Multi-Sensor Integration to Map Odor Distribution for the Detection of Chemical Sources.

PubMed

Gao, Xiang; Acar, Levent

2016-07-04

This paper addresses the problem of mapping odor distribution derived from a chemical source using multi-sensor integration and reasoning system design. Odor localization is the problem of finding the source of an odor or other volatile chemical. Most localization methods require a mobile vehicle to follow an odor plume along its entire path, which is time consuming and may be especially difficult in a cluttered environment. To solve both of the above challenges, this paper proposes a novel algorithm that combines data from odor and anemometer sensors, and combine sensors' data at different positions. Initially, a multi-sensor integration method, together with the path of airflow was used to map the pattern of odor particle movement. Then, more sensors are introduced at specific regions to determine the probable location of the odor source. Finally, the results of odor source location simulation and a real experiment are presented.

Distributed Transforms for Efficient Data Gathering in Sensor Networks

NASA Technical Reports Server (NTRS)

Ortega, Antonio (Inventor); Shen, Godwin (Inventor); Narang, Sunil K. (Inventor); Perez-Trufero, Javier (Inventor)

2014-01-01

Devices, systems, and techniques for data collecting network such as wireless sensors are disclosed. A described technique includes detecting one or more remote nodes included in the wireless sensor network using a local power level that controls a radio range of the local node. The technique includes transmitting a local outdegree. The local outdegree can be based on a quantity of the one or more remote nodes. The technique includes receiving one or more remote outdegrees from the one or more remote nodes. The technique includes determining a local node type of the local node based on detecting a node type of the one or more remote nodes, using the one or more remote outdegrees, and using the local outdegree. The technique includes adjusting characteristics, including an energy usage characteristic and a data compression characteristic, of the wireless sensor network by selectively modifying the local power level and selectively changing the local node type.

Distributed Peer-to-Peer Target Tracking in Wireless Sensor Networks

PubMed Central

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

2007-01-01

Target tracking is usually a challenging application for wireless sensor networks (WSNs) because it is always computation-intensive and requires real-time processing. This paper proposes a practical target tracking system based on the auto regressive moving average (ARMA) model in a distributed peer-to-peer (P2P) signal processing framework. In the proposed framework, wireless sensor nodes act as peers that perform target detection, feature extraction, classification and tracking, whereas target localization requires the collaboration between wireless sensor nodes for improving the accuracy and robustness. For carrying out target tracking under the constraints imposed by the limited capabilities of the wireless sensor nodes, some practically feasible algorithms, such as the ARMA model and the 2-D integer lifting wavelet transform, are adopted in single wireless sensor nodes due to their outstanding performance and light computational burden. Furthermore, a progressive multi-view localization algorithm is proposed in distributed P2P signal processing framework considering the tradeoff between the accuracy and energy consumption. Finally, a real world target tracking experiment is illustrated. Results from experimental implementations have demonstrated that the proposed target tracking system based on a distributed P2P signal processing framework can make efficient use of scarce energy and communication resources and achieve target tracking successfully.

Extensibility in local sensor based planning for hyper-redundant manipulators (robot snakes)

NASA Technical Reports Server (NTRS)

Choset, Howie; Burdick, Joel

1994-01-01

Partial Shape Modification (PSM) is a local sensor feedback method used for hyper-redundant robot manipulators, in which the redundancy is very large or infinite such as that of a robot snake. This aspect of redundancy enables local obstacle avoidance and end-effector placement in real time. Due to the large number of joints or actuators in a hyper-redundant manipulator, small displacement errors of such easily accumulate to large errors in the position of the tip relative to the base. The accuracy could be improved by a local sensor based planning method in which sensors are distributed along the length of the hyper-redundant robot. This paper extends the local sensor based planning strategy beyond the limitations of the fixed length of such a manipulator when its joint limits are met. This is achieved with an algorithm where the length of the deforming part of the robot is variable. Thus , the robot's local avoidance of obstacles is improved through the enhancement of its extensibility.

Secure Distributed Detection under Energy Constraint in IoT-Oriented Sensor Networks

PubMed Central

Zhang, Guomei; Sun, Hao

2016-01-01

We study the secure distributed detection problems under energy constraint for IoT-oriented sensor networks. The conventional channel-aware encryption (CAE) is an efficient physical-layer secure distributed detection scheme in light of its energy efficiency, good scalability and robustness over diverse eavesdropping scenarios. However, in the CAE scheme, it remains an open problem of how to optimize the key thresholds for the estimated channel gain, which are used to determine the sensor’s reporting action. Moreover, the CAE scheme does not jointly consider the accuracy of local detection results in determining whether to stay dormant for a sensor. To solve these problems, we first analyze the error probability and derive the optimal thresholds in the CAE scheme under a specified energy constraint. These results build a convenient mathematic framework for our further innovative design. Under this framework, we propose a hybrid secure distributed detection scheme. Our proposal can satisfy the energy constraint by keeping some sensors inactive according to the local detection confidence level, which is characterized by likelihood ratio. In the meanwhile, the security is guaranteed through randomly flipping the local decisions forwarded to the fusion center based on the channel amplitude. We further optimize the key parameters of our hybrid scheme, including two local decision thresholds and one channel comparison threshold. Performance evaluation results demonstrate that our hybrid scheme outperforms the CAE under stringent energy constraints, especially in the high signal-to-noise ratio scenario, while the security is still assured. PMID:27999282

Temperature measurement and damage detection in concrete beams exposed to fire using PPP-BOTDA based fiber optic sensors

NASA Astrophysics Data System (ADS)

Bao, Yi; Hoehler, Matthew S.; Smith, Christopher M.; Bundy, Matthew; Chen, Genda

2017-10-01

In this study, Brillouin scattering-based distributed fiber optic sensor is implemented to measure temperature distributions and detect cracks in concrete structures subjected to fire for the first time. A telecommunication-grade optical fiber is characterized as a high temperature sensor with pulse pre-pump Brillouin optical time domain analysis (PPP-BODTA), and implemented to measure spatially-distributed temperatures in reinforced concrete beams in fire. Four beams were tested to failure in a natural gas fueled compartment fire, each instrumented with one fused silica, single-mode optical fiber as a distributed sensor and four thermocouples. Prior to concrete cracking, the distributed temperature was validated at locations of the thermocouples by a relative difference of less than 9%. The cracks in concrete can be identified as sharp peaks in the temperature distribution since the cracks are locally filled with hot air. Concrete cracking did not affect the sensitivity of the distributed sensor but concrete spalling broke the optical fiber loop required for PPP-BOTDA measurements.

Recent progress in distributed fiber optic sensors.

PubMed

Bao, Xiaoyi; Chen, Liang

2012-01-01

Rayleigh, Brillouin and Raman scatterings in fibers result from the interaction of photons with local material characteristic features like density, temperature and strain. For example an acoustic/mechanical wave generates a dynamic density variation; such a variation may be affected by local temperature, strain, vibration and birefringence. By detecting changes in the amplitude, frequency and phase of light scattered along a fiber, one can realize a distributed fiber sensor for measuring localized temperature, strain, vibration and birefringence over lengths ranging from meters to one hundred kilometers. Such a measurement can be made in the time domain or frequency domain to resolve location information. With coherent detection of the scattered light one can observe changes in birefringence and beat length for fibers and devices. The progress on state of the art technology for sensing performance, in terms of spatial resolution and limitations on sensing length is reviewed. These distributed sensors can be used for disaster prevention in the civil structural monitoring of pipelines, bridges, dams and railroads. A sensor with centimeter spatial resolution and high precision measurement of temperature, strain, vibration and birefringence can find applications in aerospace smart structures, material processing, and the characterization of optical materials and devices.

Recent Progress in Distributed Fiber Optic Sensors

PubMed Central

Bao, Xiaoyi; Chen, Liang

2012-01-01

Rayleigh, Brillouin and Raman scatterings in fibers result from the interaction of photons with local material characteristic features like density, temperature and strain. For example an acoustic/mechanical wave generates a dynamic density variation; such a variation may be affected by local temperature, strain, vibration and birefringence. By detecting changes in the amplitude, frequency and phase of light scattered along a fiber, one can realize a distributed fiber sensor for measuring localized temperature, strain, vibration and birefringence over lengths ranging from meters to one hundred kilometers. Such a measurement can be made in the time domain or frequency domain to resolve location information. With coherent detection of the scattered light one can observe changes in birefringence and beat length for fibers and devices. The progress on state of the art technology for sensing performance, in terms of spatial resolution and limitations on sensing length is reviewed. These distributed sensors can be used for disaster prevention in the civil structural monitoring of pipelines, bridges, dams and railroads. A sensor with centimeter spatial resolution and high precision measurement of temperature, strain, vibration and birefringence can find applications in aerospace smart structures, material processing, and the characterization of optical materials and devices. PMID:23012508

Distributed Transmitter Localization by Power Difference of Arrival (PDOA) on a Network of GNU Radio Sensors

DTIC Science & Technology

2015-02-03

requiring the least hardware investment is to localize by received signal strength [1, 4, 5]. Because our intended scenario of low-complexity...MHz were taken with a spectrum analyzer program on the USRP and a range finder was used to measure the distance between the emitter and sensor

Distributed Water Pollution Source Localization with Mobile UV-Visible Spectrometer Probes in Wireless Sensor Networks.

PubMed

Ma, Junjie; Meng, Fansheng; Zhou, Yuexi; Wang, Yeyao; Shi, Ping

2018-02-16

Pollution accidents that occur in surface waters, especially in drinking water source areas, greatly threaten the urban water supply system. During water pollution source localization, there are complicated pollutant spreading conditions and pollutant concentrations vary in a wide range. This paper provides a scalable total solution, investigating a distributed localization method in wireless sensor networks equipped with mobile ultraviolet-visible (UV-visible) spectrometer probes. A wireless sensor network is defined for water quality monitoring, where unmanned surface vehicles and buoys serve as mobile and stationary nodes, respectively. Both types of nodes carry UV-visible spectrometer probes to acquire in-situ multiple water quality parameter measurements, in which a self-adaptive optical path mechanism is designed to flexibly adjust the measurement range. A novel distributed algorithm, called Dual-PSO, is proposed to search for the water pollution source, where one particle swarm optimization (PSO) procedure computes the water quality multi-parameter measurements on each node, utilizing UV-visible absorption spectra, and another one finds the global solution of the pollution source position, regarding mobile nodes as particles. Besides, this algorithm uses entropy to dynamically recognize the most sensitive parameter during searching. Experimental results demonstrate that online multi-parameter monitoring of a drinking water source area with a wide dynamic range is achieved by this wireless sensor network and water pollution sources are localized efficiently with low-cost mobile node paths.

Distributed Water Pollution Source Localization with Mobile UV-Visible Spectrometer Probes in Wireless Sensor Networks

PubMed Central

Zhou, Yuexi; Wang, Yeyao; Shi, Ping

2018-01-01

Pollution accidents that occur in surface waters, especially in drinking water source areas, greatly threaten the urban water supply system. During water pollution source localization, there are complicated pollutant spreading conditions and pollutant concentrations vary in a wide range. This paper provides a scalable total solution, investigating a distributed localization method in wireless sensor networks equipped with mobile ultraviolet-visible (UV-visible) spectrometer probes. A wireless sensor network is defined for water quality monitoring, where unmanned surface vehicles and buoys serve as mobile and stationary nodes, respectively. Both types of nodes carry UV-visible spectrometer probes to acquire in-situ multiple water quality parameter measurements, in which a self-adaptive optical path mechanism is designed to flexibly adjust the measurement range. A novel distributed algorithm, called Dual-PSO, is proposed to search for the water pollution source, where one particle swarm optimization (PSO) procedure computes the water quality multi-parameter measurements on each node, utilizing UV-visible absorption spectra, and another one finds the global solution of the pollution source position, regarding mobile nodes as particles. Besides, this algorithm uses entropy to dynamically recognize the most sensitive parameter during searching. Experimental results demonstrate that online multi-parameter monitoring of a drinking water source area with a wide dynamic range is achieved by this wireless sensor network and water pollution sources are localized efficiently with low-cost mobile node paths. PMID:29462929

Temperature Measurement and Damage Detection in Concrete Beams Exposed to Fire Using PPP-BOTDA Based Fiber Optic Sensors.

PubMed

Bao, Yi; Hoehler, Matthew S; Smith, Christopher M; Bundy, Matthew; Chen, Genda

2017-10-01

In this study, distributed fiber optic sensors based on pulse pre-pump Brillouin optical time domain analysis (PPP-BODTA) are characterized and deployed to measure spatially-distributed temperatures in reinforced concrete specimens exposed to fire. Four beams were tested to failure in a natural gas fueled compartment fire, each instrumented with one fused silica, single-mode optical fiber as a distributed sensor and four thermocouples. Prior to concrete cracking, the distributed temperature was validated at locations of the thermocouples by a relative difference of less than 9 %. The cracks in concrete can be identified as sharp peaks in the temperature distribution since the cracks are locally filled with hot air. Concrete cracking did not affect the sensitivity of the distributed sensor but concrete spalling broke the optical fiber loop required for PPP-BOTDA measurements.

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.

Distributed processing method for arbitrary view generation in camera sensor network

NASA Astrophysics Data System (ADS)

Tehrani, Mehrdad P.; Fujii, Toshiaki; Tanimoto, Masayuki

2003-05-01

Camera sensor network as a new advent of technology is a network that each sensor node can capture video signals, process and communicate them with other nodes. The processing task in this network is to generate arbitrary view, which can be requested from central node or user. To avoid unnecessary communication between nodes in camera sensor network and speed up the processing time, we have distributed the processing tasks between nodes. In this method, each sensor node processes part of interpolation algorithm to generate the interpolated image with local communication between nodes. The processing task in camera sensor network is ray-space interpolation, which is an object independent method and based on MSE minimization by using adaptive filtering. Two methods were proposed for distributing processing tasks, which are Fully Image Shared Decentralized Processing (FIS-DP), and Partially Image Shared Decentralized Processing (PIS-DP), to share image data locally. Comparison of the proposed methods with Centralized Processing (CP) method shows that PIS-DP has the highest processing speed after FIS-DP, and CP has the lowest processing speed. Communication rate of CP and PIS-DP is almost same and better than FIS-DP. So, PIS-DP is recommended because of its better performance than CP and FIS-DP.

A novel method for in-situ monitoring of local voltage, temperature and humidity distributions in fuel cells using flexible multi-functional micro sensors.

PubMed

Lee, Chi-Yuan; Fan, Wei-Yuan; Chang, Chih-Ping

2011-01-01

In this investigation, micro voltage, temperature and humidity sensors were fabricated and integrated for the first time on a stainless steel foil using micro-electro-mechanical systems (MEMS). These flexible multi-functional micro sensors have the advantages of high temperature resistance, flexibility, smallness, high sensitivity and precision of location. They were embedded in a proton exchange membrane fuel cell (PEMFC) and used to simultaneously measure variations in the inner voltage, temperature and humidity. The accuracy and reproducibility of the calibrated results obtained using the proposed micro sensors is excellent. The experimental results indicate that, at high current density and 100%RH or 75%RH, the relative humidity midstream and downstream saturates due to severe flooding. The performance of the PEM fuel cell can be stabilized using home-made flexible multi-functional micro sensors by the in-situ monitoring of local voltage, temperature and humidity distributions within it.

A Novel Method for In-Situ Monitoring of Local Voltage, Temperature and Humidity Distributions in Fuel Cells Using Flexible Multi-Functional Micro Sensors

PubMed Central

Lee, Chi-Yuan; Fan, Wei-Yuan; Chang, Chih-Ping

2011-01-01

In this investigation, micro voltage, temperature and humidity sensors were fabricated and integrated for the first time on a stainless steel foil using micro-electro-mechanical systems (MEMS). These flexible multi-functional micro sensors have the advantages of high temperature resistance, flexibility, smallness, high sensitivity and precision of location. They were embedded in a proton exchange membrane fuel cell (PEMFC) and used to simultaneously measure variations in the inner voltage, temperature and humidity. The accuracy and reproducibility of the calibrated results obtained using the proposed micro sensors is excellent. The experimental results indicate that, at high current density and 100%RH or 75%RH, the relative humidity midstream and downstream saturates due to severe flooding. The performance of the PEM fuel cell can be stabilized using home-made flexible multi-functional micro sensors by the in-situ monitoring of local voltage, temperature and humidity distributions within it. PMID:22319361

Collaborative Localization Algorithms for Wireless Sensor Networks with Reduced Localization Error

PubMed Central

Sahoo, Prasan Kumar; Hwang, I-Shyan

2011-01-01

Localization is an important research issue in Wireless Sensor Networks (WSNs). Though Global Positioning System (GPS) can be used to locate the position of the sensors, unfortunately it is limited to outdoor applications and is costly and power consuming. In order to find location of sensor nodes without help of GPS, collaboration among nodes is highly essential so that localization can be accomplished efficiently. In this paper, novel localization algorithms are proposed to find out possible location information of the normal nodes in a collaborative manner for an outdoor environment with help of few beacons and anchor nodes. In our localization scheme, at most three beacon nodes should be collaborated to find out the accurate location information of any normal node. Besides, analytical methods are designed to calculate and reduce the localization error using probability distribution function. Performance evaluation of our algorithm shows that there is a tradeoff between deployed number of beacon nodes and localization error, and average localization time of the network can be increased with increase in the number of normal nodes deployed over a region. PMID:22163738

A Theoretical Study and Numerical Simulation of a Quasi-Distributed Sensor Based on the Low-Finesse Fabry-Perot Interferometer: Frequency-Division Multiplexing.

PubMed

Guillen Bonilla, José Trinidad; Guillen Bonilla, Alex; Rodríguez Betancourtt, Verónica M; Guillen Bonilla, Héctor; Casillas Zamora, Antonio

2017-04-14

The application of the sensor optical fibers in the areas of scientific instrumentation and industrial instrumentation is very attractive due to its numerous advantages. In the industry of civil engineering for example, quasi-distributed sensors made with optical fiber are used for reliable strain and temperature measurements. Here, a quasi-distributed sensor in the frequency domain is discussed. The sensor consists of a series of low-finesse Fabry-Perot interferometers where each Fabry-Perot interferometer acts as a local sensor. Fabry-Perot interferometers are formed by pairs of identical low reflective Bragg gratings imprinted in a single mode fiber. All interferometer sensors have different cavity length, provoking frequency-domain multiplexing. The optical signal represents the superposition of all interference patterns which can be decomposed using the Fourier transform. The frequency spectrum was analyzed and sensor's properties were defined. Following that, a quasi-distributed sensor was numerically simulated. Our sensor simulation considers sensor properties, signal processing, noise system, and instrumentation. The numerical results show the behavior of resolution vs. signal-to-noise ratio. From our results, the Fabry-Perot sensor has high resolution and low resolution. Both resolutions are conceivable because the Fourier Domain Phase Analysis (FDPA) algorithm elaborates two evaluations of Bragg wavelength shift.

New estimation architecture for multisensor data fusion

NASA Astrophysics Data System (ADS)

Covino, Joseph M.; Griffiths, Barry E.

1991-07-01

This paper describes a novel method of hierarchical asynchronous distributed filtering called the Net Information Approach (NIA). The NIA is a Kalman-filter-based estimation scheme for spatially distributed sensors which must retain their local optimality yet require a nearly optimal global estimate. The key idea of the NIA is that each local sensor-dedicated filter tells the global filter 'what I've learned since the last local-to-global transmission,' whereas in other estimation architectures the local-to-global transmission consists of 'what I think now.' An algorithm based on this idea has been demonstrated on a small-scale target-tracking problem with many encouraging results. Feasibility of this approach was demonstrated by comparing NIA performance to an optimal centralized Kalman filter (lower bound) via Monte Carlo simulations.

Distributed Power Allocation for Wireless Sensor Network Localization: A Potential Game Approach.

