (ADS)

Boulay, N.; Lhémery, A.; Zhang, F.

2018-05-01

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

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.

Nonlinear optimization-based device-free localization with outlier link rejection.

PubMed

Xiao, Wendong; Song, Biao; Yu, Xiting; Chen, Peiyuan

2015-04-07

Device-free localization (DFL) is an emerging wireless technique for estimating the location of target that does not have any attached electronic device. It has found extensive use in Smart City applications such as healthcare at home and hospitals, location-based services at smart spaces, city emergency response and infrastructure security. In DFL, wireless devices are used as sensors that can sense the target by transmitting and receiving wireless signals collaboratively. Many DFL systems are implemented based on received signal strength (RSS) measurements and the location of the target is estimated by detecting the changes of the RSS measurements of the wireless links. Due to the uncertainty of the wireless channel, certain links may be seriously polluted and result in erroneous detection. In this paper, we propose a novel nonlinear optimization approach with outlier link rejection (NOOLR) for RSS-based DFL. It consists of three key strategies, including: (1) affected link identification by differential RSS detection; (2) outlier link rejection via geometrical positional relationship among links; (3) target location estimation by formulating and solving a nonlinear optimization problem. Experimental results demonstrate that NOOLR is robust to the fluctuation of the wireless signals with superior localization accuracy compared with the existing Radio Tomographic Imaging (RTI) approach.

Active Control Technology at NASA Langley Research Center

NASA Technical Reports Server (NTRS)

Antcliff, Richard R.; McGowan, Anna-Marie R.

2000-01-01

NASA Langley has a long history of attacking important technical Opportunities from a broad base of supporting disciplines. The research and development at Langley in this subject area range from the test tube to the test flight, The information covered here will range from the development of innovative new materials, sensors and actuators, to the incorporation of smart sensors and actuators in practical devices, to the optimization of the location of these devices, to, finally, a wide variety of applications of these devices utilizing Langley's facilities and expertise. Advanced materials are being developed for sensors and actuators, as well as polymers for integrating smart devices into composite structures. Contributions reside in three key areas: computational materials; advanced piezoelectric materials; and integrated composite structures.

Methods and systems for seed planting management and control

DOEpatents

Svoboda, John M.; Hess, J. Richard; Hoskinson, Reed L.; Harker, David J.

2002-01-01

A seed planting system providing optimal seed spacing in an agricultural field. The seed planting system includes a mobile seed planter having one or more planting shoes, or members being adapted for towing by a farm vehicle or being self-propelled. Sensors, disposed proximate to respective planting shoes, detect seed planting events and send corresponding signals to a computer. Contemporaneously, a geospatial locator acquires, and transmits to the computer, the geospatial location of each planted seed. The computer correlates the geospatial location data with the seed deposition data and generates a seed distribution profile indicating the location of each seed planted in a zone of interest to enable the control of speed spacing.

Optimal Sensor Fusion for Structural Health Monitoring of Aircraft Composite Components

DTIC Science & Technology

2011-09-01

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

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

PubMed Central

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

2012-01-01

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

Reduced-Order Modeling and Wavelet Analysis of Turbofan Engine Structural Response Due to Foreign Object Damage (FOD) Events

NASA Technical Reports Server (NTRS)

Turso, James; Lawrence, Charles; Litt, Jonathan

2004-01-01

The development of a wavelet-based feature extraction technique specifically targeting FOD-event induced vibration signal changes in gas turbine engines is described. The technique performs wavelet analysis of accelerometer signals from specified locations on the engine and is shown to be robust in the presence of significant process and sensor noise. It is envisioned that the technique will be combined with Kalman filter thermal/health parameter estimation for FOD-event detection via information fusion from these (and perhaps other) sources. Due to the lack of high-frequency FOD-event test data in the open literature, a reduced-order turbofan structural model (ROM) was synthesized from a finite element model modal analysis to support the investigation. In addition to providing test data for algorithm development, the ROM is used to determine the optimal sensor location for FOD-event detection. In the presence of significant noise, precise location of the FOD event in time was obtained using the developed wavelet-based feature.

Reduced-Order Modeling and Wavelet Analysis of Turbofan Engine Structural Response Due to Foreign Object Damage "FOD" Events

NASA Technical Reports Server (NTRS)

Turso, James A.; Lawrence, Charles; Litt, Jonathan S.

2007-01-01

The development of a wavelet-based feature extraction technique specifically targeting FOD-event induced vibration signal changes in gas turbine engines is described. The technique performs wavelet analysis of accelerometer signals from specified locations on the engine and is shown to be robust in the presence of significant process and sensor noise. It is envisioned that the technique will be combined with Kalman filter thermal/ health parameter estimation for FOD-event detection via information fusion from these (and perhaps other) sources. Due to the lack of high-frequency FOD-event test data in the open literature, a reduced-order turbofan structural model (ROM) was synthesized from a finite-element model modal analysis to support the investigation. In addition to providing test data for algorithm development, the ROM is used to determine the optimal sensor location for FOD-event detection. In the presence of significant noise, precise location of the FOD event in time was obtained using the developed wavelet-based feature.

Optimized Sensor Network and Multi-Agent Decision Support for Smart Traffic Light Management.

PubMed

Cruz-Piris, Luis; Rivera, Diego; Fernandez, Susel; Marsa-Maestre, Ivan

2018-02-02

One of the biggest challenges in modern societies is to solve vehicular traffic problems. Sensor networks in traffic environments have contributed to improving the decision-making process of Intelligent Transportation Systems. However, one of the limiting factors for the effectiveness of these systems is in the deployment of sensors to provide accurate information about the traffic. Our proposal is using the centrality measurement of a graph as a base to locate the best locations for sensor installation in a traffic network. After integrating these sensors in a simulation scenario, we define a Multi-Agent Systems composed of three types of agents: traffic light management agents, traffic jam detection agents, and agents that control the traffic lights at an intersection. The ultimate goal of these Multi-Agent Systems is to improve the trip duration for vehicles in the network. To validate our solution, we have developed the needed elements for modelling the sensors and agents in the simulation environment. We have carried out experiments using the Simulation of Urban MObility (SUMO) traffic simulator and the Travel and Activity PAtterns Simulation (TAPAS) Cologne traffic scenario. The obtained results show that our proposal allows to reduce the sensor network while still obtaining relevant information to have a global view of the environment. Finally, regarding the Multi-Agent Systems, we have carried out experiments that show that our proposal is able to improve other existing solutions such as conventional traffic light management systems (static or dynamic) in terms of reduction of vehicle trip duration and reduction of the message exchange overhead in the sensor network.

Optimized Sensor Network and Multi-Agent Decision Support for Smart Traffic Light Management

PubMed Central

2018-01-01

One of the biggest challenges in modern societies is to solve vehicular traffic problems. Sensor networks in traffic environments have contributed to improving the decision-making process of Intelligent Transportation Systems. However, one of the limiting factors for the effectiveness of these systems is in the deployment of sensors to provide accurate information about the traffic. Our proposal is using the centrality measurement of a graph as a base to locate the best locations for sensor installation in a traffic network. After integrating these sensors in a simulation scenario, we define a Multi-Agent Systems composed of three types of agents: traffic light management agents, traffic jam detection agents, and agents that control the traffic lights at an intersection. The ultimate goal of these Multi-Agent Systems is to improve the trip duration for vehicles in the network. To validate our solution, we have developed the needed elements for modelling the sensors and agents in the simulation environment. We have carried out experiments using the Simulation of Urban MObility (SUMO) traffic simulator and the Travel and Activity PAtterns Simulation (TAPAS) Cologne traffic scenario. The obtained results show that our proposal allows to reduce the sensor network while still obtaining relevant information to have a global view of the environment. Finally, regarding the Multi-Agent Systems, we have carried out experiments that show that our proposal is able to improve other existing solutions such as conventional traffic light management systems (static or dynamic) in terms of reduction of vehicle trip duration and reduction of the message exchange overhead in the sensor network. PMID:29393884

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.

Large Scale Environmental Monitoring through Integration of Sensor and Mesh Networks.

PubMed

Jurdak, Raja; Nafaa, Abdelhamid; Barbirato, Alessio

2008-11-24

Monitoring outdoor environments through networks of wireless sensors has received interest for collecting physical and chemical samples at high spatial and temporal scales. A central challenge to environmental monitoring applications of sensor networks is the short communication range of the sensor nodes, which increases the complexity and cost of monitoring commodities that are located in geographically spread areas. To address this issue, we propose a new communication architecture that integrates sensor networks with medium range wireless mesh networks, and provides users with an advanced web portal for managing sensed information in an integrated manner. Our architecture adopts a holistic approach targeted at improving the user experience by optimizing the system performance for handling data that originates at the sensors, traverses the mesh network, and resides at the server for user consumption. This holistic approach enables users to set high level policies that can adapt the resolution of information collected at the sensors, set the preferred performance targets for their application, and run a wide range of queries and analysis on both real-time and historical data. All system components and processes will be described in this paper.

Design and Implementation of a Wireless Sensor and Actuator Network to Support the Intelligent Control of Efficient Energy Usage.

PubMed

Blanco, Jesús; García, Andrés; Morenas, Javier de Las

2018-06-09

Energy saving has become a major concern for the developed society of our days. This paper presents a Wireless Sensor and Actuator Network (WSAN) designed to provide support to an automatic intelligent system, based on the Internet of Things (IoT), which enables a responsible consumption of energy. The proposed overall system performs an efficient energetic management of devices, machines and processes, optimizing their operation to achieve a reduction in their overall energy usage at any given time. For this purpose, relevant data is collected from intelligent sensors, which are in-stalled at the required locations, as well as from the energy market through the Internet. This information is analysed to provide knowledge about energy utilization, and to improve efficiency. The system takes autonomous decisions automatically, based on the available information and the specific requirements in each case. The proposed system has been implanted and tested in a food factory. Results show a great optimization of energy efficiency and a substantial improvement on energy and costs savings.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Commercial Applications Multispectral Sensor System

NASA Technical Reports Server (NTRS)

Birk, Ronald J.; Spiering, Bruce

1993-01-01

NASA's Office of Commercial Programs is funding a multispectral sensor system to be used in the development of remote sensing applications. The Airborne Terrestrial Applications Sensor (ATLAS) is designed to provide versatility in acquiring spectral and spatial information. The ATLAS system will be a test bed for the development of specifications for airborne and spaceborne remote sensing instrumentation for dedicated applications. This objective requires spectral coverage from the visible through thermal infrared wavelengths, variable spatial resolution from 2-25 meters; high geometric and geo-location accuracy; on-board radiometric calibration; digital recording; and optimized performance for minimized cost, size, and weight. ATLAS is scheduled to be available in 3rd quarter 1992 for acquisition of data for applications such as environmental monitoring, facilities management, geographic information systems data base development, and mineral exploration.

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.

Integrated Structural/Control Design via Multiobjective Optimization

DTIC Science & Technology

1990-05-10

motivation is to yield a tractable 0 problem whose solution is readily synthesized and easily implemented. Likewise, the combinatorial approaches to...stations PsI, Ps2, Ps3, Ps4 on arms 3 and 4 and stations Ps5, Ps6, Ps7, Ps8 on arms I and 2. The sensor influence matrix H is 1 oT 0T 0 UoT (psi) T H= 0...t, Ps4 ), v (t,psS) ..... v (t,Ps8) ] T (4-30a) -V = Yp (4-30b) The locations Pul and Pu2 of the torque actuators and Psi, Ps2 .... Ps8 of the sensors

Optimum electrode configuration selection for electrical resistance change based damage detection in composites using an effective independence measure

NASA Astrophysics Data System (ADS)

Escalona, Luis; Díaz-Montiel, Paulina; Venkataraman, Satchi

2016-04-01

Laminated carbon fiber reinforced polymer (CFRP) composite materials are increasingly used in aerospace structures due to their superior mechanical properties and reduced weight. Assessing the health and integrity of these structures requires non-destructive evaluation (NDE) techniques to detect and measure interlaminar delamination and intralaminar matrix cracking damage. The electrical resistance change (ERC) based NDE technique uses the inherent changes in conductive properties of the composite to characterize internal damage. Several works that have explored the ERC technique have been limited to thin cross-ply laminates with simple linear or circular electrode arrangements. This paper investigates a method of optimum selection of electrode configurations for delamination detection in thick cross-ply laminates using ERC. Inverse identification of damage requires numerical optimization of the measured response with a model predicted response. Here, the electrical voltage field in the CFRP composite laminate is calculated using finite element analysis (FEA) models for different specified delamination size and locations, and location of ground and current electrodes. Reducing the number of sensor locations and measurements is needed to reduce hardware requirements, and computational effort needed for inverse identification. This paper explores the use of effective independence (EI) measure originally proposed for sensor location optimization in experimental vibration modal analysis. The EI measure is used for selecting the minimum set of resistance measurements among all possible combinations of selecting a pair of electrodes among the n electrodes. To enable use of EI to ERC required, it is proposed in this research a singular value decomposition SVD to obtain a spectral representation of the resistance measurements in the laminate. The effectiveness of EI measure in eliminating redundant electrode pairs is demonstrated by performing inverse identification of damage using the full set of resistance measurements and the reduced set of measurements. The investigation shows that the EI measure is effective for optimally selecting the electrode pairs needed for resistance measurements in ERC based damage detection.

Passive wireless sensor systems can recognize activites of daily living.

PubMed

Urwyler, Prabitha; Stucki, Reto; Muri, Rene; Mosimann, Urs P; Nef, Tobias

2015-08-01

The ability to determine what activity of daily living a person performs is of interest in many application domains. It is possible to determine the physical and cognitive capabilities of the elderly by inferring what activities they perform in their houses. Our primary aim was to establish a proof of concept that a wireless sensor system can monitor and record physical activity and these data can be modeled to predict activities of daily living. The secondary aim was to determine the optimal placement of the sensor boxes for detecting activities in a room. A wireless sensor system was set up in a laboratory kitchen. The ten healthy participants were requested to make tea following a defined sequence of tasks. Data were collected from the eight wireless sensor boxes placed in specific places in the test kitchen and analyzed to detect the sequences of tasks performed by the participants. These sequence of tasks were trained and tested using the Markov Model. Data analysis focused on the reliability of the system and the integrity of the collected data. The sequence of tasks were successfully recognized for all subjects and the averaged data pattern of tasks sequences between the subjects had a high correlation. Analysis of the data collected indicates that sensors placed in different locations are capable of recognizing activities, with the movement detection sensor contributing the most to detection of tasks. The central top of the room with no obstruction of view was considered to be the best location to record data for activity detection. Wireless sensor systems show much promise as easily deployable to monitor and recognize activities of daily living.

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.

Exploration of Objective Functions for Optimal Placement of Weather Stations

NASA Astrophysics Data System (ADS)

Snyder, A.; Dietterich, T.; Selker, J. S.

2016-12-01

Many regions of Earth lack ground-based sensing of weather variables. For example, most countries in Sub-Saharan Africa do not have reliable weather station networks. This absence of sensor data has many consequences ranging from public safety (poor prediction and detection of severe weather events), to agriculture (lack of crop insurance), to science (reduced quality of world-wide weather forecasts, climate change measurement, etc.). The Trans-African Hydro-Meteorological Observatory (TAHMO.org) project seeks to address these problems by deploying and operating a large network of weather stations throughout Sub-Saharan Africa. To design the TAHMO network, we must determine where to locate each weather station. We can formulate this as the following optimization problem: Determine a set of N sites that jointly optimize the value of an objective function. The purpose of this poster is to propose and assess several objective functions. In addition to standard objectives (e.g., minimizing the summed squared error of interpolated values over the entire region), we consider objectives that minimize the maximum error over the region and objectives that optimize the detection of extreme events. An additional issue is that each station measures more than 10 variables—how should we balance the accuracy of our interpolated maps for each variable? Weather sensors inevitably drift out of calibration or fail altogether. How can we incorporate robustness to failed sensors into our network design? Another important requirement is that the network should make it possible to detect failed sensors by comparing their readings with those of other stations. How can this requirement be met? Finally, we provide an initial assessment of the computational cost of optimizing these various objective functions. We invite everyone to join the discussion at our poster by proposing additional objectives, identifying additional issues to consider, and expanding our bibliography of relevant papers. A prize (derived from grapes grown in Oregon) will be awarded for the most insightful contribution to the discussion!

Developing a robust wireless sensor network structure for environmental sensing

NASA Astrophysics Data System (ADS)

Zhang, Z.; Oroza, C.; Glaser, S. D.; Bales, R. C.; Conklin, M. H.

2013-12-01

The American River Hydrologic Observatory is being strategically deployed as a real-time ground-based measurement network that delivers accurate and timely information on snow conditions and other hydrologic attributes with a previously unheard of granularity of time and space. The basin-scale network involves 18 sub-networks set out at physiographically representative locations spanning the seasonally snow-covered half of the 5000 km2 American river basin. Each sub-network, covering about a 1-km2 area, consists of 10 wirelessly networked sensing nodes that continuously measure and telemeter temperature, and snow depth; plus selected locations are equipped with sensors for relative humidity, solar radiation, and soil moisture at several depths. The sensor locations were chosen to maximize the variance sampled for snow depth within the basin. Network design and deployment involves an iterative but efficient process. After sensor-station locations are determined, a robust network of interlinking sensor stations and signal repeaters must be constructed to route sensor data to a central base station with a two-way communicable data uplink. Data can then be uploaded from site to remote servers in real time through satellite and cell modems. Signal repeaters are placed for robustness of a self-healing network with redundant signal paths to the base station. Manual, trial-and-error heuristic approaches for node placement are inefficient and labor intensive. In that approach field personnel must restructure the network in real time and wait for new network statistics to be calculated at the base station before finalizing a placement, acting without knowledge of the global topography or overall network structure. We show how digital elevation plus high-definition aerial photographs to give foliage coverage can optimize planning of signal repeater placements and guarantee a robust network structure prior to the physical deployment. We can also 'stress test' the final network by simulating the failure of an individual node and investigating the effect and the self-healing ability of the stressed network. The resulting sensor network can survive temporary service interruption from a small subset of signal repeaters and sensor stations. The robustness and the resilient of the network performance ensure the integrity of the dataset and the real-time transmissibility during harsh conditions.

Robust Modal Filtering and Control of the X-56A Model with Simulated Fiber Optic Sensor Failures

NASA Technical Reports Server (NTRS)

Suh, Peter M.; Chin, Alexander W.; Marvis, Dimitri N.

2014-01-01

The X-56A aircraft is a remotely-piloted aircraft with flutter modes intentionally designed into the flight envelope. The X-56A program must demonstrate flight control while suppressing all unstable modes. A previous X-56A model study demonstrated a distributed-sensing-based active shape and active flutter suppression controller. The controller relies on an estimator which is sensitive to bias. This estimator is improved herein, and a real-time robust estimator is derived and demonstrated on 1530 fiber optic sensors. It is shown in simulation that the estimator can simultaneously reject 230 worst-case fiber optic sensor failures automatically. These sensor failures include locations with high leverage (or importance). To reduce the impact of leverage outliers, concentration based on a Mahalanobis trim criterion is introduced. A redescending M-estimator with Tukey bisquare weights is used to improve location and dispersion estimates within each concentration step in the presence of asymmetry (or leverage). A dynamic simulation is used to compare the concentrated robust estimator to a state-of-the-art real-time robust multivariate estimator. The estimators support a previously-derived mu-optimal shape controller. It is found that during the failure scenario, the concentrated modal estimator keeps the system stable.

A spatial domain decomposition approach to distributed H ∞ observer design of a linear unstable parabolic distributed parameter system with spatially discrete sensors

NASA Astrophysics Data System (ADS)

Wang, Jun-Wei; Liu, Ya-Qiang; Hu, Yan-Yan; Sun, Chang-Yin

2017-12-01

This paper discusses the design problem of distributed H∞ Luenberger-type partial differential equation (PDE) observer for state estimation of a linear unstable parabolic distributed parameter system (DPS) with external disturbance and measurement disturbance. Both pointwise measurement in space and local piecewise uniform measurement in space are considered; that is, sensors are only active at some specified points or applied at part thereof of the spatial domain. The spatial domain is decomposed into multiple subdomains according to the location of the sensors such that only one sensor is located at each subdomain. By using Lyapunov technique, Wirtinger's inequality at each subdomain, and integration by parts, a Lyapunov-based design of Luenberger-type PDE observer is developed such that the resulting estimation error system is exponentially stable with an H∞ performance constraint, and presented in terms of standard linear matrix inequalities (LMIs). For the case of local piecewise uniform measurement in space, the first mean value theorem for integrals is utilised in the observer design development. Moreover, the problem of optimal H∞ observer design is also addressed in the sense of minimising the attenuation level. Numerical simulation results are presented to show the satisfactory performance of the proposed design method.

Robust Modal Filtering and Control of the X-56A Model with Simulated Fiber Optic Sensor Failures

NASA Technical Reports Server (NTRS)

Suh, Peter M.; Chin, Alexander W.; Mavris, Dimitri N.

2016-01-01

The X-56A aircraft is a remotely-piloted aircraft with flutter modes intentionally designed into the flight envelope. The X-56A program must demonstrate flight control while suppressing all unstable modes. A previous X-56A model study demonstrated a distributed-sensing-based active shape and active flutter suppression controller. The controller relies on an estimator which is sensitive to bias. This estimator is improved herein, and a real-time robust estimator is derived and demonstrated on 1530 fiber optic sensors. It is shown in simulation that the estimator can simultaneously reject 230 worst-case fiber optic sensor failures automatically. These sensor failures include locations with high leverage (or importance). To reduce the impact of leverage outliers, concentration based on a Mahalanobis trim criterion is introduced. A redescending M-estimator with Tukey bisquare weights is used to improve location and dispersion estimates within each concentration step in the presence of asymmetry (or leverage). A dynamic simulation is used to compare the concentrated robust estimator to a state-of-the-art real-time robust multivariate estimator. The estimators support a previously-derived mu-optimal shape controller. It is found that during the failure scenario, the concentrated modal estimator keeps the system stable.

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.

An Efficient Location Verification Scheme for Static Wireless Sensor Networks.

PubMed

Kim, In-Hwan; Kim, Bo-Sung; Song, JooSeok

2017-01-24

In wireless sensor networks (WSNs), the accuracy of location information is vital to support many interesting applications. Unfortunately, sensors have difficulty in estimating their location when malicious sensors attack the location estimation process. Even though secure localization schemes have been proposed to protect location estimation process from attacks, they are not enough to eliminate the wrong location estimations in some situations. The location verification can be the solution to the situations or be the second-line defense. The problem of most of the location verifications is the explicit involvement of many sensors in the verification process and requirements, such as special hardware, a dedicated verifier and the trusted third party, which causes more communication and computation overhead. In this paper, we propose an efficient location verification scheme for static WSN called mutually-shared region-based location verification (MSRLV), which reduces those overheads by utilizing the implicit involvement of sensors and eliminating several requirements. In order to achieve this, we use the mutually-shared region between location claimant and verifier for the location verification. The analysis shows that MSRLV reduces communication overhead by 77% and computation overhead by 92% on average, when compared with the other location verification schemes, in a single sensor verification. In addition, simulation results for the verification of the whole network show that MSRLV can detect the malicious sensors by over 90% when sensors in the network have five or more neighbors.

An Efficient Location Verification Scheme for Static Wireless Sensor Networks

PubMed Central

Kim, In-hwan; Kim, Bo-sung; Song, JooSeok

2017-01-01

In wireless sensor networks (WSNs), the accuracy of location information is vital to support many interesting applications. Unfortunately, sensors have difficulty in estimating their location when malicious sensors attack the location estimation process. Even though secure localization schemes have been proposed to protect location estimation process from attacks, they are not enough to eliminate the wrong location estimations in some situations. The location verification can be the solution to the situations or be the second-line defense. The problem of most of the location verifications is the explicit involvement of many sensors in the verification process and requirements, such as special hardware, a dedicated verifier and the trusted third party, which causes more communication and computation overhead. In this paper, we propose an efficient location verification scheme for static WSN called mutually-shared region-based location verification (MSRLV), which reduces those overheads by utilizing the implicit involvement of sensors and eliminating several requirements. In order to achieve this, we use the mutually-shared region between location claimant and verifier for the location verification. The analysis shows that MSRLV reduces communication overhead by 77% and computation overhead by 92% on average, when compared with the other location verification schemes, in a single sensor verification. In addition, simulation results for the verification of the whole network show that MSRLV can detect the malicious sensors by over 90% when sensors in the network have five or more neighbors. PMID:28125007

Improved Battery State Estimation Using Novel Sensing Techniques

NASA Astrophysics Data System (ADS)

Abdul Samad, Nassim

Lithium-ion batteries have been considered a great complement or substitute for gasoline engines due to their high energy and power density capabilities among other advantages. However, these types of energy storage devices are still yet not widespread, mainly because of their relatively high cost and safety issues, especially at elevated temperatures. This thesis extends existing methods of estimating critical battery states using model-based techniques augmented by real-time measurements from novel temperature and force sensors. Typically, temperature sensors are located near the edge of the battery, and away from the hottest core cell regions, which leads to slower response times and increased errors in the prediction of core temperatures. New sensor technology allows for flexible sensor placement at the cell surface between cells in a pack. This raises questions about the optimal locations of these sensors for best observability and temperature estimation. Using a validated model, which is developed and verified using experiments in laboratory fixtures that replicate vehicle pack conditions, it is shown that optimal sensor placement can lead to better and faster temperature estimation. Another equally important state is the state of health or the capacity fading of the cell. This thesis introduces a novel method of using force measurements for capacity fade estimation. Monitoring capacity is important for defining the range of electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEVs). Current capacity estimation techniques require a full discharge to monitor capacity. The proposed method can complement or replace current methods because it only requires a shallow discharge, which is especially useful in EVs and PHEVs. Using the accurate state estimation accomplished earlier, a method for downsizing a battery pack is shown to effectively reduce the number of cells in a pack without compromising safety. The influence on the battery performance (e.g. temperature, utilization, capacity fade, and cost) while downsizing and shifting the nominal operating SOC is demonstrated via simulations. The contributions in this thesis aim to make EVs, HEVs and PHEVs less costly while maintaining safety and reliability as more people are transitioning towards more environmentally friendly means of transportation.

Node Redeployment Algorithm Based on Stratified Connected Tree for Underwater Sensor Networks

PubMed Central

Liu, Jun; Jiang, Peng; Wu, Feng; Yu, Shanen; Song, Chunyue

2016-01-01

During the underwater sensor networks (UWSNs) operation, node drift with water environment causes network topology changes. Periodic node location examination and adjustment are needed to maintain good network monitoring quality as long as possible. In this paper, a node redeployment algorithm based on stratified connected tree for UWSNs is proposed. At every network adjustment moment, self-examination and adjustment on node locations are performed firstly. If a node is outside the monitored space, it returns to the last location recorded in its memory along straight line. Later, the network topology is stratified into a connected tree that takes the sink node as the root node by broadcasting ready information level by level, which can improve the network connectivity rate. Finally, with synthetically considering network coverage and connectivity rates, and node movement distance, the sink node performs centralized optimization on locations of leaf nodes in the stratified connected tree. Simulation results show that the proposed redeployment algorithm can not only keep the number of nodes in the monitored space as much as possible and maintain good network coverage and connectivity rates during network operation, but also reduce node movement distance during node redeployment and prolong the network lifetime. PMID:28029124

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.

Significance and interest of dense seismic arrays for understanding the mechanics of clayey landslides: a test case of 150 nodes at Super-Sauze landslide

NASA Astrophysics Data System (ADS)

Provost, Floriane; Malet, Jean-Philippe; Hibert, Clément; Vergne, Jérôme

2017-04-01

Clayey landslides present various seismic sources generated by the slope deformation (rockfall, slidequakes, tremors, fluid transfers). However, the characterization of the micro-seismicity and the construction of advanced catalogs (classification of the seismic source, time, and location) are complex for such objects because of the variety of recorded signals, the low signal to noise ratios, the highly attenuating medium, and the small size of the object that limits the picking of the P and S-waves. A full understanding of the seismic sources is hence often difficult because of the few number of seismometers, the large distance source-to-sensor (> 50m) and because of the lack of a continous spatially distributed record of the slope deformation. Recent progress in the geophysical instrumentation allowed the deployment of a dense network of 150 ZLand nodes (Tesla Corp.) combined with a Ground-Based InSAR sensor (IDS, IBIS-FM) for a period of ca. 2 months at the Super-Sauze clayey landslide (South French Alps). The Zland nodes are vertical wireless seismometers with 12 days autonomy. Three nodes were co-located at 50 locations in the most active part of the landslide and above the main scarp with a sensor-to-sensor distance of ca. 50m and a sample frequency of 400Hz. The Ground-Based InSAR sensor was installed in front of the landslide at a distance of ca. 800m and acquired an image every 15 minutes. The seismic events are detected automatically based on their spectrogram content with Signal-to-Noise Ratio (SNR) larger than 1.5 and automatically classified using the Random Forest algorithm. The landslide endogenous sources are then located by optimization of the inter-trace correlation of the first arrivals. This experiment aims to document the deformation of the landslide by combining surface and in depth information and provides a new insight into the seismic sources interpretation. The spatial distribution of the deformation is compared to the location of the endogenous seismic events in order to analyze seismic vs. aseismic deformation.

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

Large Scale Environmental Monitoring through Integration of Sensor and Mesh Networks

PubMed Central

Jurdak, Raja; Nafaa, Abdelhamid; Barbirato, Alessio

2008-01-01

Monitoring outdoor environments through networks of wireless sensors has received interest for collecting physical and chemical samples at high spatial and temporal scales. A central challenge to environmental monitoring applications of sensor networks is the short communication range of the sensor nodes, which increases the complexity and cost of monitoring commodities that are located in geographically spread areas. To address this issue, we propose a new communication architecture that integrates sensor networks with medium range wireless mesh networks, and provides users with an advanced web portal for managing sensed information in an integrated manner. Our architecture adopts a holistic approach targeted at improving the user experience by optimizing the system performance for handling data that originates at the sensors, traverses the mesh network, and resides at the server for user consumption. This holistic approach enables users to set high level policies that can adapt the resolution of information collected at the sensors, set the preferred performance targets for their application, and run a wide range of queries and analysis on both real-time and historical data. All system components and processes will be described in this paper. PMID:27873941

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.

Optimized Routing of Intelligent, Mobile Sensors for Dynamic, Data-Driven Sampling

DTIC Science & Technology

2016-09-27

nonstationary random process that requires nonuniform sampling. The ap- proach incorporates complementary representations of an unknown process: the first...lookup table as follows. A uniform grid is created in the r-domain and mapped to the R-domain, which produces a nonuniform grid of locations in the R...vehicle coverage algorithm that invokes the coor- dinate transformation from the previous section to generate nonuniform sampling trajectories [54]. We

How to Detect the Location and Time of a Covert Chemical Attack: A Bayesian Approach

DTIC Science & Technology

2009-12-01

Inverse Problems, Design and Optimization Symposium 2004. Rio de Janeiro , Brazil. Chan, R., and Yee, E. (1997). A simple model for the probability...sensor interpretation applications and has been successfully applied, for example, to estimate the source strength of pollutant releases in multi...coagulation, and second-order pollutant diffusion in sorption- desorption, are not linear. Furthermore, wide uncertainty bounds exist for several of

Vibration suppression of a piezo-equipped cylindrical shell in a broad-band frequency domain

NASA Astrophysics Data System (ADS)

Loghmani, Ali; Danesh, Mohammad; Kwak, Moon K.; Keshmiri, Mehdi

2017-12-01

This paper focuses on the dynamic modeling of a cylindrical shell equipped with piezoceramic sensors and actuators, as well as the design of a broad band multi-input and multi-output linear quadratic Gaussian controller for the suppression of vibrations. The optimal locations of actuators are derived by Genetic Algorithm (GA) to effectively control the specific structural modes of the cylinder. The dynamic model is derived based on the Sanders shell theory and the energy approach for both the cylinder and the piezoelectric transducers, all of which reflect the piezoelectric effect. The natural vibration characteristics of the cylindrical shell are investigated both theoretically and experimentally. The theoretical predictions are in good agreement with the experimental results. Then, the broad band multi-input and multi-output linear quadratic Gaussian controller was designed and applied to the test article. An active vibration control experiment is carried out on the cylindrical shell and the digital control system is used to implement the proposed control algorithm. The experimental results show that vibrations of the cylindrical shell can be suppressed by the piezoceramic sensors and actuators along with the proposed controller. The optimal location of the actuators makes the proposed control system more efficient than other configurations.

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.

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.

Optimal sensor placement for control of a supersonic mixed-compression inlet with variable geometry

NASA Astrophysics Data System (ADS)

Moore, Kenneth Thomas

A method of using fluid dynamics models for the generation of models that are useable for control design and analysis is investigated. The problem considered is the control of the normal shock location in the VDC inlet, which is a mixed-compression, supersonic, variable-geometry inlet of a jet engine. A quasi-one-dimensional set of fluid equations incorporating bleed and moving walls is developed. An object-oriented environment is developed for simulation of flow systems under closed-loop control. A public interface between the controller and fluid classes is defined. A linear model representing the dynamics of the VDC inlet is developed from the finite difference equations, and its eigenstructure is analyzed. The order of this model is reduced using the square root balanced model reduction method to produce a reduced-order linear model that is suitable for control design and analysis tasks. A modification to this method that improves the accuracy of the reduced-order linear model for the purpose of sensor placement is presented and analyzed. The reduced-order linear model is used to develop a sensor placement method that quantifies as a function of the sensor location the ability of a sensor to provide information on the variable of interest for control. This method is used to develop a sensor placement metric for the VDC inlet. The reduced-order linear model is also used to design a closed loop control system to control the shock position in the VDC inlet. The object-oriented simulation code is used to simulate the nonlinear fluid equations under closed-loop control.

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.

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

Open architecture of smart sensor suites

NASA Astrophysics Data System (ADS)

Müller, Wilmuth; Kuwertz, Achim; Grönwall, Christina; Petersson, Henrik; Dekker, Rob; Reinert, Frank; Ditzel, Maarten

2017-10-01

Experiences from recent conflicts show the strong need for smart sensor suites comprising different multi-spectral imaging sensors as core elements as well as additional non-imaging sensors. Smart sensor suites should be part of a smart sensor network - a network of sensors, databases, evaluation stations and user terminals. Its goal is to optimize the use of various information sources for military operations such as situation assessment, intelligence, surveillance, reconnaissance, target recognition and tracking. Such a smart sensor network will enable commanders to achieve higher levels of situational awareness. Within the study at hand, an open system architecture was developed in order to increase the efficiency of sensor suites. The open system architecture for smart sensor suites, based on a system-of-systems approach, enables combining different sensors in multiple physical configurations, such as distributed sensors, co-located sensors combined in a single package, tower-mounted sensors, sensors integrated in a mobile platform, and trigger sensors. The architecture was derived from a set of system requirements and relevant scenarios. Its mode of operation is adaptable to a series of scenarios with respect to relevant objects of interest, activities to be observed, available transmission bandwidth, etc. The presented open architecture is designed in accordance with the NATO Architecture Framework (NAF). The architecture allows smart sensor suites to be part of a surveillance network, linked e.g. to a sensor planning system and a C4ISR center, and to be used in combination with future RPAS (Remotely Piloted Aircraft Systems) for supporting a more flexible dynamic configuration of RPAS payloads.

Entanglement-Based dc Magnetometry with Separated Ions*

NASA Astrophysics Data System (ADS)

Ruster, T.; Kaufmann, H.; Luda, M. A.; Kaushal, V.; Schmiegelow, C. T.; Schmidt-Kaler, F.; Poschinger, U. G.

2017-07-01

We demonstrate sensing of inhomogeneous dc magnetic fields by employing entangled trapped ions, which are shuttled in a segmented Paul trap. As sensor states, we use Bell states of the type |↑↓ ⟩ +ei φ|↓↑ ⟩ encoded in two 40Ca+ ions stored at different locations. The linear Zeeman effect leads to the accumulation of a relative phase φ , which serves for measuring the magnetic-field difference between the constituent locations. Common-mode magnetic-field fluctuations are rejected by the entangled sensor state, which gives rise to excellent sensitivity without employing dynamical decoupling and therefore enables accurate dc sensing. Consecutive measurements on sensor states encoded in the S1 /2 ground state and in the D5 /2 metastable state are used to separate an ac Zeeman shift from the linear dc Zeeman effect. We measure magnetic-field differences over distances of up to 6.2 mm, with accuracies down to 300 fT and sensitivities down to 12 pT /√{Hz }. Our sensing scheme features spatial resolutions in the 20-nm range. For optimizing the information gain while maintaining a high dynamic range, we implement an algorithm for Bayesian frequency estimation.

An adaptive procedure for defect identification problems in elasticity

NASA Astrophysics Data System (ADS)

Gutiérrez, Sergio; Mura, J.

2010-07-01

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

Design, manufacture and testing of an FBG-instrumented composite wing

NASA Astrophysics Data System (ADS)

Abouzeida, E.; Quinones, V.; Gowayed, Y.; Soobramaney, P.; Flowers, G.; Black, R. J.; Costa, J. M.; Faridian, F.; Moslehi, B.

2014-02-01

In this work, our research team investigated the efficacy of using optical static and dynamic strain sensing with embedded Fiber Bragg Gratings (FBGs) in structural health monitoring (SHM) of a model composite airplane wing. A one-fourth scale model of a T38 airplane wing was designed and manufactured using fabric reinforced polymer matrix composites with FBG sensors embedded under the top layer of the composite. The accuracy and durability of the sensors were evaluated at the coupon and structural levels utilizing static and dynamic testing. Strain measurements using embedded FBGs with an optical interrogator were found to be in agreement with values measured using other strain measuring devices and with results obtained using finite element analysis (ANSYS®). Preferred locations for the FBG sensors were identified in accordance with contour maps of internal strain distributions resulting from critical load cases. Manufacturing techniques used to address handling, survivability and durability of the embedded sensors during and post manufacturing of the composites were evaluated and optimized.

A novel angle computation and calibration algorithm of bio-inspired sky-light polarization navigation sensor.

PubMed

Xian, Zhiwen; Hu, Xiaoping; Lian, Junxiang; Zhang, Lilian; Cao, Juliang; Wang, Yujie; Ma, Tao

2014-09-15

Navigation plays a vital role in our daily life. As traditional and commonly used navigation technologies, Inertial Navigation System (INS) and Global Navigation Satellite System (GNSS) can provide accurate location information, but suffer from the accumulative error of inertial sensors and cannot be used in a satellite denied environment. The remarkable navigation ability of animals shows that the pattern of the polarization sky can be used for navigation. A bio-inspired POLarization Navigation Sensor (POLNS) is constructed to detect the polarization of skylight. Contrary to the previous approach, we utilize all the outputs of POLNS to compute input polarization angle, based on Least Squares, which provides optimal angle estimation. In addition, a new sensor calibration algorithm is presented, in which the installation angle errors and sensor biases are taken into consideration. Derivation and implementation of our calibration algorithm are discussed in detail. To evaluate the performance of our algorithms, simulation and real data test are done to compare our algorithms with several exiting algorithms. Comparison results indicate that our algorithms are superior to the others and are more feasible and effective in practice.

A Fiber Optic Doppler Sensor and Its Application in Debonding Detection for Composite Structures

PubMed Central

Li, Fucai; Murayama, Hideaki; Kageyama, Kazuro; Meng, Guang; Ohsawa, Isamu; Shirai, Takehiro

2010-01-01

Debonding is one of the most important damage forms in fiber-reinforced composite structures. This work was devoted to the debonding damage detection of lap splice joints in carbon fiber reinforced plastic (CFRP) structures, which is based on guided ultrasonic wave signals captured by using fiber optic Doppler (FOD) sensor with spiral shape. Interferometers based on two types of laser sources, namely the He-Ne laser and the infrared semiconductor laser, are proposed and compared in this study for the purpose of measuring Doppler frequency shift of the FOD sensor. Locations of the FOD sensors are optimized based on mechanical characteristics of lap splice joint. The FOD sensors are subsequently used to detect the guided ultrasonic waves propagating in the CFRP structures. By taking advantage of signal processing approaches, features of the guided wave signals can be revealed. The results demonstrate that debonding in the lap splice joint results in arrival time delay of the first package in the guided wave signals, which can be the characteristic for debonding damage inspection and damage extent estimation. PMID:22219698

A fiber optic Doppler sensor and its application in debonding detection for composite structures.

PubMed

Li, Fucai; Murayama, Hideaki; Kageyama, Kazuro; Meng, Guang; Ohsawa, Isamu; Shirai, Takehiro

2010-01-01

Debonding is one of the most important damage forms in fiber-reinforced composite structures. This work was devoted to the debonding damage detection of lap splice joints in carbon fiber reinforced plastic (CFRP) structures, which is based on guided ultrasonic wave signals captured by using fiber optic Doppler (FOD) sensor with spiral shape. Interferometers based on two types of laser sources, namely the He-Ne laser and the infrared semiconductor laser, are proposed and compared in this study for the purpose of measuring Doppler frequency shift of the FOD sensor. Locations of the FOD sensors are optimized based on mechanical characteristics of lap splice joint. The FOD sensors are subsequently used to detect the guided ultrasonic waves propagating in the CFRP structures. By taking advantage of signal processing approaches, features of the guided wave signals can be revealed. The results demonstrate that debonding in the lap splice joint results in arrival time delay of the first package in the guided wave signals, which can be the characteristic for debonding damage inspection and damage extent estimation.

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

Swarm Optimization-Based Magnetometer Calibration for Personal Handheld Devices

PubMed Central

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

2012-01-01

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

A Mathematical Formulation of the SCOLE Control Problem. Part 2: Optimal Compensator Design

NASA Technical Reports Server (NTRS)

Balakrishnan, A. V.

1988-01-01

The study initiated in Part 1 of this report is concluded and optimal feedback control (compensator) design for stability augmentation is considered, following the mathematical formulation developed in Part 1. Co-located (rate) sensors and (force and moment) actuators are assumed, and allowing for both sensor and actuator noise, stabilization is formulated as a stochastic regulator problem. Specializing the general theory developed by the author, a complete, closed form solution (believed to be new with this report) is obtained, taking advantage of the fact that the inherent structural damping is light. In particular, it is possible to solve in closed form the associated infinite-dimensional steady-state Riccati equations. The SCOLE model involves associated partial differential equations in a single space variable, but the compensator design theory developed is far more general since it is given in the abstract wave equation formulation. The results thus hold for any multibody system so long as the basic model is linear.

Uncooled infrared sensors for an integrated sniper location system

NASA Astrophysics Data System (ADS)

Spera, Timothy J.; Figler, Burton D.

1997-02-01

Since July of 1995, Lockheed Martin IR Imaging Systems of Lexington, Massachusetts has been developing an integrated sniper location system for the Advanced Research Projects Agency (ARPA) and for the Department of the Navy's Naval Command Control & Ocean Surveillance Center, RDTE Division in San Diego, California. This system integrates two technologies to provide an affordable and highly effective sniper detection and location capability. The integrated sniper location system is being developed for use by the military and by law enforcement agencies. It will be man portable and can be used by individuals, at fixed ground sites, on ground vehicles, and on low flying aircraft. The integrated sniper location system combines an acoustic warning system with an uncooled infrared warning system. The acoustic warner is being developed by SenTech, Inc. of Lexington, Massachusetts. This acoustic warner provides sniper detection and coarse location information based upon the muzzle blast of the sniper's weapon and/or upon the shock wave produced by the sniper's bullet, if the bullet is supersonic. The uncooled infrared warning system provides sniper detection and fine location information based upon the weapons's muzzle flash. Combining the two technologies improves detection probability and reduces false alarm rate. This paper describes the integrated sniper location system, focusing on the uncooled infrared sensor and its associated signal processing. In addition, preliminary results from Phase I testing of the system are presented. Finally, the paper addresses the plans for implementing Phases II and III, during which the system will be optimized in terms of detection and location performance, size, weight, power, and cost.

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

Characterization of a mine fire using atmospheric monitoring system sensor data.

PubMed

Yuan, L; Thomas, R A; Zhou, L

2017-06-01

Atmospheric monitoring systems (AMS) have been widely used in underground coal mines in the United States for the detection of fire in the belt entry and the monitoring of other ventilation-related parameters such as airflow velocity and methane concentration in specific mine locations. In addition to an AMS being able to detect a mine fire, the AMS data have the potential to provide fire characteristic information such as fire growth - in terms of heat release rate - and exact fire location. Such information is critical in making decisions regarding fire-fighting strategies, underground personnel evacuation and optimal escape routes. In this study, a methodology was developed to calculate the fire heat release rate using AMS sensor data for carbon monoxide concentration, carbon dioxide concentration and airflow velocity based on the theory of heat and species transfer in ventilation airflow. Full-scale mine fire experiments were then conducted in the Pittsburgh Mining Research Division's Safety Research Coal Mine using an AMS with different fire sources. Sensor data collected from the experiments were used to calculate the heat release rates of the fires using this methodology. The calculated heat release rate was compared with the value determined from the mass loss rate of the combustible material using a digital load cell. The experimental results show that the heat release rate of a mine fire can be calculated using AMS sensor data with reasonable accuracy.

Optimal design of hydrometric monitoring networks with dynamic components based on Information Theory

NASA Astrophysics Data System (ADS)

Alfonso, Leonardo; Chacon, Juan; Solomatine, Dimitri

2016-04-01

The EC-FP7 WeSenseIt project proposes the development of a Citizen Observatory of Water, aiming at enhancing environmental monitoring and forecasting with the help of citizens equipped with low-cost sensors and personal devices such as smartphones and smart umbrellas. In this regard, Citizen Observatories may complement the limited data availability in terms of spatial and temporal density, which is of interest, among other areas, to improve hydraulic and hydrological models. At this point, the following question arises: how can citizens, who are part of a citizen observatory, be optimally guided so that the data they collect and send is useful to improve modelling and water management? This research proposes a new methodology to identify the optimal location and timing of potential observations coming from moving sensors of hydrological variables. The methodology is based on Information Theory, which has been widely used in hydrometric monitoring design [1-4]. In particular, the concepts of Joint Entropy, as a measure of the amount of information that is contained in a set of random variables, which, in our case, correspond to the time series of hydrological variables captured at given locations in a catchment. The methodology presented is a step forward in the state of the art because it solves the multiobjective optimisation problem of getting simultaneously the minimum number of informative and non-redundant sensors needed for a given time, so that the best configuration of monitoring sites is found at every particular moment in time. To this end, the existing algorithms have been improved to make them efficient. The method is applied to cases in The Netherlands, UK and Italy and proves to have a great potential to complement the existing in-situ monitoring networks. [1] Alfonso, L., A. Lobbrecht, and R. Price (2010a), Information theory-based approach for location of monitoring water level gauges in polders, Water Resour. Res., 46(3), W03528 [2] Alfonso, L., A. Lobbrecht, and R. Price (2010b), Optimization of water level monitoring network in polder systems using information theory, WATER RESOURCES RESEARCH, 46(12), W12553,10.1029/2009wr008953. [3] Alfonso, L., L. He, A. Lobbrecht, and R. Price (2013), Information theory applied to evaluate the discharge monitoring network of the Magdalena River, Journal of Hydroinformatics, 15(1), 211-228 [4] Alfonso, L., E. Ridolfi, S. Gaytan-Aguilar, F. Napolitano, and F. Russo (2014), Ensemble Entropy for Monitoring Network Design, Entropy, 16(3), 1365-1375

Automatic detection and visualisation of MEG ripple oscillations in epilepsy.

PubMed

van Klink, Nicole; van Rosmalen, Frank; Nenonen, Jukka; Burnos, Sergey; Helle, Liisa; Taulu, Samu; Furlong, Paul Lawrence; Zijlmans, Maeike; Hillebrand, Arjan

2017-01-01

High frequency oscillations (HFOs, 80-500 Hz) in invasive EEG are a biomarker for the epileptic focus. Ripples (80-250 Hz) have also been identified in non-invasive MEG, yet detection is impeded by noise, their low occurrence rates, and the workload of visual analysis. We propose a method that identifies ripples in MEG through noise reduction, beamforming and automatic detection with minimal user effort. We analysed 15 min of presurgical resting-state interictal MEG data of 25 patients with epilepsy. The MEG signal-to-noise was improved by using a cross-validation signal space separation method, and by calculating ~ 2400 beamformer-based virtual sensors in the grey matter. Ripples in these sensors were automatically detected by an algorithm optimized for MEG. A small subset of the identified ripples was visually checked. Ripple locations were compared with MEG spike dipole locations and the resection area if available. Running the automatic detection algorithm resulted in on average 905 ripples per patient, of which on average 148 ripples were visually reviewed. Reviewing took approximately 5 min per patient, and identified ripples in 16 out of 25 patients. In 14 patients the ripple locations showed good or moderate concordance with the MEG spikes. For six out of eight patients who had surgery, the ripple locations showed concordance with the resection area: 4/5 with good outcome and 2/3 with poor outcome. Automatic ripple detection in beamformer-based virtual sensors is a feasible non-invasive tool for the identification of ripples in MEG. Our method requires minimal user effort and is easily applicable in a clinical setting.

Microwave Nondestructive Evaluation of Dielectric Materials with a Metamaterial Lens

NASA Technical Reports Server (NTRS)

Shreiber, Daniel; Gupta, Mool; Cravey, Robin L.

2008-01-01

A novel microwave Nondestructive Evaluation (NDE) sensor was developed in an attempt to increase the sensitivity of the microwave NDE method for detection of defects small relative to a wavelength. The sensor was designed on the basis of a negative index material (NIM) lens. Characterization of the lens was performed to determine its resonant frequency, index of refraction, focus spot size, and optimal focusing length (for proper sample location). A sub-wavelength spot size (3 dB) of 0.48 lambda was obtained. The proof of concept for the sensor was achieved when a fiberglass sample with a 3 mm diameter through hole (perpendicular to the propagation direction of the wave) was tested. The hole was successfully detected with an 8.2 cm wavelength electromagnetic wave. This method is able to detect a defect that is 0.037 lambda. This method has certain advantages over other far field and near field microwave NDE methods currently in use.

Development of Rotary-Wing UAS for Use in Atmospheric Sensing of Near-Storm Environments

NASA Astrophysics Data System (ADS)

Greene, B. R.; Chilson, P. B.; Salazar-Cerreno, J.; Duthoit, S.; Doyle, B.; Wolf, B.; Segales, A.; Fiebrich, C. A.; Waugh, S.; Fredrickson, S.; Oncley, S.; Tudor, L.; Semmer, S.

2017-12-01

The capabilities of small unmanned aircraft systems (sUAS) to make atmospheric observations is rapidly being realized as a means to collect previously unobtainable observations in the lowest part of Earth's atmosphere. However, in order for these systems to provide meaningful kinematic and thermodynamic data, it is imperative to establish an understanding of the strengths and limitations of the sensors and retrieval algorithms implemented in both controlled and realistic conditions. This initial objective is comprised of two experimental stages, the first of which is calibration of thermodynamic sensors against references from the Oklahoma Mesonet and the National Center for Atmospheric Research in order to understand their quasi-ideal response characteristics. Furthermore, efforts have been made to calculate horizontal wind fields using Euler angles derived from the sUAS's autopilot. The second stage is validation of these sensor performances once mounted onto a rotary-wing sUAS by comparing measurements with instrumented towers, radiosondes, and other sUAS. It appears that these measurements are robust provided that instrument packages are mounted such that they receive adequate air flow and proper solar shielding. Moreover, experiments to locate this optimal location have been performed, and involved systematically displacing the sensors and wind probe underneath the rotor wash in an isolated chamber using a linear actuator. Once a platform's atmospheric sensing capabilities are optimized, its utility has been proven in applications from turbulence to providing forecasters with quasi-real time profiles in convective environments deemed by the Storm Prediction Center to be of highest risk for severe thunderstorms. After addressing the development of platforms operated by the University of Oklahoma, results from recent field campaigns, Collaboration Leading Operational UAS Development for Meteorology and Atmospheric Physics (CLOUD-MAP) and Environmental Profiling and Initiation of Convection (EPIC), will be discussed. These campaigns demonstrated the potential for sUAS to improve forecasting abilities and our understanding of the atmosphere, and provide a bright outlook on the future of sUAS applications.

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

Delay-Aware Energy-Efficient Routing towards a Path-Fixed Mobile Sink in Industrial Wireless Sensor Networks.

PubMed

Wu, Shaobo; Chou, Wusheng; Niu, Jianwei; Guizani, Mohsen

2018-03-18

Wireless sensor networks (WSNs) involve more mobile elements with their widespread development in industries. Exploiting mobility present in WSNs for data collection can effectively improve the network performance. However, when the sink (i.e., data collector) path is fixed and the movement is uncontrollable, existing schemes fail to guarantee delay requirements while achieving high energy efficiency. This paper proposes a delay-aware energy-efficient routing algorithm for WSNs with a path-fixed mobile sink, named DERM, which can strike a desirable balance between the delivery latency and energy conservation. We characterize the object of DERM as realizing the energy-optimal anycast to time-varying destination regions, and introduce a location-based forwarding technique tailored for this problem. To reduce the control overhead, a lightweight sink location calibration method is devised, which cooperates with the rough estimation based on the mobility pattern to determine the sink location. We also design a fault-tolerant mechanism called track routing to tackle location errors for ensuring reliable and on-time data delivery. We comprehensively evaluate DERM by comparing it with two canonical routing schemes and a baseline solution presented in this work. Extensive evaluation results demonstrate that DERM can provide considerable energy savings while meeting the delay constraint and maintaining a high delivery ratio.

Delay-Aware Energy-Efficient Routing towards a Path-Fixed Mobile Sink in Industrial Wireless Sensor Networks

PubMed Central

Wu, Shaobo; Chou, Wusheng; Niu, Jianwei; Guizani, Mohsen

2018-01-01

Wireless sensor networks (WSNs) involve more mobile elements with their widespread development in industries. Exploiting mobility present in WSNs for data collection can effectively improve the network performance. However, when the sink (i.e., data collector) path is fixed and the movement is uncontrollable, existing schemes fail to guarantee delay requirements while achieving high energy efficiency. This paper proposes a delay-aware energy-efficient routing algorithm for WSNs with a path-fixed mobile sink, named DERM, which can strike a desirable balance between the delivery latency and energy conservation. We characterize the object of DERM as realizing the energy-optimal anycast to time-varying destination regions, and introduce a location-based forwarding technique tailored for this problem. To reduce the control overhead, a lightweight sink location calibration method is devised, which cooperates with the rough estimation based on the mobility pattern to determine the sink location. We also design a fault-tolerant mechanism called track routing to tackle location errors for ensuring reliable and on-time data delivery. We comprehensively evaluate DERM by comparing it with two canonical routing schemes and a baseline solution presented in this work. Extensive evaluation results demonstrate that DERM can provide considerable energy savings while meeting the delay constraint and maintaining a high delivery ratio. PMID:29562628

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.

Validation of Foot Placement Locations from Ankle Data of a Kinect v2 Sensor

PubMed Central

Geerse, Daphne; Coolen, Bert; Kolijn, Detmar; Roerdink, Melvyn

2017-01-01

The Kinect v2 sensor may be a cheap and easy to use sensor to quantify gait in clinical settings, especially when applied in set-ups integrating multiple Kinect sensors to increase the measurement volume. Reliable estimates of foot placement locations are required to quantify spatial gait parameters. This study aimed to systematically evaluate the effects of distance from the sensor, side and step length on estimates of foot placement locations based on Kinect’s ankle body points. Subjects (n = 12) performed stepping trials at imposed foot placement locations distanced 2 m or 3 m from the Kinect sensor (distance), for left and right foot placement locations (side), and for five imposed step lengths. Body points’ time series of the lower extremities were recorded with a Kinect v2 sensor, placed frontoparallelly on the left side, and a gold-standard motion-registration system. Foot placement locations, step lengths, and stepping accuracies were compared between systems using repeated-measures ANOVAs, agreement statistics and two one-sided t-tests to test equivalence. For the right side at the 2 m distance from the sensor we found significant between-systems differences in foot placement locations and step lengths, and evidence for nonequivalence. This distance by side effect was likely caused by differences in body orientation relative to the Kinect sensor. It can be reduced by using Kinect’s higher-dimensional depth data to estimate foot placement locations directly from the foot’s point cloud and/or by using smaller inter-sensor distances in the case of a multi-Kinect v2 set-up to estimate foot placement locations at greater distances from the sensor. PMID:28994731

Validation of Foot Placement Locations from Ankle Data of a Kinect v2 Sensor.

PubMed

Geerse, Daphne; Coolen, Bert; Kolijn, Detmar; Roerdink, Melvyn

2017-10-10

The Kinect v2 sensor may be a cheap and easy to use sensor to quantify gait in clinical settings, especially when applied in set-ups integrating multiple Kinect sensors to increase the measurement volume. Reliable estimates of foot placement locations are required to quantify spatial gait parameters. This study aimed to systematically evaluate the effects of distance from the sensor, side and step length on estimates of foot placement locations based on Kinect's ankle body points. Subjects (n = 12) performed stepping trials at imposed foot placement locations distanced 2 m or 3 m from the Kinect sensor (distance), for left and right foot placement locations (side), and for five imposed step lengths. Body points' time series of the lower extremities were recorded with a Kinect v2 sensor, placed frontoparallelly on the left side, and a gold-standard motion-registration system. Foot placement locations, step lengths, and stepping accuracies were compared between systems using repeated-measures ANOVAs, agreement statistics and two one-sided t -tests to test equivalence. For the right side at the 2 m distance from the sensor we found significant between-systems differences in foot placement locations and step lengths, and evidence for nonequivalence. This distance by side effect was likely caused by differences in body orientation relative to the Kinect sensor. It can be reduced by using Kinect's higher-dimensional depth data to estimate foot placement locations directly from the foot's point cloud and/or by using smaller inter-sensor distances in the case of a multi-Kinect v2 set-up to estimate foot placement locations at greater distances from the sensor.

Reputation-Based Secure Sensor Localization in Wireless Sensor Networks

PubMed Central

He, Jingsha; Xu, Jing; Zhu, Xingye; Zhang, Yuqiang; Zhang, Ting; Fu, Wanqing

2014-01-01

Location information of sensor nodes in wireless sensor networks (WSNs) is very important, for it makes information that is collected and reported by the sensor nodes spatially meaningful for applications. Since most current sensor localization schemes rely on location information that is provided by beacon nodes for the regular sensor nodes to locate themselves, the accuracy of localization depends on the accuracy of location information from the beacon nodes. Therefore, the security and reliability of the beacon nodes become critical in the localization of regular sensor nodes. In this paper, we propose a reputation-based security scheme for sensor localization to improve the security and the accuracy of sensor localization in hostile or untrusted environments. In our proposed scheme, the reputation of each beacon node is evaluated based on a reputation evaluation model so that regular sensor nodes can get credible location information from highly reputable beacon nodes to accomplish localization. We also perform a set of simulation experiments to demonstrate the effectiveness of the proposed reputation-based security scheme. And our simulation results show that the proposed security scheme can enhance the security and, hence, improve the accuracy of sensor localization in hostile or untrusted environments. PMID:24982940

Incorporation of beams into bossed diaphragm for a high sensitivity and overload micro pressure sensor

NASA Astrophysics Data System (ADS)

Yu, Zhongliang; Zhao, Yulong; Sun, Lu; Tian, Bian; Jiang, Zhuangde

2013-01-01

The paper presents a piezoresistive absolute micro pressure sensor, which is of great benefits for altitude location. In this investigation, the design, fabrication, and test of the sensor are involved. By analyzing the stress distribution of sensitive elements using finite element method, a novel structure through the introduction of sensitive beams into traditional bossed diaphragm is built up. The proposed configuration presents its advantages in terms of high sensitivity and high overload resistance compared with the conventional bossed diaphragm and flat diaphragm structures. Curve fittings of surface stress and deflection based on ANSYS simulation results are performed to establish the equations about the sensor. Nonlinear optimization by MATLAB is carried out to determine the structure dimensions. The output signals in both static and dynamic environments are evaluated. Silicon bulk micromachining technology is utilized to fabricate the sensor prototype, and the fabrication process is discussed. Experimental results demonstrate the sensor features a high sensitivity of 11.098 μV/V/Pa in the operating range of 500 Pa at room temperature, and a high overload resistance of 200 times overpressure to promise its survival under atmosphere. Due to the excellent performance above, the sensor can be applied in measuring the absolute micro pressure lower than 500 Pa.

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

NASA Astrophysics Data System (ADS)

Jeong, Junho; Kim, Seungkeun; Suk, Jinyoung

2017-12-01

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

Fusing Satellite-Derived Irradiance and Point Measurements through Optimal Interpolation

NASA Astrophysics Data System (ADS)

Lorenzo, A.; Morzfeld, M.; Holmgren, W.; Cronin, A.

2016-12-01

Satellite-derived irradiance is widely used throughout the design and operation of a solar power plant. While satellite-derived estimates cover a large area, they also have large errors compared to point measurements from sensors on the ground. We describe an optimal interpolation routine that fuses the broad spatial coverage of satellite-derived irradiance with the high accuracy of point measurements. The routine can be applied to any satellite-derived irradiance and point measurement datasets. Unique aspects of this work include the fact that information is spread using cloud location and thickness and that a number of point measurements are collected from rooftop PV systems. The routine is sensitive to errors in the satellite image geolocation, so care must be taken to adjust the cloud locations based on the solar and satellite geometries. Analysis of the optimal interpolation routine over Tucson, AZ, with 20 point measurements shows a significant improvement in the irradiance estimate for two distinct satellite image to irradiance algorithms. Improved irradiance estimates can be used for resource assessment, distributed generation production estimates, and irradiance forecasts.

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

PubMed

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

2017-07-19

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

Freezing of gait and fall detection in Parkinson's disease using wearable sensors: a systematic review.

PubMed

Silva de Lima, Ana Lígia; Evers, Luc J W; Hahn, Tim; Bataille, Lauren; Hamilton, Jamie L; Little, Max A; Okuma, Yasuyuki; Bloem, Bastiaan R; Faber, Marjan J

2017-08-01

Despite the large number of studies that have investigated the use of wearable sensors to detect gait disturbances such as Freezing of gait (FOG) and falls, there is little consensus regarding appropriate methodologies for how to optimally apply such devices. Here, an overview of the use of wearable systems to assess FOG and falls in Parkinson's disease (PD) and validation performance is presented. A systematic search in the PubMed and Web of Science databases was performed using a group of concept key words. The final search was performed in January 2017, and articles were selected based upon a set of eligibility criteria. In total, 27 articles were selected. Of those, 23 related to FOG and 4 to falls. FOG studies were performed in either laboratory or home settings, with sample sizes ranging from 1 PD up to 48 PD presenting Hoehn and Yahr stage from 2 to 4. The shin was the most common sensor location and accelerometer was the most frequently used sensor type. Validity measures ranged from 73-100% for sensitivity and 67-100% for specificity. Falls and fall risk studies were all home-based, including samples sizes of 1 PD up to 107 PD, mostly using one sensor containing accelerometers, worn at various body locations. Despite the promising validation initiatives reported in these studies, they were all performed in relatively small sample sizes, and there was a significant variability in outcomes measured and results reported. Given these limitations, the validation of sensor-derived assessments of PD features would benefit from more focused research efforts, increased collaboration among researchers, aligning data collection protocols, and sharing data sets.

A novel design for sap flux data acquisition in large research plots using open source components

NASA Astrophysics Data System (ADS)

Hawthorne, D. A.; Oishi, A. C.

2017-12-01

Sap flux sensors are a widely-used tool for estimating in-situ, tree-level transpiration rates. These probes are installed in the stems of multiple trees within a study area and are typically left in place throughout the year. Sensors vary in their design and theory of operation, but all require electrical power for a heating element and produce at least one analog signal that must be digitized for storage. There are two topologies traditionally adopted to energize these sensors and gather the data from them. In one, a single data logger and power source are used. Dedicated cables radiate out from the logger to supply power to each of the probes and retrieve analog signals. In the other layout, a standalone data logger is located at each monitored tree. Batteries must then be distributed throughout the plot to service these loggers. We present a hybrid solution based on industrial control systems that employs a central data logger and battery, but co-locates digitizing hardware with the sensors at each tree. Each hardware node is able to communicate and share power over wire links with neighboring nodes. The resulting network provides a fault-tolerant path between the logger and each sensor. The approach is optimized to limit disturbance of the study plot, protect signal integrity and to enhance system reliability. This open-source implementation is built on the Arduino micro-controller system and employs RS485 and Modbus communications protocols. It is supported by laptop based management software coded in Python. The system is designed to be readily fabricated and programmed by non-experts. It works with a variety of sap-flux measurement techniques and it is able to interface to additional environmental sensors.

Priority design parameters of industrialized optical fiber sensors in civil engineering

NASA Astrophysics Data System (ADS)

Wang, Huaping; Jiang, Lizhong; Xiang, Ping

2018-03-01

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

Optimal sensor fusion for land vehicle navigation

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

Morrow, J.D.

1990-10-01

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

Implementation and Analysis of a Wireless Sensor Network-Based Pet Location Monitoring System for Domestic Scenarios

PubMed Central

Aguirre, Erik; Lopez-Iturri, Peio; Azpilicueta, Leyre; Astrain, José Javier; Villadangos, Jesús; Santesteban, Daniel; Falcone, Francisco

2016-01-01

The flexibility of new age wireless networks and the variety of sensors to measure a high number of variables, lead to new scenarios where anything can be monitored by small electronic devices, thereby implementing Wireless Sensor Networks (WSN). Thanks to ZigBee, RFID or WiFi networks the precise location of humans or animals as well as some biological parameters can be known in real-time. However, since wireless sensors must be attached to biological tissues and they are highly dispersive, propagation of electromagnetic waves must be studied to deploy an efficient and well-working network. The main goal of this work is to study the influence of wireless channel limitations in the operation of a specific pet monitoring system, validated at physical channel as well as at functional level. In this sense, radio wave propagation produced by ZigBee devices operating at the ISM 2.4 GHz band is studied through an in-house developed 3D Ray Launching simulation tool, in order to analyze coverage/capacity relations for the optimal system selection as well as deployment strategy in terms of number of transceivers and location. Furthermore, a simplified dog model is developed for simulation code, considering not only its morphology but also its dielectric properties. Relevant wireless channel information such as power distribution, power delay profile and delay spread graphs are obtained providing an extensive wireless channel analysis. A functional dog monitoring system is presented, operating over the implemented ZigBee network and providing real time information to Android based devices. The proposed system can be scaled in order to consider different types of domestic pets as well as new user based functionalities. PMID:27589751

Implementation and Analysis of a Wireless Sensor Network-Based Pet Location Monitoring System for Domestic Scenarios.