PubMed

Ke, Mingxing; Li, Ding; Tian, Shiwei; Zhang, Yuli; Tong, Kaixiang; Xu, Yuhua

2018-05-08

The problem of distributed power allocation in wireless sensor network (WSN) localization systems is investigated in this paper, using the game theoretic approach. Existing research focuses on the minimization of the localization errors of individual agent nodes over all anchor nodes subject to power budgets. When the service area and the distribution of target nodes are considered, finding the optimal trade-off between localization accuracy and power consumption is a new critical task. To cope with this issue, we propose a power allocation game where each anchor node minimizes the square position error bound (SPEB) of the service area penalized by its individual power. Meanwhile, it is proven that the power allocation game is an exact potential game which has one pure Nash equilibrium (NE) at least. In addition, we also prove the existence of an ϵ -equilibrium point, which is a refinement of NE and the better response dynamic approach can reach the end solution. Analytical and simulation results demonstrate that: (i) when prior distribution information is available, the proposed strategies have better localization accuracy than the uniform strategies; (ii) when prior distribution information is unknown, the performance of the proposed strategies outperforms power management strategies based on the second-order cone program (SOCP) for particular agent nodes after obtaining the estimated distribution of agent nodes. In addition, proposed strategies also provide an instructional trade-off between power consumption and localization accuracy.

Agent Collaborative Target Localization and Classification in Wireless Sensor Networks

PubMed Central

Wang, Xue; Bi, Dao-wei; Ding, Liang; Wang, Sheng

2007-01-01

Wireless sensor networks (WSNs) are autonomous networks that have been frequently deployed to collaboratively perform target localization and classification tasks. Their autonomous and collaborative features resemble the characteristics of agents. Such similarities inspire the development of heterogeneous agent architecture for WSN in this paper. The proposed agent architecture views WSN as multi-agent systems and mobile agents are employed to reduce in-network communication. According to the architecture, an energy based acoustic localization algorithm is proposed. In localization, estimate of target location is obtained by steepest descent search. The search algorithm adapts to measurement environments by dynamically adjusting its termination condition. With the agent architecture, target classification is accomplished by distributed support vector machine (SVM). Mobile agents are employed for feature extraction and distributed SVM learning to reduce communication load. Desirable learning performance is guaranteed by combining support vectors and convex hull vectors. Fusion algorithms are designed to merge SVM classification decisions made from various modalities. Real world experiments with MICAz sensor nodes are conducted for vehicle localization and classification. Experimental results show the proposed agent architecture remarkably facilitates WSN designs and algorithm implementation. The localization and classification algorithms also prove to be accurate and energy efficient.

A Theoretical Study and Numerical Simulation of a Quasi-Distributed Sensor Based on the Low-Finesse Fabry-Perot Interferometer: Frequency-Division Multiplexing

PubMed Central

Guillen Bonilla, José Trinidad; Guillen Bonilla, Alex; Rodríguez Betancourtt, Verónica M.; Guillen Bonilla, Héctor; Casillas Zamora, Antonio

2017-01-01

The application of the sensor optical fibers in the areas of scientific instrumentation and industrial instrumentation is very attractive due to its numerous advantages. In the industry of civil engineering for example, quasi-distributed sensors made with optical fiber are used for reliable strain and temperature measurements. Here, a quasi-distributed sensor in the frequency domain is discussed. The sensor consists of a series of low-finesse Fabry-Perot interferometers where each Fabry-Perot interferometer acts as a local sensor. Fabry-Perot interferometers are formed by pairs of identical low reflective Bragg gratings imprinted in a single mode fiber. All interferometer sensors have different cavity length, provoking frequency-domain multiplexing. The optical signal represents the superposition of all interference patterns which can be decomposed using the Fourier transform. The frequency spectrum was analyzed and sensor’s properties were defined. Following that, a quasi-distributed sensor was numerically simulated. Our sensor simulation considers sensor properties, signal processing, noise system, and instrumentation. The numerical results show the behavior of resolution vs. signal-to-noise ratio. From our results, the Fabry-Perot sensor has high resolution and low resolution. Both resolutions are conceivable because the Fourier Domain Phase Analysis (FDPA) algorithm elaborates two evaluations of Bragg wavelength shift. PMID:28420083

Localization in Self-Healing Autonomous Sensor Networks (SASNet): Studies on Cooperative Localization of Sensor Nodes using Distributed Maps

DTIC Science & Technology

2008-01-01

CCA-MAP algorithm are analyzed. Further, we discuss the design considerations of the discussed cooperative localization algorithms to compare and...MAP and CCA-MAP to compare and evaluate their performance. Then a preliminary design analysis is given to address the implementation requirements and...plus précis, avec un nombre inférieur de nœuds ancres, comparativement aux autres types de schémas de localisation. En réalité, les algorithmes de

A Brief Overview of NASA Glenn Research Center Sensor and Electronics Activities

NASA Technical Reports Server (NTRS)

Hunter, Gary W.

2012-01-01

Aerospace applications require a range of sensing technologies. There is a range of sensor and sensor system technologies being developed using microfabrication and micromachining technology to form smart sensor systems and intelligent microsystems. Drive system intelligence to the local (sensor) level -- distributed smart sensor systems. Sensor and sensor system development examples: (1) Thin-film physical sensors (2) High temperature electronics and wireless (3) "lick and stick" technology. NASA GRC is a world leader in aerospace sensor technology with a broad range of development and application experience. Core microsystems technology applicable to a range of application environmentS.

Experimental study of low-cost fiber optic distributed temperature sensor system performance

NASA Astrophysics Data System (ADS)

Dashkov, Michael V.; Zharkov, Alexander D.

2016-03-01

The distributed control of temperature is an actual task for various application such as oil & gas fields, high-voltage power lines, fire alarm systems etc. The most perspective are optical fiber distributed temperature sensors (DTS). They have advantages on accuracy, resolution and range, but have a high cost. Nevertheless, for some application the accuracy of measurement and localization aren't so important as cost. The results of an experimental study of low-cost Raman based DTS based on standard OTDR are represented.

Detection, Localization and Quantification of Impact Events on a Stiffened Composite Panel with Embedded Fiber Bragg Grating Sensor Networks

PubMed Central

Lamberti, Alfredo; Luyckx, Geert; Van Paepegem, Wim; Rezayat, Ali; Vanlanduit, Steve

2017-01-01

Nowadays, it is possible to manufacture smart composite materials with embedded fiber optic sensors. These sensors can be exploited during the composites’ operating life to identify occurring damages such as delaminations. For composite materials adopted in the aviation and wind energy sector, delaminations are most often caused by impacts with external objects. The detection, localization and quantification of such impacts are therefore crucial for the prevention of catastrophic events. In this paper, we demonstrate the feasibility to perform impact identification in smart composite structures with embedded fiber optic sensors. For our analyses, we manufactured a carbon fiber reinforced plate in which we embedded a distributed network of fiber Bragg grating (FBG) sensors. We impacted the plate with a modal hammer and we identified the impacts by processing the FBG data with an improved fast phase correlation (FPC) algorithm in combination with a variable selective least squares (VS-LS) inverse solver approach. A total of 164 impacts distributed on 41 possible impact locations were analyzed. We compared our methodology with the traditional P-Inv based approach. In terms of impact localization, our methodology performed better in 70.7% of the cases. An improvement on the impact time domain reconstruction was achieved in 95.1% of the cases. PMID:28368319

Detection, Localization and Quantification of Impact Events on a Stiffened Composite Panel with Embedded Fiber Bragg Grating Sensor Networks.

PubMed

Lamberti, Alfredo; Luyckx, Geert; Van Paepegem, Wim; Rezayat, Ali; Vanlanduit, Steve

2017-04-01

Nowadays, it is possible to manufacture smart composite materials with embedded fiber optic sensors. These sensors can be exploited during the composites' operating life to identify occurring damages such as delaminations. For composite materials adopted in the aviation and wind energy sector, delaminations are most often caused by impacts with external objects. The detection, localization and quantification of such impacts are therefore crucial for the prevention of catastrophic events. In this paper, we demonstrate the feasibility to perform impact identification in smart composite structures with embedded fiber optic sensors. For our analyses, we manufactured a carbon fiber reinforced plate in which we embedded a distributed network of fiber Bragg grating (FBG) sensors. We impacted the plate with a modal hammer and we identified the impacts by processing the FBG data with an improved fast phase correlation (FPC) algorithm in combination with a variable selective least squares (VS-LS) inverse solver approach. A total of 164 impacts distributed on 41 possible impact locations were analyzed. We compared our methodology with the traditional P-Inv based approach. In terms of impact localization, our methodology performed better in 70.7% of the cases. An improvement on the impact time domain reconstruction was achieved in 95 . 1 % of the cases.

A cost-effective quasi-distributed liquid leakage sensor based on the polymer optical fiber and flexible lamp belt with LEDs.

PubMed

Zhang, Yingzi; Hou, Yulong; Zhang, Yanjun; Hu, Yanjun; Zhang, Liang; Gao, Xiaolong; Zhang, Huixin; Liu, Wenyi

2018-04-16

A quasi-distributed liquid leakage (QDLL) sensor in local area is proposed and experimentally demonstrated, providing a real-time yet low-cost method than the existing local QDLL sensor. The sensor mainly consists of a flexible lamp belt (FLB) with light-emitting diodes (LEDs) and a polymer optical fiber (POF) processed with side-coupling structures. The side-coupling structures are illuminated by the LEDs one by one, forming a series of sensing probes. The lights are side-coupled into the POF through the side-coupling structure and pulse sequences are obtained from the power meters connected to the both ends of the POF. Each pulse represents a sensing probe, and the intensity of them increase when the coupling medium changes from air to liquid. The location of the leakage incident can be got by the position of each pulse in its output sequence. The influence of different side-coupling structures on side-coupling ratio are investigated. The experiment results validate the detection and localization abilities of the QDLL sensor along a 1 m-long POF with a spatial resolution of 0.1 m, which can be improved by adjusting the side-coupling structure. Furthermore, the temperature dependence is studied and can be compensated.

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.

Three-Axis Ground Reaction Force Distribution during Straight Walking.

PubMed

Hori, Masataka; Nakai, Akihito; Shimoyama, Isao

2017-10-24

We measured the three-axis ground reaction force (GRF) distribution during straight walking. Small three-axis force sensors composed of rubber and sensor chips were fabricated and calibrated. After sensor calibration, 16 force sensors were attached to the left shoe. The three-axis force distribution during straight walking was measured, and the local features of the three-axis force under the sole of the shoe were analyzed. The heel area played a role in receiving the braking force, the base area of the fourth and fifth toes applied little vertical or shear force, the base area of the second and third toes generated a portion of the propulsive force and received a large vertical force, and the base area of the big toe helped move the body's center of mass to the other foot. The results demonstrate that measuring the three-axis GRF distribution is useful for a detailed analysis of bipedal locomotion.

Monitoring industrial facilities using principles of integration of fiber classifier and local sensor networks

NASA Astrophysics Data System (ADS)

Korotaev, Valery V.; Denisov, Victor M.; Rodrigues, Joel J. P. C.; Serikova, Mariya G.; Timofeev, Andrey V.

2015-05-01

The paper deals with the creation of integrated monitoring systems. They combine fiber-optic classifiers and local sensor networks. These systems allow for the monitoring of complex industrial objects. Together with adjacent natural objects, they form the so-called geotechnical systems. An integrated monitoring system may include one or more spatially continuous fiber-optic classifiers based on optic fiber and one or more arrays of discrete measurement sensors, which are usually combined in sensor networks. Fiber-optic classifiers are already widely used for the control of hazardous extended objects (oil and gas pipelines, railways, high-rise buildings, etc.). To monitor local objects, discrete measurement sensors are generally used (temperature, pressure, inclinometers, strain gauges, accelerometers, sensors measuring the composition of impurities in the air, and many others). However, monitoring complex geotechnical systems require a simultaneous use of continuous spatially distributed sensors based on fiber-optic cable and connected local discrete sensors networks. In fact, we are talking about integration of the two monitoring methods. This combination provides an additional way to create intelligent monitoring systems. Modes of operation of intelligent systems can automatically adapt to changing environmental conditions. For this purpose, context data received from one sensor (e.g., optical channel) may be used to change modes of work of other sensors within the same monitoring system. This work also presents experimental results of the prototype of the integrated monitoring system.

Strategies for lidar characterization of particulates from point and area sources

NASA Astrophysics Data System (ADS)

Wojcik, Michael D.; Moore, Kori D.; Martin, Randal S.; Hatfield, Jerry

2010-10-01

Use of ground based remote sensing technologies such as scanning lidar systems (light detection and ranging) has gained traction in characterizing ambient aerosols due to some key advantages such as wide area of regard (10 km2), fast response time, high spatial resolution (<10 m) and high sensitivity. Energy Dynamics Laboratory and Utah State University, in conjunction with the USDA-ARS, has developed a three-wavelength scanning lidar system called Aglite that has been successfully deployed to characterize particle motion, concentration, and size distribution at both point and diffuse area sources in agricultural and industrial settings. A suite of massbased and size distribution point sensors are used to locally calibrate the lidar. Generating meaningful particle size distribution, mass concentration, and emission rate results based on lidar data is dependent on strategic onsite deployment of these point sensors with successful local meteorological measurements. Deployment strategies learned from field use of this entire measurement system over five years include the characterization of local meteorology and its predictability prior to deployment, the placement of point sensors to prevent contamination and overloading, the positioning of the lidar and beam plane to avoid hard target interferences, and the usefulness of photographic and written observational data.

Optic fiber sensor-based smart bridge cable with functionality of self-sensing

NASA Astrophysics Data System (ADS)

He, Jianping; Zhou, Zhi; Jinping, Ou

2013-02-01

Bridge cables, characterized by distributed large span, serving in harsh environment and vulnerability to random damage, are the key load-sustaining components of cable-based bridges. To ensure the safety of the bridge structure, it is critical to monitor the loading conditions of these cables under lengthwise random damages. Aiming at obtaining accurate monitoring at the critical points as well as the general information of the cable force distributed along the entire cable, this paper presents a study on cable force monitoring by combining optical fiber Bragg grating (FBG) sensors and Brillouin optical time domain analysis/reflectory (BOTDA/R) sensing technique in one single optical fiber. A smart FRP-OF-FBG rebar based cable was fabricated by protruding a FRP packaged OF-FBG sensor into the bridge cable. And its sensing characteristics, stability under high stress state temperature self-compensation as well as BOTDA/R distributed data improvement by local FBG sensors have been investigated. The results show that FRP-OF-FBG rebar in the smart cable can deform consistantly along with the steel wire and the cable force obtained from the optical fiber sensors agree well with theoretical value with relative error less than ±5%. Besides, the temperature self-compensation method provides a significant cost-effective technique for the FRP-OF-FBG based cables' in situ cable force measurement. And furthermore, potential damages of the bridge cable, e.g. wire breaking and corrosion, can be characterized and symbolized by the discontinuity and fluctuation of the distributed BOTDA data thereafter accuracy improved by local FBG sensors.

SoundCompass: A Distributed MEMS Microphone Array-Based Sensor for Sound Source Localization

PubMed Central

Tiete, Jelmer; Domínguez, Federico; da Silva, Bruno; Segers, Laurent; Steenhaut, Kris; Touhafi, Abdellah

2014-01-01

Sound source localization is a well-researched subject with applications ranging from localizing sniper fire in urban battlefields to cataloging wildlife in rural areas. One critical application is the localization of noise pollution sources in urban environments, due to an increasing body of evidence linking noise pollution to adverse effects on human health. Current noise mapping techniques often fail to accurately identify noise pollution sources, because they rely on the interpolation of a limited number of scattered sound sensors. Aiming to produce accurate noise pollution maps, we developed the SoundCompass, a low-cost sound sensor capable of measuring local noise levels and sound field directionality. Our first prototype is composed of a sensor array of 52 Microelectromechanical systems (MEMS) microphones, an inertial measuring unit and a low-power field-programmable gate array (FPGA). This article presents the SoundCompass’s hardware and firmware design together with a data fusion technique that exploits the sensing capabilities of the SoundCompass in a wireless sensor network to localize noise pollution sources. Live tests produced a sound source localization accuracy of a few centimeters in a 25-m2 anechoic chamber, while simulation results accurately located up to five broadband sound sources in a 10,000-m2 open field. PMID:24463431

Future electro-optical sensors and processing in urban operations

NASA Astrophysics Data System (ADS)

Grönwall, Christina; Schwering, Piet B.; Rantakokko, Jouni; Benoist, Koen W.; Kemp, Rob A. W.; Steinvall, Ove; Letalick, Dietmar; Björkert, Stefan

2013-10-01

In the electro-optical sensors and processing in urban operations (ESUO) study we pave the way for the European Defence Agency (EDA) group of Electro-Optics experts (IAP03) for a common understanding of the optimal distribution of processing functions between the different platforms. Combinations of local, distributed and centralized processing are proposed. In this way one can match processing functionality to the required power, and available communication systems data rates, to obtain the desired reaction times. In the study, three priority scenarios were defined. For these scenarios, present-day and future sensors and signal processing technologies were studied. The priority scenarios were camp protection, patrol and house search. A method for analyzing information quality in single and multi-sensor systems has been applied. A method for estimating reaction times for transmission of data through the chain of command has been proposed and used. These methods are documented and can be used to modify scenarios, or be applied to other scenarios. Present day data processing is organized mainly locally. Very limited exchange of information with other platforms is present; this is performed mainly at a high information level. Main issues that arose from the analysis of present-day systems and methodology are the slow reaction time due to the limited field of view of present-day sensors and the lack of robust automated processing. Efficient handover schemes between wide and narrow field of view sensors may however reduce the delay times. The main effort in the study was in forecasting the signal processing of EO-sensors in the next ten to twenty years. Distributed processing is proposed between hand-held and vehicle based sensors. This can be accompanied by cloud processing on board several vehicles. Additionally, to perform sensor fusion on sensor data originating from different platforms, and making full use of UAV imagery, a combination of distributed and centralized processing is essential. There is a central role for sensor fusion of heterogeneous sensors in future processing. The changes that occur in the urban operations of the future due to the application of these new technologies will be the improved quality of information, with shorter reaction time, and with lower operator load.

Distributed resource allocation under communication constraints

NASA Astrophysics Data System (ADS)

Dodin, Pierre; Nimier, Vincent

2001-03-01

This paper deals with a study of the multi-sensor management problem for multi-target tracking. The collaboration between many sensors observing the same target means that they are able to fuse their data during the information process. Then one must take into account this possibility to compute the optimal association sensors-target at each step of time. In order to solve this problem for real large scale system, one must both consider the information aspect and the control aspect of the problem. To unify these problems, one possibility is to use a decentralized filtering algorithm locally driven by an assignment algorithm. The decentralized filtering algorithm we use in our model is the filtering algorithm of Grime, which relaxes the usual full-connected hypothesis. By full-connected, one means that the information in a full-connected system is totally distributed everywhere at the same moment, which is unacceptable for a real large scale system. We modelize the distributed assignment decision with the help of a greedy algorithm. Each sensor performs a global optimization, in order to estimate other information sets. A consequence of the relaxation of the full- connected hypothesis is that the sensors' information set are not the same at each step of time, producing an information dis- symmetry in the system. The assignment algorithm uses a local knowledge of this dis-symmetry. By testing the reactions and the coherence of the local assignment decisions of our system, against maneuvering targets, we show that it is still possible to manage with decentralized assignment control even though the system is not full-connected.

Network hydraulics inclusion in water quality event detection using multiple sensor stations data.

PubMed

Oliker, Nurit; Ostfeld, Avi

2015-09-01

Event detection is one of the current most challenging topics in water distribution systems analysis: how regular on-line hydraulic (e.g., pressure, flow) and water quality (e.g., pH, residual chlorine, turbidity) measurements at different network locations can be efficiently utilized to detect water quality contamination events. This study describes an integrated event detection model which combines multiple sensor stations data with network hydraulics. To date event detection modelling is likely limited to single sensor station location and dataset. Single sensor station models are detached from network hydraulics insights and as a result might be significantly exposed to false positive alarms. This work is aimed at decreasing this limitation through integrating local and spatial hydraulic data understanding into an event detection model. The spatial analysis complements the local event detection effort through discovering events with lower signatures by exploring the sensors mutual hydraulic influences. The unique contribution of this study is in incorporating hydraulic simulation information into the overall event detection process of spatially distributed sensors. The methodology is demonstrated on two example applications using base runs and sensitivity analyses. Results show a clear advantage of the suggested model over single-sensor event detection schemes. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Fan, Qiaoyun; Zhong, Xuyang; Sun, Junhua

2018-03-01

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

Tomographic Imaging on Distributed Unattended Ground Sensor Arrays

DTIC Science & Technology

2002-05-14

communication, the recently released Bluetooth standard warrants investigation into its usefulness on ground sensors. Although not as powerful or as fast...NTSC,” June 2001, http://archive.ncsa.uiuc.edu/ SCMS /training/general/details/ntsc.html [14] Techfest, “PCI local bus technical summary,” 1999, http

Relative Localization in Wireless Sensor Networks for Measurement of Electric Fields under HVDC Transmission Lines

PubMed Central

Cui, Yong; Wang, Qiusheng; Yuan, Haiwen; Song, Xiao; Hu, Xuemin; Zhao, Luxing

2015-01-01

In the wireless sensor networks (WSNs) for electric field measurement system under the High-Voltage Direct Current (HVDC) transmission lines, it is necessary to obtain the electric field distribution with multiple sensors. The location information of each sensor is essential to the correct analysis of measurement results. Compared with the existing approach which gathers the location information by manually labelling sensors during deployment, the automatic localization can reduce the workload and improve the measurement efficiency. A novel and practical range-free localization algorithm for the localization of one-dimensional linear topology wireless networks in the electric field measurement system is presented. The algorithm utilizes unknown nodes' neighbor lists based on the Received Signal Strength Indicator (RSSI) values to determine the relative locations of nodes. The algorithm is able to handle the exceptional situation of the output permutation which can effectively improve the accuracy of localization. The performance of this algorithm under real circumstances has been evaluated through several experiments with different numbers of nodes and different node deployments in the China State Grid HVDC test base. Results show that the proposed algorithm achieves an accuracy of over 96% under different conditions. PMID:25658390

Relative localization in wireless sensor networks for measurement of electric fields under HVDC transmission lines.

PubMed

Cui, Yong; Wang, Qiusheng; Yuan, Haiwen; Song, Xiao; Hu, Xuemin; Zhao, Luxing

2015-02-04

In the wireless sensor networks (WSNs) for electric field measurement system under the High-Voltage Direct Current (HVDC) transmission lines, it is necessary to obtain the electric field distribution with multiple sensors. The location information of each sensor is essential to the correct analysis of measurement results. Compared with the existing approach which gathers the location information by manually labelling sensors during deployment, the automatic localization can reduce the workload and improve the measurement efficiency. A novel and practical range-free localization algorithm for the localization of one-dimensional linear topology wireless networks in the electric field measurement system is presented. The algorithm utilizes unknown nodes' neighbor lists based on the Received Signal Strength Indicator (RSSI) values to determine the relative locations of nodes. The algorithm is able to handle the exceptional situation of the output permutation which can effectively improve the accuracy of localization. The performance of this algorithm under real circumstances has been evaluated through several experiments with different numbers of nodes and different node deployments in the China State Grid HVDC test base. Results show that the proposed algorithm achieves an accuracy of over 96% under different conditions.

Distributed least-squares estimation of a remote chemical source via convex combination in wireless sensor networks.

PubMed

Cao, Meng-Li; Meng, Qing-Hao; Zeng, Ming; Sun, Biao; Li, Wei; Ding, Cheng-Jun

2014-06-27

This paper investigates the problem of locating a continuous chemical source using the concentration measurements provided by a wireless sensor network (WSN). Such a problem exists in various applications: eliminating explosives or drugs, detecting the leakage of noxious chemicals, etc. The limited power and bandwidth of WSNs have motivated collaborative in-network processing which is the focus of this paper. We propose a novel distributed least-squares estimation (DLSE) method to solve the chemical source localization (CSL) problem using a WSN. The DLSE method is realized by iteratively conducting convex combination of the locally estimated chemical source locations in a distributed manner. Performance assessments of our method are conducted using both simulations and real experiments. In the experiments, we propose a fitting method to identify both the release rate and the eddy diffusivity. The results show that the proposed DLSE method can overcome the negative interference of local minima and saddle points of the objective function, which would hinder the convergence of local search methods, especially in the case of locating a remote chemical source.

Using Hybrid Angle/Distance Information for Distributed Topology Control in Vehicular Sensor Networks

PubMed Central

Huang, Chao-Chi; Chiu, Yang-Hung; Wen, Chih-Yu

2014-01-01

In a vehicular sensor network (VSN), the key design issue is how to organize vehicles effectively, such that the local network topology can be stabilized quickly. In this work, each vehicle with on-board sensors can be considered as a local controller associated with a group of communication members. In order to balance the load among the nodes and govern the local topology change, a group formation scheme using localized criteria is implemented. The proposed distributed topology control method focuses on reducing the rate of group member change and avoiding the unnecessary information exchange. Two major phases are sequentially applied to choose the group members of each vehicle using hybrid angle/distance information. The operation of Phase I is based on the concept of the cone-based method, which can select the desired vehicles quickly. Afterwards, the proposed time-slot method is further applied to stabilize the network topology. Given the network structure in Phase I, a routing scheme is presented in Phase II. The network behaviors are explored through simulation and analysis in a variety of scenarios. The results show that the proposed mechanism is a scalable and effective control framework for VSNs. PMID:25350506

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.

In-situ Monitoring of Internal Local Temperature and Voltage of Proton Exchange Membrane Fuel Cells

PubMed Central

Lee, Chi-Yuan; Fan, Wei-Yuan; Hsieh, Wei-Jung

2010-01-01

The distribution of temperature and voltage of a fuel cell are key factors that influence performance. Conventional sensors are normally large, and are also useful only for making external measurements of fuel cells. Centimeter-scale sensors for making invasive measurements are frequently unable to accurately measure the interior changes of a fuel cell. This work focuses mainly on fabricating flexible multi-functional microsensors (for temperature and voltage) to measure variations in the local temperature and voltage of proton exchange membrane fuel cells (PEMFC) that are based on micro-electro-mechanical systems (MEMS). The power density at 0.5 V without a sensor is 450 mW/cm2, and that with a sensor is 426 mW/cm2. Since the reaction area of a fuel cell with a sensor is approximately 12% smaller than that without a sensor, but the performance of the former is only 5% worse. PMID:22163556

In-situ monitoring of internal local temperature and voltage of proton exchange membrane fuel cells.

PubMed

Lee, Chi-Yuan; Fan, Wei-Yuan; Hsieh, Wei-Jung

2010-01-01

The distribution of temperature and voltage of a fuel cell are key factors that influence performance. Conventional sensors are normally large, and are also useful only for making external measurements of fuel cells. Centimeter-scale sensors for making invasive measurements are frequently unable to accurately measure the interior changes of a fuel cell. This work focuses mainly on fabricating flexible multi-functional microsensors (for temperature and voltage) to measure variations in the local temperature and voltage of proton exchange membrane fuel cells (PEMFC) that are based on micro-electro-mechanical systems (MEMS). The power density at 0.5 V without a sensor is 450 mW/cm(2), and that with a sensor is 426 mW/cm(2). Since the reaction area of a fuel cell with a sensor is approximately 12% smaller than that without a sensor, but the performance of the former is only 5% worse.

Gossip and Distributed Kalman Filtering: Weak Consensus Under Weak Detectability

NASA Astrophysics Data System (ADS)

Kar, Soummya; Moura, José M. F.

2011-04-01

The paper presents the gossip interactive Kalman filter (GIKF) for distributed Kalman filtering for networked systems and sensor networks, where inter-sensor communication and observations occur at the same time-scale. The communication among sensors is random; each sensor occasionally exchanges its filtering state information with a neighbor depending on the availability of the appropriate network link. We show that under a weak distributed detectability condition: 1. the GIKF error process remains stochastically bounded, irrespective of the instability properties of the random process dynamics; and 2. the network achieves \\emph{weak consensus}, i.e., the conditional estimation error covariance at a (uniformly) randomly selected sensor converges in distribution to a unique invariant measure on the space of positive semi-definite matrices (independent of the initial state.) To prove these results, we interpret the filtered states (estimates and error covariances) at each node in the GIKF as stochastic particles with local interactions. We analyze the asymptotic properties of the error process by studying as a random dynamical system the associated switched (random) Riccati equation, the switching being dictated by a non-stationary Markov chain on the network graph.

Distributed fault detection over sensor networks with Markovian switching topologies

NASA Astrophysics Data System (ADS)

Ge, Xiaohua; Han, Qing-Long

2014-05-01

This paper deals with the distributed fault detection for discrete-time Markov jump linear systems over sensor networks with Markovian switching topologies. The sensors are scatteredly deployed in the sensor field and the fault detectors are physically distributed via a communication network. The system dynamics changes and sensing topology variations are modeled by a discrete-time Markov chain with incomplete mode transition probabilities. Each of these sensor nodes firstly collects measurement outputs from its all underlying neighboring nodes, processes these data in accordance with the Markovian switching topologies, and then transmits the processed data to the remote fault detector node. Network-induced delays and accumulated data packet dropouts are incorporated in the data transmission between the sensor nodes and the distributed fault detector nodes through the communication network. To generate localized residual signals, mode-independent distributed fault detection filters are proposed. By means of the stochastic Lyapunov functional approach, the residual system performance analysis is carried out such that the overall residual system is stochastically stable and the error between each residual signal and the fault signal is made as small as possible. Furthermore, a sufficient condition on the existence of the mode-independent distributed fault detection filters is derived in the simultaneous presence of incomplete mode transition probabilities, Markovian switching topologies, network-induced delays, and accumulated data packed dropouts. Finally, a stirred-tank reactor system is given to show the effectiveness of the developed theoretical results.

Long-Term Simultaneous Localization and Mapping in Dynamic Environments

DTIC Science & Technology

2015-01-01

core competencies required for autonomous mobile robotics is the ability to use sensors to perceive the environment. From this noisy sensor data, the...and mapping (SLAM), is a prerequisite for almost all higher-level autonomous behavior in mobile robotics. By associating the robot???s sensory...distributed stochastic neighbor embedding x ABSTRACT One of the core competencies required for autonomous mobile robotics is the ability to use sensors

Wireless Power Transfer for Distributed Estimation in Sensor Networks

NASA Astrophysics Data System (ADS)

Mai, Vien V.; Shin, Won-Yong; Ishibashi, Koji

2017-04-01

This paper studies power allocation for distributed estimation of an unknown scalar random source in sensor networks with a multiple-antenna fusion center (FC), where wireless sensors are equipped with radio-frequency based energy harvesting technology. The sensors' observation is locally processed by using an uncoded amplify-and-forward scheme. The processed signals are then sent to the FC, and are coherently combined at the FC, at which the best linear unbiased estimator (BLUE) is adopted for reliable estimation. We aim to solve the following two power allocation problems: 1) minimizing distortion under various power constraints; and 2) minimizing total transmit power under distortion constraints, where the distortion is measured in terms of mean-squared error of the BLUE. Two iterative algorithms are developed to solve the non-convex problems, which converge at least to a local optimum. In particular, the above algorithms are designed to jointly optimize the amplification coefficients, energy beamforming, and receive filtering. For each problem, a suboptimal design, a single-antenna FC scenario, and a common harvester deployment for colocated sensors, are also studied. Using the powerful semidefinite relaxation framework, our result is shown to be valid for any number of sensors, each with different noise power, and for an arbitrarily number of antennas at the FC.

An approach to estimate spatial distribution of analyte within cells using spectrally-resolved fluorescence microscopy.

PubMed

Sharma, Dharmendar Kumar; Irfanullah, Mir; Basu, Santanu Kumar; Madhu, Sheri; De, Suman; Jadhav, Sameer; Ravikanth, Mangalampalli; Chowdhury, Arindam

2017-01-18

While fluorescence microscopy has become an essential tool amongst chemists and biologists for the detection of various analyte within cellular environments, non-uniform spatial distribution of sensors within cells often restricts extraction of reliable information on relative abundance of analytes in different subcellular regions. As an alternative to existing sensing methodologies such as ratiometric or FRET imaging, where relative proportion of analyte with respect to the sensor can be obtained within cells, we propose a methodology using spectrally-resolved fluorescence microscopy, via which both the relative abundance of sensor as well as their relative proportion with respect to the analyte can be simultaneously extracted for local subcellular regions. This method is exemplified using a BODIPY sensor, capable of detecting mercury ions within cellular environments, characterized by spectral blue-shift and concurrent enhancement of emission intensity. Spectral emission envelopes collected from sub-microscopic regions allowed us to compare the shift in transition energies as well as integrated emission intensities within various intracellular regions. Construction of a 2D scatter plot using spectral shifts and emission intensities, which depend on the relative amount of analyte with respect to sensor and the approximate local amounts of the probe, respectively, enabled qualitative extraction of relative abundance of analyte in various local regions within a single cell as well as amongst different cells. Although the comparisons remain semi-quantitative, this approach involving analysis of multiple spectral parameters opens up an alternative way to extract spatial distribution of analyte in heterogeneous systems. The proposed method would be especially relevant for fluorescent probes that undergo relatively nominal shift in transition energies compared to their emission bandwidths, which often restricts their usage for quantitative ratiometric imaging in cellular media due to strong cross-talk between energetically separated detection channels.

An approach to estimate spatial distribution of analyte within cells using spectrally-resolved fluorescence microscopy

NASA Astrophysics Data System (ADS)

Sharma, Dharmendar Kumar; Irfanullah, Mir; Basu, Santanu Kumar; Madhu, Sheri; De, Suman; Jadhav, Sameer; Ravikanth, Mangalampalli; Chowdhury, Arindam

2017-03-01

While fluorescence microscopy has become an essential tool amongst chemists and biologists for the detection of various analyte within cellular environments, non-uniform spatial distribution of sensors within cells often restricts extraction of reliable information on relative abundance of analytes in different subcellular regions. As an alternative to existing sensing methodologies such as ratiometric or FRET imaging, where relative proportion of analyte with respect to the sensor can be obtained within cells, we propose a methodology using spectrally-resolved fluorescence microscopy, via which both the relative abundance of sensor as well as their relative proportion with respect to the analyte can be simultaneously extracted for local subcellular regions. This method is exemplified using a BODIPY sensor, capable of detecting mercury ions within cellular environments, characterized by spectral blue-shift and concurrent enhancement of emission intensity. Spectral emission envelopes collected from sub-microscopic regions allowed us to compare the shift in transition energies as well as integrated emission intensities within various intracellular regions. Construction of a 2D scatter plot using spectral shifts and emission intensities, which depend on the relative amount of analyte with respect to sensor and the approximate local amounts of the probe, respectively, enabled qualitative extraction of relative abundance of analyte in various local regions within a single cell as well as amongst different cells. Although the comparisons remain semi-quantitative, this approach involving analysis of multiple spectral parameters opens up an alternative way to extract spatial distribution of analyte in heterogeneous systems. The proposed method would be especially relevant for fluorescent probes that undergo relatively nominal shift in transition energies compared to their emission bandwidths, which often restricts their usage for quantitative ratiometric imaging in cellular media due to strong cross-talk between energetically separated detection channels. Dedicated to Professor Kankan Bhattacharyya.

Ubiquitous Low-Cost Functionalized Multi-Walled Carbon Nanotube Sensors for Distributed Methane Leak Detection

DOE PAGES

Humayun, Md Tanim; Divan, Ralu; Stan, Liliana; ...

2016-06-16

This paper presents a highly sensitive, energy efficient and low-cost distributed methane (CH 4) sensor system (DMSS) for continuous monitoring, detection, and localization of CH 4 leaks in natural gas infrastructure, such as transmission and distribution pipelines, wells, and production pads. The CH 4 sensing element, a key component of the DMSS, consists of a metal oxide nanocrystal (MONC) functionalized multi-walled carbon nanotube (MWCNT) mesh which, in comparison to existing literature, shows stronger relative resistance change while interacting with lower parts per million (ppm) concentration of CH 4. A Gaussian plume triangulation algorithm has been developed for the DMSS. Givenmore » a geometric model of the surrounding environment the algorithm can precisely detect and localize a CH 4 leak as well as estimate its mass emission rate. A UV-based surface recovery technique making the sensor recover 10 times faster than the reported ones is presented for the DMSS. In conclusion, a control algorithm based on the UV-accelerated recovery is developed which facilitates faster leak detection.« less

Direct Estimation of Power Distribution in Reactors for Nuclear Thermal Space Propulsion

NASA Astrophysics Data System (ADS)

Aldemir, Tunc; Miller, Don W.; Burghelea, Andrei

2004-02-01

A recently proposed constant temperature power sensor (CTPS) has the capability to directly measure the local power deposition rate in nuclear reactor cores proposed for space thermal propulsion. Such a capability reduces the uncertainties in the estimated power peaking factors and hence increases the reliability of the nuclear engine. The CTPS operation is sensitive to the changes in the local thermal conditions. A procedure is described for the automatic on-line calibration of the sensor through estimation of changes in thermal .conditions.

Experimental Analysis of Steel Beams Subjected to Fire Enhanced by Brillouin Scattering-Based Fiber Optic Sensor Data.

PubMed

Bao, Yi; Chen, Yizheng; Hoehler, Matthew S; Smith, Christopher M; Bundy, Matthew; Chen, Genda

2017-01-01

This paper presents high temperature measurements using a Brillouin scattering-based fiber optic sensor and the application of the measured temperatures and building code recommended material parameters into enhanced thermomechanical analysis of simply supported steel beams subjected to combined thermal and mechanical loading. The distributed temperature sensor captures detailed, nonuniform temperature distributions that are compared locally with thermocouple measurements with less than 4.7% average difference at 95% confidence level. The simulated strains and deflections are validated using measurements from a second distributed fiber optic (strain) sensor and two linear potentiometers, respectively. The results demonstrate that the temperature-dependent material properties specified in the four investigated building codes lead to strain predictions with less than 13% average error at 95% confidence level and that the Europe building code provided the best predictions. However, the implicit consideration of creep in Europe is insufficient when the beam temperature exceeds 800°C.

Microwave moisture sensing of wet bales

USDA-ARS?s Scientific Manuscript database

Sensing of moisture in very wet lint bales is unique due to the fact that moisture distribution is typically non-uniform and can in some instances be highly localized. This issue is even further complicated by the use of a sensor that reads only a portion of the bale and/or with a sensor that provid...

In-Situ Measurement of High-Temperature Proton Exchange Membrane Fuel Cell Stack Using Flexible Five-in-One Micro-Sensor

PubMed Central

Lee, Chi-Yuan; Weng, Fang-Bor; Kuo, Yzu-Wei; Tsai, Chao-Hsuan; Cheng, Yen-Ting; Cheng, Chih-Kai; Lin, Jyun-Ting

2016-01-01

In the chemical reaction that proceeds in a high-temperature proton exchange membrane fuel cell stack (HT-PEMFC stack), the internal local temperature, voltage, pressure, flow and current nonuniformity may cause poor membrane material durability and nonuniform fuel distribution, thus influencing the performance and lifetime of the fuel cell stack. In this paper micro-electro-mechanical systems (MEMS) are utilized to develop a high-temperature electrochemical environment-resistant five-in-one micro-sensor embedded in the cathode channel plate of an HT-PEMFC stack, and materials and process parameters are appropriately selected to protect the micro-sensor against failure or destruction during long-term operation. In-situ measurement of the local temperature, voltage, pressure, flow and current distributions in the HT-PEMFC stack is carried out. This integrated micro-sensor has five functions, and is favorably characterized by small size, good acid resistance and temperature resistance, quick response, real-time measurement, and the goal is being able to be put in any place for measurement without affecting the performance of the battery. PMID:27763559

In-Situ Measurement of High-Temperature Proton Exchange Membrane Fuel Cell Stack Using Flexible Five-in-One Micro-Sensor.

PubMed

Lee, Chi-Yuan; Weng, Fang-Bor; Kuo, Yzu-Wei; Tsai, Chao-Hsuan; Cheng, Yen-Ting; Cheng, Chih-Kai; Lin, Jyun-Ting

2016-10-18

In the chemical reaction that proceeds in a high-temperature proton exchange membrane fuel cell stack (HT-PEMFC stack), the internal local temperature, voltage, pressure, flow and current nonuniformity may cause poor membrane material durability and nonuniform fuel distribution, thus influencing the performance and lifetime of the fuel cell stack. In this paper micro-electro-mechanical systems (MEMS) are utilized to develop a high-temperature electrochemical environment-resistant five-in-one micro-sensor embedded in the cathode channel plate of an HT-PEMFC stack, and materials and process parameters are appropriately selected to protect the micro-sensor against failure or destruction during long-term operation. In-situ measurement of the local temperature, voltage, pressure, flow and current distributions in the HT-PEMFC stack is carried out. This integrated micro-sensor has five functions, and is favorably characterized by small size, good acid resistance and temperature resistance, quick response, real-time measurement, and the goal is being able to be put in any place for measurement without affecting the performance of the battery.