PubMed

Aguirre, Erik; Lopez-Iturri, Peio; Azpilicueta, Leyre; Astrain, José Javier; Villadangos, Jesús; Santesteban, Daniel; Falcone, Francisco

2016-08-30

The flexibility of new age wireless networks and the variety of sensors to measure a high number of variables, lead to new scenarios where anything can be monitored by small electronic devices, thereby implementing Wireless Sensor Networks (WSN). Thanks to ZigBee, RFID or WiFi networks the precise location of humans or animals as well as some biological parameters can be known in real-time. However, since wireless sensors must be attached to biological tissues and they are highly dispersive, propagation of electromagnetic waves must be studied to deploy an efficient and well-working network. The main goal of this work is to study the influence of wireless channel limitations in the operation of a specific pet monitoring system, validated at physical channel as well as at functional level. In this sense, radio wave propagation produced by ZigBee devices operating at the ISM 2.4 GHz band is studied through an in-house developed 3D Ray Launching simulation tool, in order to analyze coverage/capacity relations for the optimal system selection as well as deployment strategy in terms of number of transceivers and location. Furthermore, a simplified dog model is developed for simulation code, considering not only its morphology but also its dielectric properties. Relevant wireless channel information such as power distribution, power delay profile and delay spread graphs are obtained providing an extensive wireless channel analysis. A functional dog monitoring system is presented, operating over the implemented ZigBee network and providing real time information to Android based devices. The proposed system can be scaled in order to consider different types of domestic pets as well as new user based functionalities.

Self-deployable mobile sensor networks for on-demand surveillance

NASA Astrophysics Data System (ADS)

Miao, Lidan; Qi, Hairong; Wang, Feiyi

2005-05-01

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

Strain-Based Damage Determination Using Finite Element Analysis for Structural Health Management

NASA Technical Reports Server (NTRS)

Hochhalter, Jacob D.; Krishnamurthy, Thiagaraja; Aguilo, Miguel A.

2016-01-01

A damage determination method is presented that relies on in-service strain sensor measurements. The method employs a gradient-based optimization procedure combined with the finite element method for solution to the forward problem. It is demonstrated that strains, measured at a limited number of sensors, can be used to accurately determine the location, size, and orientation of damage. Numerical examples are presented to demonstrate the general procedure. This work is motivated by the need to provide structural health management systems with a real-time damage characterization. The damage cases investigated herein are characteristic of point-source damage, which can attain critical size during flight. The procedure described can be used to provide prognosis tools with the current damage configuration.

On the importance of telemetric temperature sensor location during intraperitoneal implantation in rats.

PubMed

Chapon, P A; Bulla, J; Gauthier, A; Moussay, S

2014-04-01

This study aims to assess the thermal homogeneity of the intraperitoneal (IP) cavity and the relevance of using a fixed telemetric temperature sensor at a given location in studying rodents. Ten rats were intraperitoneally implanted with three Jonah® capsules each; after assessing the accuracy and reliability of the sensors. Two capsules were attached, one to the right iliac fossa (RIF) and the other to the left hypochondrium (LH), and another was placed between the intestines but not attached (Free). In the ex vivo condition, the differences between sensors and reference values remained in the range of ±0.1. In the in vivo condition, each sensor enabled the observation of temperature patterns. However, sensor location affected mean and median temperature values while the rats were moving freely. Indeed, temperature data collected in the LH were 0.1 significantly higher than those collected in the RIF and temperature data collected in the LH were 0.11 significantly higher than those collected with the Free capsules. In in vivo conditions, intra-sensor variability of temperature data was not affected by sensor location. Taking into account sensor accuracy, similar intra-sensor variability, and mean differences observed between the three locations, the impact of sensor location within the IP cavity could be considered negligible. In in vivo conditions, temperature differences between locations regularly exceeded ±0.2 and reached up to 2.5. These extreme values could be explained by behavioral factors such as food or water intake. Finally, considering the good thermal homogeneity of the IP cavity and possible adverse consequences of sensor attachment, it seems better to let sensors range free within the cavity.

Optimal Sensor Management and Signal Processing for New EMI Systems

DTIC Science & Technology

2010-09-01

adaptive techniques that would improve the speed of data collection and increase the mobility of a TEMTADS system. Although an active learning technique...data, SIG has simulated the active selection based on the data already collected at Camp SLO. In this setup, the active learning approach was constrained...to work only on a 5x5 grid (corresponding to twenty five transmitters and co-located receivers). The first technique assumes that active learning will

A Localization Method for Underwater Wireless Sensor Networks Based on Mobility Prediction and Particle Swarm Optimization Algorithms

PubMed Central

Zhang, Ying; Liang, Jixing; Jiang, Shengming; Chen, Wei

2016-01-01

Due to their special environment, Underwater Wireless Sensor Networks (UWSNs) are usually deployed over a large sea area and the nodes are usually floating. This results in a lower beacon node distribution density, a longer time for localization, and more energy consumption. Currently most of the localization algorithms in this field do not pay enough consideration on the mobility of the nodes. In this paper, by analyzing the mobility patterns of water near the seashore, a localization method for UWSNs based on a Mobility Prediction and a Particle Swarm Optimization algorithm (MP-PSO) is proposed. In this method, the range-based PSO algorithm is used to locate the beacon nodes, and their velocities can be calculated. The velocity of an unknown node is calculated by using the spatial correlation of underwater object’s mobility, and then their locations can be predicted. The range-based PSO algorithm may cause considerable energy consumption and its computation complexity is a little bit high, nevertheless the number of beacon nodes is relatively smaller, so the calculation for the large number of unknown nodes is succinct, and this method can obviously decrease the energy consumption and time cost of localizing these mobile nodes. The simulation results indicate that this method has higher localization accuracy and better localization coverage rate compared with some other widely used localization methods in this field. PMID:26861348

A Glider-Assisted Link Disruption Restoration Mechanism in Underwater Acoustic Sensor Networks.

PubMed

Jin, Zhigang; Wang, Ning; Su, Yishan; Yang, Qiuling

2018-02-07

Underwater acoustic sensor networks (UASNs) have become a hot research topic. In UASNs, nodes can be affected by ocean currents and external forces, which could result in sudden link disruption. Therefore, designing a flexible and efficient link disruption restoration mechanism to ensure the network connectivity is a challenge. In the paper, we propose a glider-assisted restoration mechanism which includes link disruption recognition and related link restoring mechanism. In the link disruption recognition mechanism, the cluster heads collect the link disruption information and then schedule gliders acting as relay nodes to restore the disrupted link. Considering the glider's sawtooth motion, we design a relay location optimization algorithm with a consideration of both the glider's trajectory and acoustic channel attenuation model. The utility function is established by minimizing the channel attenuation and the optimal location of glider is solved by a multiplier method. The glider-assisted restoration mechanism can greatly improve the packet delivery rate and reduce the communication energy consumption and it is more general for the restoration of different link disruption scenarios. The simulation results show that glider-assisted restoration mechanism can improve the delivery rate of data packets by 15-33% compared with cooperative opportunistic routing (OVAR), the hop-by-hop vector-based forwarding (HH-VBF) and the vector based forward (VBF) methods, and reduce communication energy consumption by 20-58% for a typical network's setting.

A Glider-Assisted Link Disruption Restoration Mechanism in Underwater Acoustic Sensor Networks

PubMed Central

Wang, Ning; Su, Yishan; Yang, Qiuling

2018-01-01

Underwater acoustic sensor networks (UASNs) have become a hot research topic. In UASNs, nodes can be affected by ocean currents and external forces, which could result in sudden link disruption. Therefore, designing a flexible and efficient link disruption restoration mechanism to ensure the network connectivity is a challenge. In the paper, we propose a glider-assisted restoration mechanism which includes link disruption recognition and related link restoring mechanism. In the link disruption recognition mechanism, the cluster heads collect the link disruption information and then schedule gliders acting as relay nodes to restore the disrupted link. Considering the glider’s sawtooth motion, we design a relay location optimization algorithm with a consideration of both the glider’s trajectory and acoustic channel attenuation model. The utility function is established by minimizing the channel attenuation and the optimal location of glider is solved by a multiplier method. The glider-assisted restoration mechanism can greatly improve the packet delivery rate and reduce the communication energy consumption and it is more general for the restoration of different link disruption scenarios. The simulation results show that glider-assisted restoration mechanism can improve the delivery rate of data packets by 15–33% compared with cooperative opportunistic routing (OVAR), the hop-by-hop vector-based forwarding (HH-VBF) and the vector based forward (VBF) methods, and reduce communication energy consumption by 20–58% for a typical network’s setting. PMID:29414898

State estimation of spatio-temporal phenomena

NASA Astrophysics Data System (ADS)

Yu, Dan

This dissertation addresses the state estimation problem of spatio-temporal phenomena which can be modeled by partial differential equations (PDEs), such as pollutant dispersion in the atmosphere. After discretizing the PDE, the dynamical system has a large number of degrees of freedom (DOF). State estimation using Kalman Filter (KF) is computationally intractable, and hence, a reduced order model (ROM) needs to be constructed first. Moreover, the nonlinear terms, external disturbances or unknown boundary conditions can be modeled as unknown inputs, which leads to an unknown input filtering problem. Furthermore, the performance of KF could be improved by placing sensors at feasible locations. Therefore, the sensor scheduling problem to place multiple mobile sensors is of interest. The first part of the dissertation focuses on model reduction for large scale systems with a large number of inputs/outputs. A commonly used model reduction algorithm, the balanced proper orthogonal decomposition (BPOD) algorithm, is not computationally tractable for large systems with a large number of inputs/outputs. Inspired by the BPOD and randomized algorithms, we propose a randomized proper orthogonal decomposition (RPOD) algorithm and a computationally optimal RPOD (RPOD*) algorithm, which construct an ROM to capture the input-output behaviour of the full order model, while reducing the computational cost of BPOD by orders of magnitude. It is demonstrated that the proposed RPOD* algorithm could construct the ROM in real-time, and the performance of the proposed algorithms on different advection-diffusion equations. Next, we consider the state estimation problem of linear discrete-time systems with unknown inputs which can be treated as a wide-sense stationary process with rational power spectral density, while no other prior information needs to be known. We propose an autoregressive (AR) model based unknown input realization technique which allows us to recover the input statistics from the output data by solving an appropriate least squares problem, then fit an AR model to the recovered input statistics and construct an innovations model of the unknown inputs using the eigensystem realization algorithm. The proposed algorithm outperforms the augmented two-stage Kalman Filter (ASKF) and the unbiased minimum-variance (UMV) algorithm are shown in several examples. Finally, we propose a framework to place multiple mobile sensors to optimize the long-term performance of KF in the estimation of the state of a PDE. The major challenges are that placing multiple sensors is an NP-hard problem, and the optimization problem is non-convex in general. In this dissertation, first, we construct an ROM using RPOD* algorithm, and then reduce the feasible sensor locations into a subset using the ROM. The Information Space Receding Horizon Control (I-RHC) approach and a modified Monte Carlo Tree Search (MCTS) approach are applied to solve the sensor scheduling problem using the subset. Various applications have been provided to demonstrate the performance of the proposed approach.

Optical-fibre sensor system for monitoring the performance of the gas propellant centrifuge separator of a spacecraft

NASA Astrophysics Data System (ADS)

Romo-Medrano, Katya E.; Khotiaintsev, Sergei N.; García-Garduño, Victor

2004-08-01

An optical-fibre sensor system is presented for monitoring void fraction distribution in a spacecraft's gas and propellant centrifuge separator. The system could be used at the separator development stage or for monitoring, during ground tests, the elements of the spacecraft propulsion system. Our sensor system employs an array of point optical-fibre refractometric transducers installed in the form of several linear radial arrays on the separator rotating blades. We employed a small-size hemispherical optical detection element as the transducer and we optimized its parameters through numerical ray-tracing. The aim is to minimize the effect of the thin film of liquid that forms on the transducer's surface in this application. The features of this sensor system are: (1) an efficient matrix-type multiplexing scheme, (2) the installation of the main optoelectronic unit of the sensor in a hermetically sealed container inside the separator tank located on the rotating shaft and (3) the spark-proof and explosion-proof design of the sensor circuits and elements. The sensor is simple, reliable, low-cost and is capable of withstanding the factors involved during operation of the propulsion system such as cryogenic temperatures and chemically aggressive liquids. The novel elements and design concepts implemented in this sensor system can also find applications in other sensors for spacecraft propulsion systems and also in a variety of optical-fibre sensors used in scientific research and industry.

Optimal Multi-Type Sensor Placement for Structural Identification by Static-Load Testing

PubMed Central

Papadopoulou, Maria; Vernay, Didier; Smith, Ian F. C.

2017-01-01

Assessing ageing infrastructure is a critical challenge for civil engineers due to the difficulty in the estimation and integration of uncertainties in structural models. Field measurements are increasingly used to improve knowledge of the real behavior of a structure; this activity is called structural identification. Error-domain model falsification (EDMF) is an easy-to-use model-based structural-identification methodology which robustly accommodates systematic uncertainties originating from sources such as boundary conditions, numerical modelling and model fidelity, as well as aleatory uncertainties from sources such as measurement error and material parameter-value estimations. In most practical applications of structural identification, sensors are placed using engineering judgment and experience. However, since sensor placement is fundamental to the success of structural identification, a more rational and systematic method is justified. This study presents a measurement system design methodology to identify the best sensor locations and sensor types using information from static-load tests. More specifically, three static-load tests were studied for the sensor system design using three types of sensors for a performance evaluation of a full-scale bridge in Singapore. Several sensor placement strategies are compared using joint entropy as an information-gain metric. A modified version of the hierarchical algorithm for sensor placement is proposed to take into account mutual information between load tests. It is shown that a carefully-configured measurement strategy that includes multiple sensor types and several load tests maximizes information gain. PMID:29240684

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.

Objectively Optimized Observation Direction System Providing Situational Awareness for a Sensor Web

NASA Astrophysics Data System (ADS)

Aulov, O.; Lary, D. J.

2010-12-01

There is great utility in having a flexible and automated objective observation direction system for the decadal survey missions and beyond. Such a system allows us to optimize the observations made by suite of sensors to address specific goals from long term monitoring to rapid response. We have developed such a prototype using a network of communicating software elements to control a heterogeneous network of sensor systems, which can have multiple modes and flexible viewing geometries. Our system makes sensor systems intelligent and situationally aware. Together they form a sensor web of multiple sensors working together and capable of automated target selection, i.e. the sensors “know” where they are, what they are able to observe, what targets and with what priorities they should observe. This system is implemented in three components. The first component is a Sensor Web simulator. The Sensor Web simulator describes the capabilities and locations of each sensor as a function of time, whether they are orbital, sub-orbital, or ground based. The simulator has been implemented using AGIs Satellite Tool Kit (STK). STK makes it easy to analyze and visualize optimal solutions for complex space scenarios, and perform complex analysis of land, sea, air, space assets, and shares results in one integrated solution. The second component is target scheduler that was implemented with STK Scheduler. STK Scheduler is powered by a scheduling engine that finds better solutions in a shorter amount of time than traditional heuristic algorithms. The global search algorithm within this engine is based on neural network technology that is capable of finding solutions to larger and more complex problems and maximizing the value of limited resources. The third component is a modeling and data assimilation system. It provides situational awareness by supplying the time evolution of uncertainty and information content metrics that are used to tell us what we need to observe and the priority we should give to the observations. A prototype of this component was implemented with AutoChem. AutoChem is NASA release software constituting an automatic code generation, symbolic differentiator, analysis, documentation, and web site creation tool for atmospheric chemical modeling and data assimilation. Its model is explicit and uses an adaptive time-step, error monitoring time integration scheme for stiff systems of equations. AutoChem was the first model to ever have the facility to perform 4D-Var data assimilation and Kalman filter. The project developed a control system with three main accomplishments. First, fully multivariate observational and theoretical information with associated uncertainties was combined using a full Kalman filter data assimilation system. Second, an optimal distribution of the computations and of data queries was achieved by utilizing high performance computers/load balancing and a set of automatically mirrored databases. Third, inter-instrument bias correction was performed using machine learning. The PI for this project was Dr. David Lary of the UMBC Joint Center for Earth Systems Technology at NASA/Goddard Space Flight Center.

An Energy-Efficient Mobile Sink-Based Unequal Clustering Mechanism for WSNs.

PubMed

Gharaei, Niayesh; Abu Bakar, Kamalrulnizam; Mohd Hashim, Siti Zaiton; Hosseingholi Pourasl, Ali; Siraj, Mohammad; Darwish, Tasneem

2017-08-11

Network lifetime and energy efficiency are crucial performance metrics used to evaluate wireless sensor networks (WSNs). Decreasing and balancing the energy consumption of nodes can be employed to increase network lifetime. In cluster-based WSNs, one objective of applying clustering is to decrease the energy consumption of the network. In fact, the clustering technique will be considered effective if the energy consumed by sensor nodes decreases after applying clustering, however, this aim will not be achieved if the cluster size is not properly chosen. Therefore, in this paper, the energy consumption of nodes, before clustering, is considered to determine the optimal cluster size. A two-stage Genetic Algorithm (GA) is employed to determine the optimal interval of cluster size and derive the exact value from the interval. Furthermore, the energy hole is an inherent problem which leads to a remarkable decrease in the network's lifespan. This problem stems from the asynchronous energy depletion of nodes located in different layers of the network. For this reason, we propose Circular Motion of Mobile-Sink with Varied Velocity Algorithm (CM2SV2) to balance the energy consumption ratio of cluster heads (CH). According to the results, these strategies could largely increase the network's lifetime by decreasing the energy consumption of sensors and balancing the energy consumption among CHs.

Precision Sensing by Two Opposing Gradient Sensors: How Does Escherichia coli Find its Preferred pH Level?

PubMed Central

Hu, Bo; Tu, Yuhai

2013-01-01

It is essential for bacteria to find optimal conditions for their growth and survival. The optimal levels of certain environmental factors (such as pH and temperature) often correspond to some intermediate points of the respective gradients. This requires the ability of bacteria to navigate from both directions toward the optimum location and is distinct from the conventional unidirectional chemotactic strategy. Remarkably, Escherichia coli cells can perform such a precision sensing task in pH taxis by using the same chemotaxis machinery, but with opposite pH responses from two different chemoreceptors (Tar and Tsr). To understand bacterial pH sensing, we developed an Ising-type model for a mixed cluster of opposing receptors based on the push-pull mechanism. Our model can quantitatively explain experimental observations in pH taxis for various mutants and wild-type cells. We show how the preferred pH level depends on the relative abundance of the competing sensors and how the sensory activity regulates the behavioral response. Our model allows us to make quantitative predictions on signal integration of pH and chemoattractant stimuli. Our study reveals two general conditions and a robust push-pull scheme for precision sensing, which should be applicable in other adaptive sensory systems with opposing gradient sensors. PMID:23823247

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 experimental designs for the estimation of thermal properties of composite materials

NASA Technical Reports Server (NTRS)

Scott, Elaine P.; Moncman, Deborah A.

1994-01-01

Reliable estimation of thermal properties is extremely important in the utilization of new advanced materials, such as composite materials. The accuracy of these estimates can be increased if the experiments are designed carefully. The objectives of this study are to design optimal experiments to be used in the prediction of these thermal properties and to then utilize these designs in the development of an estimation procedure to determine the effective thermal properties (thermal conductivity and volumetric heat capacity). The experiments were optimized by choosing experimental parameters that maximize the temperature derivatives with respect to all of the unknown thermal properties. This procedure has the effect of minimizing the confidence intervals of the resulting thermal property estimates. Both one-dimensional and two-dimensional experimental designs were optimized. A heat flux boundary condition is required in both analyses for the simultaneous estimation of the thermal properties. For the one-dimensional experiment, the parameters optimized were the heating time of the applied heat flux, the temperature sensor location, and the experimental time. In addition to these parameters, the optimal location of the heat flux was also determined for the two-dimensional experiments. Utilizing the optimal one-dimensional experiment, the effective thermal conductivity perpendicular to the fibers and the effective volumetric heat capacity were then estimated for an IM7-Bismaleimide composite material. The estimation procedure used is based on the minimization of a least squares function which incorporates both calculated and measured temperatures and allows for the parameters to be estimated simultaneously.

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2013-12-24

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

Active Control Technology at NASA Langley Research Center

NASA Technical Reports Server (NTRS)

Antcliff, Richard R.; McGowan, Anna-Marie R.

2000-01-01

NASA Langley has a long history of attacking important technical opportunities from a broad base of supporting disciplines. The research and development at Langley in this subject area range from the test tube to the test flight. The information covered here will range from the development of innovative new materials, sensors and actuators, to the incorporation of smart sensors and actuators in practical devices, to the optimization of the location of these devices, to, finally, a wide variety of applications of these devices utilizing Langley's facilities and expertise. Advanced materials are being developed for sensors and actuators, as well as polymers for integrating smart devices into composite structures. Contributions reside in three key areas: computational materials; advanced piezoelectric materials; and integrated composite structures. The computational materials effort is focused on developing predictive tools for the efficient design of new materials with the appropriate combination of properties for next generation smart airframe systems. Research in the area of advanced piezoelectrics includes optimizing the efficiency, force output, use temperature, and energy transfer between the structure and device for both ceramic and polymeric materials. For structural health monitoring, advanced non-destructive techniques including fiber optics are being developed for detection of delaminations, cracks and environmental deterioration in aircraft structures. The computational materials effort is focused on developing predictive tools for the efficient design of new materials with the appropriate combination of properties for next generation smart airframe system. Innovative fabrication techniques processing structural composites with sensor and actuator integration are being developed.

Optimal Parameter Exploration for Online Change-Point Detection in Activity Monitoring Using Genetic Algorithms

PubMed Central

Khan, Naveed; McClean, Sally; Zhang, Shuai; Nugent, Chris

2016-01-01

In recent years, smart phones with inbuilt sensors have become popular devices to facilitate activity recognition. The sensors capture a large amount of data, containing meaningful events, in a short period of time. The change points in this data are used to specify transitions to distinct events and can be used in various scenarios such as identifying change in a patient’s vital signs in the medical domain or requesting activity labels for generating real-world labeled activity datasets. Our work focuses on change-point detection to identify a transition from one activity to another. Within this paper, we extend our previous work on multivariate exponentially weighted moving average (MEWMA) algorithm by using a genetic algorithm (GA) to identify the optimal set of parameters for online change-point detection. The proposed technique finds the maximum accuracy and F_measure by optimizing the different parameters of the MEWMA, which subsequently identifies the exact location of the change point from an existing activity to a new one. Optimal parameter selection facilitates an algorithm to detect accurate change points and minimize false alarms. Results have been evaluated based on two real datasets of accelerometer data collected from a set of different activities from two users, with a high degree of accuracy from 99.4% to 99.8% and F_measure of up to 66.7%. PMID:27792177

Optimum sensor placement for microphone arrays

NASA Astrophysics Data System (ADS)

Rabinkin, Daniel V.

Microphone arrays can be used for high-quality sound pickup in reverberant and noisy environments. Sound capture using conventional single microphone methods suffers severe degradation under these conditions. The beamforming capabilities of microphone array systems allow highly directional sound capture, providing enhanced signal-to-noise ratio (SNR) when compared to single microphone performance. The overall performance of an array system is governed by its ability to locate and track sound sources and its ability to capture sound from desired spatial volumes. These abilities are strongly affected by the spatial placement of microphone sensors. A method is needed to optimize placement for a specified number of sensors in a given acoustical environment. The objective of the optimization is to obtain the greatest average system SNR for sound capture in the region of interest. A two-step sound source location method is presented. In the first step, time delay of arrival (TDOA) estimates for select microphone pairs are determined using a modified version of the Omologo-Svaizer cross-power spectrum phase expression. In the second step, the TDOA estimates are used in a least-mean-squares gradient descent search algorithm to obtain a location estimate. Statistics for TDOA estimate error as a function of microphone pair/sound source geometry and acoustic environment are gathered from a set of experiments. These statistics are used to model position estimation accuracy for a given array geometry. The effectiveness of sound source capture is also dependent on array geometry and the acoustical environment. Simple beamforming and time delay compensation (TDC) methods provide spatial selectivity but suffer performance degradation in reverberant environments. Matched filter array (MFA) processing can mitigate the effects of reverberation. The shape and gain advantage of the capture region for these techniques is described and shown to be highly influenced by the placement of array sensors. A procedure is developed to evaluate a given array configuration based on the above-mentioned metrics. Constrained placement optimizations are performed that maximize SNR for both TDC and MFA capture methods. Results are compared for various acoustic environments and various enclosure sizes. General guidelines are presented for placement strategy and bandwidth dependence, as they relate to reverberation levels, ambient noise, and enclosure geometry. An overall performance function is described based on these metrics. Performance of the microphone array system is also constrained by the design limitations of the supporting hardware. Two newly developed hardware architectures are presented that support the described algorithms. A low- cost 8-channel system with off-the-shelf componentry was designed and its performance evaluated. A massively parallel 512-channel custom-built system is in development-its capabilities and the rationale for its design are described.

A Novel Angle Computation and Calibration Algorithm of Bio-Inspired Sky-Light Polarization Navigation Sensor

PubMed Central

Xian, Zhiwen; Hu, Xiaoping; Lian, Junxiang; Zhang, Lilian; Cao, Juliang; Wang, Yujie; Ma, Tao

2014-01-01

Navigation plays a vital role in our daily life. As traditional and commonly used navigation technologies, Inertial Navigation System (INS) and Global Navigation Satellite System (GNSS) can provide accurate location information, but suffer from the accumulative error of inertial sensors and cannot be used in a satellite denied environment. The remarkable navigation ability of animals shows that the pattern of the polarization sky can be used for navigation. A bio-inspired POLarization Navigation Sensor (POLNS) is constructed to detect the polarization of skylight. Contrary to the previous approach, we utilize all the outputs of POLNS to compute input polarization angle, based on Least Squares, which provides optimal angle estimation. In addition, a new sensor calibration algorithm is presented, in which the installation angle errors and sensor biases are taken into consideration. Derivation and implementation of our calibration algorithm are discussed in detail. To evaluate the performance of our algorithms, simulation and real data test are done to compare our algorithms with several exiting algorithms. Comparison results indicate that our algorithms are superior to the others and are more feasible and effective in practice. PMID:25225872

On-Board Event-Based State Estimation for Trajectory Approaching and Tracking of a Vehicle

PubMed Central

Martínez-Rey, Miguel; Espinosa, Felipe; Gardel, Alfredo; Santos, Carlos

2015-01-01

For the problem of pose estimation of an autonomous vehicle using networked external sensors, the processing capacity and battery consumption of these sensors, as well as the communication channel load should be optimized. Here, we report an event-based state estimator (EBSE) consisting of an unscented Kalman filter that uses a triggering mechanism based on the estimation error covariance matrix to request measurements from the external sensors. This EBSE generates the events of the estimator module on-board the vehicle and, thus, allows the sensors to remain in stand-by mode until an event is generated. The proposed algorithm requests a measurement every time the estimation distance root mean squared error (DRMS) value, obtained from the estimator's covariance matrix, exceeds a threshold value. This triggering threshold can be adapted to the vehicle's working conditions rendering the estimator even more efficient. An example of the use of the proposed EBSE is given, where the autonomous vehicle must approach and follow a reference trajectory. By making the threshold a function of the distance to the reference location, the estimator can halve the use of the sensors with a negligible deterioration in the performance of the approaching maneuver. PMID:26102489

Optical fiber evanescent absorption sensors for high-temperature gas sensing in advanced coal-fired power plants

NASA Astrophysics Data System (ADS)

Buric, Michael P.; Ohodnicky, Paul R.; Duy, Janice

2012-10-01

Modern advanced energy systems such as coal-fired power plants, gasifiers, or similar infrastructure present some of the most challenging harsh environments for sensors. The power industry would benefit from new, ultra-high temperature devices capable of surviving in hot and corrosive environments for embedded sensing at the highest value locations. For these applications, we are currently exploring optical fiber evanescent wave absorption spectroscopy (EWAS) based sensors consisting of high temperature core materials integrated with novel high temperature gas sensitive cladding materials. Mathematical simulations can be used to assist in sensor development efforts, and we describe a simulation code that assumes a single thick cladding layer with gas sensitive optical constants. Recent work has demonstrated that Au nanoparticle-incorporated metal oxides show a potentially useful response for high temperature optical gas sensing applications through the sensitivity of the localized surface plasmon resonance absorption peak to ambient atmospheric conditions. Hence, the simulation code has been applied to understand how such a response can be exploited in an optical fiber based EWAS sensor configuration. We demonstrate that interrogation can be used to optimize the sensing response in such materials.

Water Security Toolkit User Manual: Version 1.3 | Science ...

EPA Pesticide Factsheets

User manual: Data Product/Software The Water Security Toolkit (WST) is a suite of tools that help provide the information necessary to make good decisions resulting in the minimization of further human exposure to contaminants, and the maximization of the effectiveness of intervention strategies. WST assists in the evaluation of multiple response actions in order to select the most beneficial consequence management strategy. It includes hydraulic and water quality modeling software and optimization methodologies to identify: (1) sensor locations to detect contamination, (2) locations in the network in which the contamination was introduced, (3) hydrants to remove contaminated water from the distribution system, (4) locations in the network to inject decontamination agents to inactivate, remove or destroy contaminants, (5) locations in the network to take grab sample to confirm contamination or cleanup and (6) valves to close in order to isolate contaminated areas of the network.

40 CFR 63.1452 - What are my monitoring requirements?

Code of Federal Regulations, 2014 CFR

2014-07-01

... device, associated sensor(s), and recording equipment according to the manufacturers' specifications. Locate the sensor(s) used for monitoring in or as close to a position that provides a representative... section. (i) Locate the flow sensor and other necessary equipment such as straightening vanes in a...

40 CFR 63.1452 - What are my monitoring requirements?

Code of Federal Regulations, 2012 CFR

2012-07-01

... device, associated sensor(s), and recording equipment according to the manufacturers' specifications. Locate the sensor(s) used for monitoring in or as close to a position that provides a representative... section. (i) Locate the flow sensor and other necessary equipment such as straightening vanes in a...

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.

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

Potential of IMU Sensors in Performance Analysis of Professional Alpine Skiers

PubMed Central

Yu, Gwangjae; Jang, Young Jae; Kim, Jinhyeok; Kim, Jin Hae; Kim, Hye Young; Kim, Kitae; Panday, Siddhartha Bikram

2016-01-01

In this paper, we present an analysis to identify a sensor location for an inertial measurement unit (IMU) on the body of a skier and propose the best location to capture turn motions for training. We also validate the manner in which the data from the IMU sensor on the proposed location can characterize ski turns and performance with a series of statistical analyses, including a comparison with data collected from foot pressure sensors. The goal of the study is to logically identify the ideal location on the skier’s body to attach the IMU sensor and the best use of the data collected for the skier. The statistical analyses and the hierarchical clustering method indicate that the pelvis is the best location for attachment of an IMU, and numerical validation shows that the data collected from this location can effectively estimate the performance and characteristics of the skier. Moreover, placement of the sensor at this location does not distract the skier’s motion, and the sensor can be easily attached and detached. The findings of this study can be used for the development of a wearable device for the routine training of professional skiers. PMID:27043579

PADF electromagnetic source localization using extremum seeking control

NASA Astrophysics Data System (ADS)

Al Issa, Huthaifa A.; Ordóñez, Raúl

2014-10-01

Wireless Sensor Networks (WSNs) are a significant technology attracting considerable research interest. Recent advances in wireless communications and electronics have enabled the development of low-cost, low-power and multi-functional sensors that are small in size and communicate over short distances. Most WSN applications require knowing or measuring locations of thousands of sensors accurately. For example, sensing data without knowing the sensor location is often meaningless. Locations of sensor nodes are fundamental to providing location stamps, locating and tracking objects, forming clusters, and facilitating routing. This research focused on the modeling and implementation of distributed, mobile radar sensor networks. In particular, we worked on the problem of Position-Adaptive Direction Finding (PADF), to determine the location of a non- collaborative transmitter, possibly hidden within a structure, by using a team of cooperative intelligent sensor networks. Position-Adaptive radar concepts have been formulated and investigated at the Air Force Research Laboratory (AFRL) within the past few years. In this paper, we present the simulation performance analysis on the application aspect. We apply Extremum Seeking Control (ESC) schemes by using the swarm seeking problem, where the goal is to design a control law for each individual sensor that can minimize the error metric by adapting the sensor positions in real-time, thereby minimizing the unknown estimation error. As a result we achieved source seeking and collision avoidance of the entire group of the sensor positions.

Real-Time Alpine Measurement System Using Wireless Sensor Networks

PubMed Central

2017-01-01

Monitoring the snow pack is crucial for many stakeholders, whether for hydro-power optimization, water management or flood control. Traditional forecasting relies on regression methods, which often results in snow melt runoff predictions of low accuracy in non-average years. Existing ground-based real-time measurement systems do not cover enough physiographic variability and are mostly installed at low elevations. We present the hardware and software design of a state-of-the-art distributed Wireless Sensor Network (WSN)-based autonomous measurement system with real-time remote data transmission that gathers data of snow depth, air temperature, air relative humidity, soil moisture, soil temperature, and solar radiation in physiographically representative locations. Elevation, aspect, slope and vegetation are used to select network locations, and distribute sensors throughout a given network location, since they govern snow pack variability at various scales. Three WSNs were installed in the Sierra Nevada of Northern California throughout the North Fork of the Feather River, upstream of the Oroville dam and multiple powerhouses along the river. The WSNs gathered hydrologic variables and network health statistics throughout the 2017 water year, one of northern Sierra’s wettest years on record. These networks leverage an ultra-low-power wireless technology to interconnect their components and offer recovery features, resilience to data loss due to weather and wildlife disturbances and real-time topological visualizations of the network health. Data show considerable spatial variability of snow depth, even within a 1 km2 network location. Combined with existing systems, these WSNs can better detect precipitation timing and phase in, monitor sub-daily dynamics of infiltration and surface runoff during precipitation or snow melt, and inform hydro power managers about actual ablation and end-of-season date across the landscape. PMID:29120376

Real-Time Alpine Measurement System Using Wireless Sensor Networks.

PubMed

Malek, Sami A; Avanzi, Francesco; Brun-Laguna, Keoma; Maurer, Tessa; Oroza, Carlos A; Hartsough, Peter C; Watteyne, Thomas; Glaser, Steven D

2017-11-09

Monitoring the snow pack is crucial for many stakeholders, whether for hydro-power optimization, water management or flood control. Traditional forecasting relies on regression methods, which often results in snow melt runoff predictions of low accuracy in non-average years. Existing ground-based real-time measurement systems do not cover enough physiographic variability and are mostly installed at low elevations. We present the hardware and software design of a state-of-the-art distributed Wireless Sensor Network (WSN)-based autonomous measurement system with real-time remote data transmission that gathers data of snow depth, air temperature, air relative humidity, soil moisture, soil temperature, and solar radiation in physiographically representative locations. Elevation, aspect, slope and vegetation are used to select network locations, and distribute sensors throughout a given network location, since they govern snow pack variability at various scales. Three WSNs were installed in the Sierra Nevada of Northern California throughout the North Fork of the Feather River, upstream of the Oroville dam and multiple powerhouses along the river. The WSNs gathered hydrologic variables and network health statistics throughout the 2017 water year, one of northern Sierra's wettest years on record. These networks leverage an ultra-low-power wireless technology to interconnect their components and offer recovery features, resilience to data loss due to weather and wildlife disturbances and real-time topological visualizations of the network health. Data show considerable spatial variability of snow depth, even within a 1 km 2 network location. Combined with existing systems, these WSNs can better detect precipitation timing and phase in, monitor sub-daily dynamics of infiltration and surface runoff during precipitation or snow melt, and inform hydro power managers about actual ablation and end-of-season date across the landscape.

Information Fusion for High Level Situation Assessment and Prediction

DTIC Science & Technology

2007-03-01

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

Planar location of the simulative acoustic source based on fiber optic sensor array

NASA Astrophysics Data System (ADS)

Liang, Yi-Jun; Liu, Jun-feng; Zhang, Qiao-ping; Mu, Lin-lin

2010-06-01

A fiber optic sensor array which is structured by four Sagnac fiber optic sensors is proposed to detect and locate a simulative source of acoustic emission (AE). The sensing loops of Sagnac interferometer (SI) are regarded as point sensors as their small size. Based on the derived output light intensity expression of SI, the optimum work condition of the Sagnac fiber optic sensor is discussed through the simulation of MATLAB. Four sensors are respectively placed on a steel plate to structure the sensor array and the location algorithms are expatiated. When an impact is generated by an artificial AE source at any position of the plate, the AE signal will be detected by four sensors at different times. With the help of a single chip microcomputer (SCM) which can calculate the position of the AE source and display it on LED, we have implemented an intelligent detection and location.

Active control of flexural vibrations in beams

NASA Technical Reports Server (NTRS)

Gerhold, Carl H.

1987-01-01

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

Adaptive and mobile ground sensor array.

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

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

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

Fiber-Amplifier-Enhanced QEPAS Sensor for Simultaneous Trace Gas Detection of NH3 and H2S

PubMed Central

Wu, Hongpeng; Dong, Lei; Liu, Xiaoli; Zheng, Huadan; Yin, Xukun; Ma, Weiguang; Zhang, Lei; Yin, Wangbao; Jia, Suotang

2015-01-01

A selective and sensitive quartz enhanced photoacoustic spectroscopy (QEPAS) sensor, employing an erbium-doped fiber amplifier (EDFA), and a distributed feedback (DFB) laser operating at 1582 nm was demonstrated for simultaneous detection of ammonia (NH3) and hydrogen sulfide (H2S). Two interference-free absorption lines located at 6322.45 cm−1 and 6328.88 cm−1 for NH3 and H2S detection, respectively, were identified. The sensor was optimized in terms of current modulation depth for both of the two target gases. An electrical modulation cancellation unit was equipped to suppress the background noise caused by the stray light. An Allan-Werle variance analysis was performed to investigate the long-term performance of the fiber-amplifier-enhanced QEPAS sensor. Benefitting from the high power boosted by the EDFA, a detection sensitivity (1σ) of 52 parts per billion by volume (ppbv) and 17 ppbv for NH3 and H2S, respectively, were achieved with a 132 s data acquisition time at atmospheric pressure and room temperature. PMID:26506351

Characterization of a mine fire using atmospheric monitoring system sensor data

PubMed Central

Yuan, L.; Thomas, R.A.; Zhou, L.

2017-01-01

Atmospheric monitoring systems (AMS) have been widely used in underground coal mines in the United States for the detection of fire in the belt entry and the monitoring of other ventilation-related parameters such as airflow velocity and methane concentration in specific mine locations. In addition to an AMS being able to detect a mine fire, the AMS data have the potential to provide fire characteristic information such as fire growth — in terms of heat release rate — and exact fire location. Such information is critical in making decisions regarding fire-fighting strategies, underground personnel evacuation and optimal escape routes. In this study, a methodology was developed to calculate the fire heat release rate using AMS sensor data for carbon monoxide concentration, carbon dioxide concentration and airflow velocity based on the theory of heat and species transfer in ventilation airflow. Full-scale mine fire experiments were then conducted in the Pittsburgh Mining Research Division’s Safety Research Coal Mine using an AMS with different fire sources. Sensor data collected from the experiments were used to calculate the heat release rates of the fires using this methodology. The calculated heat release rate was compared with the value determined from the mass loss rate of the combustible material using a digital load cell. The experimental results show that the heat release rate of a mine fire can be calculated using AMS sensor data with reasonable accuracy. PMID:28845058

Modeling the energy performance of event-driven wireless sensor network by using static sink and mobile sink.

PubMed

Chen, Jiehui; Salim, Mariam B; Matsumoto, Mitsuji

2010-01-01

Wireless Sensor Networks (WSNs) designed for mission-critical applications suffer from limited sensing capacities, particularly fast energy depletion. Regarding this, mobile sinks can be used to balance the energy consumption in WSNs, but the frequent location updates of the mobile sinks can lead to data collisions and rapid energy consumption for some specific sensors. This paper explores an optimal barrier coverage based sensor deployment for event driven WSNs where a dual-sink model was designed to evaluate the energy performance of not only static sensors, but Static Sink (SS) and Mobile Sinks (MSs) simultaneously, based on parameters such as sensor transmission range r and the velocity of the mobile sink v, etc. Moreover, a MS mobility model was developed to enable SS and MSs to effectively collaborate, while achieving spatiotemporal energy performance efficiency by using the knowledge of the cumulative density function (cdf), Poisson process and M/G/1 queue. The simulation results verified that the improved energy performance of the whole network was demonstrated clearly and our eDSA algorithm is more efficient than the static-sink model, reducing energy consumption approximately in half. Moreover, we demonstrate that our results are robust to realistic sensing models and also validate the correctness of our results through extensive simulations.

Modeling the Energy Performance of Event-Driven Wireless Sensor Network by Using Static Sink and Mobile Sink

PubMed Central

Chen, Jiehui; Salim, Mariam B.; Matsumoto, Mitsuji

2010-01-01

Wireless Sensor Networks (WSNs) designed for mission-critical applications suffer from limited sensing capacities, particularly fast energy depletion. Regarding this, mobile sinks can be used to balance the energy consumption in WSNs, but the frequent location updates of the mobile sinks can lead to data collisions and rapid energy consumption for some specific sensors. This paper explores an optimal barrier coverage based sensor deployment for event driven WSNs where a dual-sink model was designed to evaluate the energy performance of not only static sensors, but Static Sink (SS) and Mobile Sinks (MSs) simultaneously, based on parameters such as sensor transmission range r and the velocity of the mobile sink v, etc. Moreover, a MS mobility model was developed to enable SS and MSs to effectively collaborate, while achieving spatiotemporal energy performance efficiency by using the knowledge of the cumulative density function (cdf), Poisson process and M/G/1 queue. The simulation results verified that the improved energy performance of the whole network was demonstrated clearly and our eDSA algorithm is more efficient than the static-sink model, reducing energy consumption approximately in half. Moreover, we demonstrate that our results are robust to realistic sensing models and also validate the correctness of our results through extensive simulations. PMID:22163503

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

PubMed

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

2010-01-01

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

Optimization Strategies for Sensor and Actuator Placement

NASA Technical Reports Server (NTRS)

Padula, Sharon L.; Kincaid, Rex K.

1999-01-01

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

Geometrical optimization of a local ballistic magnetic sensor

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

Kanda, Yuhsuke; Hara, Masahiro; Nomura, Tatsuya

2014-04-07

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

A reconfigurable computing platform for plume tracking with mobile sensor networks

NASA Astrophysics Data System (ADS)

Kim, Byung Hwa; D'Souza, Colin; Voyles, Richard M.; Hesch, Joel; Roumeliotis, Stergios I.

2006-05-01

Much work has been undertaken recently toward the development of low-power, high-performance sensor networks. There are many static remote sensing applications for which this is appropriate. The focus of this development effort is applications that require higher performance computation, but still involve severe constraints on power and other resources. Toward that end, we are developing a reconfigurable computing platform for miniature robotic and human-deployed sensor systems composed of several mobile nodes. The system provides static and dynamic reconfigurability for both software and hardware by the combination of CPU (central processing unit) and FPGA (field-programmable gate array) allowing on-the-fly reprogrammability. Static reconfigurability of the hardware manifests itself in the form of a "morphing bus" architecture that permits the modular connection of various sensors with no bus interface logic. Dynamic hardware reconfigurability provides for the reallocation of hardware resources at run-time as the mobile, resource-constrained nodes encounter unknown environmental conditions that render various sensors ineffective. This computing platform will be described in the context of work on chemical/biological/radiological plume tracking using a distributed team of mobile sensors. The objective for a dispersed team of ground and/or aerial autonomous vehicles (or hand-carried sensors) is to acquire measurements of the concentration of the chemical agent from optimal locations and estimate its source and spread. This requires appropriate distribution, coordination and communication within the team members across a potentially unknown environment. The key problem is to determine the parameters of the distribution of the harmful agent so as to use these values for determining its source and predicting its spread. The accuracy and convergence rate of this estimation process depend not only on the number and accuracy of the sensor measurements but also on their spatial distribution over time (the sampling strategy). For the safety of a human-deployed distribution of sensors, optimized trajectories to minimize human exposure are also of importance. The systems described in this paper are currently being developed. Parts of the system are already in existence and some results from these are described.

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.

Measuring PM and related air pollutants using low-cost ...

EPA Pesticide Factsheets

Emerging air quality sensors may play a key role in better characterizing levels of air pollution in a variety of settings There are a wide range of low-cost (< $500 US) sensors on the market, but few have been characterized. If accurate, this new generation of inexpensive sensors can potentially allow larger fleets of monitors to be deployed to better study the spatial and temporal variability of pollutants. The small size and light weight of these sensors also allows for the possibility of wearable or drone applications. Sensor networks will very likely play a key role in future estimates of human health impacts of pollutants, in particular particulate matter (PM), and will allow for the better characterization of pollutant sources and source regions.We will present measurements from an assortment of sensors, costing $20-$700, that have been used to measure air pollution in the US, India, and China with a focus on estimating PM concentrations. Their performance has been evaluated in these very different settings with low concentrations seen in the US (up to approximately 20 ug m-3) and much higher concentrations measured in India and China (up to approximately 300 ug m-3). Based on these studies the optimal concentration ranges of these sensors have been determined. Used in conjunction with data from a carbon dioxide sensor, emissions factors were estimated in some of the locations. In addition temperature and humidity sensors can be used to calculate c

Aircraft Cabin Environmental Quality Sensors

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

Gundel, Lara; Kirchstetter, Thomas; Spears, Michael

2010-05-06

The Indoor Environment Department at Lawrence Berkeley National Laboratory (LBNL) teamed with seven universities to participate in a Federal Aviation Administration (FAA) Center of Excellence (COE) for research on environmental quality in aircraft. This report describes research performed at LBNL on selecting and evaluating sensors for monitoring environmental quality in aircraft cabins, as part of Project 7 of the FAA's COE for Airliner Cabin Environmental Research (ACER)1 effort. This part of Project 7 links to the ozone, pesticide, and incident projects for data collection and monitoring and is a component of a broader research effort on sensors by ACER. Resultsmore » from UCB and LBNL's concurrent research on ozone (ACER Project 1) are found in Weschler et al., 2007; Bhangar et al. 2008; Coleman et al., 2008 and Strom-Tejsen et al., 2008. LBNL's research on pesticides (ACER Project 2) in airliner cabins is described in Maddalena and McKone (2008). This report focused on the sensors needed for normal contaminants and conditions in aircraft. The results are intended to complement and coordinate with results from other ACER members who concentrated primarily on (a) sensors for chemical and biological pollutants that might be released intentionally in aircraft; (b) integration of sensor systems; and (c) optimal location of sensors within aircraft. The parameters and sensors were selected primarily to satisfy routine monitoring needs for contaminants and conditions that commonly occur in aircraft. However, such sensor systems can also be incorporated into research programs on environmental quality in aircraft cabins.« less

A New Approach to Design Autonomous Wireless Sensor Node Based on RF Energy Harvesting System.

PubMed

Mouapi, Alex; Hakem, Nadir

2018-01-05

Energy Harvesting techniques are increasingly seen as the solution for freeing the wireless sensor nodes from their battery dependency. However, it remains evident that network performance features, such as network size, packet length, and duty cycle, are influenced by the sum of recovered energy. This paper proposes a new approach to defining the specifications of a stand-alone wireless node based on a Radio-frequency Energy Harvesting System (REHS). To achieve adequate performance regarding the range of the Wireless Sensor Network (WSN), techniques for minimizing the energy consumed by the sensor node are combined with methods for optimizing the performance of the REHS. For more rigor in the design of the autonomous node, a comprehensive energy model of the node in a wireless network is established. For an equitable distribution of network charges between the different nodes that compose it, the Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol is used for this purpose. The model considers five energy-consumption sources, most of which are ignored in recently used models. By using the hardware parameters of commercial off-the-shelf components (Mica2 Motes and CC2520 of Texas Instruments), the energy requirement of a sensor node is quantified. A miniature REHS based on a judicious choice of rectifying diodes is then designed and developed to achieve optimal performance in the Industrial Scientific and Medical (ISM) band centralized at 2.45 GHz . Due to the mismatch between the REHS and the antenna, a band pass filter is designed to reduce reflection losses. A gradient method search is used to optimize the output characteristics of the adapted REHS. At 1 mW of input RF power, the REHS provides an output DC power of 0.57 mW and a comparison with the energy requirement of the node allows the Base Station (BS) to be located at 310 m from the wireless nodes when the Wireless Sensor Network (WSN) has 100 nodes evenly spread over an area of 300 × 300 m 2 and when each round lasts 10 min . The result shows that the range of the autonomous WSN increases when the controlled physical phenomenon varies very slowly. Having taken into account all the dissipation sources coexisting in a sensor node and using actual measurements of an REHS, this work provides the guidelines for the design of autonomous nodes based on REHS.

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

Large-band seismic characterization of the INFN Gran Sasso National Laboratory

NASA Astrophysics Data System (ADS)

Acernese, F.; Canonico, R.; De Rosa, R.; Giordano, G.; Romano, R.; Barone, F.

2013-04-01

In this paper we present the scientific data recorded by tunable mechanical monolithic horizontal seismometers located in the Gran Sasso National Laboratory of the INFN, within thermally insulating enclosures onto concrete slabs connected to the bedrock. The main goals of this long-term large-band measurements are for the seismic characterization of the site in the frequency band 10-6÷10Hz and the acquisition of all the relevant information for the optimization of the sensors.

Optimizing Site Locations for Determining Shape from Photometric Light Curves

DTIC Science & Technology

2009-09-01

discretize t satellite sh there be a c telescopes Space situa the operati – as well a (Codified d in order to satellites in the degrad photometri ...Departm ller or too far a used to charac llite varies as the solar phase pe. One way ver time or by e following qu l sensor locati the satellite fr...four satellite element sets used in this study and the six time periods in which we determined passes of various orientations to the terminator. Thus

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.

Probe for optically monitoring progress of in-situ vitrification of soil

DOEpatents

Timmerman, Craig L.; Oma, Kenton H.; Davis, Karl C.

1988-01-01

A detector system for sensing the progress of an ISV process along an expected path comprises multiple sensors each having an input port. The input ports are distributed along the expected path of the ISV process between a starting location and an expected ending location. Each sensor generates an electrical signal representative of the temperature in the vicinity of its input port. A signal processor is coupled to the sensors to receive an electrical signal generated by a sensor, and generate a signal which is encoded with information which identifies the sensor and whether the ISV process has reached the sensor's input port. A transmitter propagates the encoded signal. The signal processor and the transmitter are below ground at a location beyond the expected ending location of the ISV process in the direction from the starting location to the expected ending location. A signal receiver and a decoder are located above ground for receiving the encoded signal propagated by the transmitter, decoding the encoded signal and providing a human-perceptible indication of the progress of the ISV process.

Probe for optically monitoring progress of in-situ vitrification of soil

DOEpatents

Timmerman, C.L.; Oma, K.H.; Davis, K.C.

1988-08-09

A detector system for sensing the progress of an ISV process along an expected path comprises multiple sensors each having an input port. The input ports are distributed along the expected path of the ISV process between a starting location and an expected ending location. Each sensor generates an electrical signal representative of the temperature in the vicinity of its input port. A signal processor is coupled to the sensors to receive an electrical signal generated by a sensor, and generate a signal which is encoded with information which identifies the sensor and whether the ISV process has reached the sensor's input port. A transmitter propagates the encoded signal. The signal processor and the transmitter are below ground at a location beyond the expected ending location of the ISV process in the direction from the starting location to the expected ending location. A signal receiver and a decoder are located above ground for receiving the encoded signal propagated by the transmitter, decoding the encoded signal and providing a human-perceptible indication of the progress of the ISV process. 7 figs.

An optical sensor for detecting the contact location of a gas-liquid interface on a body.

PubMed

Belden, Jesse; Jandron, Michael

2014-08-01

An optical sensor for detecting the dynamic contact location of a gas-liquid interface along the length of a body is described. The sensor is developed in the context of applications to supercavitating bodies requiring measurement of the dynamic cavity contact location; however, the sensing method is extendable to other applications as well. The optical principle of total internal reflection is exploited to detect changes in refractive index of the medium contacting the body at discrete locations along its length. The derived theoretical operation of the sensor predicts a signal attenuation of 18 dB when a sensed location changes from air-contacting to water-contacting. Theory also shows that spatial resolution (d) scales linearly with sensor length (L(s)) and a resolution of 0.01L(s) can be achieved. A prototype sensor is constructed from simple components and response characteristics are quantified for different ambient light conditions as well as partial wetting states. Three methods of sensor calibration are described and a signal processing framework is developed that allows for robust detection of the gas-liquid contact location. In a tank draining experiment, the prototype sensor resolves the water level with accuracy limited only by the spatial resolution, which is constrained by the experimental setup. A more representative experiment is performed in which the prototype sensor accurately measures the dynamic contact location of a gas cavity on a water tunnel wall.

Acoustic calibration apparatus for calibrating plethysmographic acoustic pressure sensors

NASA Technical Reports Server (NTRS)

Zuckerwar, Allan J. (Inventor); Davis, David C. (Inventor)

1995-01-01

An apparatus for calibrating an acoustic sensor is described. The apparatus includes a transmission material having an acoustic impedance approximately matching the acoustic impedance of the actual acoustic medium existing when the acoustic sensor is applied in actual in-service conditions. An elastic container holds the transmission material. A first sensor is coupled to the container at a first location on the container and a second sensor coupled to the container at a second location on the container, the second location being different from the first location. A sound producing device is coupled to the container and transmits acoustic signals inside the container.

Acoustic calibration apparatus for calibrating plethysmographic acoustic pressure sensors

NASA Technical Reports Server (NTRS)

Zuckerwar, Allan J. (Inventor); Davis, David C. (Inventor)

1994-01-01

An apparatus for calibrating an acoustic sensor is described. The apparatus includes a transmission material having an acoustic impedance approximately matching the acoustic impedance of the actual acoustic medium existing when the acoustic sensor is applied in actual in-service conditions. An elastic container holds the transmission material. A first sensor is coupled to the container at a first location on the container and a second sensor coupled to the container at a second location on the container, the second location being different from the first location. A sound producing device is coupled to the container and transmits acoustic signals inside the container.

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

PubMed Central

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

2014-01-01

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

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

PubMed

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

2017-08-01

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

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

NASA Technical Reports Server (NTRS)

Foyle, David C.

1993-01-01

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

Analysis of radio wave propagation for ISM 2.4 GHz Wireless Sensor Networks in inhomogeneous vegetation environments.

PubMed

Azpilicueta, Leire; López-Iturri, Peio; Aguirre, Erik; Mateo, Ignacio; Astrain, José Javier; Villadangos, Jesús; Falcone, Francisco

2014-12-10

The use of wireless networks has experienced exponential growth due to the improvements in terms of battery life and low consumption of the devices. However, it is compulsory to conduct previous radio propagation analysis when deploying a wireless sensor network. These studies are necessary to perform an estimation of the range coverage, in order to optimize the distance between devices in an actual network deployment. In this work, the radio channel characterization for ISM 2.4 GHz Wireless Sensor Networks (WSNs) in an inhomogeneous vegetation environment has been analyzed. This analysis allows designing environment monitoring tools based on ZigBee and WiFi where WSN and smartphones cooperate, providing rich and customized monitoring information to users in a friendly manner. The impact of topology as well as morphology of the environment is assessed by means of an in-house developed 3D Ray Launching code, to emulate the realistic operation in the framework of the scenario. Experimental results gathered from a measurement campaign conducted by deploying a ZigBee Wireless Sensor Network, are analyzed and compared with simulations in this paper. The scenario where this network is intended to operate is a combination of buildings and diverse vegetation species. To gain insight in the effects of radio propagation, a simplified vegetation model has been developed, considering the material parameters and simplified geometry embedded in the simulation scenario. An initial location-based application has been implemented in a real scenario, to test the functionality within a context aware scenario. The use of deterministic tools can aid to know the impact of the topological influence in the deployment of the optimal Wireless Sensor Network in terms of capacity, coverage and energy consumption, making the use of these systems attractive for multiple applications in inhomogeneous vegetation environments.

Optimal Sampling to Provide User-Specific Climate Information.

NASA Astrophysics Data System (ADS)

Panturat, Suwanna

The types of weather-related world problems which are of socio-economic importance selected in this study as representative of three different levels of user groups include: (i) a regional problem concerned with air pollution plumes which lead to acid rain in the north eastern United States, (ii) a state-level problem in the form of winter wheat production in Oklahoma, and (iii) an individual-level problem involving reservoir management given errors in rainfall estimation at Lake Ellsworth, upstream from Lawton, Oklahoma. The study is aimed at designing optimal sampling networks which are based on customer value systems and also abstracting from data sets that information which is most cost-effective in reducing the climate-sensitive aspects of a given user problem. Three process models being used in this study to interpret climate variability in terms of the variables of importance to the user comprise: (i) the HEFFTER-SAMSON diffusion model as the climate transfer function for acid rain, (ii) the CERES-MAIZE plant process model for winter wheat production and (iii) the AGEHYD streamflow model selected as "a black box" for reservoir management. A state-of-the-art Non Linear Program (NLP) algorithm for minimizing an objective function is employed to determine the optimal number and location of various sensors. Statistical quantities considered in determining sensor locations including Bayes Risk, the chi-squared value, the probability of the Type I error (alpha) and the probability of the Type II error (beta) and the noncentrality parameter delta^2. Moreover, the number of years required to detect a climate change resulting in a given bushel per acre change in mean wheat production is determined; the number of seasons of observations required to reduce the standard deviation of the error variance of the ambient sulfur dioxide to less than a certain percent of the mean is found; and finally the policy of maintaining pre-storm flood pools at selected levels is examined given information from the optimal sampling network as defined by the study.

A multipath routing protocol based on clustering and ant colony optimization for wireless sensor networks.

PubMed

Yang, Jing; Xu, Mai; Zhao, Wei; Xu, Baoguo

2010-01-01

For monitoring burst events in a kind of reactive wireless sensor networks (WSNs), a multipath routing protocol (MRP) based on dynamic clustering and ant colony optimization (ACO) is proposed. Such an approach can maximize the network lifetime and reduce the energy consumption. An important attribute of WSNs is their limited power supply, and therefore some metrics (such as energy consumption of communication among nodes, residual energy, path length) were considered as very important criteria while designing routing in the MRP. Firstly, a cluster head (CH) is selected among nodes located in the event area according to some parameters, such as residual energy. Secondly, an improved ACO algorithm is applied in the search for multiple paths between the CH and sink node. Finally, the CH dynamically chooses a route to transmit data with a probability that depends on many path metrics, such as energy consumption. The simulation results show that MRP can prolong the network lifetime, as well as balance of energy consumption among nodes and reduce the average energy consumption effectively.

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

NASA Astrophysics Data System (ADS)

Prawin, J.; Rama Mohan Rao, A.

2018-01-01

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

Improving slowness estimate stability and visualization using limited sensor pair correlation on seismic arrays

NASA Astrophysics Data System (ADS)

Gibbons, Steven J.; Näsholm, S. P.; Ruigrok, E.; Kværna, T.

2018-04-01

Seismic arrays enhance signal detection and parameter estimation by exploiting the time-delays between arriving signals on sensors at nearby locations. Parameter estimates can suffer due to both signal incoherence, with diminished waveform similarity between sensors, and aberration, with time-delays between coherent waveforms poorly represented by the wave-front model. Sensor-to-sensor correlation approaches to parameter estimation have an advantage over direct beamforming approaches in that individual sensor-pairs can be omitted without necessarily omitting entirely the data from each of the sensors involved. Specifically, we can omit correlations between sensors for which signal coherence in an optimal frequency band is anticipated to be poor or for which anomalous time-delays are anticipated. In practice, this usually means omitting correlations between more distant sensors. We present examples from International Monitoring System seismic arrays with poor parameter estimates resulting when classical f-k analysis is performed over the full array aperture. We demonstrate improved estimates and slowness grid displays using correlation beamforming restricted to correlations between sufficiently closely spaced sensors. This limited sensor-pair correlation (LSPC) approach has lower slowness resolution than would ideally be obtained by considering all sensor-pairs. However, this ideal estimate may be unattainable due to incoherence and/or aberration and the LSPC estimate can often exploit all channels, with the associated noise-suppression, while mitigating the complications arising from correlations between very distant sensors. The greatest need for the method is for short-period signals on large aperture arrays although we also demonstrate significant improvement for secondary regional phases on a small aperture array. LSPC can also provide a robust and flexible approach to parameter estimation on three-component seismic arrays.

Optimized spectroscopic scheme for enhanced precision CO measurements with applications to urban source attribution

NASA Astrophysics Data System (ADS)

Nottrott, A.; Hoffnagle, J.; Farinas, A.; Rella, C.

2014-12-01

Carbon monoxide (CO) is an urban pollutant generated by internal combustion engines which contributes to the formation of ground level ozone (smog). CO is also an excellent tracer for emissions from mobile combustion sources. In this work we present an optimized spectroscopic sampling scheme that enables enhanced precision CO measurements. The scheme was implemented on the Picarro G2401 Cavity Ring-Down Spectroscopy (CRDS) analyzer which measures CO2, CO, CH4 and H2O at 0.2 Hz. The optimized scheme improved the raw precision of CO measurements by 40% from 5 ppb to 3 ppb. Correlations of measured CO2, CO, CH4 and H2O from an urban tower were partitioned by wind direction and combined with a concentration footprint model for source attribution. The application of a concentration footprint for source attribution has several advantages. The upwind extent of the concentration footprint for a given sensor is much larger than the flux footprint. Measurements of mean concentration at the sensor location can be used to estimate source strength from a concentration footprint, while measurements of the vertical concentration flux are necessary to determine source strength from the flux footprint. Direct measurement of vertical concentration flux requires high frequency temporal sampling and increases the cost and complexity of the measurement system.

A Depth-Adjustment Deployment Algorithm Based on Two-Dimensional Convex Hull and Spanning Tree for Underwater Wireless Sensor Networks.

PubMed

Jiang, Peng; Liu, Shuai; Liu, Jun; Wu, Feng; Zhang, Le

2016-07-14

Most of the existing node depth-adjustment deployment algorithms for underwater wireless sensor networks (UWSNs) just consider how to optimize network coverage and connectivity rate. However, these literatures don't discuss full network connectivity, while optimization of network energy efficiency and network reliability are vital topics for UWSN deployment. Therefore, in this study, a depth-adjustment deployment algorithm based on two-dimensional (2D) convex hull and spanning tree (NDACS) for UWSNs is proposed. First, the proposed algorithm uses the geometric characteristics of a 2D convex hull and empty circle to find the optimal location of a sleep node and activate it, minimizes the network coverage overlaps of the 2D plane, and then increases the coverage rate until the first layer coverage threshold is reached. Second, the sink node acts as a root node of all active nodes on the 2D convex hull and then forms a small spanning tree gradually. Finally, the depth-adjustment strategy based on time marker is used to achieve the three-dimensional overall network deployment. Compared with existing depth-adjustment deployment algorithms, the simulation results show that the NDACS algorithm can maintain full network connectivity with high network coverage rate, as well as improved network average node degree, thus increasing network reliability.

A Depth-Adjustment Deployment Algorithm Based on Two-Dimensional Convex Hull and Spanning Tree for Underwater Wireless Sensor Networks

PubMed Central

Jiang, Peng; Liu, Shuai; Liu, Jun; Wu, Feng; Zhang, Le

2016-01-01

Most of the existing node depth-adjustment deployment algorithms for underwater wireless sensor networks (UWSNs) just consider how to optimize network coverage and connectivity rate. However, these literatures don’t discuss full network connectivity, while optimization of network energy efficiency and network reliability are vital topics for UWSN deployment. Therefore, in this study, a depth-adjustment deployment algorithm based on two-dimensional (2D) convex hull and spanning tree (NDACS) for UWSNs is proposed. First, the proposed algorithm uses the geometric characteristics of a 2D convex hull and empty circle to find the optimal location of a sleep node and activate it, minimizes the network coverage overlaps of the 2D plane, and then increases the coverage rate until the first layer coverage threshold is reached. Second, the sink node acts as a root node of all active nodes on the 2D convex hull and then forms a small spanning tree gradually. Finally, the depth-adjustment strategy based on time marker is used to achieve the three-dimensional overall network deployment. Compared with existing depth-adjustment deployment algorithms, the simulation results show that the NDACS algorithm can maintain full network connectivity with high network coverage rate, as well as improved network average node degree, thus increasing network reliability. PMID:27428970

Systems and methods for measuring component matching

NASA Technical Reports Server (NTRS)

Courter, Kelly J. (Inventor); Slenk, Joel E. (Inventor)

2006-01-01

Systems and methods for measuring a contour match between adjacent components are disclosed. In one embodiment, at least two pressure sensors are located between adjacent components. Each pressure sensor is adapted to obtain a pressure measurement at a location a predetermined distance away from the other pressure sensors, and to output a pressure measurement for each sensor location. An output device is adapted to receive the pressure measurements from at least two pressure sensors and display the pressure measurements. In one aspect, the pressure sensors include flexible thin film pressure sensors. In accordance with other aspects of the invention, a method is provided for measuring a contour match between two interfacing components including measuring at least one pressure applied to at least one sensor between the interfacing components.

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.