Anchor Node Localization for Wireless Sensor Networks Using Video and Compass Information Fusion

PubMed Central

Pescaru, Dan; Curiac, Daniel-Ioan

2014-01-01

Distributed sensing, computing and communication capabilities of wireless sensor networks require, in most situations, an efficient node localization procedure. In the case of random deployments in harsh or hostile environments, a general localization process within global coordinates is based on a set of anchor nodes able to determine their own position using GPS receivers. In this paper we propose another anchor node localization technique that can be used when GPS devices cannot accomplish their mission or are considered to be too expensive. This novel technique is based on the fusion of video and compass data acquired by the anchor nodes and is especially suitable for video- or multimedia-based wireless sensor networks. For these types of wireless networks the presence of video cameras is intrinsic, while the presence of digital compasses is also required for identifying the cameras' orientations. PMID:24594614

Uniform competency-based local feature extraction for remote sensing images

NASA Astrophysics Data System (ADS)

Sedaghat, Amin; Mohammadi, Nazila

2018-01-01

Local feature detectors are widely used in many photogrammetry and remote sensing applications. The quantity and distribution of the local features play a critical role in the quality of the image matching process, particularly for multi-sensor high resolution remote sensing image registration. However, conventional local feature detectors cannot extract desirable matched features either in terms of the number of correct matches or the spatial and scale distribution in multi-sensor remote sensing images. To address this problem, this paper proposes a novel method for uniform and robust local feature extraction for remote sensing images, which is based on a novel competency criterion and scale and location distribution constraints. The proposed method, called uniform competency (UC) local feature extraction, can be easily applied to any local feature detector for various kinds of applications. The proposed competency criterion is based on a weighted ranking process using three quality measures, including robustness, spatial saliency and scale parameters, which is performed in a multi-layer gridding schema. For evaluation, five state-of-the-art local feature detector approaches, namely, scale-invariant feature transform (SIFT), speeded up robust features (SURF), scale-invariant feature operator (SFOP), maximally stable extremal region (MSER) and hessian-affine, are used. The proposed UC-based feature extraction algorithms were successfully applied to match various synthetic and real satellite image pairs, and the results demonstrate its capability to increase matching performance and to improve the spatial distribution. The code to carry out the UC feature extraction is available from href="https://www.researchgate.net/publication/317956777_UC-Feature_Extraction.

Novel auto-correction method in a fiber-optic distributed-temperature sensor using reflected anti-Stokes Raman scattering.

PubMed

Hwang, Dusun; Yoon, Dong-Jin; Kwon, Il-Bum; Seo, Dae-Cheol; Chung, Youngjoo

2010-05-10

A novel method for auto-correction of fiber optic distributed temperature sensor using anti-Stokes Raman back-scattering and its reflected signal is presented. This method processes two parts of measured signal. One part is the normal back scattered anti-Stokes signal and the other part is the reflected signal which eliminate not only the effect of local losses due to the micro-bending or damages on fiber but also the differential attenuation. Because the beams of the same wavelength are used to cancel out the local variance in transmission medium there is no differential attenuation inherently. The auto correction concept was verified by the bending experiment on different bending points. (c) 2010 Optical Society of America.

Energy efficient wireless sensor network for structural health monitoring using distributed embedded piezoelectric transducers

NASA Astrophysics Data System (ADS)

Li, Peng; Olmi, Claudio; Song, Gangbing

2010-04-01

Piezoceramic based transducers are widely researched and used for structural health monitoring (SHM) systems due to the piezoceramic material's inherent advantage of dual sensing and actuation. Wireless sensor network (WSN) technology benefits from advances made in piezoceramic based structural health monitoring systems, allowing easy and flexible installation, low system cost, and increased robustness over wired system. However, piezoceramic wireless SHM systems still faces some drawbacks, one of these is that the piezoceramic based SHM systems require relatively high computational capabilities to calculate damage information, however, battery powered WSN sensor nodes have strict power consumption limitation and hence limited computational power. On the other hand, commonly used centralized processing networks require wireless sensors to transmit all data back to the network coordinator for analysis. This signal processing procedure can be problematic for piezoceramic based SHM applications as it is neither energy efficient nor robust. In this paper, we aim to solve these problems with a distributed wireless sensor network for piezoceramic base structural health monitoring systems. Three important issues: power system, waking up from sleep impact detection, and local data processing, are addressed to reach optimized energy efficiency. Instead of sweep sine excitation that was used in the early research, several sine frequencies were used in sequence to excite the concrete structure. The wireless sensors record the sine excitations and compute the time domain energy for each sine frequency locally to detect the energy change. By comparing the data of the damaged concrete frame with the healthy data, we are able to find out the damage information of the concrete frame. A relative powerful wireless microcontroller was used to carry out the sampling and distributed data processing in real-time. The distributed wireless network dramatically reduced the data transmission between wireless sensor and the wireless coordinator, which in turn reduced the power consumption of the overall system.

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

Karakaya, Mahmut; Qi, Hairong

This paper addresses the communication and energy efficiency in collaborative visual sensor networks (VSNs) for people localization, a challenging computer vision problem of its own. We focus on the design of a light-weight and energy efficient solution where people are localized based on distributed camera nodes integrating the so-called certainty map generated at each node, that records the target non-existence information within the camera s field of view. We first present a dynamic itinerary for certainty map integration where not only each sensor node transmits a very limited amount of data but that a limited number of camera nodes ismore » involved. Then, we perform a comprehensive analytical study to evaluate communication and energy efficiency between different integration schemes, i.e., centralized and distributed integration. Based on results obtained from analytical study and real experiments, the distributed method shows effectiveness in detection accuracy as well as energy and bandwidth efficiency.« less

UGV navigation in wireless sensor and actuator network environments

NASA Astrophysics Data System (ADS)

Zhang, Guyu; Li, Jianfeng; Duncan, Christian A.; Kanno, Jinko; Selmic, Rastko R.

2012-06-01

We consider a navigation problem in a distributed, self-organized and coordinate-free Wireless Sensor and Ac- tuator Network (WSAN). We rst present navigation algorithms that are veried using simulation results. Con- sidering more than one destination and multiple mobile Unmanned Ground Vehicles (UGVs), we introduce a distributed solution to the Multi-UGV, Multi-Destination navigation problem. The objective of the solution to this problem is to eciently allocate UGVs to dierent destinations and carry out navigation in the network en- vironment that minimizes total travel distance. The main contribution of this paper is to develop a solution that does not attempt to localize either the UGVs or the sensor and actuator nodes. Other than some connectivity as- sumptions about the communication graph, we consider that no prior information about the WSAN is available. The solution presented here is distributed, and the UGV navigation is solely based on feedback from neigh- boring sensor and actuator nodes. One special case discussed in the paper, the Single-UGV, Multi-Destination navigation problem, is essentially equivalent to the well-known and dicult Traveling Salesman Problem (TSP). Simulation results are presented that illustrate the navigation distance traveled through the network. We also introduce an experimental testbed for the realization of coordinate-free and localization-free UGV navigation. We use the Cricket platform as the sensor and actuator network and a Pioneer 3-DX robot as the UGV. The experiments illustrate the UGV navigation in a coordinate-free WSAN environment where the UGV successfully arrives at the assigned destinations.

Local sensor based on nanowire field effect transistor from inhomogeneously doped silicon on insulator

NASA Astrophysics Data System (ADS)

Presnov, Denis E.; Bozhev, Ivan V.; Miakonkikh, Andrew V.; Simakin, Sergey G.; Trifonov, Artem S.; Krupenin, Vladimir A.

2018-02-01

We present the original method for fabricating a sensitive field/charge sensor based on field effect transistor (FET) with a nanowire channel that uses CMOS-compatible processes only. A FET with a kink-like silicon nanowire channel was fabricated from the inhomogeneously doped silicon on insulator wafer very close (˜100 nm) to the extremely sharp corner of a silicon chip forming local probe. The single e-beam lithographic process with a shadow deposition technique, followed by separate two reactive ion etching processes, was used to define the narrow semiconductor nanowire channel. The sensors charge sensitivity was evaluated to be in the range of 0.1-0.2 e /√{Hz } from the analysis of their transport and noise characteristics. The proposed method provides a good opportunity for the relatively simple manufacture of a local field sensor for measuring the electrical field distribution, potential profiles, and charge dynamics for a wide range of mesoscopic objects. Diagnostic systems and devices based on such sensors can be used in various fields of physics, chemistry, material science, biology, electronics, medicine, etc.

Distributed Algorithm for Voronoi Partition of Wireless Sensor Networks with a Limited Sensing Range.

PubMed

He, Chenlong; Feng, Zuren; Ren, Zhigang

2018-02-03

For Wireless Sensor Networks (WSNs), the Voronoi partition of a region is a challenging problem owing to the limited sensing ability of each sensor and the distributed organization of the network. In this paper, an algorithm is proposed for each sensor having a limited sensing range to compute its limited Voronoi cell autonomously, so that the limited Voronoi partition of the entire WSN is generated in a distributed manner. Inspired by Graham's Scan (GS) algorithm used to compute the convex hull of a point set, the limited Voronoi cell of each sensor is obtained by sequentially scanning two consecutive bisectors between the sensor and its neighbors. The proposed algorithm called the Boundary Scan (BS) algorithm has a lower computational complexity than the existing Range-Constrained Voronoi Cell (RCVC) algorithm and reaches the lower bound of the computational complexity of the algorithms used to solve the problem of this kind. Moreover, it also improves the time efficiency of a key step in the Adjust-Sensing-Radius (ASR) algorithm used to compute the exact Voronoi cell. Extensive numerical simulations are performed to demonstrate the correctness and effectiveness of the BS algorithm. The distributed realization of the BS combined with a localization algorithm in WSNs is used to justify the WSN nature of the proposed algorithm.

Distributed Algorithm for Voronoi Partition of Wireless Sensor Networks with a Limited Sensing Range

PubMed Central

Feng, Zuren; Ren, Zhigang

2018-01-01

For Wireless Sensor Networks (WSNs), the Voronoi partition of a region is a challenging problem owing to the limited sensing ability of each sensor and the distributed organization of the network. In this paper, an algorithm is proposed for each sensor having a limited sensing range to compute its limited Voronoi cell autonomously, so that the limited Voronoi partition of the entire WSN is generated in a distributed manner. Inspired by Graham’s Scan (GS) algorithm used to compute the convex hull of a point set, the limited Voronoi cell of each sensor is obtained by sequentially scanning two consecutive bisectors between the sensor and its neighbors. The proposed algorithm called the Boundary Scan (BS) algorithm has a lower computational complexity than the existing Range-Constrained Voronoi Cell (RCVC) algorithm and reaches the lower bound of the computational complexity of the algorithms used to solve the problem of this kind. Moreover, it also improves the time efficiency of a key step in the Adjust-Sensing-Radius (ASR) algorithm used to compute the exact Voronoi cell. Extensive numerical simulations are performed to demonstrate the correctness and effectiveness of the BS algorithm. The distributed realization of the BS combined with a localization algorithm in WSNs is used to justify the WSN nature of the proposed algorithm. PMID:29401649

Smart Distributed Sensor Fields: Algorithms for Tactical Sensors

DTIC Science & Technology

2013-12-23

ranging from detecting, identifying, localizing/tracking interesting events, discarding irrelevant data, to providing actionable intelligence currently...tracking interesting events, discarding irrelevant data, to providing actionable intelligence currently requires significant human super- vision. Human...view of the overall system. The main idea is to reduce the problem to the relevant data, and then reason intelligently over that data. This process

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

Architecture for distributed actuation and sensing using smart piezoelectric elements

NASA Astrophysics Data System (ADS)

Etienne-Cummings, Ralph; Pourboghrat, Farzad; Maruboyina, Hari K.; Abrate, Serge; Dhali, Shirshak K.

1998-07-01

We discuss vibration control of a cantilevered plate with multiple sensors and actuators. An architecture is chosen to minimize the number of control and sensing wires required. A custom VLSI chip, integrated with the sensor/actuator elements, controls the local behavior of the plate. All the actuators are addressed in parallel; local decode logic selects which actuator is stimulated. Downloaded binary data controls the applied voltage and modulation frequency for each actuator, and High Voltage MOSFETs are used to activate them. The sensors, which are independent adjacent piezoelectric ceramic elements, can be accessed in a random or sequential manner. An A/D card and GPIB interconnected test equipment allow a PC to read the sensors' outputs and dictate the actuation procedure. A visual programming environment is used to integrate the sensors, controller and actuators. Based on the constitutive relations for the piezoelectric material, simple models for the sensors and actuators are derived. A two level hierarchical robust controller is derived for motion control and for damping of vibrations.

Balanced PIN-TIA photoreceiver with integrated 3 dB fiber coupler for distributed fiber optic sensors

NASA Astrophysics Data System (ADS)

Datta, Shubhashish; Rajagopalan, Sruti; Lemke, Shaun; Joshi, Abhay

2014-06-01

We report a balanced PIN-TIA photoreceiver integrated with a 3 dB fiber coupler for distributed fiber optic sensors. This detector demonstrates -3 dB bandwidth >15 GHz and coupled conversion gain >65 V/W per photodiode through either input port of the 3 dB coupler, and can be operated at local oscillator power of +17 dBm. The combined common mode rejection of the balanced photoreceiver and the integrated 3 dB coupler is >20 dB. We also present measurement results with various optical stimuli, namely impulses, sinusoids, and pseudo-random sequences, which are relevant for time domain reflectometry, frequency domain reflectometry, and code correlation sensors, respectively.

Precision of EM Simulation Based Wireless Location Estimation in Multi-Sensor Capsule Endoscopy

PubMed Central

Ye, Yunxing; Aisha, Ain-Ul; Swar, Pranay; Pahlavan, Kaveh

2018-01-01

In this paper, we compute and examine two-way localization limits for an RF endoscopy pill as it passes through an individuals gastrointestinal (GI) tract. We obtain finite-difference time-domain and finite element method-based simulation results position assessment employing time of arrival (TOA). By means of a 3-D human body representation from a full-wave simulation software and lognormal models for TOA propagation from implant organs to body surface, we calculate bounds on location estimators in three digestive organs: stomach, small intestine, and large intestine. We present an investigation of the causes influencing localization precision, consisting of a range of organ properties; peripheral sensor array arrangements, number of pills in cooperation, and the random variations in transmit power of sensor nodes. We also perform a localization precision investigation for the situation where the transmission signal of the antenna is arbitrary with a known probability distribution. The computational solver outcome shows that the number of receiver antennas on the exterior of the body has higher impact on the precision of the location than the amount of capsules in collaboration within the GI region. The large intestine is influenced the most by the transmitter power probability distribution. PMID:29651364

Precision of EM Simulation Based Wireless Location Estimation in Multi-Sensor Capsule Endoscopy.

PubMed

Khan, Umair; Ye, Yunxing; Aisha, Ain-Ul; Swar, Pranay; Pahlavan, Kaveh

2018-01-01

In this paper, we compute and examine two-way localization limits for an RF endoscopy pill as it passes through an individuals gastrointestinal (GI) tract. We obtain finite-difference time-domain and finite element method-based simulation results position assessment employing time of arrival (TOA). By means of a 3-D human body representation from a full-wave simulation software and lognormal models for TOA propagation from implant organs to body surface, we calculate bounds on location estimators in three digestive organs: stomach, small intestine, and large intestine. We present an investigation of the causes influencing localization precision, consisting of a range of organ properties; peripheral sensor array arrangements, number of pills in cooperation, and the random variations in transmit power of sensor nodes. We also perform a localization precision investigation for the situation where the transmission signal of the antenna is arbitrary with a known probability distribution. The computational solver outcome shows that the number of receiver antennas on the exterior of the body has higher impact on the precision of the location than the amount of capsules in collaboration within the GI region. The large intestine is influenced the most by the transmitter power probability distribution.

Convergence Rate Analysis of Distributed Gossip (Linear Parameter) Estimation: Fundamental Limits and Tradeoffs

NASA Astrophysics Data System (ADS)

Kar, Soummya; Moura, José M. F.

2011-08-01

The paper considers gossip distributed estimation of a (static) distributed random field (a.k.a., large scale unknown parameter vector) observed by sparsely interconnected sensors, each of which only observes a small fraction of the field. We consider linear distributed estimators whose structure combines the information \\emph{flow} among sensors (the \\emph{consensus} term resulting from the local gossiping exchange among sensors when they are able to communicate) and the information \\emph{gathering} measured by the sensors (the \\emph{sensing} or \\emph{innovations} term.) This leads to mixed time scale algorithms--one time scale associated with the consensus and the other with the innovations. The paper establishes a distributed observability condition (global observability plus mean connectedness) under which the distributed estimates are consistent and asymptotically normal. We introduce the distributed notion equivalent to the (centralized) Fisher information rate, which is a bound on the mean square error reduction rate of any distributed estimator; we show that under the appropriate modeling and structural network communication conditions (gossip protocol) the distributed gossip estimator attains this distributed Fisher information rate, asymptotically achieving the performance of the optimal centralized estimator. Finally, we study the behavior of the distributed gossip estimator when the measurements fade (noise variance grows) with time; in particular, we consider the maximum rate at which the noise variance can grow and still the distributed estimator being consistent, by showing that, as long as the centralized estimator is consistent, the distributed estimator remains consistent.

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.

Instrumentation by distributed optical fiber sensors of a new ballastless track structure

NASA Astrophysics Data System (ADS)

Chapeleau, Xavier; Cottineau, Louis-Marie; Sedran, Thierry; Gueguen, Ivan; Cailliau, Joël

2013-04-01

While relatively expensive to build, ballastless track structures are presently seen as an attractive alternative to conventional ballast. With its service life of at least 60 years, they require little maintenance and hence they offer great availability. Other reasons for using ballastless tracks instead of ballasted tracks are the lack of suitable ballast material and the need of less noise and vibration for high-speed, in particularly. A new ballastless track structure has been designed to be circulated up to 300km/h, with a target life of 100 years. It is an interoperable way on concrete slabs that are cast-in-place and slip formed. This structure has been built and tested at the scale one in our laboratory. Indeed, ten millions cyclic loads were applied at 2.5Hz to evaluate the fatigue behaviour under selected mechanical and thermal conditions. To monitor the thermo-mechanical behavior of this new structure and to verify the numerical simulations used for its design, a lot of sensors have been embedded. In particularly, we have tested an optical fiber as distributed sensors to measure strain distribution in the railway model. This sensor can also be used to detect, localize and monitor cracks in concrete slabs. The optical fiber sensing technique ("Rayleigh technique") used in this experimentation has a centimetric spatial resolution which allows to measure complex strain profiles unlike electrical strain gauges which only give local information. Firstly, optical cables used as sensors have been successfully embedded and attached to the reinforcing steel bars in the structure. We have noted that they are resistant enough to resist concrete pouring and working activities. Secondly, strains measured by conventional strain gauges has confirmed the quality of the strain profiles measurements obtained by optical fiber sensors. Moreover, we have found a good agreement between experimental profiles measurements and those obtained by numerical simulations. Early during the fatigue test, some cracks have been observed. It is a current phenomenon in concrete slab which is due to drying shrinkage, load action, environmental factors and creep of concrete. Cracks can reduce the durability of the tract structure. So, it is important to be able to monitor them during the service of ballastless track line. We have demonstrated that cracks can detect, localized and monitor by a judicious placement of optical fibers. A crack corresponds to the appearance of a narrow peak on the strain profile. This peak can be detected and localized thanks to the very high spatial resolution of the optical Rayleigh sensing technique. Thus, we have noted that the cracks remain localized in slab edge without affecting the mechanical performances of the ballastless track structure. In conclusion, distributed sensing based on optical fiber sensor is a promising technique to monitor ballastless track structures and more generally, civil engineering structures. Some tests on a portion of a ballastless track line (still under construction) are planned in the next month.