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

Computation of Optimal Actuator/Sensor Locations

DTIC Science & Technology

2013-12-26

weighting matrices Q = I and R = 0.01, and a minimum variance LQ-cost (with V = I ), a plot of the L2 norm of the control signal versus actuator...0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 0.05 0.1 0.15 0.2 0.25 actuator location lin ea r− qu ad ra tic c os t ( re la tiv e) Q = I , R = 100 Q... I , R = 1 Q = I , R = 0.01 Q = I , R = 0.0001 (a) 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 actuator location lin

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

PubMed Central

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

2017-01-01

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

Optimal Electrode Selection for Electrical Resistance Tomography in Carbon Fiber Reinforced Polymer Composites

PubMed Central

Escalona Galvis, Luis Waldo; Diaz-Montiel, Paulina; Venkataraman, Satchi

2017-01-01

Electrical Resistance Tomography (ERT) offers a non-destructive evaluation (NDE) technique that takes advantage of the inherent electrical properties in carbon fiber reinforced polymer (CFRP) composites for internal damage characterization. This paper investigates a method of optimum selection of sensing configurations for delamination detection in thick cross-ply laminates using ERT. Reduction in the number of sensing locations and measurements is necessary to minimize hardware and computational effort. The present work explores the use of an effective independence (EI) measure originally proposed for sensor location optimization in experimental vibration modal analysis. The EI measure is used for selecting the minimum set of resistance measurements among all possible combinations resulting from selecting sensing electrode pairs. Singular Value Decomposition (SVD) is applied to obtain a spectral representation of the resistance measurements in the laminate for subsequent EI based reduction to take place. The electrical potential field in a CFRP laminate is calculated using finite element analysis (FEA) applied on models for two different laminate layouts considering a set of specified delamination sizes and locations with two different sensing arrangements. The effectiveness of the EI measure in eliminating redundant electrode pairs is demonstrated by performing inverse identification of damage using the full set and the reduced set of resistance measurements. This investigation shows that the EI measure is effective for optimally selecting the electrode pairs needed for resistance measurements in ERT based damage detection. PMID:28772485

Optimal Electrode Selection for Electrical Resistance Tomography in Carbon Fiber Reinforced Polymer Composites.

PubMed

Escalona Galvis, Luis Waldo; Diaz-Montiel, Paulina; Venkataraman, Satchi

2017-02-04

Electrical Resistance Tomography (ERT) offers a non-destructive evaluation (NDE) technique that takes advantage of the inherent electrical properties in carbon fiber reinforced polymer (CFRP) composites for internal damage characterization. This paper investigates a method of optimum selection of sensing configurations for delamination detection in thick cross-ply laminates using ERT. Reduction in the number of sensing locations and measurements is necessary to minimize hardware and computational effort. The present work explores the use of an effective independence (EI) measure originally proposed for sensor location optimization in experimental vibration modal analysis. The EI measure is used for selecting the minimum set of resistance measurements among all possible combinations resulting from selecting sensing electrode pairs. Singular Value Decomposition (SVD) is applied to obtain a spectral representation of the resistance measurements in the laminate for subsequent EI based reduction to take place. The electrical potential field in a CFRP laminate is calculated using finite element analysis (FEA) applied on models for two different laminate layouts considering a set of specified delamination sizes and locations with two different sensing arrangements. The effectiveness of the EI measure in eliminating redundant electrode pairs is demonstrated by performing inverse identification of damage using the full set and the reduced set of resistance measurements. This investigation shows that the EI measure is effective for optimally selecting the electrode pairs needed for resistance measurements in ERT based damage detection.

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

PubMed

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

2017-07-20

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

A miniature tension sensor to measure surgical suture tension of deformable musculoskeletal tissues during joint motion.

PubMed

Kiriyama, Yoshimori; Matsumoto, Hideo; Toyama, Yoshiaki; Nagura, Takeo

2014-02-01

The aim of this study was to develop a new suture tension sensor for musculoskeletal soft tissue that shows deformation or movements. The suture tension sensor was 10 mm in size, which was small enough to avoid conflicting with the adjacent sensor. Furthermore, the sensor had good linearity up to a tension of 50 N, which is equivalent to the breaking strength of a size 1 absorbable suture defined by the United States Pharmacopeia. The design and mechanism were analyzed using a finite element model prior to developing the actual sensor. Based on the analysis, adequate material was selected, and the output linearity was confirmed and compared with the simulated result. To evaluate practical application, the incision of the skin and capsule were sutured during simulated total knee arthroplasty. When conventional surgery and minimally invasive surgery were performed, suture tensions were compared. In minimally invasive surgery, the distal portion of the knee was dissected, and the proximal portion of the knee was dissected additionally in conventional surgery. In the skin suturing, the maximum tension was 4.4 N, and this tension was independent of the sensor location. In contrast, the sensor suturing the capsule in the distal portion had a tension of 4.4 N in minimally invasive surgery, while the proximal sensor had a tension of 44 N in conventional surgery. The suture tensions increased nonlinearly and were dependent on the knee flexion angle. Furthermore, the tension changes showed hysteresis. This miniature tension sensor may help establish the optimal suturing method with adequate tension to ensure wound healing and early recovery.

Design and Application of Hybrid Magnetic Field-Eddy Current Probe

NASA Technical Reports Server (NTRS)

Wincheski, Buzz; Wallace, Terryl; Newman, Andy; Leser, Paul; Simpson, John

2013-01-01

The incorporation of magnetic field sensors into eddy current probes can result in novel probe designs with unique performance characteristics. One such example is a recently developed electromagnetic probe consisting of a two-channel magnetoresistive sensor with an embedded single-strand eddy current inducer. Magnetic flux leakage maps of ferrous materials are generated from the DC sensor response while high-resolution eddy current imaging is simultaneously performed at frequencies up to 5 megahertz. In this work the design and optimization of this probe will be presented, along with an application toward analysis of sensory materials with embedded ferromagnetic shape-memory alloy (FSMA) particles. The sensory material is designed to produce a paramagnetic to ferromagnetic transition in the FSMA particles under strain. Mapping of the stray magnetic field and eddy current response of the sample with the hybrid probe can thereby image locations in the structure which have experienced an overstrain condition. Numerical modeling of the probe response is performed with good agreement with experimental results.

Attribution of soil information associated with modeling background clutter

NASA Astrophysics Data System (ADS)

Mason, George; Melloh, Rae

2006-05-01

This paper examines the attribution of data fields required to generate high resolution soil profiles for support of Computational Test Bed (CTB) used for countermine research. The countermine computational test bed is designed to realistically simulate the geo-environment to support the evaluation of sensors used to locate unexploded ordnance. The goal of the CTB is to derive expected moisture, chemical compounds, and measure heat migration over time, from which we expect to optimize sensor performance. Several tests areas were considered for the collection of soils data to populate the CTB. Collection of bulk soil properties has inherent spatial resolution limits. Novel techniques are therefore required to populate a high resolution model. This paper presents correlations between spatial variability in texture as related to hydraulic permeability and heat transfer properties of the soil. The extracted physical properties are used to exercise models providing a signature of subsurface media and support the simulation of detection by various sensors of buried and surface ordnance.

Generalized Minimum-Time Follow-up Approaches Applied to Tasking Electro-Optical Sensor Tasking

NASA Astrophysics Data System (ADS)

Murphy, T. S.; Holzinger, M. J.

This work proposes a methodology for tasking of sensors to search an area of state space for a particular object, group of objects, or class of objects. This work creates a general unified mathematical framework for analyzing reacquisition, search, scheduling, and custody operations. In particular, this work looks at searching for unknown space object(s) with prior knowledge in the form of a set, which can be defined via an uncorrelated track, region of state space, or a variety of other methods. The follow-up tasking can occur from a variable location and time, which often requires searching a large region of the sky. This work analyzes the area of a search region over time to inform a time optimal search method. Simulation work looks at analyzing search regions relative to a particular sensor, and testing a tasking algorithm to search through the region. The tasking algorithm is also validated on a reacquisition problem with a telescope system at Georgia Tech.

Fluid pipeline leak detection and location with miniature RF tags

DOEpatents

McIntyre, Timothy J.

2017-05-16

Sensors locate troublesome leaks in pipes or conduits that carry a flowing medium. These sensors, through tailored physical and geometric properties, preferentially seek conduit leaks or breaches due to flow streaming. The sensors can be queried via transceivers outside the conduit or located and interrogated inside by submersible unmanned vehicle to identify and characterize the nature of a leak. The sensors can be functionalized with other capabilities for additional leak and pipeline characterization if needed. Sensors can be recovered from a conduit flow stream and reused for future leak detection activities.

Eddy current sensor concepts for the Bridgman growth of semiconductors

NASA Astrophysics Data System (ADS)

Dharmasena, Kumar P.; Wadley, Haydn N. G.

1997-03-01

Electromagnetic finite element methods have been used to identify eddy current sensor designs for monitoring CdTe vertical Bridgman crystal growth. A model system consisting of pairs of silicon cylinders with electrical conductivities similar to those of solid and liquid CdTe has been used to evaluate the multifrequency response of several sensors designed for locating and characterizing the curvature of liquid-solid interfaces during vertical Bridgman growth. At intermediate frequencies (100-800 kHz), the sensor's imaginary impedance monotonically increases as interfacial curvature changes from concave to convex or the interface location moves upwards through the sensor. The experimental data are in excellent agreement with theoretical predictions. At higher test frequencies (˜ 5 MHz), the test circuit's parasitics contribute to the sensor's response. Even so, the predicted trends with interface location/curvature were found to be still preserved, and the experiments confirm that the sensor's high frequency response depends more on interface location and has only a small sensitivity to curvature. Multifrequency data obtained from these types of sensors have the potential to separately discriminate the location and the shape of liquid-solid interfaces during the vertical Bridgman growth of CdTe and other semiconductor materials of higher electrical conductivity.

The Video Collaborative Localization of a Miner's Lamp Based on Wireless Multimedia Sensor Networks for Underground Coal Mines.

PubMed

You, Kaiming; Yang, Wei; Han, Ruisong

2015-09-29

Based on wireless multimedia sensor networks (WMSNs) deployed in an underground coal mine, a miner's lamp video collaborative localization algorithm was proposed to locate miners in the scene of insufficient illumination and bifurcated structures of underground tunnels. In bifurcation area, several camera nodes are deployed along the longitudinal direction of tunnels, forming a collaborative cluster in wireless way to monitor and locate miners in underground tunnels. Cap-lamps are regarded as the feature of miners in the scene of insufficient illumination of underground tunnels, which means that miners can be identified by detecting their cap-lamps. A miner's lamp will project mapping points on the imaging plane of collaborative cameras and the coordinates of mapping points are calculated by collaborative cameras. Then, multiple straight lines between the positions of collaborative cameras and their corresponding mapping points are established. To find the three-dimension (3D) coordinate location of the miner's lamp a least square method is proposed to get the optimal intersection of the multiple straight lines. Tests were carried out both in a corridor and a realistic scenario of underground tunnel, which show that the proposed miner's lamp video collaborative localization algorithm has good effectiveness, robustness and localization accuracy in real world conditions of underground tunnels.

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.

Location verification algorithm of wearable sensors for wireless body area networks.

PubMed

Wang, Hua; Wen, Yingyou; Zhao, Dazhe

2018-01-01

Knowledge of the location of sensor devices is crucial for many medical applications of wireless body area networks, as wearable sensors are designed to monitor vital signs of a patient while the wearer still has the freedom of movement. However, clinicians or patients can misplace the wearable sensors, thereby causing a mismatch between their physical locations and their correct target positions. An error of more than a few centimeters raises the risk of mistreating patients. The present study aims to develop a scheme to calculate and detect the position of wearable sensors without beacon nodes. A new scheme was proposed to verify the location of wearable sensors mounted on the patient's body by inferring differences in atmospheric air pressure and received signal strength indication measurements from wearable sensors. Extensive two-sample t tests were performed to validate the proposed scheme. The proposed scheme could easily recognize a 30-cm horizontal body range and a 65-cm vertical body range to correctly perform sensor localization and limb identification. All experiments indicate that the scheme is suitable for identifying wearable sensor positions in an indoor environment.

Sensor-Data Fusion for Multi-Person Indoor Location Estimation.

PubMed

Mohebbi, Parisa; Stroulia, Eleni; Nikolaidis, Ioanis

2017-10-18

We consider the problem of estimating the location of people as they move and work in indoor environments. More specifically, we focus on the scenario where one of the persons of interest is unable or unwilling to carry a smartphone, or any other "wearable" device, which frequently arises in caregiver/cared-for situations. We consider the case of indoor spaces populated with anonymous binary sensors (Passive Infrared motion sensors) and eponymous wearable sensors (smartphones interacting with Estimote beacons), and we propose a solution to the resulting sensor-fusion problem. Using a data set with sensor readings collected from one-person and two-person sessions engaged in a variety of activities of daily living, we investigate the relative merits of relying solely on anonymous sensors, solely on eponymous sensors, or on their combination. We examine how the lack of synchronization across different sensing sources impacts the quality of location estimates, and discuss how it could be mitigated without resorting to device-level mechanisms. Finally, we examine the trade-off between the sensors' coverage of the monitored space and the quality of the location estimates.

Investigating local controls on soil moisture temporal stability using an inverse modeling approach

NASA Astrophysics Data System (ADS)

Bogena, Heye; Qu, Wei; Huisman, Sander; Vereecken, Harry

2013-04-01

A better understanding of the temporal stability of soil moisture and its relation to local and nonlocal controls is a major challenge in modern hydrology. Both local controls, such as soil and vegetation properties, and non-local controls, such as topography and climate variability, affect soil moisture dynamics. Wireless sensor networks are becoming more readily available, which opens up opportunities to investigate spatial and temporal variability of soil moisture with unprecedented resolution. In this study, we employed the wireless sensor network SoilNet developed by the Forschungszentrum Jülich to investigate soil moisture variability of a grassland headwater catchment in Western Germany within the framework of the TERENO initiative. In particular, we investigated the effect of soil hydraulic parameters on the temporal stability of soil moisture. For this, the HYDRUS-1D code coupled with a global optimizer (DREAM) was used to inversely estimate Mualem-van Genuchten parameters from soil moisture observations at three depths under natural (transient) boundary conditions for 83 locations in the headwater catchment. On the basis of the optimized parameter sets, we then evaluated to which extent the variability in soil hydraulic conductivity, pore size distribution, air entry suction and soil depth between these 83 locations controlled the temporal stability of soil moisture, which was independently determined from the observed soil moisture data. It was found that the saturated hydraulic conductivity (Ks) was the most significant attribute to explain temporal stability of soil moisture as expressed by the mean relative difference (MRD).

Model-based occluded object recognition using Petri nets

NASA Astrophysics Data System (ADS)

Zhou, Chuan; Hura, Gurdeep S.

1998-09-01

This paper discusses the use of Petri nets to model the process of the object matching between an image and a model under different 2D geometric transformations. This transformation finds its applications in sensor-based robot control, flexible manufacturing system and industrial inspection, etc. A description approach for object structure is presented by its topological structure relation called Point-Line Relation Structure (PLRS). It has been shown how Petri nets can be used to model the matching process, and an optimal or near optimal matching can be obtained by tracking the reachability graph of the net. The experiment result shows that object can be successfully identified and located under 2D transformation such as translations, rotations, scale changes and distortions due to object occluded partially.

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.

Precision sensing by two opposing gradient sensors: how does Escherichia coli find its preferred pH level?

PubMed

Hu, Bo; Tu, Yuhai

2013-07-02

It is essential for bacteria to find optimal conditions for their growth and survival. The optimal levels of certain environmental factors (such as pH and temperature) often correspond to some intermediate points of the respective gradients. This requires the ability of bacteria to navigate from both directions toward the optimum location and is distinct from the conventional unidirectional chemotactic strategy. Remarkably, Escherichia coli cells can perform such a precision sensing task in pH taxis by using the same chemotaxis machinery, but with opposite pH responses from two different chemoreceptors (Tar and Tsr). To understand bacterial pH sensing, we developed an Ising-type model for a mixed cluster of opposing receptors based on the push-pull mechanism. Our model can quantitatively explain experimental observations in pH taxis for various mutants and wild-type cells. We show how the preferred pH level depends on the relative abundance of the competing sensors and how the sensory activity regulates the behavioral response. Our model allows us to make quantitative predictions on signal integration of pH and chemoattractant stimuli. Our study reveals two general conditions and a robust push-pull scheme for precision sensing, which should be applicable in other adaptive sensory systems with opposing gradient sensors. Copyright © 2013 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Localization with a mobile beacon in underwater acoustic sensor networks.

PubMed

Lee, Sangho; Kim, Kiseon

2012-01-01

Localization is one of the most important issues associated with underwater acoustic sensor networks, especially when sensor nodes are randomly deployed. Given that it is difficult to deploy beacon nodes at predetermined locations, localization schemes with a mobile beacon on the sea surface or along the planned path are inherently convenient, accurate, and energy-efficient. In this paper, we propose a new range-free Localization with a Mobile Beacon (LoMoB). The mobile beacon periodically broadcasts a beacon message containing its location. Sensor nodes are individually localized by passively receiving the beacon messages without inter-node communications. For location estimation, a set of potential locations are obtained as candidates for a node's location and then the node's location is determined through the weighted mean of all the potential locations with the weights computed based on residuals.

Localization with a Mobile Beacon in Underwater Acoustic Sensor Networks

PubMed Central

Lee, Sangho; Kim, Kiseon

2012-01-01

Localization is one of the most important issues associated with underwater acoustic sensor networks, especially when sensor nodes are randomly deployed. Given that it is difficult to deploy beacon nodes at predetermined locations, localization schemes with a mobile beacon on the sea surface or along the planned path are inherently convenient, accurate, and energy-efficient. In this paper, we propose a new range-free Localization with a Mobile Beacon (LoMoB). The mobile beacon periodically broadcasts a beacon message containing its location. Sensor nodes are individually localized by passively receiving the beacon messages without inter-node communications. For location estimation, a set of potential locations are obtained as candidates for a node's location and then the node's location is determined through the weighted mean of all the potential locations with the weights computed based on residuals. PMID:22778597

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

PubMed Central

Messina, Marco; Njuguna, James; Palas, Chrysovalantis

2018-01-01

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

Sensor-Motor Maps for Describing Linear Reflex Composition in Hopping.

PubMed

Schumacher, Christian; Seyfarth, André

2017-01-01

In human and animal motor control several sensory organs contribute to a network of sensory pathways modulating the motion depending on the task and the phase of execution to generate daily motor tasks such as locomotion. To better understand the individual and joint contribution of reflex pathways in locomotor tasks, we developed a neuromuscular model that describes hopping movements. In this model, we consider the influence of proprioceptive length (LFB), velocity (VFB) and force feedback (FFB) pathways of a leg extensor muscle on hopping stability, performance and efficiency (metabolic effort). Therefore, we explore the space describing the blending of the monosynaptic reflex pathway gains. We call this reflex parameter space a sensor-motor map . The sensor-motor maps are used to visualize the functional contribution of sensory pathways in multisensory integration. We further evaluate the robustness of these sensor-motor maps to changes in tendon elasticity, body mass, segment length and ground compliance. The model predicted that different reflex pathway compositions selectively optimize specific hopping characteristics (e.g., performance and efficiency). Both FFB and LFB were pathways that enable hopping. FFB resulted in the largest hopping heights, LFB enhanced hopping efficiency and VFB had the ability to disable hopping. For the tested case, the topology of the sensor-motor maps as well as the location of functionally optimal compositions were invariant to changes in system designs (tendon elasticity, body mass, segment length) or environmental parameters (ground compliance). Our results indicate that different feedback pathway compositions may serve different functional roles. The topology of the sensor-motor map was predicted to be robust against changes in the mechanical system design indicating that the reflex system can use different morphological designs, which does not apply for most robotic systems (for which the control often follows a specific design). Consequently, variations in body mechanics are permitted with consistent compositions of sensory feedback pathways. Given the variability in human body morphology, such variations are highly relevant for human motor control.

40 CFR 63.7741 - What are the installation, operation, and maintenance requirements for my monitors?

Code of Federal Regulations, 2010 CFR

2010-07-01

... paragraphs (a)(1)(i) through (iv) of this section. (i) Locate the flow sensor and other necessary equipment... sensor with a minimum measurement sensitivity of 2 percent of the flow rate. (iii) Conduct a flow sensor... paragraphs (a)(2)(i) through (vi) of this section. (i) Locate the pressure sensor(s) in or as close as...

40 CFR 63.7741 - What are the installation, operation, and maintenance requirements for my monitors?

Code of Federal Regulations, 2012 CFR

2012-07-01

... paragraphs (a)(1)(i) through (iv) of this section. (i) Locate the flow sensor and other necessary equipment... sensor with a minimum measurement sensitivity of 2 percent of the flow rate. (iii) Conduct a flow sensor... paragraphs (a)(2)(i) through (vi) of this section. (i) Locate the pressure sensor(s) in or as close as...

40 CFR 63.7741 - What are the installation, operation, and maintenance requirements for my monitors?

Code of Federal Regulations, 2014 CFR

2014-07-01

... paragraphs (a)(1)(i) through (iv) of this section. (i) Locate the flow sensor and other necessary equipment... sensor with a minimum measurement sensitivity of 2 percent of the flow rate. (iii) Conduct a flow sensor... paragraphs (a)(2)(i) through (vi) of this section. (i) Locate the pressure sensor(s) in or as close as...

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.

Distributed cluster management techniques for unattended ground sensor networks

NASA Astrophysics Data System (ADS)

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

2005-05-01

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

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

PubMed

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

2018-01-15

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

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

PubMed

Mathew, Ribu; Sankar, A Ravi

2018-05-01

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

Estimating parameters with pre-specified accuracies in distributed parameter systems using optimal experiment design

NASA Astrophysics Data System (ADS)

Potters, M. G.; Bombois, X.; Mansoori, M.; Hof, Paul M. J. Van den

2016-08-01

Estimation of physical parameters in dynamical systems driven by linear partial differential equations is an important problem. In this paper, we introduce the least costly experiment design framework for these systems. It enables parameter estimation with an accuracy that is specified by the experimenter prior to the identification experiment, while at the same time minimising the cost of the experiment. We show how to adapt the classical framework for these systems and take into account scaling and stability issues. We also introduce a progressive subdivision algorithm that further generalises the experiment design framework in the sense that it returns the lowest cost by finding the optimal input signal, and optimal sensor and actuator locations. Our methodology is then applied to a relevant problem in heat transfer studies: estimation of conductivity and diffusivity parameters in front-face experiments. We find good correspondence between numerical and theoretical results.

A low-complexity geometric bilateration method for localization in Wireless Sensor Networks and its comparison with Least-Squares methods.

PubMed

Cota-Ruiz, Juan; Rosiles, Jose-Gerardo; Sifuentes, Ernesto; Rivas-Perea, Pablo

2012-01-01

This research presents a distributed and formula-based bilateration algorithm that can be used to provide initial set of locations. In this scheme each node uses distance estimates to anchors to solve a set of circle-circle intersection (CCI) problems, solved through a purely geometric formulation. The resulting CCIs are processed to pick those that cluster together and then take the average to produce an initial node location. The algorithm is compared in terms of accuracy and computational complexity with a Least-Squares localization algorithm, based on the Levenberg-Marquardt methodology. Results in accuracy vs. computational performance show that the bilateration algorithm is competitive compared with well known optimized localization algorithms.

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

Damage Detection/Locating System Providing Thermal Protection

NASA Technical Reports Server (NTRS)

Woodard, Stanley E. (Inventor); Jones, Thomas W. (Inventor); Taylor, Bryant D. (Inventor); Qamar, A. Shams (Inventor)

2010-01-01

A damage locating system also provides thermal protection. An array of sensors substantially tiles an area of interest. Each sensor is a reflective-surface conductor having operatively coupled inductance and capacitance. A magnetic field response recorder is provided to interrogate each sensor before and after a damage condition. Changes in response are indicative of damage and a corresponding location thereof.

Localization of interictal epileptic spikes with MEG: optimization of an automated beamformer screening method (SAMepi) in a diverse epilepsy population

PubMed Central

Scott, Jonathan M.; Robinson, Stephen E.; Holroyd, Tom; Coppola, Richard; Sato, Susumu; Inati, Sara K.

2016-01-01

OBJECTIVE To describe and optimize an automated beamforming technique followed by identification of locations with excess kurtosis (g2) for efficient detection and localization of interictal spikes in medically refractory epilepsy patients. METHODS Synthetic Aperture Magnetometry with g2 averaged over a sliding time window (SAMepi) was performed in 7 focal epilepsy patients and 5 healthy volunteers. The effect of varied window lengths on detection of spiking activity was evaluated. RESULTS Sliding window lengths of 0.5–10 seconds performed similarly, with 0.5 and 1 second windows detecting spiking activity in one of the 3 virtual sensor locations with highest kurtosis. These locations were concordant with the region of eventual surgical resection in these 7 patients who remained seizure free at one year. Average g2 values increased with increasing sliding window length in all subjects. In healthy volunteers kurtosis values stabilized in datasets longer than two minutes. CONCLUSIONS SAMepi using g2 averaged over 1 second sliding time windows in datasets of at least 2 minutes duration reliably identified interictal spiking and the presumed seizure focus in these 7 patients. Screening the 5 locations with highest kurtosis values for spiking activity is an efficient and accurate technique for localizing interictal activity using MEG. SIGNIFICANCE SAMepi should be applied using the parameter values and procedure described for optimal detection and localization of interictal spikes. Use of this screening procedure could significantly improve the efficiency of MEG analysis if clinically validated. PMID:27760068

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

An Automated Method for Navigation Assessment for Earth Survey Sensors Using Island Targets

NASA Technical Reports Server (NTRS)

Patt, F. S.; Woodward, R. H.; Gregg, W. W.

1997-01-01

An automated method has been developed for performing navigation assessment on satellite-based Earth sensor data. The method utilizes islands as targets which can be readily located in the sensor data and identified with reference locations. The essential elements are an algorithm for classifying the sensor data according to source, a reference catalogue of island locations, and a robust pattern-matching algorithm for island identification. The algorithms were developed and tested for the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), an ocean colour sensor. This method will allow navigation error statistics to be automatically generated for large numbers of points, supporting analysis over large spatial and temporal ranges.

Automated navigation assessment for earth survey sensors using island targets

NASA Technical Reports Server (NTRS)

Patt, Frederick S.; Woodward, Robert H.; Gregg, Watson W.

1997-01-01

An automated method has been developed for performing navigation assessment on satellite-based Earth sensor data. The method utilizes islands as targets which can be readily located in the sensor data and identified with reference locations. The essential elements are an algorithm for classifying the sensor data according to source, a reference catalog of island locations, and a robust pattern-matching algorithm for island identification. The algorithms were developed and tested for the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), an ocean color sensor. This method will allow navigation error statistics to be automatically generated for large numbers of points, supporting analysis over large spatial and temporal ranges.

Inverse modeling methods for indoor airborne pollutant tracking: literature review and fundamentals.

PubMed

Liu, X; Zhai, Z

2007-12-01

Reduction in indoor environment quality calls for effective control and improvement measures. Accurate and prompt identification of contaminant sources ensures that they can be quickly removed and contaminated spaces isolated and cleaned. This paper discusses the use of inverse modeling to identify potential indoor pollutant sources with limited pollutant sensor data. The study reviews various inverse modeling methods for advection-dispersion problems and summarizes the methods into three major categories: forward, backward, and probability inverse modeling methods. The adjoint probability inverse modeling method is indicated as an appropriate model for indoor air pollutant tracking because it can quickly find source location, strength and release time without prior information. The paper introduces the principles of the adjoint probability method and establishes the corresponding adjoint equations for both multi-zone airflow models and computational fluid dynamics (CFD) models. The study proposes a two-stage inverse modeling approach integrating both multi-zone and CFD models, which can provide a rapid estimate of indoor pollution status and history for a whole building. Preliminary case study results indicate that the adjoint probability method is feasible for indoor pollutant inverse modeling. The proposed method can help identify contaminant source characteristics (location and release time) with limited sensor outputs. This will ensure an effective and prompt execution of building management strategies and thus achieve a healthy and safe indoor environment. The method can also help design optimal sensor networks.

Lightning Imaging Sensor (LIS) for the Earth Observing System

NASA Technical Reports Server (NTRS)

Christian, Hugh J.; Blakeslee, Richard J.; Goodman, Steven J.

1992-01-01

Not only are scientific objectives and instrument characteristics given of a calibrated optical LIS for the EOS but also for the Tropical Rainfall Measuring Mission (TRMM) which was designed to acquire and study the distribution and variability of total lightning on a global basis. The LIS can be traced to a lightning mapper sensor planned for flight on the GOES meteorological satellites. The LIS consists of a staring imager optimized to detect and locate lightning. The LIS will detect and locate lightning with storm scale resolution (i.e., 5 to 10 km) over a large region of the Earth's surface along the orbital track of the satellite, mark the time of occurrence of the lightning, and measure the radiant energy. The LIS will have a nearly uniform 90 pct. detection efficiency within the area viewed by the sensor, and will detect intracloud and cloud-to-ground discharges during day and night conditions. Also, the LIS will monitor individual storms and storm systems long enough to obtain a measure of the lightning flashing rate when they are within the field of view of the LIS. The LIS attributes include low cost, low weight and power, low data rate, and important science. The LIS will study the hydrological cycle, general circulation and sea surface temperature variations, along with examinations of the electrical coupling of thunderstorms with the ionosphere and magnetosphere, and observations and modeling of the global electric circuit.

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

PubMed Central

Santoyo-Ramón, José Antonio

2018-01-01

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

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.

Clustering and Beamforming for Efficient Communication in Wireless Sensor Networks

PubMed Central

Porcel-Rodríguez, Francisco; Valenzuela-Valdés, Juan; Padilla, Pablo; Luna-Valero, Francisco; Luque-Baena, Rafael; López-Gordo, Miguel Ángel

2016-01-01

Energy efficiency is a critical issue for wireless sensor networks (WSNs) as sensor nodes have limited power availability. In order to address this issue, this paper tries to maximize the power efficiency in WSNs by means of the evaluation of WSN node networks and their performance when both clustering and antenna beamforming techniques are applied. In this work, four different scenarios are defined, each one considering different numbers of sensors: 50, 20, 10, five, and two nodes per scenario, and each scenario is randomly generated thirty times in order to statistically validate the results. For each experiment, two different target directions for transmission are taken into consideration in the optimization process (φ = 0° and θ = 45°; φ = 45°, and θ = 45°). Each scenario is evaluated for two different types of antennas, an ideal isotropic antenna and a conventional dipole one. In this set of experiments two types of WSN are evaluated: in the first one, all of the sensors have the same amount of power for communications purposes; in the second one, each sensor has a different amount of power for its communications purposes. The analyzed cases in this document are focused on 2D surface and 3D space for the node location. To the authors’ knowledge, this is the first time that beamforming and clustering are simultaneously applied to increase the network lifetime in WSNs. PMID:27556463

Semi-physical simulation test for micro CMOS star sensor

NASA Astrophysics Data System (ADS)

Yang, Jian; Zhang, Guang-jun; Jiang, Jie; Fan, Qiao-yun

2008-03-01

A designed star sensor must be extensively tested before launching. Testing star sensor requires complicated process with much time and resources input. Even observing sky on the ground is a challenging and time-consuming job, requiring complicated and expensive equipments, suitable time and location, and prone to be interfered by weather. And moreover, not all stars distributed on the sky can be observed by this testing method. Semi-physical simulation in laboratory reduces the testing cost and helps to debug, analyze and evaluate the star sensor system while developing the model. The test system is composed of optical platform, star field simulator, star field simulator computer, star sensor and the central data processing computer. The test system simulates the starlight with high accuracy and good parallelism, and creates static or dynamic image in FOV (Field of View). The conditions of the test are close to observing real sky. With this system, the test of a micro star tracker designed by Beijing University of Aeronautics and Astronautics has been performed successfully. Some indices including full-sky autonomous star identification time, attitude update frequency and attitude precision etc. meet design requirement of the star sensor. Error source of the testing system is also analyzed. It is concluded that the testing system is cost-saving, efficient, and contributes to optimizing the embed arithmetic, shortening the development cycle and improving engineering design processes.

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

PubMed

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

2018-04-01

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

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.

Sensor-Data Fusion for Multi-Person Indoor Location Estimation

PubMed Central

2017-01-01

We consider the problem of estimating the location of people as they move and work in indoor environments. More specifically, we focus on the scenario where one of the persons of interest is unable or unwilling to carry a smartphone, or any other “wearable” device, which frequently arises in caregiver/cared-for situations. We consider the case of indoor spaces populated with anonymous binary sensors (Passive Infrared motion sensors) and eponymous wearable sensors (smartphones interacting with Estimote beacons), and we propose a solution to the resulting sensor-fusion problem. Using a data set with sensor readings collected from one-person and two-person sessions engaged in a variety of activities of daily living, we investigate the relative merits of relying solely on anonymous sensors, solely on eponymous sensors, or on their combination. We examine how the lack of synchronization across different sensing sources impacts the quality of location estimates, and discuss how it could be mitigated without resorting to device-level mechanisms. Finally, we examine the trade-off between the sensors’ coverage of the monitored space and the quality of the location estimates. PMID:29057812

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.

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

NASA Astrophysics Data System (ADS)

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

2013-06-01

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

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

Prototyping a compact system for active vibration isolation using piezoelectric sensors and actuators.

PubMed

Shen, Hui; Wang, Chun; Li, Liufeng; Chen, Lisheng

2013-05-01

Being small in size and weight, piezoelectric transducers hold unique positions in vibration sensing and control. Here, we explore the possibility of building a compact vibration isolation system using piezoelectric sensors and actuators. The mechanical resonances of a piezoelectric actuator around a few kHz are suppressed by an order of magnitude via electrical damping, which improves the high-frequency response. Working with a strain gauge located on the piezoelectric actuator, an auxiliary control loop eliminates the drift associated with a large servo gain at dc. Following this approach, we design, optimize, and experimentally verify the loop responses using frequency domain analysis. The vibration isolation between 1 Hz and 200 Hz is achieved and the attenuation peaks at 60 near vibration frequency of 20 Hz. Restrictions and potentials for extending the isolation to lower vibration frequencies are discussed.

Optimal Location through Distributed Algorithm to Avoid Energy Hole in Mobile Sink WSNs

PubMed Central

Qing-hua, Li; Wei-hua, Gui; Zhi-gang, Chen

2014-01-01

In multihop data collection sensor network, nodes near the sink need to relay on remote data and, thus, have much faster energy dissipation rate and suffer from premature death. This phenomenon causes energy hole near the sink, seriously damaging the network performance. In this paper, we first compute energy consumption of each node when sink is set at any point in the network through theoretical analysis; then we propose an online distributed algorithm, which can adjust sink position based on the actual energy consumption of each node adaptively to get the actual maximum lifetime. Theoretical analysis and experimental results show that the proposed algorithms significantly improve the lifetime of wireless sensor network. It lowers the network residual energy by more than 30% when it is dead. Moreover, the cost for moving the sink is relatively smaller. PMID:24895668

Operations-Focused Optimized Theater Weather Sensing Strategies Using Preemptive Binary Integer Programming

DTIC Science & Technology

2009-03-01

8217 Clear old problem data Do While Trim(Sheets("Campaign").Range("AF" & CStr (LOOP_COUNTER))) <> "" LOOP_COUNTER = LOOP_COUNTER + 1 Loop Do While...Trim(Sheets("Campaign").Range("A" & CStr (LOOP_COUNTER))) <> "" ’ Loop through all problem instances Sheets("Campaign").Range("R1:AF1").Rows...total number of locations M = Sheets("Campaign").Range("F" & CStr (LOOP_COUNTER)) ’ Record total number of sensor types N

Zernike Wavefront Sensor Modeling Development for LOWFS on WFIRST-AFTA

NASA Technical Reports Server (NTRS)

Wang, Xu; Wallace, J. Kent; Shi, Fang

2015-01-01

WFIRST-AFTA design makes use of an existing 2.4m telescope for direct imaging of exoplanets. To maintain the high contrast needed for the coronagraph, wavefront error (WFE) of the optical system needs to be continuously sensed and controlled. Low Order Wavefront Sensing (LOWFS) uses the rejected starlight from an immediate focal plane to sense wavefront changes (mostly thermally induced low order WFE) by combining the LOWFS mask (a phase plate located at the small center region with reflective layer) with the starlight rejection masks, i.e. Hybrid Lyot Coronagraph (HLC)'s occulter or Shaped Pupil Coronagraph (SPC)'s field stop. Zernike wavefront sensor (ZWFS) measures phase via the phase-contrast method and is known to be photon noise optimal for measuring low order aberrations. Recently, ZWFS was selected as the baseline LOWFS technology on WFIST/AFTA for its good sensitivity, accuracy, and its easy integration with the starlight rejection mask. In this paper, we review the theory of ZWFS operation, describe the ZWFS algorithm development, and summarize various numerical sensitivity studies on the sensor performance. In the end, the predicted sensor performance on SPC and HLC configurations are presented.

Parametric investigation of scalable tactile sensors

NASA Astrophysics Data System (ADS)

Saadatzi, Mohammad Nasser; Yang, Zhong; Baptist, Joshua R.; Sahasrabuddhe, Ritvij R.; Wijayasinghe, Indika B.; Popa, Dan O.

2017-05-01

In the near future, robots and humans will share the same environment and perform tasks cooperatively. For intuitive, safe, and reliable physical human-robot interaction (pHRI), sensorized robot skins for tactile measurements of contact are necessary. In a previous study, we presented skins consisting of strain gauge arrays encased in silicone encapsulants. Although these structures could measure normal forces applied directly onto the sensing elements, they also exhibited blind spots and response asymmetry to certain loading patterns. This study presents a parametric investigation of piezoresistive polymeric strain gauge that exhibits a symmetric omniaxial response thanks to its novel star-shaped structure. This strain gauge relies on the use of gold micro-patterned star-shaped structures with a thin layer of PEDOT:PSS which is a flexible polymer with piezoresistive properties. In this paper, the sensor is first modeled and comprehensively analyzed in the finite-element simulation environment COMSOL. Simulations include stress-strain loading for a variety of structure parameters such as gauge lengths, widths, and spacing, as well as multiple load locations relative to the gauge. Subsequently, sensors with optimized configurations obtained through simulations were fabricated using cleanroom photolithographic and spin-coating processes, and then experimentally tested. Results show a trend-wise agreement between experiments and simulations.

Damage detection in composite materials using Lamb wave methods

NASA Astrophysics Data System (ADS)

Kessler, Seth S.; Spearing, S. Mark; Soutis, Constantinos

2002-04-01

Cost-effective and reliable damage detection is critical for the utilization of composite materials. This paper presents part of an experimental and analytical survey of candidate methods for in situ damage detection of composite materials. Experimental results are presented for the application of Lamb wave techniques to quasi-isotropic graphite/epoxy test specimens containing representative damage modes, including delamination, transverse ply cracks and through-holes. Linear wave scans were performed on narrow laminated specimens and sandwich beams with various cores by monitoring the transmitted waves with piezoceramic sensors. Optimal actuator and sensor configurations were devised through experimentation, and various types of driving signal were explored. These experiments provided a procedure capable of easily and accurately determining the time of flight of a Lamb wave pulse between an actuator and sensor. Lamb wave techniques provide more information about damage presence and severity than previously tested methods (frequency response techniques), and provide the possibility of determining damage location due to their local response nature. These methods may prove suitable for structural health monitoring applications since they travel long distances and can be applied with conformable piezoelectric actuators and sensors that require little power.

Chemical Discrimination in Turbulent Gas Mixtures with MOX Sensors Validated by Gas Chromatography-Mass Spectrometry

PubMed Central

Fonollosa, Jordi; Rodríguez-Luján, Irene; Trincavelli, Marco; Vergara, Alexander; Huerta, Ramón

2014-01-01

Chemical detection systems based on chemo-resistive sensors usually include a gas chamber to control the sample air flow and to minimize turbulence. However, such a kind of experimental setup does not reproduce the gas concentration fluctuations observed in natural environments and destroys the spatio-temporal information contained in gas plumes. Aiming at reproducing more realistic environments, we utilize a wind tunnel with two independent gas sources that get naturally mixed along a turbulent flow. For the first time, chemo-resistive gas sensors are exposed to dynamic gas mixtures generated with several concentration levels at the sources. Moreover, the ground truth of gas concentrations at the sensor location was estimated by means of gas chromatography-mass spectrometry. We used a support vector machine as a tool to show that chemo-resistive transduction can be utilized to reliably identify chemical components in dynamic turbulent mixtures, as long as sufficient gas concentration coverage is used. We show that in open sampling systems, training the classifiers only on high concentrations of gases produces less effective classification and that it is important to calibrate the classification method with data at low gas concentrations to achieve optimal performance. PMID:25325339

Chemical discrimination in turbulent gas mixtures with MOX sensors validated by gas chromatography-mass spectrometry.

PubMed

Fonollosa, Jordi; Rodríguez-Luján, Irene; Trincavelli, Marco; Vergara, Alexander; Huerta, Ramón

2014-10-16

Chemical detection systems based on chemo-resistive sensors usually include a gas chamber to control the sample air flow and to minimize turbulence. However, such a kind of experimental setup does not reproduce the gas concentration fluctuations observed in natural environments and destroys the spatio-temporal information contained in gas plumes. Aiming at reproducing more realistic environments, we utilize a wind tunnel with two independent gas sources that get naturally mixed along a turbulent flow. For the first time, chemo-resistive gas sensors are exposed to dynamic gas mixtures generated with several concentration levels at the sources. Moreover, the ground truth of gas concentrations at the sensor location was estimated by means of gas chromatography-mass spectrometry. We used a support vector machine as a tool to show that chemo-resistive transduction can be utilized to reliably identify chemical components in dynamic turbulent mixtures, as long as sufficient gas concentration coverage is used. We show that in open sampling systems, training the classifiers only on high concentrations of gases produces less effective classification and that it is important to calibrate the classification method with data at low gas concentrations to achieve optimal performance.

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.

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

PubMed Central

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

2007-01-01

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

Preliminary Design of a Lightning Optical Camera and ThundEr (LOCATE) Sensor

NASA Technical Reports Server (NTRS)

Phanord, Dieudonne D.; Koshak, William J.; Rybski, Paul M.; Arnold, James E. (Technical Monitor)

2001-01-01

The preliminary design of an optical/acoustical instrument is described for making highly accurate real-time determinations of the location of cloud-to-ground (CG) lightning. The instrument, named the Lightning Optical Camera And ThundEr (LOCATE) sensor, will also image the clear and cloud-obscured lightning channel produced from CGs and cloud flashes, and will record the transient optical waveforms produced from these discharges. The LOCATE sensor will consist of a full (360 degrees) field-of-view optical camera for obtaining CG channel image and azimuth, a sensitive thunder microphone for obtaining CG range, and a fast photodiode system for time-resolving the lightning optical waveform. The optical waveform data will be used to discriminate CGs from cloud flashes. Together, the optical azimuth and thunder range is used to locate CGs and it is anticipated that a network of LOCATE sensors would determine CG source location to well within 100 meters. All of this would be accomplished for a relatively inexpensive cost compared to present RF lightning location technologies, but of course the range detection is limited and will be quantified in the future. The LOCATE sensor technology would have practical applications for electric power utility companies, government (e.g. NASA Kennedy Space Center lightning safety and warning), golf resort lightning safety, telecommunications, and other industries.

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.

A New Approach to Design Autonomous Wireless Sensor Node Based on RF Energy Harvesting System

PubMed Central

Hakem, Nadir

2018-01-01

Energy Harvesting techniques are increasingly seen as the solution for freeing the wireless sensor nodes from their battery dependency. However, it remains evident that network performance features, such as network size, packet length, and duty cycle, are influenced by the sum of recovered energy. This paper proposes a new approach to defining the specifications of a stand-alone wireless node based on a Radio-frequency Energy Harvesting System (REHS). To achieve adequate performance regarding the range of the Wireless Sensor Network (WSN), techniques for minimizing the energy consumed by the sensor node are combined with methods for optimizing the performance of the REHS. For more rigor in the design of the autonomous node, a comprehensive energy model of the node in a wireless network is established. For an equitable distribution of network charges between the different nodes that compose it, the Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol is used for this purpose. The model considers five energy-consumption sources, most of which are ignored in recently used models. By using the hardware parameters of commercial off-the-shelf components (Mica2 Motes and CC2520 of Texas Instruments), the energy requirement of a sensor node is quantified. A miniature REHS based on a judicious choice of rectifying diodes is then designed and developed to achieve optimal performance in the Industrial Scientific and Medical (ISM) band centralized at 2.45 GHz. Due to the mismatch between the REHS and the antenna, a band pass filter is designed to reduce reflection losses. A gradient method search is used to optimize the output characteristics of the adapted REHS. At 1 mW of input RF power, the REHS provides an output DC power of 0.57 mW and a comparison with the energy requirement of the node allows the Base Station (BS) to be located at 310 m from the wireless nodes when the Wireless Sensor Network (WSN) has 100 nodes evenly spread over an area of 300 × 300 m2 and when each round lasts 10 min. The result shows that the range of the autonomous WSN increases when the controlled physical phenomenon varies very slowly. Having taken into account all the dissipation sources coexisting in a sensor node and using actual measurements of an REHS, this work provides the guidelines for the design of autonomous nodes based on REHS. PMID:29304002

Thin-film fiber optic hydrogen and temperature sensor system

DOEpatents

Nave, Stanley E.

1998-01-01

The invention discloses a sensor probe device for monitoring of hydrogen gas concentrations and temperatures by the same sensor probe. The sensor probe is constructed using thin-film deposition methods for the placement of a multitude of layers of materials sensitive to hydrogen concentrations and temperature on the end of a light transparent lens located within the sensor probe. The end of the lens within the sensor probe contains a lens containing a layer of hydrogen permeable material which excludes other reactive gases, a layer of reflective metal material that forms a metal hydride upon absorbing hydrogen, and a layer of semi-conducting solid that is transparent above a temperature dependent minimum wavelength for temperature detection. The three layers of materials are located at the distal end of the lens located within the sensor probe. The lens focuses light generated by broad-band light generator and connected by fiber-optics to the sensor probe, onto a reflective metal material layer, which passes through the semi-conducting solid layer, onto two optical fibers located at the base of the sensor probe. The reflected light is transmitted over fiberoptic cables to a spectrometer and system controller. The absence of electrical signals and electrical wires in the sensor probe provides for an elimination of the potential for spark sources when monitoring in hydrogen rich environments, and provides a sensor free from electrical interferences.

Thin-film fiber optic hydrogen and temperature sensor system

DOEpatents

Nave, S.E.

1998-07-21

The invention discloses a sensor probe device for monitoring of hydrogen gas concentrations and temperatures by the same sensor probe. The sensor probe is constructed using thin-film deposition methods for the placement of a multitude of layers of materials sensitive to hydrogen concentrations and temperature on the end of a light transparent lens located within the sensor probe. The end of the lens within the sensor probe contains a lens containing a layer of hydrogen permeable material which excludes other reactive gases, a layer of reflective metal material that forms a metal hydride upon absorbing hydrogen, and a layer of semi-conducting solid that is transparent above a temperature dependent minimum wavelength for temperature detection. The three layers of materials are located at the distal end of the lens located within the sensor probe. The lens focuses light generated by broad-band light generator and connected by fiber-optics to the sensor probe, onto a reflective metal material layer, which passes through the semi-conducting solid layer, onto two optical fibers located at the base of the sensor probe. The reflected light is transmitted over fiber optic cables to a spectrometer and system controller. The absence of electrical signals and electrical wires in the sensor probe provides for an elimination of the potential for spark sources when monitoring in hydrogen rich environments, and provides a sensor free from electrical interferences. 3 figs.

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

NASA Astrophysics Data System (ADS)

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

2005-03-01

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

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

PubMed Central

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

2018-01-01

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

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.

Connectivity Restoration in Wireless Sensor Networks via Space Network Coding.

PubMed

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

2017-04-20

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

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.

V/STOL tilt rotor research aircraft. Volume 3: Ship 2 instrumentation

NASA Technical Reports Server (NTRS)

1978-01-01

Information covering sensor cables, sensor installation, and sensor calibration for the XV-15 aircraft number 2 is included. For each junction box (J-box) designation there is a schematic of the J-box disconnect harness, instrumentation worksheets which show sensor location, and calibration data sheets for each sensor associated with that J-box. An index of measurement data codes to J-box locations is given in a table. Cross references are given.

V/STOL tilt rotor research aircraft. Volume 2: Ship 1 instrumentation

NASA Technical Reports Server (NTRS)

1978-01-01

Information covering sensor cables, sensor installation, and sensor calibration for the XV-15 aircraft number 1 is included. For each junction box (J-box) designation there is a schematic of the J-box disconnect harness instrumentation worksheets which show sensor location, and calibration data sheets for each sensor associated with that J-box. An index of measurement item codes to J-box locations is given in a table. Cross references are given.

LTCC Thick Film Process Characterization

DOE PAGES

Girardi, M. A.; Peterson, K. A.; Vianco, P. T.

2016-05-01

Low temperature cofired ceramic (LTCC) technology has proven itself in military/space electronics, wireless communication, microsystems, medical and automotive electronics, and sensors. The use of LTCC for high frequency applications is appealing due to its low losses, design flexibility and packaging and integration capability. Moreover, we summarize the LTCC thick film process including some unconventional process steps such as feature machining in the unfired state and thin film definition of outer layer conductors. The LTCC thick film process was characterized to optimize process yields by focusing on these factors: 1) Print location, 2) Print thickness, 3) Drying of tapes and panels,more » 4) Shrinkage upon firing, and 5) Via topography. Statistical methods were used to analyze critical process and product characteristics in the determination towards that optimization goal.« less

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.

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

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

Design and testing of a multi-sensor pedestrian location and navigation platform.

PubMed

Morrison, Aiden; Renaudin, Valérie; Bancroft, Jared B; Lachapelle, Gérard

2012-01-01

Navigation and location technologies are continually advancing, allowing ever higher accuracies and operation under ever more challenging conditions. The development of such technologies requires the rapid evaluation of a large number of sensors and related utilization strategies. The integration of Global Navigation Satellite Systems (GNSSs) such as the Global Positioning System (GPS) with accelerometers, gyros, barometers, magnetometers and other sensors is allowing for novel applications, but is hindered by the difficulties to test and compare integrated solutions using multiple sensor sets. In order to achieve compatibility and flexibility in terms of multiple sensors, an advanced adaptable platform is required. This paper describes the design and testing of the NavCube, a multi-sensor navigation, location and timing platform. The system provides a research tool for pedestrian navigation, location and body motion analysis in an unobtrusive form factor that enables in situ data collections with minimal gait and posture impact. Testing and examples of applications of the NavCube are provided.

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

Characterization of Methane Emission Sources Using Genetic Algorithms and Atmospheric Transport Modeling

NASA Astrophysics Data System (ADS)

Cao, Y.; Cervone, G.; Barkley, Z.; Lauvaux, T.; Deng, A.; Miles, N.; Richardson, S.

2016-12-01

Fugitive methane emission rates for the Marcellus shale area are estimated using a genetic algorithm that finds optimal weights to minimize the error between simulated and observed concentrations. The overall goal is to understand the relative contribution of methane due to Shale gas extraction. Methane sensors were installed on four towers located in northeastern Pennsylvania to measure atmospheric concentrations since May 2015. Inverse Lagrangian dispersion model runs are performed from each of these tower locations for each hour of 2015. Simulated methane concentrations at each of the four towers are computed by multiplying the resulting footprints from the atmospheric simulations by thousands of emission sources grouped into 11 classes. The emission sources were identified using GIS techniques, and include conventional and unconventional wells, different types of compressor stations, pipelines, landfills, farming and wetlands. Initial estimates for each source are calculated based on emission factors from EPA and few regional studies. A genetic algorithm is then used to identify optimal emission rates for the 11 classes of methane emissions and to explore extreme events and spatial and temporal structures in the emissions associated with natural gas activities.

Optimization of RFID network planning using Zigbee and WSN

NASA Astrophysics Data System (ADS)

Hasnan, Khalid; Ahmed, Aftab; Badrul-aisham, Bakhsh, Qadir

2015-05-01

Everyone wants to be ease in their life. Radio frequency identification (RFID) wireless technology is used to make our life easier. RFID technology increases productivity, accuracy and convenience in delivery of service in supply chain. It is used for various applications such as preventing theft of automobiles, tolls collection without stopping, no checkout lines at grocery stores, managing traffic, hospital management, corporate campuses and airports, mobile asset tracking, warehousing, tracking library books, and to track a wealth of assets in supply chain management. Efficiency of RFID can be enhanced by integrating with wireless sensor network (WSN), zigbee mesh network and internet of things (IOT). The proposed system is used for identifying, sensing and real-time locating system (RTLS) of items in an indoor heterogeneous region. The system gives real-time richer information of object's characteristics, location and their environmental parameters like temperature, noise and humidity etc. RTLS reduce human error, optimize inventory management, increase productivity and information accuracy at indoor heterogeneous network. The power consumption and the data transmission rate of the system can be minimized by using low power hardware design.

Local search for optimal global map generation using mid-decadal landsat images

USGS Publications Warehouse

Khatib, L.; Gasch, J.; Morris, Robert; Covington, S.

2007-01-01

NASA and the US Geological Survey (USGS) are seeking to generate a map of the entire globe using Landsat 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) sensor data from the "mid-decadal" period of 2004 through 2006. The global map is comprised of thousands of scene locations and, for each location, tens of different images of varying quality to chose from. Furthermore, it is desirable for images of adjacent scenes be close together in time of acquisition, to avoid obvious discontinuities due to seasonal changes. These characteristics make it desirable to formulate an automated solution to the problem of generating the complete map. This paper formulates a Global Map Generator problem as a Constraint Optimization Problem (GMG-COP) and describes an approach to solving it using local search. Preliminary results of running the algorithm on image data sets are summarized. The results suggest a significant improvement in map quality using constraint-based solutions. Copyright ?? 2007, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.

An Obstacle-Tolerant Path Planning Algorithm for Mobile-Anchor-Node-Assisted Localization

PubMed Central

Tsai, Rong-Guei

2018-01-01

The location information obtained using a sensor is a critical requirement in wireless sensor networks. Numerous localization schemes have been proposed, among which mobile-anchor-node-assisted localization (MANAL) can reduce costs and overcome environmental constraints. A mobile anchor node (MAN) provides its own location information to assist the localization of sensor nodes. Numerous path planning schemes have been proposed for MANAL, but most scenarios assume the absence of obstacles in the environment. However, in a realistic environment, sensor nodes cannot be located because the obstacles block the path traversed by the MAN, thereby rendering the sensor incapable of receiving sufficient three location information from the MAN. This study proposes the obstacle-tolerant path planning (OTPP) approach to solve the sensor location problem owing to obstacle blockage. OTPP can approximate the optimum beacon point number and path planning, thereby ensuring that all the unknown nodes can receive the three location information from the MAN and reduce the number of MAN broadcast packet times. Experimental results demonstrate that OTPP performs better than Z-curves because it reduces the total number of beacon points utilized and is thus more suitable in an obstacle-present environment. Compared to the Z-curve, OTPP can reduce localization error and improve localization coverage. PMID:29547582

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

PubMed

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

2011-01-01

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

Data fusion for a vision-aided radiological detection system: Calibration algorithm performance

NASA Astrophysics Data System (ADS)

Stadnikia, Kelsey; Henderson, Kristofer; Martin, Allan; Riley, Phillip; Koppal, Sanjeev; Enqvist, Andreas

2018-05-01

In order to improve the ability to detect, locate, track and identify nuclear/radiological threats, the University of Florida nuclear detection community has teamed up with the 3D vision community to collaborate on a low cost data fusion system. The key is to develop an algorithm to fuse the data from multiple radiological and 3D vision sensors as one system. The system under development at the University of Florida is being assessed with various types of radiological detectors and widely available visual sensors. A series of experiments were devised utilizing two EJ-309 liquid organic scintillation detectors (one primary and one secondary), a Microsoft Kinect for Windows v2 sensor and a Velodyne HDL-32E High Definition LiDAR Sensor which is a highly sensitive vision sensor primarily used to generate data for self-driving cars. Each experiment consisted of 27 static measurements of a source arranged in a cube with three different distances in each dimension. The source used was Cf-252. The calibration algorithm developed is utilized to calibrate the relative 3D-location of the two different types of sensors without need to measure it by hand; thus, preventing operator manipulation and human errors. The algorithm can also account for the facility dependent deviation from ideal data fusion correlation. Use of the vision sensor to determine the location of a sensor would also limit the possible locations and it does not allow for room dependence (facility dependent deviation) to generate a detector pseudo-location to be used for data analysis later. Using manually measured source location data, our algorithm-predicted the offset detector location within an average of 20 cm calibration-difference to its actual location. Calibration-difference is the Euclidean distance from the algorithm predicted detector location to the measured detector location. The Kinect vision sensor data produced an average calibration-difference of 35 cm and the HDL-32E produced an average calibration-difference of 22 cm. Using NaI and He-3 detectors in place of the EJ-309, the calibration-difference was 52 cm for NaI and 75 cm for He-3. The algorithm is not detector dependent; however, from these results it was determined that detector dependent adjustments are required.

REMORA 3: The first instrumented fuel experiment with on-line gas composition measurement by acoustic sensor

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

Lambert, T.; Muller, E.; Federici, E.

With the aim to improve the knowledge of nuclear fuel behaviour, the development of advanced instrumentation used during in-pile experiments in Material Testing Reactor (MTR) is necessary. To obtain data on high Burn-Up MOX fuel performance under transient operating conditions, especially in order to differentiate between the kinetics of fission gas and helium releases and to acquire data on the degradation of the fuel conductivity, a highly instrumented in-pile experiment called REMORA 3 has been conducted by CEA and IES (Southern Electronic Inst. - CNRS - Montpellier 2 Univ.). A rodlet extracted from a fuel rod base irradiated for fivemore » cycles in a French EDF commercial PWR has been re-instrumented with a fuel centerline thermocouple, a pressure transducer and an advanced acoustic sensor. This latter, patented by CEA and IES, is 1 used in addition to pressure measurement to determine the composition of the gases located in the free volume and the molar fractions of fission gas and helium. This instrumented fuel rodlet has been re-irradiated in a specific rig, GRIFFONOS, located in the periphery of the OSIRIS experimental reactor core at CEA Saclay. First of all, an important design stage and test phases have been performed before the irradiation in order to optimize the response and the accuracy of the sensors: - To control the influence of the temperature on the acoustic sensor behaviour, a thermal mock-up has been built. - To determine the temperature of the gas located in the acoustic cavity as a function of the coolant temperature, and the average temperature of the gases located in the rodlet free volume as a function of the linear heat rate, thermal calculations have been achieved. The former temperature is necessary to calculate the molar fractions of the gases and the latter is used to calculate the total amount of released gas from the internal rod pressure measurements. - At the end of the instrumented rod manufacturing, specific internal free volume and pressure measurements have been carried out. Preliminary calculations of the REMORA 3 experiments have been performed from these measurements, with the aim to determine free volume evolution as a function of linear heat rate history. - A tracer gas has been added to the filling gas in order to optimize the accuracy of the helium balance at the time of the post irradiation examination. The two phases of the REMORA 3 irradiation have been achieved at the end of 2010 in the OSIRIS reactor. Slight acoustic signal degradation, observed during the test under high neutron and gamma flux, has led to an efficiency optimization of the signal processing. The instrumentation ran smoothly and allowed to reach all the experimental objectives. After non destructive examination performed in the Osiris reactor pool, typically gamma spectrometry and neutron radiography, the instrumented rod and the device have been disassembled. Then the instrumented rod has been transported to the LECA facility in Cadarache Centre for post irradiation examination. The internal pressure and volume of the rodlet as well as precise gas composition measurements will be known after puncturing step performed in a hot cell of this facility. That will allow us to qualify the in-pile measurements and to finalize the data which will be used for the validation of the fuel behaviour computer codes. (authors)« less

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

PubMed

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

2017-09-21

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

The Video Collaborative Localization of a Miner’s Lamp Based on Wireless Multimedia Sensor Networks for Underground Coal Mines

PubMed Central

You, Kaiming; Yang, Wei; Han, Ruisong

2015-01-01

Based on wireless multimedia sensor networks (WMSNs) deployed in an underground coal mine, a miner’s lamp video collaborative localization algorithm was proposed to locate miners in the scene of insufficient illumination and bifurcated structures of underground tunnels. In bifurcation area, several camera nodes are deployed along the longitudinal direction of tunnels, forming a collaborative cluster in wireless way to monitor and locate miners in underground tunnels. Cap-lamps are regarded as the feature of miners in the scene of insufficient illumination of underground tunnels, which means that miners can be identified by detecting their cap-lamps. A miner’s lamp will project mapping points on the imaging plane of collaborative cameras and the coordinates of mapping points are calculated by collaborative cameras. Then, multiple straight lines between the positions of collaborative cameras and their corresponding mapping points are established. To find the three-dimension (3D) coordinate location of the miner’s lamp a least square method is proposed to get the optimal intersection of the multiple straight lines. Tests were carried out both in a corridor and a realistic scenario of underground tunnel, which show that the proposed miner’s lamp video collaborative localization algorithm has good effectiveness, robustness and localization accuracy in real world conditions of underground tunnels. PMID:26426023

Multifocal Fluorescence Microscope for Fast Optical Recordings of Neuronal Action Potentials

PubMed Central

Shtrahman, Matthew; Aharoni, Daniel B.; Hardy, Nicholas F.; Buonomano, Dean V.; Arisaka, Katsushi; Otis, Thomas S.

2015-01-01

In recent years, optical sensors for tracking neural activity have been developed and offer great utility. However, developing microscopy techniques that have several kHz bandwidth necessary to reliably capture optically reported action potentials (APs) at multiple locations in parallel remains a significant challenge. To our knowledge, we describe a novel microscope optimized to measure spatially distributed optical signals with submillisecond and near diffraction-limit resolution. Our design uses a spatial light modulator to generate patterned illumination to simultaneously excite multiple user-defined targets. A galvanometer driven mirror in the emission path streaks the fluorescence emanating from each excitation point during the camera exposure, using unused camera pixels to capture time varying fluorescence at rates that are ∼1000 times faster than the camera’s native frame rate. We demonstrate that this approach is capable of recording Ca2+ transients resulting from APs in neurons labeled with the Ca2+ sensor Oregon Green Bapta-1 (OGB-1), and can localize the timing of these events with millisecond resolution. Furthermore, optically reported APs can be detected with the voltage sensitive dye DiO-DPA in multiple locations within a neuron with a signal/noise ratio up to ∼40, resolving delays in arrival time along dendrites. Thus, the microscope provides a powerful tool for photometric measurements of dynamics requiring submillisecond sampling at multiple locations. PMID:25650920

Satellite, climatological, and theoretical inputs for modeling of the diurnal cycle of fire emissions

NASA Astrophysics Data System (ADS)

Hyer, E. J.; Reid, J. S.; Schmidt, C. C.; Giglio, L.; Prins, E.

2009-12-01

The diurnal cycle of fire activity is crucial for accurate simulation of atmospheric effects of fire emissions, especially at finer spatial and temporal scales. Estimating diurnal variability in emissions is also a critical problem for construction of emissions estimates from multiple sensors with variable coverage patterns. An optimal diurnal emissions estimate will use as much information as possible from satellite fire observations, compensate known biases in those observations, and use detailed theoretical models of the diurnal cycle to fill in missing information. As part of ongoing improvements to the Fire Location and Monitoring of Burning Emissions (FLAMBE) fire monitoring system, we evaluated several different methods of integrating observations with different temporal sampling. We used geostationary fire detections from WF_ABBA, fire detection data from MODIS, empirical diurnal cycles from TRMM, and simple theoretical diurnal curves based on surface heating. Our experiments integrated these data in different combinations to estimate the diurnal cycles of emissions for each location and time. Hourly emissions estimates derived using these methods were tested using an aerosol transport model. We present results of this comparison, and discuss the implications of our results for the broader problem of multi-sensor data fusion in fire emissions modeling.

Development of Navigation Doppler Lidar for Future Landing Mission

NASA Technical Reports Server (NTRS)

Amzajerdian, Farzin; Hines, Glenn D.; Petway, Larry B.; Barnes, Bruce W.; Pierrottet, Diego F.; Carson, John M., III

2016-01-01

A coherent Navigation Doppler Lidar (NDL) sensor has been developed under the Autonomous precision Landing and Hazard Avoidance Technology (ALHAT) project to support future NASA missions to planetary bodies. This lidar sensor provides accurate surface-relative altitude and vector velocity data during the descent phase that can be used by an autonomous Guidance, Navigation, and Control (GN&C) system to precisely navigate the vehicle from a few kilometers above the ground to a designated location and execute a controlled soft touchdown. The operation and performance of the NDL was demonstrated through closed-loop flights onboard the rocket-propelled Morpheus vehicle in 2014. In Morpheus flights, conducted at the NASA Kennedy Space Center, the NDL data was used by an autonomous GN&C system to navigate and land the vehicle precisely at the selected location surrounded by hazardous rocks and craters. Since then, development efforts for the NDL have shifted toward enhancing performance, optimizing design, and addressing spaceflight size and mass constraints and environmental and reliability requirements. The next generation NDL, with expanded operational envelope and significantly reduced size, will be demonstrated in 2017 through a new flight test campaign onboard a commercial rocketpropelled test vehicle.