Distributed Spectral Monitoring For Emitter Localization

DTIC Science & Technology

2018-02-12

localization techniques in a DSA sensor network. The results of the research are presented through simulation of localization algorithms, emulation of a...network on a wireless RF environment emulator, and field tests. The results of the various tests in both the lab and field are obtained and analyzed to... are two main classes of localization techniques, and the technique to use will depend on the information available with the emitter. The first class

Distributed temperature sensors development using an stepped-helical ultrasonic waveguide

NASA Astrophysics Data System (ADS)

Periyannan, Suresh; Rajagopal, Prabhu; Balasubramaniam, Krishnan

2018-04-01

This paper presents the design and development of the distributed ultrasonic waveguide temperature sensors using some stepped-helical structures. Distributed sensing has several applications in various industries (oil, glass, steel) for measurement of physical parameters such as level, temperature, viscosity, etc. This waveguide incorporates a special notch or bend for obtaining ultrasonic wave reflections from the desired locations (Gage-lengths) where local measurements are desired. In this paper, a multi-location measurement wave-guide, with a measurement capability of 18 locations in a single wire, has been fabricated. The distribution of these sensors is both in the axial as well as radial directions using a stepped-helical spring configuration. Also, different high temperature materials have been chosen for the wave-guide. Both lower order axi-symmetric guided ultrasonic modes (L(0,1) and T(0,1)) were employed. These wave modes were generated/received (pulse-echo approach) using conventional longitudinal and shear transducers, respectively. Also, both the wave modes were simultaneously generated/received and compared using shear transducer for developing the distributed helical wave-guide sensors. The effect of dispersion of the wave modes due to curvature effects will also be discussed.

Experimental Analysis of Steel Beams Subjected to Fire Enhanced by Brillouin Scattering-Based Fiber Optic Sensor Data

PubMed Central

Bao, Yi; Chen, Yizheng; Hoehler, Matthew S.; Smith, Christopher M.; Bundy, Matthew; Chen, Genda

2016-01-01

This paper presents high temperature measurements using a Brillouin scattering-based fiber optic sensor and the application of the measured temperatures and building code recommended material parameters into enhanced thermomechanical analysis of simply supported steel beams subjected to combined thermal and mechanical loading. The distributed temperature sensor captures detailed, nonuniform temperature distributions that are compared locally with thermocouple measurements with less than 4.7% average difference at 95% confidence level. The simulated strains and deflections are validated using measurements from a second distributed fiber optic (strain) sensor and two linear potentiometers, respectively. The results demonstrate that the temperature-dependent material properties specified in the four investigated building codes lead to strain predictions with less than 13% average error at 95% confidence level and that the Europe building code provided the best predictions. However, the implicit consideration of creep in Europe is insufficient when the beam temperature exceeds 800°C. PMID:28239230

Distributed Fiber Optic Sensors For The Monitoring Of A Tunnel Crossing A Landslide

NASA Astrophysics Data System (ADS)

Minardo, Aldo; Picarelli, Luciano; Zeni, Giovanni; Catalano, Ester; Coscetta, Agnese; Zhang, Lei; DiMaio, Caterina; Vassallo, Roberto; Coviello, Roberto; Macchia, Giuseppe Nicola Paolo; Zeni, Luigi

2017-04-01

Optical fiber distributed sensors have recently gained great attention in structural and environmental monitoring due to specific advantages because they share all the classical advantages common to all optical fiber sensors such as immunity to electromagnetic interferences, high sensitivity, small size and possibility to be embedded into the structures, multiplexing and remote interrogation capabilities [1], but also offer the unique feature of allowing the exploitation of a telecommunication grade optical fiber cable as the sensing element to measure deformation and temperature profiles over long distances, without any added devices. In particular, distributed optical fiber sensors based on stimulated Brillouin scattering through the so-called Brillouin Optical Time Domain Analysis (BOTDA), allow to measure strain and temperature profiles up to tens of kilometers with a strain accuracy of ±10µɛ and a temperature accuracy of ±1°C. These sensors have already been employed in static and dynamic monitoring of a variety of structures resulting able to identify and localize many kind of failures [2,3,4]. This paper deals with the application of BOTDA to the monitoring of the deformations of a railway tunnel (200 m long) constructed in the accumulation of Varco d'Izzo earthflow, Potenza city, in the Southern Italian Apennine. The earthflow, which occurs in the tectonized clay shale formation called Varicoloured Clays, although very slow, causes continuous damage to buildings and infrastructures built upon or across it. The railway tunnel itself had to be re-constructed in 1992. Since then, the Italian National Railway monitored the structure by means of localized fissure-meters. Recently, thanks to a collaboration with the rail Infrastructure Manager (RFI), monitoring of various zones of the landslide including the tunnel is based on advanced systems, among which the optical fiber distributed sensors. First results show how the sensing optical fiber cable is able to detect the formation of localized strains and cracks, following the evolution of their width and identifying their location along the tunnel walls. It is worth noticing that the distributed nature of the sensor makes it possible to perform the monitoring with no preliminary information about the possible location of concentrated deformation. The sensing cable is simply glued to the tunnel walls and the system will remotely detect and locate any deformation and fracture wherever they occur along the fiber path, so representing a powerful early warning system. [1] J. M. López-Higuera, L. R. Cobo, A. Q. Incera, A. Cobo, "Fiber Optic Sensors in Structural Health Monitoring", Journal of Lightwave Technology, 29, 2011. [2] L. Zeni, L. Picarelli, B. Avolio, A. Coscetta, R. Papa, G. Zeni, C. Di Maio, R. Vassallo, A. Minardo, "Brillouin Optical Time Domain Analysis for Geotechnical Monitoring", Journal of Rock Mechanics and Geotechnical Engineering, 7, 2015 [3] A. Minardo, G. Porcaro, D. Giannetta, R. Bernini, L. Zeni, "Real-time monitoring of railway traffic using slope-assisted Brillouin distributed sensors", Applied Optics, 52, 2013 [4] A. Minardo, A. Coscetta, S. Pirozzi, R. Bernini, L. Zeni, "Experimental modal analysis of an aluminum rectangular plate by use of the slope-assisted BOTDA method", Smart Materials & Structures, 22, 2014

Adaptive behaviors in multi-agent source localization using passive sensing.

PubMed

Shaukat, Mansoor; Chitre, Mandar

2016-12-01

In this paper, the role of adaptive group cohesion in a cooperative multi-agent source localization problem is investigated. A distributed source localization algorithm is presented for a homogeneous team of simple agents. An agent uses a single sensor to sense the gradient and two sensors to sense its neighbors. The algorithm is a set of individualistic and social behaviors where the individualistic behavior is as simple as an agent keeping its previous heading and is not self-sufficient in localizing the source. Source localization is achieved as an emergent property through agent's adaptive interactions with the neighbors and the environment. Given a single agent is incapable of localizing the source, maintaining team connectivity at all times is crucial. Two simple temporal sampling behaviors, intensity-based-adaptation and connectivity-based-adaptation, ensure an efficient localization strategy with minimal agent breakaways. The agent behaviors are simultaneously optimized using a two phase evolutionary optimization process. The optimized behaviors are estimated with analytical models and the resulting collective behavior is validated against the agent's sensor and actuator noise, strong multi-path interference due to environment variability, initialization distance sensitivity and loss of source signal.

Decentralized cooperative TOA/AOA target tracking for hierarchical wireless sensor networks.

PubMed

Chen, Ying-Chih; Wen, Chih-Yu

2012-11-08

This paper proposes a distributed method for cooperative target tracking in hierarchical wireless sensor networks. The concept of leader-based information processing is conducted to achieve object positioning, considering a cluster-based network topology. Random timers and local information are applied to adaptively select a sub-cluster for the localization task. The proposed energy-efficient tracking algorithm allows each sub-cluster member to locally estimate the target position with a Bayesian filtering framework and a neural networking model, and further performs estimation fusion in the leader node with the covariance intersection algorithm. This paper evaluates the merits and trade-offs of the protocol design towards developing more efficient and practical algorithms for object position estimation.

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

PubMed

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

2010-01-01

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

Improving the durability of the optical fiber sensor based on strain transfer analysis

NASA Astrophysics Data System (ADS)

Wang, Huaping; Jiang, Lizhong; Xiang, Ping

2018-05-01

To realize the reliable and long-term strain detection, the durability of optical fiber sensors has attracted more and more attention. The packaging technique has been considered as an effective method, which can enhance the survival ratios of optical fiber sensors to resist the harsh construction and service environment in civil engineering. To monitor the internal strain of structures, the embedded installation is adopted. Due to the different material properties between host material and the protective layer, the monitored structure embedded with sensors can be regarded as a typical model containing inclusions. Interfacial characteristic between the sensor and host material exists obviously, and the contacted interface is prone to debonding failure induced by the large interfacial shear stress. To recognize the local interfacial debonding damage and extend the effective life cycle of the embedded sensor, strain transfer analysis of a general three-layered sensing model is conducted to investigate the failure mechanism. The perturbation of the embedded sensor on the local strain field of host material is discussed. Based on the theoretical analysis, the distribution of the interfacial shear stress along the sensing length is characterized and adopted for the diagnosis of local interfacial debonding, and the sensitive parameters influencing the interfacial shear stress are also investigated. The research in this paper explores the interfacial debonding failure mechanism of embedded sensors based on the strain transfer analysis and provides theoretical basis for enhancing the interfacial bonding properties and improving the durability of embedded optical fiber sensors.

Printed strain sensors for early damage detection in engineering structures

NASA Astrophysics Data System (ADS)

Zymelka, Daniel; Yamashita, Takahiro; Takamatsu, Seiichi; Itoh, Toshihiro; Kobayashi, Takeshi

2018-05-01

In this paper, we demonstrate the analysis of strain measurements recorded using a screen-printed sensors array bonded to a metal plate and subjected to high strains. The analysis was intended to evaluate the capabilities of the printed strain sensors to detect abnormal strain distribution before actual defects (cracks) in the analyzed structures appear. The results demonstrate that the developed device can accurately localize the enhanced strains at the very early stage of crack formation. The promising performance and low fabrication cost confirm the potential suitability of the printed strain sensors for applications within the framework of structural health monitoring (SHM).

An Integrated Wireless Wearable Sensor System for Posture Recognition and Indoor Localization.

PubMed

Huang, Jian; Yu, Xiaoqiang; Wang, Yuan; Xiao, Xiling

2016-10-31

In order to provide better monitoring for the elderly or patients, we developed an integrated wireless wearable sensor system that can realize posture recognition and indoor localization in real time. Five designed sensor nodes which are respectively fixed on lower limbs and a standard Kalman filter are used to acquire basic attitude data. After the attitude angles of five body segments (two thighs, two shanks and the waist) are obtained, the pitch angles of the left thigh and waist are used to realize posture recognition. Based on all these attitude angles of body segments, we can also calculate the coordinates of six lower limb joints (two hip joints, two knee joints and two ankle joints). Then, a novel relative localization algorithm based on step length is proposed to realize the indoor localization of the user. Several sparsely distributed active Radio Frequency Identification (RFID) tags are used to correct the accumulative error in the relative localization algorithm and a set-membership filter is applied to realize the data fusion. The experimental results verify the effectiveness of the proposed algorithms.

An Integrated Wireless Wearable Sensor System for Posture Recognition and Indoor Localization

PubMed Central

Huang, Jian; Yu, Xiaoqiang; Wang, Yuan; Xiao, Xiling

2016-01-01

In order to provide better monitoring for the elderly or patients, we developed an integrated wireless wearable sensor system that can realize posture recognition and indoor localization in real time. Five designed sensor nodes which are respectively fixed on lower limbs and a standard Kalman filter are used to acquire basic attitude data. After the attitude angles of five body segments (two thighs, two shanks and the waist) are obtained, the pitch angles of the left thigh and waist are used to realize posture recognition. Based on all these attitude angles of body segments, we can also calculate the coordinates of six lower limb joints (two hip joints, two knee joints and two ankle joints). Then, a novel relative localization algorithm based on step length is proposed to realize the indoor localization of the user. Several sparsely distributed active Radio Frequency Identification (RFID) tags are used to correct the accumulative error in the relative localization algorithm and a set-membership filter is applied to realize the data fusion. The experimental results verify the effectiveness of the proposed algorithms. PMID:27809230

Direct measurements of local bed shear stress in the presence of pressure gradients

NASA Astrophysics Data System (ADS)

Pujara, Nimish; Liu, Philip L.-F.

2014-07-01

This paper describes the development of a shear plate sensor capable of directly measuring the local mean bed shear stress in small-scale and large-scale laboratory flumes. The sensor is capable of measuring bed shear stress in the range 200 Pa with an accuracy up to 1 %. Its size, 43 mm in the flow direction, is designed to be small enough to give spatially local measurements, and its bandwidth, 75 Hz, is high enough to resolve time-varying forcing. Typically, shear plate sensors are restricted to use in zero pressure gradient flows because secondary forces on the edge of the shear plate caused by pressure gradients can introduce large errors. However, by analysis of the pressure distribution at the edges of the shear plate in mild pressure gradients, we introduce a new methodology for correcting for the pressure gradient force. The developed sensor includes pressure tappings to measure the pressure gradient in the flow, and the methodology for correction is applied to obtain accurate measurements of bed shear stress under solitary waves in a small-scale wave flume. The sensor is also validated by measurements in a turbulent flat plate boundary layer in open channel flow.

Communal Cooperation in Sensor Networks for Situation Management

NASA Technical Reports Server (NTRS)

Jones, Kennie H.; Lodding, Kenneth N.; Olariu, Stephan; Wilson, Larry; Xin,Chunsheng

2006-01-01

Situation management is a rapidly evolving science where managed sources are processed as realtime streams of events and fused in a way that maximizes comprehension, thus enabling better decisions for action. Sensor networks provide a new technology that promises ubiquitous input and action throughout an environment, which can substantially improve information available to the process. Here we describe a NASA program that requires improvements in sensor networks and situation management. We present an approach for massively deployed sensor networks that does not rely on centralized control but is founded in lessons learned from the way biological ecosystems are organized. In this approach, fully distributed data aggregation and integration can be performed in a scalable fashion where individual motes operate based on local information, making local decisions that achieve globally-meaningful results. This exemplifies the robust, fault-tolerant infrastructure required for successful situation management systems.

Information-theoretical noninvasive damage detection in bridge structures

NASA Astrophysics Data System (ADS)

Sudu Ambegedara, Amila; Sun, Jie; Janoyan, Kerop; Bollt, Erik

2016-11-01

Damage detection of mechanical structures such as bridges is an important research problem in civil engineering. Using spatially distributed sensor time series data collected from a recent experiment on a local bridge in Upper State New York, we study noninvasive damage detection using information-theoretical methods. Several findings are in order. First, the time series data, which represent accelerations measured at the sensors, more closely follow Laplace distribution than normal distribution, allowing us to develop parameter estimators for various information-theoretic measures such as entropy and mutual information. Second, as damage is introduced by the removal of bolts of the first diaphragm connection, the interaction between spatially nearby sensors as measured by mutual information becomes weaker, suggesting that the bridge is "loosened." Finally, using a proposed optimal mutual information interaction procedure to prune away indirect interactions, we found that the primary direction of interaction or influence aligns with the traffic direction on the bridge even after damaging the bridge.

Decision Fusion with Channel Errors in Distributed Decode-Then-Fuse Sensor Networks

PubMed Central

Yan, Yongsheng; Wang, Haiyan; Shen, Xiaohong; Zhong, Xionghu

2015-01-01

Decision fusion for distributed detection in sensor networks under non-ideal channels is investigated in this paper. Usually, the local decisions are transmitted to the fusion center (FC) and decoded, and a fusion rule is then applied to achieve a global decision. We propose an optimal likelihood ratio test (LRT)-based fusion rule to take the uncertainty of the decoded binary data due to modulation, reception mode and communication channel into account. The average bit error rate (BER) is employed to characterize such an uncertainty. Further, the detection performance is analyzed under both non-identical and identical local detection performance indices. In addition, the performance of the proposed method is compared with the existing optimal and suboptimal LRT fusion rules. The results show that the proposed fusion rule is more robust compared to these existing ones. PMID:26251908

Concepts and Development of Bio-Inspired Distributed Embedded Wired/Wireless Sensor Array Architectures for Acoustic Wave Sensing in Integrated Aerospace Vehicles

NASA Technical Reports Server (NTRS)

Ghoshal, Anindya; Prosser, William H.; Kirikera, Goutham; Schulz, Mark J.; Hughes, Derke J.; Orisamolu, Wally

2003-01-01

This paper discusses the modeling of acoustic emissions in plate structures and their sensing by embedded or surface bonded piezoelectric sensor arrays. Three different modeling efforts for acoustic emission (AE) wave generation and propagation are discussed briefly along with their advantages and disadvantages. Continuous sensors placed at right angles on a plate are being discussed as a new approach to measure and locate the source of acoustic waves. Evolutionary novel signal processing algorithms and bio-inspired distributed sensor array systems are used on large structures and integrated aerospace vehicles for AE source localization and preliminary results are presented. These systems allow for a great reduction in the amount of data that needs to be processed and also reduce the chances of false alarms from ambient noises. It is envisioned that these biomimetic sensor arrays and signal processing techniques will be useful for both wireless and wired sensor arrays for real time health monitoring of large integrated aerospace vehicles and earth fixed civil structures. The sensor array architectures can also be used with other types of sensors and for other applications.

Enhanced response and sensitivity of self-corrugated graphene sensors with anisotropic charge distribution

PubMed Central

Yol Jeong, Seung; Jeong, Sooyeon; Won Lee, Sang; Tae Kim, Sung; Kim, Daeho; Jin Jeong, Hee; Tark Han, Joong; Baeg, Kang-Jun; Yang, Sunhye; Seok Jeong, Mun; Lee, Geon-Woong

2015-01-01

We introduce a high-performance molecular sensor using self-corrugated chemically modified graphene as a three dimensional (3D) structure that indicates anisotropic charge distribution. This is capable of room-temperature operation, and, in particular, exhibiting high sensitivity and reversible fast response with equilibrium region. The morphology consists of periodic, “cratered” arrays that can be formed by condensation and evaporation of graphene oxide (GO) solution on interdigitated electrodes. Subsequent hydrazine reduction, the corrugated edge area of the graphene layers have a high electric potential compared with flat graphene films. This local accumulation of electrons interacts with a large number of gas molecules. The sensitivity of 3D-graphene sensors significantly increases in the atmosphere of NO2 gas. The intriguing structures have several advantages for straightforward fabrication on patterned substrates, high-performance graphene sensors without post-annealing process. PMID:26053892

Electric fish as natural models for technical sensor systems

NASA Astrophysics Data System (ADS)

von der Emde, Gerhard; Bousack, Herbert; Huck, Christina; Mayekar, Kavita; Pabst, Michael; Zhang, Yi

2009-05-01

Instead of vision, many animals use alternative senses for object detection. Weakly electric fish employ "active electrolocation", during which they discharge an electric organ emitting electrical current pulses (electric organ discharges, EOD). Local EODs are sensed by electroreceptors in the fish's skin, which respond to changes of the signal caused by nearby objects. Fish can gain information about attributes of an object, such as size, shape, distance, and complex impedance. When close to the fish, each object projects an 'electric image' onto the fish's skin. In order to get information about an object, the fish has to analyze the object's electric image by sampling its voltage distribution with the electroreceptors. We now know a great deal about the mechanisms the fish use to gain information about objects in their environment. Inspired by the remarkable capabilities of weakly electric fish in detecting and recognizing objects with their electric sense, we are designing technical sensor systems that can solve similar sensing problems. We applied the principles of active electrolocation to devices that produce electrical current pulses in water and simultaneously sense local current densities. Depending on the specific task, sensors can be designed which detect an object, localize it in space, determine its distance, and measure certain object properties such as material properties, thickness, or material faults. We present first experiments and FEM simulations on the optimal sensor arrangement regarding the sensor requirements e. g. localization of objects or distance measurements. Different methods of the sensor read-out and signal processing are compared.

Fire Source Localization Based on Distributed Temperature Sensing by a Dual-Line Optical Fiber System.

PubMed

Sun, Miao; Tang, Yuquan; Yang, Shuang; Li, Jun; Sigrist, Markus W; Dong, Fengzhong

2016-06-06

We propose a method for localizing a fire source using an optical fiber distributed temperature sensor system. A section of two parallel optical fibers employed as the sensing element is installed near the ceiling of a closed room in which the fire source is located. By measuring the temperature of hot air flows, the problem of three-dimensional fire source localization is transformed to two dimensions. The method of the source location is verified with experiments using burning alcohol as fire source, and it is demonstrated that the method represents a robust and reliable technique for localizing a fire source also for long sensing ranges.

Prototyping the E-ELT M1 local control system communication infrastructure

NASA Astrophysics Data System (ADS)

Argomedo, J.; Kornweibel, N.; Grudzien, T.; Dimmler, M.; Andolfato, L.; Barriga, P.

2016-08-01

The primary mirror of the E-ELT is composed of 798 hexagonal segments of about 1.45 meters across. Each segment can be moved in piston and tip-tilt using three position actuators. Inductive edge sensors are used to provide feedback for global reconstruction of the mirror shape. The E-ELT M1 Local Control System will provide a deterministic infrastructure for collecting edge sensor and actuators readings and distribute the new position actuators references while at the same time providing failure detection, isolation and notification, synchronization, monitoring and configuration management. The present paper describes the prototyping activities carried out to verify the feasibility of the E-ELT M1 local control system communication architecture design and assess its performance and potential limitations.

Supersonic projectile models for asynchronous shooter localization

NASA Astrophysics Data System (ADS)

Kozick, Richard J.; Whipps, Gene T.; Ash, Joshua N.

2011-06-01

In this work we consider the localization of a gunshot using a distributed sensor network measuring time differences of arrival between a firearm's muzzle blast and the shockwave induced by a supersonic bullet. This so-called MB-SW approach is desirable because time synchronization is not required between the sensors, however it suffers from increased computational complexity and requires knowledge of the bullet's velocity at all points along its trajectory. While the actual velocity profile of a particular gunshot is unknown, one may use a parameterized model for the velocity profile and simultaneously fit the model and localize the shooter. In this paper we study efficient solutions for the localization problem and identify deceleration models that trade off localization accuracy and computational complexity. We also develop a statistical analysis that includes bias due to mismatch between the true and actual deceleration models and covariance due to additive noise.

Development of two-dimensional interdigitated center of pressure sensor

NASA Astrophysics Data System (ADS)

Yoo, Byungseok; Pines, Darryll J.

2017-12-01

This paper presents the development of a two-dimensional (2D) flexible patch sensor to detect and monitor the center of pressure (CoP) location and the total magnitude of a spatially distributed pressure to the specific surface areas of engineering structures. The CoP sensor with the contact mode induced by a pressure distribution was formulated by force sensitive resistor technology and was mainly composed of a thin conductive polymer layer, adhesive spacers, and two interdigitated patterned electrode films with unique sensing aperture shadings. By properly mapping the interdigitated electrode patterns to the top and bottom surfaces of the conductive polymer, the proposed sensor ideally enables to measure an overall applied pressure level and its centroid location within a predetermined sensing region in real-time. The CoP sensor containing 36 sensing sections within a dimension of around 3 × 3 inches was prototyped and experimentally investigated to verify its capability to identify the CoP location and magnitude due to the presence of a permanent magnet-based local pressure distribution. Only five electric wires connected to the CoP sensor to inspect the pressure-sensing positions of 36 segments. The evaluation results of the measured sensor data demonstrate good agreements with the actual test parameters such as the total pressure and its centroid position with about 5% locational error. However, to provide accurate information on the overall pressure range, the compensation factors must be determined and applied to the individual sensing sections of the sensor.

An Event-Based Approach to Distributed Diagnosis of Continuous Systems

NASA Technical Reports Server (NTRS)

Daigle, Matthew; Roychoudhurry, Indranil; Biswas, Gautam; Koutsoukos, Xenofon

2010-01-01

Distributed fault diagnosis solutions are becoming necessary due to the complexity of modern engineering systems, and the advent of smart sensors and computing elements. This paper presents a novel event-based approach for distributed diagnosis of abrupt parametric faults in continuous systems, based on a qualitative abstraction of measurement deviations from the nominal behavior. We systematically derive dynamic fault signatures expressed as event-based fault models. We develop a distributed diagnoser design algorithm that uses these models for designing local event-based diagnosers based on global diagnosability analysis. The local diagnosers each generate globally correct diagnosis results locally, without a centralized coordinator, and by communicating a minimal number of measurements between themselves. The proposed approach is applied to a multi-tank system, and results demonstrate a marked improvement in scalability compared to a centralized approach.

Community Seismic Network

NASA Astrophysics Data System (ADS)

Clayton, R. W.; Kohler, M. D.; Massari, A.; Heaton, T. H.; Guy, R.; Chandy, M.; Bunn, J.; Strand, L.

2014-12-01

The CSN is now in its 3rdyear of operation and has expanded to 400 stations in the Los Angeles region. The goal of the network is to produce a map of strong shaking immediately following a major earthquake as a proxy for damage and a guide for first responders. We have also instrumented a number of buildings with the goal of determining the state of health of these structures before and after they have been shaken. In one 15-story structure, our sensors distributed two per floor, and show body waves propagating in the structure after a moderate local earthquake (M4.4 in Encino, CA). Sensors in a 52-story structure, which we plan to instrument with two sensors per floor as well, show the modes of the building (see Figure) down to the fundamental mode at 5 sec due to a M5.1 earthquake in La Habra, CA. The CSN utilizes a number of technologies that will likely be important in building robust low-cost networks. These include: Distributed computing - the sensors themselves are smart-sensors that perform the basic detection and size estimation in the onboard computers and send the results immediately (without packetization latency) to the central facility. Cloud computing - the central facility is housed in the cloud, which means it is more robust than a local site, and has expandable computing resources available so that it can operate with minimal resources during quiet times but still be able to exploit an very large computing facility during an earthquake. Low-cost/low-maintenance sensors - the MEM sensors are capable of staying onscale to +/- 2g, and can measure events in the Los Angeles Basin a low as magnitude 3.

Absolute vs. relative error characterization of electromagnetic tracking accuracy

NASA Astrophysics Data System (ADS)

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

2010-02-01

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

Distributed policy based access to networked heterogeneous ISR data sources

NASA Astrophysics Data System (ADS)

Bent, G.; Vyvyan, D.; Wood, David; Zerfos, Petros; Calo, Seraphin

2010-04-01

Within a coalition environment, ad hoc Communities of Interest (CoI's) come together, perhaps for only a short time, with different sensors, sensor platforms, data fusion elements, and networks to conduct a task (or set of tasks) with different coalition members taking different roles. In such a coalition, each organization will have its own inherent restrictions on how it will interact with the others. These are usually stated as a set of policies, including security and privacy policies. The capability that we want to enable for a coalition operation is to provide access to information from any coalition partner in conformance with the policies of all. One of the challenges in supporting such ad-hoc coalition operations is that of providing efficient access to distributed sources of data, where the applications requiring the data do not have knowledge of the location of the data within the network. To address this challenge the International Technology Alliance (ITA) program has been developing the concept of a Dynamic Distributed Federated Database (DDFD), also know as a Gaian Database. This type of database provides a means for accessing data across a network of distributed heterogeneous data sources where access to the information is controlled by a mixture of local and global policies. We describe how a network of disparate ISR elements can be expressed as a DDFD and how this approach enables sensor and other information sources to be discovered autonomously or semi-autonomously and/or combined, fused formally defined local and global policies.

Analysis of Energy Consumption for Ad Hoc Wireless Sensor Networks Using a Bit-Meter-per-Joule Metric

NASA Astrophysics Data System (ADS)

Gao, J. L.

2002-04-01

In this article, we present a system-level characterization of the energy consumption for sensor network application scenarios. We compute a power efficiency metric -- average watt-per-meter -- for each radio transmission and extend this local metric to find the global energy consumption. This analysis shows how overall energy consumption varies with transceiver characteristics, node density, data traffic distribution, and base-station location.

Ultrafast Radiation Detection by Modulation of an Optical Probe Beam

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

Vernon, S P; Lowry, M E

2006-02-22

We describe a new class of radiation sensor that utilizes optical interferometry to measure radiation-induced changes in the optical refractive index of a semiconductor sensor medium. Radiation absorption in the sensor material produces a transient, non-equilibrium, electron-hole pair distribution that locally modifies the complex, optical refractive index of the sensor medium. Changes in the real (imaginary) part of the local refractive index produce a differential phase shift (absorption) of an optical probe used to interrogate the sensor material. In contrast to conventional radiation detectors where signal levels are proportional to the incident energy, signal levels in these optical sensors aremore » proportional to the incident radiation energy flux. This allows for reduction of the sensor form factor with no degradation in detection sensitivity. Furthermore, since the radiation induced, non-equilibrium electron-hole pair distribution is effectively measured ''in place'' there is no requirement to spatially separate and collect the generated charges; consequently, the sensor risetime is of the order of the hot-electron thermalization time {le} 10 fs and the duration of the index perturbation is determined by the carrier recombination time which is of order {approx} 600 fs in, direct-bandgap semiconductors, with a high density of recombination defects; consequently, the optical sensors can be engineered with sub-ps temporal response. A series of detectors were designed, and incorporated into Mach Zehnder and Fabry-Perot interferometer-based detection systems: proof of concept, lower detection sensitivity, Mach-Zehnder detectors were characterized at beamline 6.3 at SSRL; three generations of high sensitivity single element and imaging Fabry-Perot detectors were measured at the LLNL Europa facility. Our results indicate that this technology can be used to provide x-ray detectors and x-ray imaging systems with single x-ray sensitivity and S/N {approx} 30 at x-ray energies {approx} 10 keV.« less

Multi-source feature extraction and target recognition in wireless sensor networks based on adaptive distributed wavelet compression algorithms

NASA Astrophysics Data System (ADS)

Hortos, William S.

2008-04-01

Proposed distributed wavelet-based algorithms are a means to compress sensor data received at the nodes forming a wireless sensor network (WSN) by exchanging information between neighboring sensor nodes. Local collaboration among nodes compacts the measurements, yielding a reduced fused set with equivalent information at far fewer nodes. Nodes may be equipped with multiple sensor types, each capable of sensing distinct phenomena: thermal, humidity, chemical, voltage, or image signals with low or no frequency content as well as audio, seismic or video signals within defined frequency ranges. Compression of the multi-source data through wavelet-based methods, distributed at active nodes, reduces downstream processing and storage requirements along the paths to sink nodes; it also enables noise suppression and more energy-efficient query routing within the WSN. Targets are first detected by the multiple sensors; then wavelet compression and data fusion are applied to the target returns, followed by feature extraction from the reduced data; feature data are input to target recognition/classification routines; targets are tracked during their sojourns through the area monitored by the WSN. Algorithms to perform these tasks are implemented in a distributed manner, based on a partition of the WSN into clusters of nodes. In this work, a scheme of collaborative processing is applied for hierarchical data aggregation and decorrelation, based on the sensor data itself and any redundant information, enabled by a distributed, in-cluster wavelet transform with lifting that allows multiple levels of resolution. The wavelet-based compression algorithm significantly decreases RF bandwidth and other resource use in target processing tasks. Following wavelet compression, features are extracted. The objective of feature extraction is to maximize the probabilities of correct target classification based on multi-source sensor measurements, while minimizing the resource expenditures at participating nodes. Therefore, the feature-extraction method based on the Haar DWT is presented that employs a maximum-entropy measure to determine significant wavelet coefficients. Features are formed by calculating the energy of coefficients grouped around the competing clusters. A DWT-based feature extraction algorithm used for vehicle classification in WSNs can be enhanced by an added rule for selecting the optimal number of resolution levels to improve the correct classification rate and reduce energy consumption expended in local algorithm computations. Published field trial data for vehicular ground targets, measured with multiple sensor types, are used to evaluate the wavelet-assisted algorithms. Extracted features are used in established target recognition routines, e.g., the Bayesian minimum-error-rate classifier, to compare the effects on the classification performance of the wavelet compression. Simulations of feature sets and recognition routines at different resolution levels in target scenarios indicate the impact on classification rates, while formulas are provided to estimate reduction in resource use due to distributed compression.

Distributed Tracking in Distributed Sensor Networks

DTIC Science & Technology

1988-05-26

Glocal Track 6-17 6-12: Case II: Initial Glocal Track 6-18 6-13: Local Tracking Results with Multiple Model Approach 6-19 6-14: Model Probability History...3480.0- 2290.0e iee. onee -5800 -4600.8 -3400.8 -2208.8 -1886 X (Mi) Figure 6-11: Case 1: Initial Glocal Track 6-17 460. 420. 38 . 3488.9 1st 3498.9

Biomimetic Models for An Ecological Approach to Massively-Deployed Sensor Networks

NASA Technical Reports Server (NTRS)

Jones, Kennie H.; Lodding, Kenneth N.; Olariu, Stephan; Wilson, Larry; Xin, Chunsheng

2005-01-01

Promises of ubiquitous control of the physical environment by massively-deployed wireless sensor networks open avenues for new applications that will redefine the way we live and work. Due to small size and low cost of sensor devices, visionaries promise systems enabled by deployment of massive numbers of sensors ubiquitous throughout our environment working in concert. Recent research has concentrated on developing techniques for performing relatively simple tasks with minimal energy expense, assuming some form of centralized control. Unfortunately, centralized control is not conducive to parallel activities and does not scale to massive size networks. Execution of simple tasks in sparse networks will not lead to the sophisticated applications predicted. We propose a new way of looking at massively-deployed sensor networks, motivated by lessons learned from the way biological ecosystems are organized. We demonstrate that in such a model, fully distributed data aggregation can be performed in a scalable fashion in massively deployed sensor networks, where motes operate on local information, making local decisions that are aggregated across the network to achieve globally-meaningful effects. We show that such architectures may be used to facilitate communication and synchronization in a fault-tolerant manner, while balancing workload and required energy expenditure throughout the network.

Monthly AOD maps combining strengths of remote sensing products

NASA Astrophysics Data System (ADS)

Kinne, Stefan

2010-05-01

The mid-visible aerosol optical depth (AOD) is the most prominent property to quantify aerosol amount the atmospheric column. Almost all aerosol retrievals of satellite sensors provide estimates for this property, however, often with limited success. As sensors differ in capabilities individual retrievals have local and regional strengths and weaknesses. Focusing on individual retrieval strengths a satellite based AOD composite has been constructed. Hereby, every retrieval performance has been assessed in statistical comparisons to ground-based sun-photometry, which provide highly accurate references though only at few globally distributed monitoring sites. Based on these comparisons, which consider bias as well as spatial patterns and seasonality, the regionally best performing satellite AOD products are combined. The resulting remote sensing AOD composite provide a general reference for the spatial and temporal AOD distribution on an (almost) global basis - solely tied to sensor data.

Optical fiber sensors-based temperature distribution measurement in ex vivo radiofrequency ablation with submillimeter resolution.

PubMed

Macchi, Edoardo Gino; Tosi, Daniele; Braschi, Giovanni; Gallati, Mario; Cigada, Alfredo; Busca, Giorgio; Lewis, Elfed

2014-01-01

Radiofrequency thermal ablation (RFTA) induces a high-temperature field in a biological tissue having steep spatial (up to 6°C∕mm) and temporal (up to 1°C∕s) gradients. Applied in cancer care, RFTA produces a localized heating, cytotoxic for tumor cells, and is able to treat tumors with sizes up to 3 to 5 cm in diameter. The online measurement of temperature distribution at the RFTA point of care has been previously carried out with miniature thermocouples and optical fiber sensors, which exhibit problems of size, alteration of RFTA pattern, hysteresis, and sensor density worse than 1 sensor∕cm. In this work, we apply a distributed temperature sensor (DTS) with a submillimeter spatial resolution for the monitoring of RFTA in porcine liver tissue. The DTS demodulates the chaotic Rayleigh backscattering pattern with an interferometric setup to obtain the real-time temperature distribution. A measurement chamber has been set up with the fiber crossing the tissue along different diameters. Several experiments have been carried out measuring the space-time evolution of temperature during RFTA. The present work showcases the temperature monitoring in RFTA with an unprecedented spatial resolution and is exportable to in vivo measurement; the acquired data can be particularly useful for the validation of RFTA computational models.

In-flight fiber optic acoustic emission sensor (FAESense) system for the real time detection, localization, and classification of damage in composite aircraft structures

NASA Astrophysics Data System (ADS)

Mendoza, Edgar; Prohaska, John; Kempen, Connie; Esterkin, Yan; Sun, Sunjian

2013-05-01

Acoustic emission sensing is a leading structural health monitoring technique use for the early warning detection of structural damage associated with impacts, cracks, fracture, and delaminations in advanced materials. Current AE systems based on electronic PZT transducers suffer from various limitations that prevent its wide dynamic use in practical avionics and aerospace applications where weight, size and power are critical for operation. This paper describes progress towards the development of a wireless in-flight distributed fiber optic acoustic emission monitoring system (FAESense™) suitable for the onboard-unattended detection, localization, and classification of damage in avionics and aerospace structures. Fiber optic AE sensors offer significant advantages over its counterpart electronic AE sensors by using a high-density array of micron-size AE transducers distributed and multiplex over long lengths of a standard single mode optical fiber. Immediate SHM applications are found in commercial and military aircraft, helicopters, spacecraft, wind mil turbine blades, and in next generation weapon systems, as well as in the petrochemical and aerospace industries, civil structures, power utilities, and a wide spectrum of other applications.

Aerodynamic parameters from distributed heterogeneous CNT hair sensors with a feedforward neural network.

PubMed

Magar, Kaman Thapa; Reich, Gregory W; Kondash, Corey; Slinker, Keith; Pankonien, Alexander M; Baur, Jeffery W; Smyers, Brian

2016-11-10

Distributed arrays of artificial hair sensors have bio-like sensing capabilities to obtain spatial and temporal surface flow information which is an important aspect of an effective fly-by-feel system. The spatiotemporal surface flow measurement enables further exploration of additional flow features such as flow stagnation, separation, and reattachment points. Due to their inherent robustness and fault tolerant capability, distributed arrays of hair sensors are well equipped to assess the aerodynamic and flow states in adverse conditions. In this paper, a local flow measurement from an array of artificial hair sensors in a wind tunnel experiment is used with a feedforward artificial neural network to predict aerodynamic parameters such as lift coefficient, moment coefficient, free-stream velocity, and angle of attack on an airfoil. We find the prediction error within 6% and 10% for lift and moment coefficients. The error for free-stream velocity and angle of attack were within 0.12 mph and 0.37 degrees. Knowledge of these parameters are key to finding the real time forces and moments which paves the way for effective control design to increase flight agility, stability, and maneuverability.

Embedded Acoustic Sensor Array for Engine Fan Noise Source Diagnostic Test: Feasibility of Noise Telemetry via Wireless Smart Sensors

NASA Technical Reports Server (NTRS)

Zaman, Afroz; Bauch, Matthew; Raible, Daniel

2011-01-01

Aircraft engines have evolved into a highly complex system to meet ever-increasing demands. The evolution of engine technologies has primarily been driven by fuel efficiency, reliability, as well as engine noise concerns. One of the sources of engine noise is pressure fluctuations that are induced on the stator vanes. These local pressure fluctuations, once produced, propagate and coalesce with the pressure waves originating elsewhere on the stator to form a spinning pressure pattern. Depending on the duct geometry, air flow, and frequency of fluctuations, these spinning pressure patterns are self-sustaining and result in noise which eventually radiate to the far-field from engine. To investigate the nature of vane pressure fluctuations and the resulting engine noise, unsteady pressure signatures from an array of embedded acoustic sensors are recorded as a part of vane noise source diagnostics. Output time signatures from these sensors are routed to a control and data processing station adding complexity to the system and cable loss to the measured signal. "Smart" wireless sensors have data processing capability at the sensor locations which further increases the potential of wireless sensors. Smart sensors can process measured data locally and transmit only the important information through wireless communication. The aim of this wireless noise telemetry task was to demonstrate a single acoustic sensor wireless link for unsteady pressure measurement, and thus, establish the feasibility of distributed smart sensors scheme for aircraft engine vane surface unsteady pressure data transmission and characterization.

Time-optimum packet scheduling for many-to-one routing in wireless sensor networks

USGS Publications Warehouse

Song, W.-Z.; Yuan, F.; LaHusen, R.; Shirazi, B.

2007-01-01

This paper studies the wireless sensor networks (WSN) application scenario with periodical traffic from all sensors to a sink. We present a time-optimum and energy-efficient packet scheduling algorithm and its distributed implementation. We first give a general many-to-one packet scheduling algorithm for wireless networks, and then prove that it is time-optimum and costs [image omitted], N(u0)-1) time slots, assuming each node reports one unit of data in each round. Here [image omitted] is the total number of sensors, while [image omitted] denotes the number of sensors in a sink's largest branch subtree. With a few adjustments, we then show that our algorithm also achieves time-optimum scheduling in heterogeneous scenarios, where each sensor reports a heterogeneous amount of data in each round. Then we give a distributed implementation to let each node calculate its duty-cycle locally and maximize efficiency globally. In this packet-scheduling algorithm, each node goes to sleep whenever it is not transceiving, so that the energy waste of idle listening is also mitigated. Finally, simulations are conducted to evaluate network performance using the Qualnet simulator. Among other contributions, our study also identifies the maximum reporting frequency that a deployed sensor network can handle.