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

Simulation and Optimization of Large Scale Subsurface Environmental Impacts; Investigations, Remedial Design and Long Term Monitoring

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

Deschaine, L.M.; Chalmers Univ. of Technology, Dept. of Physical Resources, Complex Systems Group, Goteborg

2008-07-01

The global impact to human health and the environment from large scale chemical / radionuclide releases is well documented. Examples are the wide spread release of radionuclides from the Chernobyl nuclear reactors, the mobilization of arsenic in Bangladesh, the formation of Environmental Protection Agencies in the United States, Canada and Europe, and the like. The fiscal costs of addressing and remediating these issues on a global scale are astronomical, but then so are the fiscal and human health costs of ignoring them. An integrated methodology for optimizing the response(s) to these issues is needed. This work addresses development of optimalmore » policy design for large scale, complex, environmental issues. It discusses the development, capabilities, and application of a hybrid system of algorithms that optimizes the environmental response. It is important to note that 'optimization' does not singularly refer to cost minimization, but to the effective and efficient balance of cost, performance, risk, management, and societal priorities along with uncertainty analysis. This tool integrates all of these elements into a single decision framework. It provides a consistent approach to designing optimal solutions that are tractable, traceable, and defensible. The system is modular and scalable. It can be applied either as individual components or in total. By developing the approach in a complex systems framework, a solution methodology represents a significant improvement over the non-optimal 'trial and error' approach to environmental response(s). Subsurface environmental processes are represented by linear and non-linear, elliptic and parabolic equations. The state equations solved using numerical methods include multi-phase flow (water, soil gas, NAPL), and multicomponent transport (radionuclides, heavy metals, volatile organics, explosives, etc.). Genetic programming is used to generate the simulators either when simulation models do not exist, or to extend the accuracy of them. The uncertainty and sparse nature of information in earth science simulations necessitate stochastic representations. For discussion purposes, the solution to these site-wide challenges is divided into three sub-components; plume finding, long term monitoring, and site-wide remediation. Plume finding is the optimal estimation of the plume fringe(s) at a specified time. It is optimized by fusing geo-stochastic flow and transport simulations with the information content of data using a Kalman filter. The result is an optimal monitoring sensor network; the decision variable is location(s) of sensor in three dimensions. Long term monitoring extends this approach concept, and integrates the spatial-time correlations to optimize the decision variables of where to sample and when to sample over the project life cycle. Optimization of location and timing of samples to meet the desired accuracy of temporal plume movement is accomplished using enumeration or genetic algorithms. The remediation optimization solves the multi-component, multiphase system of equations and incorporates constraints on life-cycle costs, maximum annual costs, maximum allowable annual discharge (for assessing the monitored natural attenuation solution) and constraints on where remedial system component(s) can be located, including management overrides to force certain solutions to be chosen are incorporated for solution design. It uses a suite of optimization techniques, including the outer approximation method, Lipchitz global optimization, genetic algorithms, and the like. The automated optimal remedial design algorithm requires a stable simulator be available for the simulated process. This is commonly the case for all above specifications sans true three-dimensional multiphase flow. Much work is currently being conducted in the industry to develop stable 3D, three-phase simulators. If needed, an interim heuristic algorithm is available to get close to optimal for these conditions. This system process provides the full capability to optimize multi-source, multiphase, and multicomponent sites. The results of applying just components of these algorithms have produced predicted savings of as much as $90,000,000(US), when compared to alternative solutions. Investment in a pilot program to test the model saved 100% of the $20,000,000 predicted for the smaller test implementation. This was done without loss of effectiveness, and received an award from the Vice President - and now Nobel peace prize winner - Al Gore of the United States. (authors)« less

Mini-UAV based sensory system for measuring environmental variables in greenhouses.

PubMed

Roldán, Juan Jesús; Joossen, Guillaume; Sanz, David; del Cerro, Jaime; Barrientos, Antonio

2015-02-02

This paper describes the design, construction and validation of a mobile sensory platform for greenhouse monitoring. The complete system consists of a sensory system on board a small quadrotor (i.e., a four rotor mini-UAV). The goals of this system include taking measures of temperature, humidity, luminosity and CO2 concentration and plotting maps of these variables. These features could potentially allow for climate control, crop monitoring or failure detection (e.g., a break in a plastic cover). The sensors have been selected by considering the climate and plant growth models and the requirements for their integration onboard the quadrotor. The sensors layout and placement have been determined through a study of quadrotor aerodynamics and the influence of the airflows from its rotors. All components of the system have been developed, integrated and tested through a set of field experiments in a real greenhouse. The primary contributions of this paper are the validation of the quadrotor as a platform for measuring environmental variables and the determination of the optimal location of sensors on a quadrotor.

Mini-UAV Based Sensory System for Measuring Environmental Variables in Greenhouses

PubMed Central

Roldán, Juan Jesús; Joossen, Guillaume; Sanz, David; del Cerro, Jaime; Barrientos, Antonio

2015-01-01

This paper describes the design, construction and validation of a mobile sensory platform for greenhouse monitoring. The complete system consists of a sensory system on board a small quadrotor (i.e., a four rotor mini-UAV). The goals of this system include taking measures of temperature, humidity, luminosity and CO2 concentration and plotting maps of these variables. These features could potentially allow for climate control, crop monitoring or failure detection (e.g., a break in a plastic cover). The sensors have been selected by considering the climate and plant growth models and the requirements for their integration onboard the quadrotor. The sensors layout and placement have been determined through a study of quadrotor aerodynamics and the influence of the airflows from its rotors. All components of the system have been developed, integrated and tested through a set of field experiments in a real greenhouse. The primary contributions of this paper are the validation of the quadrotor as a platform for measuring environmental variables and the determination of the optimal location of sensors on a quadrotor. PMID:25648713

Thermal Characterization of a Simulated Fission Engine via Distributed Fiber Bragg Gratings

NASA Astrophysics Data System (ADS)

Duncan, Roger G.; Fielder, Robert S.; Seeley, Ryan J.; Kozikowski, Carrie L.; Raum, Matthew T.

2005-02-01

We report the use of distributed fiber Bragg gratings to monitor thermal conditions within a simulated nuclear reactor core located at the Early Flight Fission Test Facility of the NASA Marshall Space Flight Center. Distributed fiber-optic temperature measurements promise to add significant capability and advance the state-of-the-art in high-temperature sensing. For the work reported herein, seven probes were constructed with ten sensors each for a total of 70 sensor locations throughout the core. These discrete temperature sensors were monitored over a nine hour period while the test article was heated to over 700 °C and cooled to ambient through two operational cycles. The sensor density available permits a significantly elevated understanding of thermal effects within the simulated reactor. Fiber-optic sensor performance is shown to compare very favorably with co-located thermocouples where such co-location was feasible.

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%.

ManPortable and UGV LIVAR: advances in sensor suite integration bring improvements to target observation and identification for the electronic battlefield

NASA Astrophysics Data System (ADS)

Lynam, Jeff R.

2001-09-01

A more highly integrated, electro-optical sensor suite using Laser Illuminated Viewing and Ranging (LIVAR) techniques is being developed under the Army Advanced Concept Technology- II (ACT-II) program for enhanced manportable target surveillance and identification. The ManPortable LIVAR system currently in development employs a wide-array of sensor technologies that provides the foot-bound soldier and UGV significant advantages and capabilities in lightweight, fieldable, target location, ranging and imaging systems. The unit incorporates a wide field-of-view, 5DEG x 3DEG, uncooled LWIR passive sensor for primary target location. Laser range finding and active illumination is done with a triggered, flash-lamp pumped, eyesafe micro-laser operating in the 1.5 micron region, and is used in conjunction with a range-gated, electron-bombarded CCD digital camera to then image the target objective in a more- narrow, 0.3$DEG, field-of-view. Target range determination is acquired using the integrated LRF and a target position is calculated using data from other onboard devices providing GPS coordinates, tilt, bank and corrected magnetic azimuth. Range gate timing and coordinated receiver optics focus control allow for target imaging operations to be optimized. The onboard control electronics provide power efficient, system operations for extended field use periods from the internal, rechargeable battery packs. Image data storage, transmission, and processing performance capabilities are also being incorporated to provide the best all-around support, for the electronic battlefield, in this type of system. The paper will describe flash laser illumination technology, EBCCD camera technology with flash laser detection system, and image resolution improvement through frame averaging.

An assessment of commonly employed satellite-based remote sensors for mapping mangrove species in Mexico using an NDVI-based classification scheme.

PubMed

Valderrama-Landeros, L; Flores-de-Santiago, F; Kovacs, J M; Flores-Verdugo, F

2017-12-14

Optimizing the classification accuracy of a mangrove forest is of utmost importance for conservation practitioners. Mangrove forest mapping using satellite-based remote sensing techniques is by far the most common method of classification currently used given the logistical difficulties of field endeavors in these forested wetlands. However, there is now an abundance of options from which to choose in regards to satellite sensors, which has led to substantially different estimations of mangrove forest location and extent with particular concern for degraded systems. The objective of this study was to assess the accuracy of mangrove forest classification using different remotely sensed data sources (i.e., Landsat-8, SPOT-5, Sentinel-2, and WorldView-2) for a system located along the Pacific coast of Mexico. Specifically, we examined a stressed semiarid mangrove forest which offers a variety of conditions such as dead areas, degraded stands, healthy mangroves, and very dense mangrove island formations. The results indicated that Landsat-8 (30 m per pixel) had  the lowest overall accuracy at 64% and that WorldView-2 (1.6 m per pixel) had the highest at 93%. Moreover, the SPOT-5 and the Sentinel-2 classifications (10 m per pixel) were very similar having accuracies of 75 and 78%, respectively. In comparison to WorldView-2, the other sensors overestimated the extent of Laguncularia racemosa and underestimated the extent of Rhizophora mangle. When considering such type of sensors, the higher spatial resolution can be particularly important in mapping small mangrove islands that often occur in degraded mangrove systems.

Application of Odor Sensors to Ore Sorting and Mill Feed Control

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

Michael G. Nelson

2005-08-01

Control of the feed provided to mineral processing facilities is a continuing challenge. Much effort is currently being devoted to overcoming these problems. These projects are usually described under the general headings of Mine-to-Mill Integration or Mine-Mill Optimization. It should be possible to combine the knowledge of ore type, mineralogy, and other characteristics (located in the mine modeling system), with the advanced capabilities of state-of-the-art mill control systems, to achieve an improved level of control in mineral processing that will allow optimization of the mill processes on an almost real-time basis. This is not happening because mill feed it ismore » often treated as a uniform material, when in reality it varies in composition and characteristics. An investigation was conducted to assess the suitability of odor sensors for maintaining traceability in ore production and processing. Commercially available sensors are now used in food processing, environmental monitoring, and other applications and can detect the presence of very small amounts (0.1-500 ppm) of some molecules. An assortment of such molecules could be used to ''tag'' blocks of ore as they are mined, according to their respective characteristics. Then, as the ore came into the mill, an array of ''electronic noses'' could be used to assess its characteristics in real time. It was found that the Cyranose 320{trademark}, a commercially available odor sensor, can easily distinguish among samples of rock marked with almond, cinnamon, citronella, lemon, and orange oils. Further, the sensor could detect mixtures of rocks marked with various combinations of these oils. Treatment of mixtures of galena and silica with odorant compounds showed no detrimental effects on flotation response in laboratory tests. Additional work is recommended to determine how this concept can be extended to the marking of large volumes of materials.« less

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.

Data-centric multiobjective QoS-aware routing protocol for body sensor networks.

PubMed

Razzaque, Md Abdur; Hong, Choong Seon; Lee, Sungwon

2011-01-01

In this paper, we address Quality-of-Service (QoS)-aware routing issue for Body Sensor Networks (BSNs) in delay and reliability domains. We propose a data-centric multiobjective QoS-Aware routing protocol, called DMQoS, which facilitates the system to achieve customized QoS services for each traffic category differentiated according to the generated data types. It uses modular design architecture wherein different units operate in coordination to provide multiple QoS services. Their operation exploits geographic locations and QoS performance of the neighbor nodes and implements a localized hop-by-hop routing. Moreover, the protocol ensures (almost) a homogeneous energy dissipation rate for all routing nodes in the network through a multiobjective Lexicographic Optimization-based geographic forwarding. We have performed extensive simulations of the proposed protocol, and the results show that DMQoS has significant performance improvements over several state-of-the-art approaches.

Self-localization of wireless sensor networks using self-organizing maps

NASA Astrophysics Data System (ADS)

Ertin, Emre; Priddy, Kevin L.

2005-03-01

Recently there has been a renewed interest in the notion of deploying large numbers of networked sensors for applications ranging from environmental monitoring to surveillance. In a typical scenario a number of sensors are distributed in a region of interest. Each sensor is equipped with sensing, processing and communication capabilities. The information gathered from the sensors can be used to detect, track and classify objects of interest. For a number of locations the sensors location is crucial in interpreting the data collected from those sensors. Scalability requirements dictate sensor nodes that are inexpensive devices without a dedicated localization hardware such as GPS. Therefore the network has to rely on information collected within the network to self-localize. In the literature a number of algorithms has been proposed for network localization which uses measurements informative of range, angle, proximity between nodes. Recent work by Patwari and Hero relies on sensor data without explicit range estimates. The assumption is that the correlation structure in the data is a monotone function of the intersensor distances. In this paper we propose a new method based on unsupervised learning techniques to extract location information from the sensor data itself. We consider a grid consisting of virtual nodes and try to fit grid in the actual sensor network data using the method of self organizing maps. Then known sensor network geometry can be used to rotate and scale the grid to a global coordinate system. Finally, we illustrate how the virtual nodes location information can be used to track a target.

30 CFR 75.351 - Atmospheric monitoring systems.

Code of Federal Regulations, 2010 CFR

2010-07-01

... and type of AMS sensor at each location, and the intended air flow direction at these locations. This... methane concentration at any sensor reaches the alert level as specified in § 75.351(i). These signals... carbon monoxide, smoke, or methane concentration at any sensor reaches the alarm level as specified in...

30 CFR 75.351 - Atmospheric monitoring systems.

Code of Federal Regulations, 2011 CFR

2011-07-01

... and type of AMS sensor at each location, and the intended air flow direction at these locations. This... methane concentration at any sensor reaches the alert level as specified in § 75.351(i). These signals... carbon monoxide, smoke, or methane concentration at any sensor reaches the alarm level as specified in...

An Analysis on Sensor Locations of the Human Body for Wearable Fall Detection Devices: Principles and Practice

PubMed Central

Özdemir, Ahmet Turan

2016-01-01

Wearable devices for fall detection have received attention in academia and industry, because falls are very dangerous, especially for elderly people, and if immediate aid is not provided, it may result in death. However, some predictive devices are not easily worn by elderly people. In this work, a huge dataset, including 2520 tests, is employed to determine the best sensor placement location on the body and to reduce the number of sensor nodes for device ergonomics. During the tests, the volunteer’s movements are recorded with six groups of sensors each with a triaxial (accelerometer, gyroscope and magnetometer) sensor, which is placed tightly on different parts of the body with special straps: head, chest, waist, right-wrist, right-thigh and right-ankle. The accuracy of individual sensor groups with their location is investigated with six machine learning techniques, namely the k-nearest neighbor (k-NN) classifier, Bayesian decision making (BDM), support vector machines (SVM), least squares method (LSM), dynamic time warping (DTW) and artificial neural networks (ANNs). Each technique is applied to single, double, triple, quadruple, quintuple and sextuple sensor configurations. These configurations create 63 different combinations, and for six machine learning techniques, a total of 63 × 6 = 378 combinations is investigated. As a result, the waist region is found to be the most suitable location for sensor placement on the body with 99.96% fall detection sensitivity by using the k-NN classifier, whereas the best sensitivity achieved by the wrist sensor is 97.37%, despite this location being highly preferred for today’s wearable applications. PMID:27463719

An Analysis on Sensor Locations of the Human Body for Wearable Fall Detection Devices: Principles and Practice.

PubMed

Özdemir, Ahmet Turan

2016-07-25

Wearable devices for fall detection have received attention in academia and industry, because falls are very dangerous, especially for elderly people, and if immediate aid is not provided, it may result in death. However, some predictive devices are not easily worn by elderly people. In this work, a huge dataset, including 2520 tests, is employed to determine the best sensor placement location on the body and to reduce the number of sensor nodes for device ergonomics. During the tests, the volunteer's movements are recorded with six groups of sensors each with a triaxial (accelerometer, gyroscope and magnetometer) sensor, which is placed tightly on different parts of the body with special straps: head, chest, waist, right-wrist, right-thigh and right-ankle. The accuracy of individual sensor groups with their location is investigated with six machine learning techniques, namely the k-nearest neighbor (k-NN) classifier, Bayesian decision making (BDM), support vector machines (SVM), least squares method (LSM), dynamic time warping (DTW) and artificial neural networks (ANNs). Each technique is applied to single, double, triple, quadruple, quintuple and sextuple sensor configurations. These configurations create 63 different combinations, and for six machine learning techniques, a total of 63 × 6 = 378 combinations is investigated. As a result, the waist region is found to be the most suitable location for sensor placement on the body with 99.96% fall detection sensitivity by using the k-NN classifier, whereas the best sensitivity achieved by the wrist sensor is 97.37%, despite this location being highly preferred for today's wearable applications.

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

Nygaard, Runar; Xiao, Hai; He, Xiaoming

Energy generation by use of fossil fuels produces large volumes of CO 2 and other greenhouse gases, whose accumulation in the atmosphere is widely seen as undesirable. CO 2 Capture followed by sequestration has been identified as the solution. Subsurface geologic formations offer a potential location for long-term storage of CO 2 because of their requisite size. Unfortunately, the inaccessibility and complexity of the subsurface, the wide range of scales of variability, and the coupled nonlinear processes, impose tremendous challenges to determine the transport and predict the fate of the stored CO 2. Among the various monitoring approaches, in situmore » down-hole monitoring of the various state parameters provides critical and direct data points that can be used to validate the models, optimize the injection, detect leakage and track the CO 2 plume. However, down-hole sensors that can withstand the harsh conditions and operate over decades of the project lifecycle remain unavailable. Given that the widespread of carbon capture and storage will be the necessity and reality in the future, fundamental and applied research is required to address the significant challenges and technological gaps in lack of long-term reliable down-hole sensors This project focused on the development and demonstration of a novel, low-cost, distributed, robust ceramic coaxial cable sensor platform for in situ down-hole monitoring of geologic CO 2 injection and storage with high spatial and temporal resolutions. The coaxial cable Fabry-Perot interferometer (CCFPI) has been studied as a general sensor platform for in situ, long-term, measurement of temperature, pressure and strain, which are critical to CO 2 injection and storage. A novel signal processing scheme has been developed and demonstrated for dense multiplexing of the sensors for low-cost distributed sensing with high spatial resolution. The developed temperature, pressure and strain sensors have been extensively tested under laboratory conditions that are similar to the downhole CO 2 storage environment, showing excellent capability for in situ monitoring the various parameters that are important to model, optimize the injection, detect leakage and track the CO 2 plume. In addition, the interactions between the sensor datum and the geological models have been investigated in details for the purposes of model validation, guiding sensor installation/placement, enhancement of model prediction capability and optimization of the injection processes. This project has resulted in the successful development of new ceramic coaxial cable based sensor systems that can monitor directly the changes in pressure, temperature, and strain caused by increased reservoir pressure and reduced reservoir temperature due to the supercritical CO 2 injection. Integrated with geological models, the sensors and measurement data can improve the possibility to identify plume movement and leakage in the cap rock and wells with higher precision and more accuracy. The low cost, ease of deployment, small size and dense multiplexing features of the new sensing technology will allow a large number of sensors to be deployed to address the objective to demonstrate that 99% of the CO 2 remains in the injection zone.« less

Assimilating uncertain, dynamic and intermittent streamflow observations in hydrological models

NASA Astrophysics Data System (ADS)

Mazzoleni, Maurizio; Alfonso, Leonardo; Chacon-Hurtado, Juan; Solomatine, Dimitri

2015-09-01

Catastrophic floods cause significant socio-economical losses. Non-structural measures, such as real-time flood forecasting, can potentially reduce flood risk. To this end, data assimilation methods have been used to improve flood forecasts by integrating static ground observations, and in some cases also remote sensing observations, within water models. Current hydrologic and hydraulic research works consider assimilation of observations coming from traditional, static sensors. At the same time, low-cost, mobile sensors and mobile communication devices are becoming also increasingly available. The main goal and innovation of this study is to demonstrate the usefulness of assimilating uncertain streamflow observations that are dynamic in space and intermittent in time in the context of two different semi-distributed hydrological model structures. The developed method is applied to the Brue basin, where the dynamic observations are imitated by the synthetic observations of discharge. The results of this study show how model structures and sensors locations affect in different ways the assimilation of streamflow observations. In addition, it proves how assimilation of such uncertain observations from dynamic sensors can provide model improvements similar to those of streamflow observations coming from a non-optimal network of static physical sensors. This can be a potential application of recent efforts to build citizen observatories of water, which can make the citizens an active part in information capturing, evaluation and communication, helping simultaneously to improvement of model-based flood forecasting.

Stress Prediction for Distributed Structural Health Monitoring Using Existing Measurements and Pattern Recognition.

PubMed

Lu, Wei; Teng, Jun; Zhou, Qiushi; Peng, Qiexin

2018-02-01

The stress in structural steel members is the most useful and directly measurable physical quantity to evaluate the structural safety in structural health monitoring, which is also an important index to evaluate the stress distribution and force condition of structures during structural construction and service phases. Thus, it is common to set stress as a measure in steel structural monitoring. Considering the economy and the importance of the structural members, there are only a limited number of sensors that can be placed, which means that it is impossible to obtain the stresses of all members directly using sensors. This study aims to develop a stress response prediction method for locations where there are insufficent sensors, using measurements from a limited number of sensors and pattern recognition. The detailed improved aspects are: (1) a distributed computing process is proposed, where the same pattern is recognized by several subsets of measurements; and (2) the pattern recognition using the subset of measurements is carried out by considering the optimal number of sensors and number of fusion patterns. The validity and feasibility of the proposed method are verified using two examples: the finite-element simulation of a single-layer shell-like steel structure, and the structural health monitoring of the space steel roof of Shenzhen Bay Stadium; for the latter, the anti-noise performance of this method is verified by the stress measurements from a real-world project.

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.

Uncertainty analysis of practical structural health monitoring systems currently employed for tall buildings consisting of small number of sensors

NASA Astrophysics Data System (ADS)

Hirai, Kenta; Mita, Akira

2016-04-01

Because of social background, such as repeated large earthquakes and cheating in design and construction, structural health monitoring (SHM) systems are getting strong attention. The SHM systems are in a practical phase. An SHM system consisting of small number of sensors has been introduced to 6 tall buildings in Shinjuku area. Including them, there are 2 major issues in the SHM systems consisting of small number of sensors. First, optimal system number of sensors and the location are not well-defined. In the practice, system placement is determined based on rough prediction and experience. Second, there are some uncertainties in estimation results by the SHM systems. Thus, the purpose of this research is to provide useful information for increasing reliability of SHM system and to improve estimation results based on uncertainty analysis of the SHM systems. The important damage index used here is the inter-story drift angle. The uncertainty considered here are number of sensors, earthquake motion characteristics, noise in data, error between numerical model and real building, nonlinearity of parameter. Then I have analyzed influence of each factor to estimation accuracy. The analysis conducted here will help to decide sensor system design considering valance of cost and accuracy. Because of constraint on the number of sensors, estimation results by the SHM system has tendency to provide smaller values. To overcome this problem, a compensation algorithm was discussed and presented. The usefulness of this compensation method was demonstrated for 40 story S and RC building models with nonlinear response.

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

PubMed Central

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

2016-01-01

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

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

Grasp Assist Device with Automatic Mode Control Logic

NASA Technical Reports Server (NTRS)

Laske, Evan (Inventor); Davis, Donald R. (Inventor); Ihrke, Chris A. (Inventor)

2018-01-01

A system includes a glove, sensors, actuator assemblies, and controller. The sensors include load sensors which measure an actual grasping force and attitude sensors which determine a glove attitude. The actuator assembly provides a grasp assist force to the glove. Respective locations of work cells in the work environment and permitted work tasks for each work cell are programmed into the controller. The controller detects the glove location and attitude. A work task is selected by the controller for the location. The controller calculates a required grasp assist force using measured actual grasping forces from the load sensors. The required grasp assist force is applied via the glove using the actuator assembly to thereby assist the operator in performing the identified work task.

Sensor placement algorithm development to maximize the efficiency of acid gas removal unit for integrated gasifiction combined sycle (IGCC) power plant with CO2 capture

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

Paul, P.; Bhattacharyya, D.; Turton, R.

2012-01-01

Future integrated gasification combined cycle (IGCC) power plants with CO{sub 2} capture will face stricter operational and environmental constraints. Accurate values of relevant states/outputs/disturbances are needed to satisfy these constraints and to maximize the operational efficiency. Unfortunately, a number of these process variables cannot be measured while a number of them can be measured, but have low precision, reliability, or signal-to-noise ratio. In this work, a sensor placement (SP) algorithm is developed for optimal selection of sensor location, number, and type that can maximize the plant efficiency and result in a desired precision of the relevant measured/unmeasured states. In thismore » work, an SP algorithm is developed for an selective, dual-stage Selexol-based acid gas removal (AGR) unit for an IGCC plant with pre-combustion CO{sub 2} capture. A comprehensive nonlinear dynamic model of the AGR unit is developed in Aspen Plus Dynamics® (APD) and used to generate a linear state-space model that is used in the SP algorithm. The SP algorithm is developed with the assumption that an optimal Kalman filter will be implemented in the plant for state and disturbance estimation. The algorithm is developed assuming steady-state Kalman filtering and steady-state operation of the plant. The control system is considered to operate based on the estimated states and thereby, captures the effects of the SP algorithm on the overall plant efficiency. The optimization problem is solved by Genetic Algorithm (GA) considering both linear and nonlinear equality and inequality constraints. Due to the very large number of candidate sets available for sensor placement and because of the long time that it takes to solve the constrained optimization problem that includes more than 1000 states, solution of this problem is computationally expensive. For reducing the computation time, parallel computing is performed using the Distributed Computing Server (DCS®) and the Parallel Computing® toolbox from Mathworks®. In this presentation, we will share our experience in setting up parallel computing using GA in the MATLAB® environment and present the overall approach for achieving higher computational efficiency in this framework.« less

Sensor placement algorithm development to maximize the efficiency of acid gas removal unit for integrated gasification combined cycle (IGCC) power plant with CO{sub 2} capture

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

Paul, P.; Bhattacharyya, D.; Turton, R.

2012-01-01

Future integrated gasification combined cycle (IGCC) power plants with CO{sub 2} capture will face stricter operational and environmental constraints. Accurate values of relevant states/outputs/disturbances are needed to satisfy these constraints and to maximize the operational efficiency. Unfortunately, a number of these process variables cannot be measured while a number of them can be measured, but have low precision, reliability, or signal-to-noise ratio. In this work, a sensor placement (SP) algorithm is developed for optimal selection of sensor location, number, and type that can maximize the plant efficiency and result in a desired precision of the relevant measured/unmeasured states. In thismore » work, an SP algorithm is developed for an selective, dual-stage Selexol-based acid gas removal (AGR) unit for an IGCC plant with pre-combustion CO{sub 2} capture. A comprehensive nonlinear dynamic model of the AGR unit is developed in Aspen Plus Dynamics® (APD) and used to generate a linear state-space model that is used in the SP algorithm. The SP algorithm is developed with the assumption that an optimal Kalman filter will be implemented in the plant for state and disturbance estimation. The algorithm is developed assuming steady-state Kalman filtering and steady-state operation of the plant. The control system is considered to operate based on the estimated states and thereby, captures the effects of the SP algorithm on the overall plant efficiency. The optimization problem is solved by Genetic Algorithm (GA) considering both linear and nonlinear equality and inequality constraints. Due to the very large number of candidate sets available for sensor placement and because of the long time that it takes to solve the constrained optimization problem that includes more than 1000 states, solution of this problem is computationally expensive. For reducing the computation time, parallel computing is performed using the Distributed Computing Server (DCS®) and the Parallel Computing® toolbox from Mathworks®. In this presentation, we will share our experience in setting up parallel computing using GA in the MATLAB® environment and present the overall approach for achieving higher computational efficiency in this framework.« less

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.

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

PubMed

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

2017-07-01

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

Impurity-doped optical shock, detonation and damage location sensor

DOEpatents

Weiss, J.D.

1995-02-07

A shock, detonation, and damage location sensor providing continuous fiber-optic means of measuring shock speed and damage location, and could be designed through proper cabling to have virtually any desired crush pressure. The sensor has one or a plurality of parallel multimode optical fibers, or a singlemode fiber core, surrounded by an elongated cladding, doped along their entire length with impurities to fluoresce in response to light at a different wavelength entering one end of the fiber(s). The length of a fiber would be continuously shorted as it is progressively destroyed by a shock wave traveling parallel to its axis. The resulting backscattered and shifted light would eventually enter a detector and be converted into a proportional electrical signals which would be evaluated to determine shock velocity and damage location. The corresponding reduction in output, because of the shortening of the optical fibers, is used as it is received to determine the velocity and position of the shock front as a function of time. As a damage location sensor the sensor fiber cracks along with the structure to which it is mounted. The size of the resulting drop in detector output is indicative of the location of the crack. 8 figs.

Impurity-doped optical shock, detonation and damage location sensor

DOEpatents

Weiss, Jonathan D.

1995-01-01

A shock, detonation, and damage location sensor providing continuous fiber-optic means of measuring shock speed and damage location, and could be designed through proper cabling to have virtually any desired crush pressure. The sensor has one or a plurality of parallel multimode optical fibers, or a singlemode fiber core, surrounded by an elongated cladding, doped along their entire length with impurities to fluoresce in response to light at a different wavelength entering one end of the fiber(s). The length of a fiber would be continuously shorted as it is progressively destroyed by a shock wave traveling parallel to its axis. The resulting backscattered and shifted light would eventually enter a detector and be converted into a proportional electrical signals which would be evaluated to determine shock velocity and damage location. The corresponding reduction in output, because of the shortening of the optical fibers, is used as it is received to determine the velocity and position of the shock front as a function of time. As a damage location sensor the sensor fiber cracks along with the structure to which it is mounted. The size of the resulting drop in detector output is indicative of the location of the crack.

An Improved Tibial Force Sensor to Compute Contact Forces and Contact Locations In Vitro After Total Knee Arthroplasty.

PubMed

Roth, Joshua D; Howell, Stephen M; Hull, Maury L

2017-04-01

Contact force imbalance and contact kinematics (i.e., motion of the contact location in each compartment during flexion) of the tibiofemoral joint are both important predictors of a patient's outcome following total knee arthroplasty (TKA). Previous tibial force sensors have limitations in that they either did not determine contact forces and contact locations independently in the medial and lateral compartments or only did so within restricted areas of the tibial insert, which prevented them from thoroughly evaluating contact force imbalance and contact kinematics in vitro. Accordingly, the primary objective of this study was to present the design and verification of an improved tibial force sensor which overcomes these limitations. The improved tibial force sensor consists of a modified tibial baseplate which houses independent medial and lateral arrays of three custom tension-compression transducers each. This sensor is interchangeable with a standard tibial component because it accommodates tibial articular surface inserts with a range of sizes and thicknesses. This sensor was verified by applying known loads at known locations over the entire surface of the tibial insert to determine the errors in the computed contact force and contact location in each compartment. The root-mean-square errors (RMSEs) in contact force are ≤ 6.1 N which is 1.4% of the 450 N full-scale output. The RMSEs in contact location are ≤ 1.6 mm. This improved tibial force sensor overcomes the limitations of the previous sensors and therefore should be useful for in vitro evaluation of new alignment goals, new surgical techniques, and new component designs in TKA.

Reflection type skin friction meter

NASA Technical Reports Server (NTRS)

Bandyopadhyay, Promode R. (Inventor); Weinstein, Leonard M. (Inventor)

1993-01-01

A housing block is provided having an upper surface conforming to the test surface of a model or aircraft. An oil film is supplied upstream of a transparent wedge window located in this upper surface by an oil pump system located external to the housing block. A light source located within the housing block supplies a light beam which passes through this transparent window and is reflected back through the transparent window by the upper surface of the oil film to a photo-sensitive position sensor located within the housing. This position sensor allows the slope history of the oil film caused by and aerodynamic flow to be determined. The skin friction is determined from this slope history. Internally located mirrors augment and sensitize the reflected beam as necessary before reaching the position sensor. In addition, a filter may be provided before this sensor to filter the beam.

Impact-Locator Sensor Panels

NASA Technical Reports Server (NTRS)

Christiansen, Eric L.; Byers, Terry; Gibbons, Frank

2008-01-01

Electronic sensor systems for detecting and locating impacts of rapidly moving particles on spacecraft have been invented. Systems of this type could also be useful on Earth in settings in which the occurrence of impacts and/or the locations of impacts are not immediately obvious and there are requirements to detect and quickly locate impacts to prevent or minimize damage.