Sensor Network Localization by Eigenvector Synchronization Over the Euclidean Group

PubMed Central

CUCURINGU, MIHAI; LIPMAN, YARON; SINGER, AMIT

2013-01-01

We present a new approach to localization of sensors from noisy measurements of a subset of their Euclidean distances. Our algorithm starts by finding, embedding, and aligning uniquely realizable subsets of neighboring sensors called patches. In the noise-free case, each patch agrees with its global positioning up to an unknown rigid motion of translation, rotation, and possibly reflection. The reflections and rotations are estimated using the recently developed eigenvector synchronization algorithm, while the translations are estimated by solving an overdetermined linear system. The algorithm is scalable as the number of nodes increases and can be implemented in a distributed fashion. Extensive numerical experiments show that it compares favorably to other existing algorithms in terms of robustness to noise, sparse connectivity, and running time. While our approach is applicable to higher dimensions, in the current article, we focus on the two-dimensional case. PMID:23946700

Study on Finite Element Model Updating in Highway Bridge Static Loading Test Using Spatially-Distributed Optical Fiber Sensors

PubMed Central

Wu, Bitao; Lu, Huaxi; Chen, Bo; Gao, Zhicheng

2017-01-01

A finite model updating method that combines dynamic-static long-gauge strain responses is proposed for highway bridge static loading tests. For this method, the objective function consisting of static long-gauge stains and the first order modal macro-strain parameter (frequency) is established, wherein the local bending stiffness, density and boundary conditions of the structures are selected as the design variables. The relationship between the macro-strain and local element stiffness was studied first. It is revealed that the macro-strain is inversely proportional to the local stiffness covered by the long-gauge strain sensor. This corresponding relation is important for the modification of the local stiffness based on the macro-strain. The local and global parameters can be simultaneously updated. Then, a series of numerical simulation and experiments were conducted to verify the effectiveness of the proposed method. The results show that the static deformation, macro-strain and macro-strain modal can be predicted well by using the proposed updating model. PMID:28753912

Study on Finite Element Model Updating in Highway Bridge Static Loading Test Using Spatially-Distributed Optical Fiber Sensors.

PubMed

Wu, Bitao; Lu, Huaxi; Chen, Bo; Gao, Zhicheng

2017-07-19

A finite model updating method that combines dynamic-static long-gauge strain responses is proposed for highway bridge static loading tests. For this method, the objective function consisting of static long-gauge stains and the first order modal macro-strain parameter (frequency) is established, wherein the local bending stiffness, density and boundary conditions of the structures are selected as the design variables. The relationship between the macro-strain and local element stiffness was studied first. It is revealed that the macro-strain is inversely proportional to the local stiffness covered by the long-gauge strain sensor. This corresponding relation is important for the modification of the local stiffness based on the macro-strain. The local and global parameters can be simultaneously updated. Then, a series of numerical simulation and experiments were conducted to verify the effectiveness of the proposed method. The results show that the static deformation, macro-strain and macro-strain modal can be predicted well by using the proposed updating model.

Analysis of skin tissues spatial fluorescence distribution by the Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Y Churmakov, D.; Meglinski, I. V.; Piletsky, S. A.; Greenhalgh, D. A.

2003-07-01

A novel Monte Carlo technique of simulation of spatial fluorescence distribution within the human skin is presented. The computational model of skin takes into account the spatial distribution of fluorophores, which would arise due to the structure of collagen fibres, compared to the epidermis and stratum corneum where the distribution of fluorophores is assumed to be homogeneous. The results of simulation suggest that distribution of auto-fluorescence is significantly suppressed in the near-infrared spectral region, whereas the spatial distribution of fluorescence sources within a sensor layer embedded in the epidermis is localized at an `effective' depth.

Far-field DOA estimation and source localization for different scenarios in a distributed sensor network

NASA Astrophysics Data System (ADS)

Asgari, Shadnaz

Recent developments in the integrated circuits and wireless communications not only open up many possibilities but also introduce challenging issues for the collaborative processing of signals for source localization and beamforming in an energy-constrained distributed sensor network. In signal processing, various sensor array processing algorithms and concepts have been adopted, but must be further tailored to match the communication and computational constraints. Sometimes the constraints are such that none of the existing algorithms would be an efficient option for the defined problem and as the result; the necessity of developing a new algorithm becomes undeniable. In this dissertation, we present the theoretical and the practical issues of Direction-Of-Arrival (DOA) estimation and source localization using the Approximate-Maximum-Likelihood (AML) algorithm for different scenarios. We first investigate a robust algorithm design for coherent source DOA estimation in a limited reverberant environment. Then, we provide a least-square (LS) solution for source localization based on our newly proposed virtual array model. In another scenario, we consider the determination of the location of a disturbance source which emits both wideband acoustic and seismic signals. We devise an enhanced AML algorithm to process the data collected at the acoustic sensors. For processing the seismic signals, two distinct algorithms are investigated to determine the DOAs. Then, we consider a basic algorithm for fusion of the results yielded by the acoustic and seismic arrays. We also investigate the theoretical and practical issues of DOA estimation in a three-dimensional (3D) scenario. We show that the performance of the proposed 3D AML algorithm converges to the Cramer-Rao Bound. We use the concept of an isotropic array to reduce the complexity of the proposed algorithm by advocating a decoupled 3D version. We also explore a modified version of the decoupled 3D AML algorithm which can be used for DOA estimation with non-isotropic arrays. In this dissertation, for each scenario, efficient numerical implementations of the corresponding AML algorithm are derived and applied into a real-time sensor network testbed. Extensive simulations as well as experimental results are presented to verify the effectiveness of the proposed algorithms.

Eye/Sensor Protection against Laser Irradiation Organic Nonlinear Optical Materials

DTIC Science & Technology

1989-06-12

the dipole. When the electric field is small compared to the internal fields due to the electron!, the molecular polarizability (p), which is...polarizability tensors, respectively, the linear polarizability and the second and third-order hyperpolarizability. At lower field intensities ( small E’s) only...nonlinear optical effect: the bonding electrons are well localized so only small changes in charge distribution with changes in local field environments

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

NASA Astrophysics Data System (ADS)

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

2009-05-01

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

Skin fluorescence model based on the Monte Carlo technique

NASA Astrophysics Data System (ADS)

Churmakov, Dmitry Y.; Meglinski, Igor V.; Piletsky, Sergey A.; Greenhalgh, Douglas A.

2003-10-01

The novel Monte Carlo technique of simulation of spatial fluorescence distribution within the human skin is presented. The computational model of skin takes into account spatial distribution of fluorophores following the collagen fibers packing, whereas in epidermis and stratum corneum the distribution of fluorophores assumed to be homogeneous. The results of simulation suggest that distribution of auto-fluorescence is significantly suppressed in the NIR spectral region, while fluorescence of sensor layer embedded in epidermis is localized at the adjusted depth. The model is also able to simulate the skin fluorescence spectra.

Distributed wavefront reconstruction with SABRE for real-time large scale adaptive optics control

NASA Astrophysics Data System (ADS)

Brunner, Elisabeth; de Visser, Cornelis C.; Verhaegen, Michel

2014-08-01

We present advances on Spline based ABerration REconstruction (SABRE) from (Shack-)Hartmann (SH) wavefront measurements for large-scale adaptive optics systems. SABRE locally models the wavefront with simplex B-spline basis functions on triangular partitions which are defined on the SH subaperture array. This approach allows high accuracy through the possible use of nonlinear basis functions and great adaptability to any wavefront sensor and pupil geometry. The main contribution of this paper is a distributed wavefront reconstruction method, D-SABRE, which is a 2 stage procedure based on decomposing the sensor domain into sub-domains each supporting a local SABRE model. D-SABRE greatly decreases the computational complexity of the method and removes the need for centralized reconstruction while obtaining a reconstruction accuracy for simulated E-ELT turbulences within 1% of the global method's accuracy. Further, a generalization of the methodology is proposed making direct use of SH intensity measurements which leads to an improved accuracy of the reconstruction compared to centroid algorithms using spatial gradients.

Fabrication of a Flexible Micro Temperature Sensor for Micro Reformer Applications

PubMed Central

Lee, Chi-Yuan; Lin, Chien-Hen; Lo, Yi-Man

2011-01-01

Micro reformers still face obstacles in minimizing their size, decreasing the concentration of CO, conversion efficiency and the feasibility of integrated fabrication with fuel cells. By using a micro temperature sensor fabricated on a stainless steel-based micro reformer, this work attempts to measure the inner temperature and increase the conversion efficiency. Micro temperature sensors on a stainless steel substrate are fabricated using micro-electro-mechanical systems (MEMS) and then placed separately inside the micro reformer. Micro temperature sensors are characterized by their higher accuracy and sensitivity than those of a conventional thermocouple. To the best of our knowledge, micro temperature sensors have not been embedded before in micro reformers and commercial products, therefore, this work presents a novel approach to integrating micro temperature sensors in a stainless steel-based micro reformer in order to evaluate inner local temperature distributions and enhance reformer performance. PMID:22163817

Coordinated perception by teams of aerial and ground robots

NASA Astrophysics Data System (ADS)

Grocholsky, Benjamin P.; Swaminathan, Rahul; Kumar, Vijay; Taylor, Camillo J.; Pappas, George J.

2004-12-01

Air and ground vehicles exhibit complementary capabilities and characteristics as robotic sensor platforms. Fixed wing aircraft offer broad field of view and rapid coverage of search areas. However, minimum operating airspeed and altitude limits, combined with attitude uncertainty, place a lower limit on their ability to detect and localize ground features. Ground vehicles on the other hand offer high resolution sensing over relatively short ranges with the disadvantage of slow coverage. This paper presents a decentralized architecture and solution methodology for seamlessly realizing the collaborative potential of air and ground robotic sensor platforms. We provide a framework based on an established approach to the underlying sensor fusion problem. This provides transparent integration of information from heterogeneous sources. An information-theoretic utility measure captures the task objective and robot inter-dependencies. A simple distributed solution mechanism is employed to determine team member sensing trajectories subject to the constraints of individual vehicle and sensor sub-systems. The architecture is applied to a mission involving searching for and localizing an unknown number of targets in an user specified search area. Results for a team of two fixed wing UAVs and two all terrain UGVs equipped with vision sensors are presented.

Ability of Impedance-Based Health Monitoring To Detect Structural Damage of Propulsion System Components Assessed

NASA Technical Reports Server (NTRS)

Martin, Richard E.; Gyekenyesi, Andrew L.; Sawicki, Jerzy T.; Baaklini, George Y.

2005-01-01

Impedance-based structural-health-monitoring uses piezoelectric (PZT) patches that are bonded onto or embedded in a structure. Each individual patch behaves as both an actuator of the surrounding structural area as well as a sensor of the structural response. The size of the excited area varies with the geometry and material composition of the structure, and an active patch is driven by a sinusoidal voltage sweep. When a PZT patch is subjected to an electric field, it produces a mechanical strain; and when it is stressed, it produces an electric charge. Since the patch is bonded to the structure, driving a patch deforms and vibrates the structure. The structure then produces a localized dynamic response. This structural system response is transferred back to the PZT patch, which in turn produces an electrical response. The electromechanical impedance method is based on the principle of electromechanical coupling between the active sensor and the structure, which allows researchers to assess local structural dynamics directly by interrogating a distributed sensor array. Because of mechanical coupling between the sensor and the host structure, this mechanical effect is picked up by the sensor and, through electromechanical coupling inside the active element, is reflected in electrical impedance measured at the sensor s terminals.

Dynamic Agent Classification and Tracking Using an Ad Hoc Mobile Acoustic Sensor Network

NASA Astrophysics Data System (ADS)

Friedlander, David; Griffin, Christopher; Jacobson, Noah; Phoha, Shashi; Brooks, Richard R.

2003-12-01

Autonomous networks of sensor platforms can be designed to interact in dynamic and noisy environments to determine the occurrence of specified transient events that define the dynamic process of interest. For example, a sensor network may be used for battlefield surveillance with the purpose of detecting, identifying, and tracking enemy activity. When the number of nodes is large, human oversight and control of low-level operations is not feasible. Coordination and self-organization of multiple autonomous nodes is necessary to maintain connectivity and sensor coverage and to combine information for better understanding the dynamics of the environment. Resource conservation requires adaptive clustering in the vicinity of the event. This paper presents methods for dynamic distributed signal processing using an ad hoc mobile network of microsensors to detect, identify, and track targets in noisy environments. They seamlessly integrate data from fixed and mobile platforms and dynamically organize platforms into clusters to process local data along the trajectory of the targets. Local analysis of sensor data is used to determine a set of target attribute values and classify the target. Sensor data from a field test in the Marine base at Twentynine Palms, Calif, was analyzed using the techniques described in this paper. The results were compared to "ground truth" data obtained from GPS receivers on the vehicles.

Olfaction and Hearing Based Mobile Robot Navigation for Odor/Sound Source Search

PubMed Central

Song, Kai; Liu, Qi; Wang, Qi

2011-01-01

Bionic technology provides a new elicitation for mobile robot navigation since it explores the way to imitate biological senses. In the present study, the challenging problem was how to fuse different biological senses and guide distributed robots to cooperate with each other for target searching. This paper integrates smell, hearing and touch to design an odor/sound tracking multi-robot system. The olfactory robot tracks the chemical odor plume step by step through information fusion from gas sensors and airflow sensors, while two hearing robots localize the sound source by time delay estimation (TDE) and the geometrical position of microphone array. Furthermore, this paper presents a heading direction based mobile robot navigation algorithm, by which the robot can automatically and stably adjust its velocity and direction according to the deviation between the current heading direction measured by magnetoresistive sensor and the expected heading direction acquired through the odor/sound localization strategies. Simultaneously, one robot can communicate with the other robots via a wireless sensor network (WSN). Experimental results show that the olfactory robot can pinpoint the odor source within the distance of 2 m, while two hearing robots can quickly localize and track the olfactory robot in 2 min. The devised multi-robot system can achieve target search with a considerable success ratio and high stability. PMID:22319401

Collecting and distributing wearable sensor data: an embedded personal area network to local area network gateway server.

PubMed

Neuhaeuser, Jakob; D'Angelo, Lorenzo T

2013-01-01

The goal of the concept and of the device presented in this contribution is to be able to collect sensor data from wearable sensors directly, automatically and wirelessly and to make them available over a wired local area network. Several concepts in e-health and telemedicine make use of portable and wearable sensors to collect movement or activity data. Usually these data are either collected via a wireless personal area network or using a connection to the user's smartphone. However, users might not carry smartphones on them while inside a residential building such as a nursing home or a hospital, but also within their home. Also, in such areas the use of other wireless communication technologies might be limited. The presented system is an embedded server which can be deployed in several rooms in order to ensure live data collection in bigger buildings. Also, the collection of data batches recorded out of range, as soon as a connection is established, is also possible. Both, the system concept and the realization are presented.

Time-optimum packet scheduling for many-to-one routing in wireless sensor networks

USGS Publications Warehouse

Song, W.-Z.; Yuan, F.; LaHuser, R.

2007-01-01

This paper studies the WSN application scenario with periodical traffic from all sensors to a sink. We present a time-optimum and energy-efficient packet scheduling algorithm and its distributed implementation. We first give a general many-to-one packet scheduling algorithm for wireless networks, and then prove that it is time-optimum and costs max(2N(u1) - 1, N(u 0) -1) time slots, assuming each node reports one unit of data in each round. Here N(u0) is the total number of sensors, while N(u 1) denotes the number of sensors in a sink's largest branch subtree. With a few adjustments, we then show that our algorithm also achieves time-optimum scheduling in heterogeneous scenarios, where each sensor reports a heterogeneous amount of data in each round. Then we give a distributed implementation to let each node calculate its duty-cycle locally and maximize efficiency globally. In this packet scheduling algorithm, each node goes to sleep whenever it is not transceiving, so that the energy waste of idle listening is also eliminated. Finally, simulations are conducted to evaluate network performance using the Qualnet simulator. Among other contributions, our study also identifies the maximum reporting frequency that a deployed sensor network can handle. ??2006 IEEE.

Sensitivity of Aerosol Multi-Sensor Daily Data Intercomparison to the Level 3 Dataday Definition

NASA Technical Reports Server (NTRS)

Leptoukh, Gregory; Lary, David; Shen, Suhung; Lynnes, Christopher

2010-01-01

Topics include: why people use Level 3 products, why someone might go wrong with Level 3 products, differences in L3 from different sensors, Level 3 data day definition, MODIS vs. MODIS, AOD MODIS Terra vs. Aqua in Pacific, AOD Aqua MODIS vs. MISR correlation map, MODIS vs MISR on Terra, MODIS atmospheric data day definition, orbit time difference for Terra and Aqua 2009-01-06, maximum time difference for Terra (Calendar day), artifact explains, data day definitions, local time distribution, spatial (local time) data day definition, maximum time difference between Terra and Aqua, Removing the artifact in 16-day AOD correlation, MODIS cloud top pressure, and MODIS Terra and Aqua vs. AIRS cloud top pressure.

Layerwise mechanics and finite element for the dynamic analysis of piezoelectric composite plates

NASA Technical Reports Server (NTRS)

Saravanos, Dimitris A.; Heyliger, Paul R.; Hopkins, Dale A.

1996-01-01

Laminate and structural mechanics for the analysis of laminated composite plate structures with piezoelectric actuators and sensors are presented. The theories implement layerwise representations of displacements and electric potential, and can model both the global and local electromechanical response of smart composite laminates. Finite-element formulations are developed for the quasi-static and dynamic analysis of smart composite structures containing piezoelectric layers. Comparisons with an exact solution illustrate the accuracy, robustness and capability of the developed mechanics to capture the global and local response of thin and/or thick laminated piezoelectric plates. Additional correlations and numerical applications demonstrate the unique capabilities of the mechanics in analyzing the static and free-vibration response of composite plates with distributed piezoelectric actuators and sensors.

Spatially Resolved Sensitivity of Single-Particle Plasmon Sensors

PubMed Central

2018-01-01

The high sensitivity of localized surface plasmon resonance sensors to the local refractive index allows for the detection of single-molecule binding events. Though binding events of single objects can be detected by their induced plasmon shift, the broad distribution of observed shifts remains poorly understood. Here, we perform a single-particle study wherein single nanospheres bind to a gold nanorod, and relate the observed plasmon shift to the binding location using correlative microscopy. To achieve this we combine atomic force microscopy to determine the binding location, and single-particle spectroscopy to determine the corresponding plasmon shift. As expected, we find a larger plasmon shift for nanospheres binding at the tip of a rod compared to its sides, in good agreement with numerical calculations. However, we also find a broad distribution of shifts even for spheres that were bound at a similar location to the nanorod. Our correlative approach allows us to disentangle effects of nanoparticle dimensions and binding location, and by comparison to numerical calculations we find that the biggest contributor to this observed spread is the dispersion in nanosphere diameter. These experiments provide insight into the spatial sensitivity and signal-heterogeneity of single-particle plasmon sensors and provides a framework for signal interpretation in sensing applications. PMID:29520315

Particle Simulations of the Guard Electrode Effects on the Photoelectron Distribution Around an Electric Field Sensor

NASA Astrophysics Data System (ADS)

Miyake, Y.; Usui, H.; Kojima, H.

2010-12-01

In tenuous space plasma environment, photoelectrons emitted due to solar illumination produce a high-density photoelectron cloud localized in the vicinity of a spacecraft body and an electric field sensor. The photoelectron current emitted from the sensor has also received considerable attention because it becomes a primary factor in determining floating potentials of the sunlit spacecraft and sensor bodies. Considering the fact that asymmetric photoelectron distribution between sunlit and sunless sides of the spacecraft occasionally causes a spurious sunward electric field, we require quantitative evaluation of the photoelectron distribution around the spacecraft and its influence on electric field measurements by means of a numerical approach. In the current study, we applied the Particle-in-Cell plasma simulation to the analysis of the photoelectron environment around spacecraft. By using the PIC modeling, we can self-consistently consider the plasma kinetics. This enables us to simulate the formation of the photoelectron cloud as well as the spacecraft and sensor charging in a self-consistent manner. We report the progress of an analysis on photoelectron environment around MEFISTO, which is an electric field instrument for the BepiColombo/MMO spacecraft to Mercury’s magnetosphere. The photoelectron guard electrode is a key technology for ensuring an optimum photoelectron environment. We show some simulation results on the guard electrode effects on surrounding photoelectrons and discuss a guard operation condition for producing the optimum photoelectron environment. We also deal with another important issue, that is, how the guard electrode can mitigate an undesirable influence of an asymmetric photoelectron distribution on electric field measurements.