Greedy Sparse Approaches for Homological Coverage in Location Unaware Sensor Networks

DTIC Science & Technology

2017-12-08

GlobalSIP); 2013 Dec; Austin , TX . p. 595– 598. 33. Farah C, Schwaner F, Abedi A, Worboys M. Distributed homology algorithm to detect topological events...ARL-TR-8235•DEC 2017 US Army Research Laboratory Greedy Sparse Approaches for Homological Coverage in Location-Unaware Sensor Net- works by Terrence...8235•DEC 2017 US Army Research Laboratory Greedy Sparse Approaches for Homological Coverage in Location-Unaware Sensor Net- works by Terrence J Moore

Multi-objective trajectory optimization for the space exploration vehicle

NASA Astrophysics Data System (ADS)

Qin, Xiaoli; Xiao, Zhen

2016-07-01

The research determines temperature-constrained optimal trajectory for the space exploration vehicle by developing an optimal control formulation and solving it using a variable order quadrature collocation method with a Non-linear Programming(NLP) solver. The vehicle is assumed to be the space reconnaissance aircraft that has specified takeoff/landing locations, specified no-fly zones, and specified targets for sensor data collections. A three degree of freedom aircraft model is adapted from previous work and includes flight dynamics, and thermal constraints.Vehicle control is accomplished by controlling angle of attack, roll angle, and propellant mass flow rate. This model is incorporated into an optimal control formulation that includes constraints on both the vehicle and mission parameters, such as avoidance of no-fly zones and exploration of space targets. In addition, the vehicle models include the environmental models(gravity and atmosphere). How these models are appropriately employed is key to gaining confidence in the results and conclusions of the research. Optimal trajectories are developed using several performance costs in the optimal control formation,minimum time,minimum time with control penalties,and maximum distance.The resulting analysis demonstrates that optimal trajectories that meet specified mission parameters and constraints can be quickly determined and used for large-scale space exloration.

Towards a hybrid energy efficient multi-tree-based optimized routing protocol for wireless networks.

PubMed

Mitton, Nathalie; Razafindralambo, Tahiry; Simplot-Ryl, David; Stojmenovic, Ivan

2012-12-13

This paper considers the problem of designing power efficient routing with guaranteed delivery for sensor networks with unknown geographic locations. We propose HECTOR, a hybrid energy efficient tree-based optimized routing protocol, based on two sets of virtual coordinates. One set is based on rooted tree coordinates, and the other is based on hop distances toward several landmarks. In HECTOR, the node currently holding the packet forwards it to its neighbor that optimizes ratio of power cost over distance progress with landmark coordinates, among nodes that reduce landmark coordinates and do not increase distance in tree coordinates. If such a node does not exist, then forwarding is made to the neighbor that reduces tree-based distance only and optimizes power cost over tree distance progress ratio. We theoretically prove the packet delivery and propose an extension based on the use of multiple trees. Our simulations show the superiority of our algorithm over existing alternatives while guaranteeing delivery, and only up to 30% additional power compared to centralized shortest weighted path algorithm.

Towards a Hybrid Energy Efficient Multi-Tree-Based Optimized Routing Protocol for Wireless Networks

PubMed Central

Mitton, Nathalie; Razafindralambo, Tahiry; Simplot-Ryl, David; Stojmenovic, Ivan

2012-01-01

This paper considers the problem of designing power efficient routing with guaranteed delivery for sensor networks with unknown geographic locations. We propose HECTOR, a hybrid energy efficient tree-based optimized routing protocol, based on two sets of virtual coordinates. One set is based on rooted tree coordinates, and the other is based on hop distances toward several landmarks. In HECTOR, the node currently holding the packet forwards it to its neighbor that optimizes ratio of power cost over distance progress with landmark coordinates, among nodes that reduce landmark coordinates and do not increase distance in tree coordinates. If such a node does not exist, then forwarding is made to the neighbor that reduces tree-based distance only and optimizes power cost over tree distance progress ratio. We theoretically prove the packet delivery and propose an extension based on the use of multiple trees. Our simulations show the superiority of our algorithm over existing alternatives while guaranteeing delivery, and only up to 30% additional power compared to centralized shortest weighted path algorithm. PMID:23443398

Theory of Arachnid Prey Localization

NASA Astrophysics Data System (ADS)

Stürzl, W.; Kempter, R.; van Hemmen, J. L.

2000-06-01

Sand scorpions and many other arachnids locate their prey through highly sensitive slit sensilla at the tips (tarsi) of their eight legs. This sensor array responds to vibrations with stimulus-locked action potentials encoding the target direction. We present a neuronal model to account for stimulus angle determination using a population of second-order neurons, each receiving excitatory input from one tarsus and inhibition from a triad opposite to it. The input opens a time window whose width determines a neuron's firing probability. Stochastic optimization is realized through tuning the balance between excitation and inhibition. The agreement with experiments on the sand scorpion is excellent.

Development of a method of alignment between various SOLAR MAXIMUM MISSION experiments

NASA Technical Reports Server (NTRS)

1977-01-01

Results of an engineering study of the methods of alignment between various experiments for the solar maximum mission are described. The configuration studied consists of the instruments, mounts and instrument support platform located within the experiment module. Hardware design, fabrication methods and alignment techniques were studied with regard to optimizing the coalignment between the experiments and the fine sun sensor. The proposed hardware design was reviewed with regard to loads, stress, thermal distortion, alignment error budgets, fabrication techniques, alignment techniques and producibility. Methods of achieving comparable alignment accuracies on previous projects were also reviewed.

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

Benson, D.K.; Tracy, C.E.

The real and perceived risks of hydrogen fuel use, particularly in passenger vehicles, will require extensive safety precautions including hydrogen leak detection. Conventional hydrogen gas sensors require electrical wiring and may be too expensive for deployment in multiple locations within a vehicle. In this recently initiated project, we are attempting to develop a reversible, thin-film, chemochromic sensor that can be applied to the end of a polymer optical fiber. The presence of hydrogen gas causes the film to become darker. A light beam transmitted from a central instrument in the vehicle along the sensor fibers will be reflected from themore » ends of the fiber back to individual light detectors. A decrease in the reflected light signal will indicate the presence and concentration of hydrogen in the vicinity of the fiber sensor. The typical thin film sensor consists of a layer of transparent, amorphous tungsten oxide covered by a very thin reflective layer of palladium. When the sensor is exposed to hydrogen, a portion of the hydrogen is dissociated, diffuses through the palladium and reacts with the tungsten oxide to form a blue insertion compound, H{sub X}WO{sub 3}- When the hydrogen gas is no longer present, the hydrogen will diffuse out of the H{sub X}WO{sub 3} and oxidize at the palladium/air interface, restoring the tungsten oxide film and the light signal to normal. The principle of this detection scheme has already been demonstrated by scientists in Japan. However, the design of the sensor has not been optimized for speed of response nor tested for its hydrogen selectivity in the presence of hydrocarbon gases. The challenge of this project is to modify the basic sensor design to achieve the required rapid response and assure sufficient selectivity to avoid false readings.« less

Wearable-Sensor-Based Classification Models of Faller Status in Older Adults.

PubMed

Howcroft, Jennifer; Lemaire, Edward D; Kofman, Jonathan

2016-01-01

Wearable sensors have potential for quantitative, gait-based, point-of-care fall risk assessment that can be easily and quickly implemented in clinical-care and older-adult living environments. This investigation generated models for wearable-sensor based fall-risk classification in older adults and identified the optimal sensor type, location, combination, and modelling method; for walking with and without a cognitive load task. A convenience sample of 100 older individuals (75.5 ± 6.7 years; 76 non-fallers, 24 fallers based on 6 month retrospective fall occurrence) walked 7.62 m under single-task and dual-task conditions while wearing pressure-sensing insoles and tri-axial accelerometers at the head, pelvis, and left and right shanks. Participants also completed the Activities-specific Balance Confidence scale, Community Health Activities Model Program for Seniors questionnaire, six minute walk test, and ranked their fear of falling. Fall risk classification models were assessed for all sensor combinations and three model types: multi-layer perceptron neural network, naïve Bayesian, and support vector machine. The best performing model was a multi-layer perceptron neural network with input parameters from pressure-sensing insoles and head, pelvis, and left shank accelerometers (accuracy = 84%, F1 score = 0.600, MCC score = 0.521). Head sensor-based models had the best performance of the single-sensor models for single-task gait assessment. Single-task gait assessment models outperformed models based on dual-task walking or clinical assessment data. Support vector machines and neural networks were the best modelling technique for fall risk classification. Fall risk classification models developed for point-of-care environments should be developed using support vector machines and neural networks, with a multi-sensor single-task gait assessment.

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.

30 CFR 75.1103-5 - Automatic fire warning devices; actions and response.

Code of Federal Regulations, 2010 CFR

2010-07-01

... level reaches 10 parts per million above the established ambient level at any sensor location, automatic fire sensor and warning device systems shall provide an effective warning signal at the following... endangered and (ii) A map or schematic that shows the locations of sensors, and the intended air flow...

40 CFR 86.107-98 - Sampling and analytical system.

Code of Federal Regulations, 2012 CFR

2012-07-01

... system (recorder and sensor) shall have an accuracy of ±3 °F (±1.7 °C). The recorder (data processor... ambient temperature sensors, connected to provide one average output, located 3 feet above the floor at... wall. For diurnal emission testing, an additional temperature sensor shall be located underneath the...

40 CFR 86.107-98 - Sampling and analytical system.

Code of Federal Regulations, 2013 CFR

2013-07-01

... system (recorder and sensor) shall have an accuracy of ±3 °F (±1.7 °C). The recorder (data processor... ambient temperature sensors, connected to provide one average output, located 3 feet above the floor at... wall. For diurnal emission testing, an additional temperature sensor shall be located underneath the...

40 CFR 86.107-98 - Sampling and analytical system.

Code of Federal Regulations, 2014 CFR

2014-07-01

... system (recorder and sensor) shall have an accuracy of ±3 °F (±1.7 °C). The recorder (data processor... ambient temperature sensors, connected to provide one average output, located 3 feet above the floor at... wall. For diurnal emission testing, an additional temperature sensor shall be located underneath the...

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.

Toward increased reliability in the electric power industry: direct temperature measurement in transformers using fiber optic sensors

NASA Astrophysics Data System (ADS)

McDonald, Greg

1998-09-01

Optimal loading, prevention of catastrophic failures and reduced maintenance costs are some of the benefits of accurate determination of hot spot winding temperatures in medium and high power transformers. Temperature estimates obtained using current theoretical models are not always accurate. Traditional technology (IR, thermocouples...) are unsuitable or inadequate for direct measurement. Nortech fiber-optic temperature sensors offer EMI immunity and chemical resistance and are a proven solution to the problem. The Nortech sensor's measurement principle is based on variations in the spectral absorption of a fiber-mounted semiconductor chip and probes are interchangeable with no need for recalibration. Total length of probe + extension can be up to several hundred meters allowing system electronics to be located in the control room or mounted in the transformer instrumentation cabinet. All of the sensor materials withstand temperatures up to 250 degree(s)C and have demonstrated excellent resistance to the harsh transformer environment (hot oil, kerosene). Thorough study of the problem and industry collaboration in testing and installation allows Nortech to identify and meet the need for durable probes, leak-proof feedthroughs, standard computer interfaces and measurement software. Refined probe technology, the method's simplicity and reliable calibration are all assets that should lead to growing acceptance of this type of direct measuring in the electric power industry.

Development a low-cost carbon monoxide sensor using homemade CW-DFB QCL and board-level electronics

NASA Astrophysics Data System (ADS)

Dang, Jingmin; Yu, Haiye; Zheng, Chuantao; Wang, Lijun; Sui, Yuanyuan; Wang, Yiding

2018-05-01

A mid-infrared sensor was demonstrated for the detection of carbon monoxide (CO) at trace level. In order to reduce cost, a homemade continuous-wave mode distributed feedback quantum cascade laser (CW-DFB QCL), a mini gas cell with 1.6-m optical length, and some self-development electronic modules were adopted as excitation source, absorption pool, and signal controlling and processing tool, respectively. Wavelength modulation spectroscopy (WMS) and phase sensitive detection (PSD) techniques as well as wavelet filtering software algorithm were used to reduce the influence of light source fluctuation and system noise and to improve measurement precision and sensitivity. Under the selected P(11) absorption line located at 2099.083 cm-1, a limit of detection (LoD) of 26 parts per billion by volume (ppbv) at atmospheric pressure was achieved with a 1-s acquisition time. Allan deviation was used to characterize the long-term performance of the CO sensor, and a measurement precision of ∼3.4 ppbv was observed with an optimal integration time of ∼114 s. As a field measurement, a continuous monitoring on indoor CO concentration for a period of 24 h was conducted, which verified the reliable and robust operation of the developed sensor.

Flow Control in Wells Turbines for Harnessing Maximum Wave Power.

PubMed

Lekube, Jon; Garrido, Aitor J; Garrido, Izaskun; Otaola, Erlantz; Maseda, Javier

2018-02-10

Oceans, and particularly waves, offer a huge potential for energy harnessing all over the world. Nevertheless, the performance of current energy converters does not yet allow us to use the wave energy efficiently. However, new control techniques can improve the efficiency of energy converters. In this sense, the plant sensors play a key role within the control scheme, as necessary tools for parameter measuring and monitoring that are then used as control input variables to the feedback loop. Therefore, the aim of this work is to manage the rotational speed control loop in order to optimize the output power. With the help of outward looking sensors, a Maximum Power Point Tracking (MPPT) technique is employed to maximize the system efficiency. Then, the control decisions are based on the pressure drop measured by pressure sensors located along the turbine. A complete wave-to-wire model is developed so as to validate the performance of the proposed control method. For this purpose, a novel sensor-based flow controller is implemented based on the different measured signals. Thus, the performance of the proposed controller has been analyzed and compared with a case of uncontrolled plant. The simulations demonstrate that the flow control-based MPPT strategy is able to increase the output power, and they confirm both the viability and goodness.

Flow Control in Wells Turbines for Harnessing Maximum Wave Power

PubMed Central

Garrido, Aitor J.; Garrido, Izaskun; Otaola, Erlantz; Maseda, Javier

2018-01-01

Oceans, and particularly waves, offer a huge potential for energy harnessing all over the world. Nevertheless, the performance of current energy converters does not yet allow us to use the wave energy efficiently. However, new control techniques can improve the efficiency of energy converters. In this sense, the plant sensors play a key role within the control scheme, as necessary tools for parameter measuring and monitoring that are then used as control input variables to the feedback loop. Therefore, the aim of this work is to manage the rotational speed control loop in order to optimize the output power. With the help of outward looking sensors, a Maximum Power Point Tracking (MPPT) technique is employed to maximize the system efficiency. Then, the control decisions are based on the pressure drop measured by pressure sensors located along the turbine. A complete wave-to-wire model is developed so as to validate the performance of the proposed control method. For this purpose, a novel sensor-based flow controller is implemented based on the different measured signals. Thus, the performance of the proposed controller has been analyzed and compared with a case of uncontrolled plant. The simulations demonstrate that the flow control-based MPPT strategy is able to increase the output power, and they confirm both the viability and goodness. PMID:29439408

Cable-fault locator

NASA Technical Reports Server (NTRS)

Cason, R. L.; Mcstay, J. J.; Heymann, A. P., Sr.

1979-01-01

Inexpensive system automatically indicates location of short-circuited section of power cable. Monitor does not require that cable be disconnected from its power source or that test signals be applied. Instead, ground-current sensors are installed in manholes or at other selected locations along cable run. When fault occurs, sensors transmit information about fault location to control center. Repair crew can be sent to location and cable can be returned to service with minimum of downtime.

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

NASA Astrophysics Data System (ADS)

Fu, Liyue; Song, Aiguo

2018-02-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

Hybrid-Aware Model for Senior Wellness Service in Smart Home.

PubMed

Jung, Yuchae

2017-05-22

Smart home technology with situation-awareness is important for seniors to improve safety and security. With the development of context-aware computing, wearable sensor technology, and ubiquitous computing, it is easier for seniors to manage their health problem in smart home environment. For monitoring senior activity in smart home, wearable, and motion sensors-such as respiration rate (RR), electrocardiography (ECG), body temperature, and blood pressure (BP)-were used for monitoring movements of seniors. For context-awareness, environmental sensors-such as gas, fire, smoke, dust, temperature, and light sensors-were used for senior location data collection. Based on senior activity, senior health status can be classified into positive and negative. Based on senior location and time, senior safety is classified into safe and emergency. In this paper, we propose a hybrid inspection service middleware for monitoring elderly health risk based on senior activity and location. This hybrid-aware model for the detection of abnormal status of seniors has four steps as follows: (1) data collection from biosensors and environmental sensors; (2) monitoring senior location and time of stay in each location using environmental sensors; (3) monitoring senior activity using biometric data; finally, (4) expectation-maximization based decision-making step recommending proper treatment based on a senior health risk ratio.

Analysis of the influence location of the fiber optic sensor on the measurement and determination the heart rate of the human body

NASA Astrophysics Data System (ADS)

Nedoma, Jan; Fajkus, Marcel; Martinek, Radek; Cubik, Jakub; Kepak, Stanislav; Vanus, Jan; Zboril, Ondrej; Vasinek, Vladimir

2017-10-01

Authors of this article focused on the analysis of the influence location of the fiber-optic sensor on the measurement and determination the heart rate of the human body. The sensor uses a Fiber Bragg Grating (FBG) and is encapsulated in the polymer polydimethylsiloxane (PDMS). The combination of fiber-optic technology and its encapsulation in a polymer PDMS allows the use of the sensor e.g. in magnetic resonance environments (MRI). Among currently solved doctors requirements belongs field focusing on the study of hyperventilation and panic attacks of patients during MRI examination due to their very frequent occurrence. Proposed FBG sensor can help doctors to predict (based on heart rate) hyperventilation and panic attacks of patients during MRI examinations. For the most accurate determination of the heart rate, it is necessary to know the influence location of the sensor on the human body. The sensor functionality and analysis of the sensor placement on the heart rate has been verified by a series of real experimental measurements of test subjects in laboratory environment.

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.

Acoustic emission monitoring system

DOEpatents

Romrell, Delwin M.

1977-07-05

Methods and apparatus for identifying the source location of acoustic emissions generated within an acoustically conductive medium. A plurality of acoustic receivers are communicably coupled to the surface of the medium at a corresponding number of spaced locations. The differences in the reception time of the respective sensors in response to a given acoustic event are measured among various sensor combinations prescribed by the monitoring mode employed. Acoustic reception response encountered subsequent to the reception by a predetermined number of the prescribed sensor combinations are inhibited from being communicated to the processing circuitry, while the time measurements obtained from the prescribed sensor combinations are translated into a position measurement representative of the location on the surface most proximate the source of the emission. The apparatus is programmable to function in six separate and five distinct operating modes employing either two, three or four sensory locations. In its preferred arrangement the apparatus of this invention will re-initiate a monitoring interval if the predetermined number of sensors do not respond to a particular emission within a given time period.

Modeling, simulation, and control of an extraterrestrial oxygen production plant

NASA Technical Reports Server (NTRS)

Schooley, L.; Cellier, F.; Zeigler, B.; Doser, A.; Farrenkopf, G.

1991-01-01

The immediate objective is the development of a new methodology for simulation of process plants used to produce oxygen and/or other useful materials from local planetary resources. Computer communication, artificial intelligence, smart sensors, and distributed control algorithms are being developed and implemented so that the simulation or an actual plant can be controlled from a remote location. The ultimate result of this research will provide the capability for teleoperation of such process plants which may be located on Mars, Luna, an asteroid, or other objects in space. A very useful near-term result will be the creation of an interactive design tool, which can be used to create and optimize the process/plant design and the control strategy. This will also provide a vivid, graphic demonstration mechanism to convey the results of other researchers to the sponsor.

77 FR 58170 - Proposed Renewal of Existing Information Collection; Fire Protection (Underground Coal Mines)

Federal Register 2010, 2011, 2012, 2013, 2014

2012-09-19

... the locations of automatic fire warning sensors and the intended air flow direction at these locations...) requires that a qualified person examine the automatic fire sensor and warning device systems on a weekly....1103-8(b) requires that a record of the weekly automatic fire sensor functional tests be maintained by...

VLC-based indoor location awareness using LED light and image sensors

NASA Astrophysics Data System (ADS)

Lee, Seok-Ju; Yoo, Jong-Ho; Jung, Sung-Yoon

2012-11-01

Recently, indoor LED lighting can be considered for constructing green infra with energy saving and additionally providing LED-IT convergence services such as visible light communication (VLC) based location awareness and navigation services. For example, in case of large complex shopping mall, location awareness to navigate the destination is very important issue. However, the conventional navigation using GPS is not working indoors. Alternative location service based on WLAN has a problem that the position accuracy is low. For example, it is difficult to estimate the height exactly. If the position error of the height is greater than the height between floors, it may cause big problem. Therefore, conventional navigation is inappropriate for indoor navigation. Alternative possible solution for indoor navigation is VLC based location awareness scheme. Because indoor LED infra will be definitely equipped for providing lighting functionality, indoor LED lighting has a possibility to provide relatively high accuracy of position estimation combined with VLC technology. In this paper, we provide a new VLC based positioning system using visible LED lights and image sensors. Our system uses location of image sensor lens and location of reception plane. By using more than two image sensor, we can determine transmitter position less than 1m position error. Through simulation, we verify the validity of the proposed VLC based new positioning system using visible LED light and image sensors.

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

The Researches on Damage Detection Method for Truss Structures

NASA Astrophysics Data System (ADS)

Wang, Meng Hong; Cao, Xiao Nan

2018-06-01

This paper presents an effective method to detect damage in truss structures. Numerical simulation and experimental analysis were carried out on a damaged truss structure under instantaneous excitation. The ideal excitation point and appropriate hammering method were determined to extract time domain signals under two working conditions. The frequency response function and principal component analysis were used for data processing, and the angle between the frequency response function vectors was selected as a damage index to ascertain the location of a damaged bar in the truss structure. In the numerical simulation, the time domain signal of all nodes was extracted to determine the location of the damaged bar. In the experimental analysis, the time domain signal of a portion of the nodes was extracted on the basis of an optimal sensor placement method based on the node strain energy coefficient. The results of the numerical simulation and experimental analysis showed that the damage detection method based on the frequency response function and principal component analysis could locate the damaged bar accurately.

Optimizing Retransmission Threshold in Wireless Sensor Networks

PubMed Central

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

2016-01-01

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

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

NASA Astrophysics Data System (ADS)

Tran, T.

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

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.

Evaluation of the impact of furniture on communications performance for ubiquitous deployment of Wireless Sensor Networks in smart homes.

PubMed

Bleda, Andrés L; Jara, Antonio J; Maestre, Rafael; Santa, Guadalupe; Gómez Skarmeta, Antonio F

2012-01-01

The extensions of the environment with the integration of sensing systems in any space, in conjunction with ubiquitous computing are enabling the so-called Smart Space Sensor Networks. This new generation of networks are offering full connectivity with any object, through the Internet of Things (IoT) and/or the Web, i.e., the Web of Things. These connectivity capabilities are making it feasible to sense the behaviours of people at home and act accordingly. These sensing systems must be integrated within typical elements found at home such as furniture. For that reason, this work considers furniture as an interesting element for the transparent location of sensors. Furniture is a ubiquitous object, i.e., it can be found everywhere at home or the office, and it can integrate and hide the sensors of a network. This work addresses the lack of an exhaustive study of the effect of furniture on signal losses. In addition an easy-to-use tool for estimating the robustness of the communication channel among the sensor nodes and gateways is proposed. Specifically, the losses in a sensor network signal due to the materials found within the communication link are evaluated. Then, this work proposes a software tool that gathers the obtained results and is capable of evaluating the impact of a given set of materials on the communications. This tool also provides a mechanism to optimize the sensor network deployments during the definition of smart spaces. Specifically, it provides information such as: maximum distances between sensor nodes, most suitable type of furniture to integrate sensors, or battery life of sensor nodes. This tool has been validated empirically in the lab, and it is currently being used by several enterprise partners of the Technological Centre of Furniture and Wood in the southeast of Spain.

Evaluation of the Impact of Furniture on Communications Performance for Ubiquitous Deployment of Wireless Sensor Networks in Smart Homes

PubMed Central

Bleda, Andrés L.; Jara, Antonio J.; Maestre, Rafael; Santa, Guadalupe; Gómez Skarmeta, Antonio F.

2012-01-01

The extensions of the environment with the integration of sensing systems in any space, in conjunction with ubiquitous computing are enabling the so-called Smart Space Sensor Networks. This new generation of networks are offering full connectivity with any object, through the Internet of Things (IoT) and/or the Web, i.e., the Web of Things. These connectivity capabilities are making it feasible to sense the behaviours of people at home and act accordingly. These sensing systems must be integrated within typical elements found at home such as furniture. For that reason, this work considers furniture as an interesting element for the transparent location of sensors. Furniture is a ubiquitous object, i.e., it can be found everywhere at home or the office, and it can integrate and hide the sensors of a network. This work addresses the lack of an exhaustive study of the effect of furniture on signal losses. In addition an easy-to-use tool for estimating the robustness of the communication channel among the sensor nodes and gateways is proposed. Specifically, the losses in a sensor network signal due to the materials found within the communication link are evaluated. Then, this work proposes a software tool that gathers the obtained results and is capable of evaluating the impact of a given set of materials on the communications. This tool also provides a mechanism to optimize the sensor network deployments during the definition of smart spaces. Specifically, it provides information such as: maximum distances between sensor nodes, most suitable type of furniture to integrate sensors, or battery life of sensor nodes. This tool has been validated empirically in the lab, and it is currently being used by several enterprise partners of the Technological Centre of Furniture and Wood in the southeast of Spain. PMID:22778653

Radiometric Normalization of Large Airborne Image Data Sets Acquired by Different Sensor Types

NASA Astrophysics Data System (ADS)

Gehrke, S.; Beshah, B. T.

2016-06-01

Generating seamless mosaics of aerial images is a particularly challenging task when the mosaic comprises a large number of im-ages, collected over longer periods of time and with different sensors under varying imaging conditions. Such large mosaics typically consist of very heterogeneous image data, both spatially (different terrain types and atmosphere) and temporally (unstable atmo-spheric properties and even changes in land coverage). We present a new radiometric normalization or, respectively, radiometric aerial triangulation approach that takes advantage of our knowledge about each sensor's properties. The current implementation supports medium and large format airborne imaging sensors of the Leica Geosystems family, namely the ADS line-scanner as well as DMC and RCD frame sensors. A hierarchical modelling - with parameters for the overall mosaic, the sensor type, different flight sessions, strips and individual images - allows for adaptation to each sensor's geometric and radiometric properties. Additional parameters at different hierarchy levels can compensate radiome-tric differences of various origins to compensate for shortcomings of the preceding radiometric sensor calibration as well as BRDF and atmospheric corrections. The final, relative normalization is based on radiometric tie points in overlapping images, absolute radiometric control points and image statistics. It is computed in a global least squares adjustment for the entire mosaic by altering each image's histogram using a location-dependent mathematical model. This model involves contrast and brightness corrections at radiometric fix points with bilinear interpolation for corrections in-between. The distribution of the radiometry fixes is adaptive to each image and generally increases with image size, hence enabling optimal local adaptation even for very long image strips as typi-cally captured by a line-scanner sensor. The normalization approach is implemented in HxMap software. It has been successfully applied to large sets of heterogeneous imagery, including the adjustment of original sensor images prior to quality control and further processing as well as radiometric adjustment for ortho-image mosaic generation.

Using machine learning to produce near surface soil moisture estimates from deeper in situ records at U.S. Climate Reference Network (USCRN) locations: Analysis and applications to AMSR-E satellite validation

NASA Astrophysics Data System (ADS)

Coopersmith, Evan J.; Cosh, Michael H.; Bell, Jesse E.; Boyles, Ryan

2016-12-01

Surface soil moisture is a critical parameter for understanding the energy flux at the land atmosphere boundary. Weather modeling, climate prediction, and remote sensing validation are some of the applications for surface soil moisture information. The most common in situ measurement for these purposes are sensors that are installed at depths of approximately 5 cm. There are however, sensor technologies and network designs that do not provide an estimate at this depth. If soil moisture estimates at deeper depths could be extrapolated to the near surface, in situ networks providing estimates at other depths would see their values enhanced. Soil moisture sensors from the U.S. Climate Reference Network (USCRN) were used to generate models of 5 cm soil moisture, with 10 cm soil moisture measurements and antecedent precipitation as inputs, via machine learning techniques. Validation was conducted with the available, in situ, 5 cm resources. It was shown that a 5 cm estimate, which was extrapolated from a 10 cm sensor and antecedent local precipitation, produced a root-mean-squared-error (RMSE) of 0.0215 m3/m3. Next, these machine-learning-generated 5 cm estimates were also compared to AMSR-E estimates at these locations. These results were then compared with the performance of the actual in situ readings against the AMSR-E data. The machine learning estimates at 5 cm produced an RMSE of approximately 0.03 m3/m3 when an optimized gain and offset were applied. This is necessary considering the performance of AMSR-E in locations characterized by high vegetation water contents, which are present across North Carolina. Lastly, the application of this extrapolation technique is applied to the ECONet in North Carolina, which provides a 10 cm depth measurement as its shallowest soil moisture estimate. A raw RMSE of 0.028 m3/m3 was achieved, and with a linear gain and offset applied at each ECONet site, an RMSE of 0.013 m3/m3 was possible.

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

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

An impact source localization technique for a nuclear power plant by using sensors of different types.

PubMed

Choi, Young-Chul; Park, Jin-Ho; Choi, Kyoung-Sik

2011-01-01

In a nuclear power plant, a loose part monitoring system (LPMS) provides information on the location and the mass of a loosened or detached metal impacted onto the inner surface of the primary pressure boundary. Typically, accelerometers are mounted on the surface of a reactor vessel to localize the impact location caused by the impact of metallic substances on the reactor system. However, in some cases, the number of accelerometers is not sufficient to estimate the impact location precisely. In such a case, one of useful methods is to utilize other types of sensor that can measure the vibration of the reactor structure. For example, acoustic emission (AE) sensors are installed on the reactor structure to detect leakage or cracks on the primary pressure boundary. However, accelerometers and AE sensors have a different frequency range. The frequency of interest of AE sensors is higher than that of accelerometers. In this paper, we propose a method of impact source localization by using both accelerometer signals and AE signals, simultaneously. The main concept of impact location estimation is based on the arrival time difference of the impact stress wave between different sensor locations. However, it is difficult to find the arrival time difference between sensors, because the primary frequency ranges of accelerometers and AE sensors are different. To overcome the problem, we used phase delays of an envelope of impact signals. This is because the impact signals from the accelerometer and the AE sensor are similar in the whole shape (envelope). To verify the proposed method, we have performed experiments for a reactor mock-up model and a real nuclear power plant. The experimental results demonstrate that we can enhance the reliability and precision of the impact source localization. Therefore, if the proposed method is applied to a nuclear power plant, we can obtain the effect of additional installed sensors. Crown Copyright © 2010. Published by Elsevier Ltd. All rights reserved.

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

PubMed

Halim, Dunant; Cheng, Li; Su, Zhongqing

2011-03-01

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

Geometry optimization for micro-pressure sensor considering dynamic interference

NASA Astrophysics Data System (ADS)

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

2014-09-01

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

Optimized autonomous space in-situ sensor web for volcano monitoring

USGS Publications Warehouse

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

2010-01-01

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

An internal thermal sensor controlling temperature preference in Drosophila.

PubMed

Hamada, Fumika N; Rosenzweig, Mark; Kang, Kyeongjin; Pulver, Stefan R; Ghezzi, Alfredo; Jegla, Timothy J; Garrity, Paul A

2008-07-10

Animals from flies to humans are able to distinguish subtle gradations in temperature and show strong temperature preferences. Animals move to environments of optimal temperature and some manipulate the temperature of their surroundings, as humans do using clothing and shelter. Despite the ubiquitous influence of environmental temperature on animal behaviour, the neural circuits and strategies through which animals select a preferred temperature remain largely unknown. Here we identify a small set of warmth-activated anterior cell (AC) neurons located in the Drosophila brain, the function of which is critical for preferred temperature selection. AC neuron activation occurs just above the fly's preferred temperature and depends on dTrpA1, an ion channel that functions as a molecular sensor of warmth. Flies that selectively express dTrpA1 in the AC neurons select normal temperatures, whereas flies in which dTrpA1 function is reduced or eliminated choose warmer temperatures. This internal warmth-sensing pathway promotes avoidance of slightly elevated temperatures and acts together with a distinct pathway for cold avoidance to set the fly's preferred temperature. Thus, flies select a preferred temperature by using a thermal sensing pathway tuned to trigger avoidance of temperatures that deviate even slightly from the preferred temperature. This provides a potentially general strategy for robustly selecting a narrow temperature range optimal for survival.

Enhancing source location protection in wireless sensor networks

NASA Astrophysics Data System (ADS)

Chen, Juan; Lin, Zhengkui; Wu, Di; Wang, Bailing

2015-12-01

Wireless sensor networks are widely deployed in the internet of things to monitor valuable objects. Once the object is monitored, the sensor nearest to the object which is known as the source informs the base station about the object's information periodically. It is obvious that attackers can capture the object successfully by localizing the source. Thus, many protocols have been proposed to secure the source location. However, in this paper, we examine that typical source location protection protocols generate not only near but also highly localized phantom locations. As a result, attackers can trace the source easily from these phantom locations. To address these limitations, we propose a protocol to enhance the source location protection (SLE). With phantom locations far away from the source and widely distributed, SLE improves source location anonymity significantly. Theory analysis and simulation results show that our SLE provides strong source location privacy preservation and the average safety period increases by nearly one order of magnitude compared with existing work with low communication cost.