Catchment Integration of Sensor Array Observations to Understand Hydrologic Connectivity

NASA Astrophysics Data System (ADS)

Redfern, S.; Livneh, B.; Molotch, N. P.; Suding, K.; Neff, J. C.; Hinckley, E. L. S.

2017-12-01

Hydrologic connectivity and the land surface water balance are likely to be impacted by climate change in the coming years. Although recent work has started to demonstrate that climate modulates connectivity, we still lack knowledge of how local ecology will respond to environmental and atmospheric changes and subsequently interact with connectivity. The overarching goal of this research is to address and forecast how climate change will affect hydrologic connectivity in an alpine environment, through the use of near-surface observations (temperature, humidity, soil moisture, snow depth) from a new 16-sensor array (plus 5 precipitation gauges), together with a distributed hydrologic model, over a small catchment on Colorado's Niwot Ridge (above 3000m). Model simulations will be constrained to distributed sensor measurements taken in the study area and calibrated with streamflow. Periods of wetting and dry-down will be analyzed to identify signatures of connectivity across the landscape, its seasonal signals and its sensitivity to land cover. Further work will aim to develop future hydrologic projections, compare model output with related observations, conduct multi-physics experiments, and continue to expand the existing sensor network.

Gaussian process regression for sensor networks under localization uncertainty

USGS Publications Warehouse

Jadaliha, M.; Xu, Yunfei; Choi, Jongeun; Johnson, N.S.; Li, Weiming

2013-01-01

In this paper, we formulate Gaussian process regression with observations under the localization uncertainty due to the resource-constrained sensor networks. In our formulation, effects of observations, measurement noise, localization uncertainty, and prior distributions are all correctly incorporated in the posterior predictive statistics. The analytically intractable posterior predictive statistics are proposed to be approximated by two techniques, viz., Monte Carlo sampling and Laplace's method. Such approximation techniques have been carefully tailored to our problems and their approximation error and complexity are analyzed. Simulation study demonstrates that the proposed approaches perform much better than approaches without considering the localization uncertainty properly. Finally, we have applied the proposed approaches on the experimentally collected real data from a dye concentration field over a section of a river and a temperature field of an outdoor swimming pool to provide proof of concept tests and evaluate the proposed schemes in real situations. In both simulation and experimental results, the proposed methods outperform the quick-and-dirty solutions often used in practice.

A Wireless Sensor Network with Soft Computing Localization Techniques for Track Cycling Applications.

PubMed

Gharghan, Sadik Kamel; Nordin, Rosdiadee; Ismail, Mahamod

2016-08-06

In this paper, we propose two soft computing localization techniques for wireless sensor networks (WSNs). The two techniques, Neural Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN), focus on a range-based localization method which relies on the measurement of the received signal strength indicator (RSSI) from the three ZigBee anchor nodes distributed throughout the track cycling field. The soft computing techniques aim to estimate the distance between bicycles moving on the cycle track for outdoor and indoor velodromes. In the first approach the ANFIS was considered, whereas in the second approach the ANN was hybridized individually with three optimization algorithms, namely Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), and Backtracking Search Algorithm (BSA). The results revealed that the hybrid GSA-ANN outperforms the other methods adopted in this paper in terms of accuracy localization and distance estimation accuracy. The hybrid GSA-ANN achieves a mean absolute distance estimation error of 0.02 m and 0.2 m for outdoor and indoor velodromes, respectively.

A Wireless Sensor Network with Soft Computing Localization Techniques for Track Cycling Applications

PubMed Central

Gharghan, Sadik Kamel; Nordin, Rosdiadee; Ismail, Mahamod

2016-01-01

In this paper, we propose two soft computing localization techniques for wireless sensor networks (WSNs). The two techniques, Neural Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN), focus on a range-based localization method which relies on the measurement of the received signal strength indicator (RSSI) from the three ZigBee anchor nodes distributed throughout the track cycling field. The soft computing techniques aim to estimate the distance between bicycles moving on the cycle track for outdoor and indoor velodromes. In the first approach the ANFIS was considered, whereas in the second approach the ANN was hybridized individually with three optimization algorithms, namely Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), and Backtracking Search Algorithm (BSA). The results revealed that the hybrid GSA-ANN outperforms the other methods adopted in this paper in terms of accuracy localization and distance estimation accuracy. The hybrid GSA-ANN achieves a mean absolute distance estimation error of 0.02 m and 0.2 m for outdoor and indoor velodromes, respectively. PMID:27509495

Whisper: Local Secret Maintenance in Sensor Networks

DTIC Science & Technology

2003-02-01

networks, such as Balfanz et al. [1] and Hubaux et al. [9]; these works also use asymmetric cryptography while we use the less expensive symmetric... Balfanz , D. K. Smetters, P. Stewart and H. Chi Wong. Talking to strangers: authentication in ad-hoc wireless network. Symposium on Network and Distributed

Breaking wire detection and strain distribution of seven-wire steel cables with acoustic emission and optical fiber sensors.

DOT National Transportation Integrated Search

2013-09-01

Cable-stayed bridges have been increasingly used as river-crossing links in highway and railway transportation networks. In the event : of an abnormal situation, they can not only impact the local and national economy but also threaten the safety of ...

FASTmiR: an RNA-based sensor for in vitro quantification and live-cell localization of small RNAs

PubMed Central

Huang, Kun; Doyle, Francis; Wurz, Zachary E.; Tenenbaum, Scott A.; Hammond, Reza K.

2017-01-01

Abstract Small RNAs, including microRNAs (miRNAs) and small interfering RNAs (siRNAs), play a variety of important regulatory roles in many eukaryotes. Their small size has made it challenging to study them directly in live cells. Here we describe an RNA-based fluorescent sensor for small RNA detection both in vitro and in vivo, adaptable for any small RNA. It utilizes an sxRNA switch for detection of miRNA–mRNA interactions combined with a fluorophore-binding sequence ‘Spinach’, a GFP-like RNA aptamer for which the RNA–fluorophore complex exhibits strong and consistent fluorescence under an excitation wavelength. Two example sensors, FASTmiR171 and FASTmiR122, can rapidly detect and quantify the levels of miR171 and miR122 in vitro. The sensors can determine relative levels of miRNAs in total RNA extracts with sensitivity similar to small RNA sequencing and northern blots. FASTmiR sensors were also used to estimate the copy number range of miRNAs in total RNA extracts. To localize and analyze the spatial distribution of small RNAs in live, single cells, tandem copies of FASTmiR122 were expressed in different cell lines. FASTmiR122 was able to quantitatively detect the differences in miR122 levels in Huh7 and HEK293T cells demonstrating its potential for tracking miRNA expression and localization in vivo. PMID:28586459

A gossip based information fusion protocol for distributed frequent itemset mining

NASA Astrophysics Data System (ADS)

Sohrabi, Mohammad Karim

2018-07-01

The computational complexity, huge memory space requirement, and time-consuming nature of frequent pattern mining process are the most important motivations for distribution and parallelization of this mining process. On the other hand, the emergence of distributed computational and operational environments, which causes the production and maintenance of data on different distributed data sources, makes the parallelization and distribution of the knowledge discovery process inevitable. In this paper, a gossip based distributed itemset mining (GDIM) algorithm is proposed to extract frequent itemsets, which are special types of frequent patterns, in a wireless sensor network environment. In this algorithm, local frequent itemsets of each sensor are extracted using a bit-wise horizontal approach (LHPM) from the nodes which are clustered using a leach-based protocol. Heads of clusters exploit a gossip based protocol in order to communicate each other to find the patterns which their global support is equal to or more than the specified support threshold. Experimental results show that the proposed algorithm outperforms the best existing gossip based algorithm in term of execution time.

Wireless Sensor Platform for Cultural Heritage Monitoring and Modeling System

PubMed Central

Bermudez, Sergio A.; Schrott, Alejandro G.; Tsukada, Masahiko; Kargere, Lucretia; Marianno, Fernando; Hamann, Hendrik F.; López, Vanessa; Leona, Marco

2017-01-01

Results from three years of continuous monitoring of environmental conditions using a wireless sensor platform installed at The Cloisters, the medieval branch of the New York Metropolitan Museum of Art, are presented. The platform comprises more than 200 sensors that were distributed in five galleries to assess temperature and air flow and to quantify microclimate changes using physics-based and statistical models. The wireless sensor network data shows a very stable environment within the galleries, while the dense monitoring enables localized monitoring of subtle changes in air quality trends and impact of visitors on the microclimate conditions. The high spatial and temporal resolution data serves as a baseline study to understand the impact of visitors and building operations on the long-term preservation of art objects. PMID:28858223

Wireless Sensor Platform for Cultural Heritage Monitoring and Modeling System.

PubMed

Klein, Levente J; Bermudez, Sergio A; Schrott, Alejandro G; Tsukada, Masahiko; Dionisi-Vici, Paolo; Kargere, Lucretia; Marianno, Fernando; Hamann, Hendrik F; López, Vanessa; Leona, Marco

2017-08-31

Results from three years of continuous monitoring of environmental conditions using a wireless sensor platform installed at The Cloisters, the medieval branch of the New York Metropolitan Museum of Art, are presented. The platform comprises more than 200 sensors that were distributed in five galleries to assess temperature and air flow and to quantify microclimate changes using physics-based and statistical models. The wireless sensor network data shows a very stable environment within the galleries, while the dense monitoring enables localized monitoring of subtle changes in air quality trends and impact of visitors on the microclimate conditions. The high spatial and temporal resolution data serves as a baseline study to understand the impact of visitors and building operations on the long-term preservation of art objects.

The Role of Energy Reservoirs in Distributed Computing: Manufacturing, Implementing, and Optimizing Energy Storage in Energy-Autonomous Sensor Nodes

NASA Astrophysics Data System (ADS)

Cowell, Martin Andrew

The world already hosts more internet connected devices than people, and that ratio is only increasing. These devices seamlessly integrate with peoples lives to collect rich data and give immediate feedback about complex systems from business, health care, transportation, and security. As every aspect of global economies integrate distributed computing into their industrial systems and these systems benefit from rich datasets. Managing the power demands of these distributed computers will be paramount to ensure the continued operation of these networks, and is elegantly addressed by including local energy harvesting and storage on a per-node basis. By replacing non-rechargeable batteries with energy harvesting, wireless sensor nodes will increase their lifetimes by an order of magnitude. This work investigates the coupling of high power energy storage with energy harvesting technologies to power wireless sensor nodes; with sections covering device manufacturing, system integration, and mathematical modeling. First we consider the energy storage mechanism of supercapacitors and batteries, and identify favorable characteristics in both reservoir types. We then discuss experimental methods used to manufacture high power supercapacitors in our labs. We go on to detail the integration of our fabricated devices with collaborating labs to create functional sensor node demonstrations. With the practical knowledge gained through in-lab manufacturing and system integration, we build mathematical models to aid in device and system design. First, we model the mechanism of energy storage in porous graphene supercapacitors to aid in component architecture optimization. We then model the operation of entire sensor nodes for the purpose of optimally sizing the energy harvesting and energy reservoir components. In consideration of deploying these sensor nodes in real-world environments, we model the operation of our energy harvesting and power management systems subject to spatially and temporally varying energy availability in order to understand sensor node reliability. Looking to the future, we see an opportunity for further research to implement machine learning algorithms to control the energy resources of distributed computing networks.

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

Cryogenic-temperature profiling of high-power superconducting lines using local and distributed optical-fiber sensors.

PubMed

Chiuchiolo, Antonella; Palmieri, Luca; Consales, Marco; Giordano, Michele; Borriello, Anna; Bajas, Hugues; Galtarossa, Andrea; Bajko, Marta; Cusano, Andrea

2015-10-01

This contribution presents distributed and multipoint fiber-optic monitoring of cryogenic temperatures along a superconducting power transmission line down to 30 K and over 20 m distance. Multipoint measurements were conducted using fiber Bragg gratings sensors coated with two different functional overlays (epoxy and poly methyl methacrylate (PMMA)) demonstrating cryogenic operation in the range 300-4.2 K. Distributed measurements exploited optical frequency-domain reflectometry to analyze the Rayleigh scattering along two concatenated fibers with different coatings (acrylate and polyimide). The integrated system has been placed along the 20 m long cryostat of a superconducting power transmission line, which is currently being tested at the European Organization for Nuclear Research (CERN). Cool-down events from 300-30 K have been successfully measured in space and time, confirming the viability of these approaches to the monitoring of cryogenic temperatures along a superconducting transmission line.

Implementation of a Localization System for Sensor Networks

DTIC Science & Technology

2006-05-18

its N-point DFT is mathematically formulated as X[k] = N−1∑ n=0 x[n] W nkN , k = 0, 1, . . . , N − 1 (7.1) W knN = e −j(2π/N)kn (7.2) There are two...distributed ad-hoc wireless sensor networks. In Int. Conf. on Acoustics, Speech , and Signal Proc. (ICASSP), pages 2037 – 2040, Salt Lake City, UT. [18] J...Stability of recursive qrd-ls algorithms using finite- precision systolic array implementation. IEEE Trans. on Acoustics, Speech , and Signal Proc., 37(5

Network-Capable Application Process and Wireless Intelligent Sensors for ISHM

NASA Technical Reports Server (NTRS)

Figueroa, Fernando; Morris, Jon; Turowski, Mark; Wang, Ray

2011-01-01

Intelligent sensor technology and systems are increasingly becoming attractive means to serve as frameworks for intelligent rocket test facilities with embedded intelligent sensor elements, distributed data acquisition elements, and onboard data acquisition elements. Networked intelligent processors enable users and systems integrators to automatically configure their measurement automation systems for analog sensors. NASA and leading sensor vendors are working together to apply the IEEE 1451 standard for adding plug-and-play capabilities for wireless analog transducers through the use of a Transducer Electronic Data Sheet (TEDS) in order to simplify sensor setup, use, and maintenance, to automatically obtain calibration data, and to eliminate manual data entry and error. A TEDS contains the critical information needed by an instrument or measurement system to identify, characterize, interface, and properly use the signal from an analog sensor. A TEDS is deployed for a sensor in one of two ways. First, the TEDS can reside in embedded, nonvolatile memory (typically flash memory) within the intelligent processor. Second, a virtual TEDS can exist as a separate file, downloadable from the Internet. This concept of virtual TEDS extends the benefits of the standardized TEDS to legacy sensors and applications where the embedded memory is not available. An HTML-based user interface provides a visual tool to interface with those distributed sensors that a TEDS is associated with, to automate the sensor management process. Implementing and deploying the IEEE 1451.1-based Network-Capable Application Process (NCAP) can achieve support for intelligent process in Integrated Systems Health Management (ISHM) for the purpose of monitoring, detection of anomalies, diagnosis of causes of anomalies, prediction of future anomalies, mitigation to maintain operability, and integrated awareness of system health by the operator. It can also support local data collection and storage. This invention enables wide-area sensing and employs numerous globally distributed sensing devices that observe the physical world through the existing sensor network. This innovation enables distributed storage, distributed processing, distributed intelligence, and the availability of DiaK (Data, Information, and Knowledge) to any element as needed. It also enables the simultaneous execution of multiple processes, and represents models that contribute to the determination of the condition and health of each element in the system. The NCAP (intelligent process) can configure data-collection and filtering processes in reaction to sensed data, allowing it to decide when and how to adapt collection and processing with regard to sophisticated analysis of data derived from multiple sensors. The user will be able to view the sensing device network as a single unit that supports a high-level query language. Each query would be able to operate over data collected from across the global sensor network just as a search query encompasses millions of Web pages. The sensor web can preserve ubiquitous information access between the querier and the queried data. Pervasive monitoring of the physical world raises significant data and privacy concerns. This innovation enables different authorities to control portions of the sensing infrastructure, and sensor service authors may wish to compose services across authority boundaries.

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.

Well logging interpretation of production profile in horizontal oil-water two phase flow pipes

NASA Astrophysics Data System (ADS)

Zhai, Lu-Sheng; Jin, Ning-De; Gao, Zhong-Ke; Zheng, Xi-Ke

2012-03-01

Due to the complicated distribution of local velocity and local phase hold up along the radial direction of pipe in horizontal oil-water two phase flow, it is difficult to measure the total flow rate and phase volume fraction. In this study, we carried out dynamic experiment in horizontal oil-water two phases flow simulation well by using combination measurement system including turbine flowmeter with petal type concentrating diverter, conductance sensor and flowpassing capacitance sensor. According to the response resolution ability of the conductance and capacitance sensor in different range of total flow rate and water-cut, we use drift flux model and statistical model to predict the partial phase flow rate, respectively. The results indicate that the variable coefficient drift flux model can self-adaptively tone the model parameter according to the oil-water two phase flow characteristic, and the prediction result of partial phase flow rate of oil-water two phase flow is of high accuracy.

Fiber Bragg Grating Filter High Temperature Sensors

NASA Technical Reports Server (NTRS)

Lyons, Donald R.; Brass, Eric D.; Pencil, Eric (Technical Monitor)

2001-01-01

We present a scaled-down method for determining high temperatures using fiber-based Bragg gratings. Bragg gratings are distributed along the length of the optical fiber, and have high reflectivities whenever the optical wavelength is twice the grating spacing. These spatially distinct Bragg regions (located in the core of a fiber) are sensitive to local temperature changes. Since these fibers are silica-based they are easily affected by localized changes in temperature, which results in changes to both the grating spacing and the wavelength reflectivity. We exploit the shift in wavelength reflectivity to measure the change in the local temperature. Note that the Bragg region (sensing area) is some distance away from where the temperature is being measured. This is done so that we can measure temperatures that are much higher than the damage threshold of the fiber. We do this by affixing the fiber with the Bragg sensor to a material with a well-known coefficient of thermal expansion, and model the heat gradient from the region of interest to the actual sensor. The research described in this paper will culminate in a working device as well as be the second portion of a publication pending submission to Optics Letters.

Influence of Global and Local Membrane Curvature on Mechanosensitive Ion Channels: A Finite Element Approach

PubMed Central

Bavi, Omid; Cox, Charles D.; Vossoughi, Manouchehr; Naghdabadi, Reza; Jamali, Yousef; Martinac, Boris

2016-01-01

Mechanosensitive (MS) channels are ubiquitous molecular force sensors that respond to a number of different mechanical stimuli including tensile, compressive and shear stress. MS channels are also proposed to be molecular curvature sensors gating in response to bending in their local environment. One of the main mechanisms to functionally study these channels is the patch clamp technique. However, the patch of membrane surveyed using this methodology is far from physiological. Here we use continuum mechanics to probe the question of how curvature, in a standard patch clamp experiment, at different length scales (global and local) affects a model MS channel. Firstly, to increase the accuracy of the Laplace’s equation in tension estimation in a patch membrane and to be able to more precisely describe the transient phenomena happening during patch clamping, we propose a modified Laplace’s equation. Most importantly, we unambiguously show that the global curvature of a patch, which is visible under the microscope during patch clamp experiments, is of negligible energetic consequence for activation of an MS channel in a model membrane. However, the local curvature (RL < 50) and the direction of bending are able to cause considerable changes in the stress distribution through the thickness of the membrane. Not only does local bending, in the order of physiologically relevant curvatures, cause a substantial change in the pressure profile but it also significantly modifies the stress distribution in response to force application. Understanding these stress variations in regions of high local bending is essential for a complete understanding of the effects of curvature on MS channels. PMID:26861405

Analyses of integrated aircraft cabin contaminant monitoring network based on Kalman consensus filter.

PubMed

Wang, Rui; Li, Yanxiao; Sun, Hui; Chen, Zengqiang

2017-11-01

The modern civil aircrafts use air ventilation pressurized cabins subject to the limited space. In order to monitor multiple contaminants and overcome the hypersensitivity of the single sensor, the paper constructs an output correction integrated sensor configuration using sensors with different measurement theories after comparing to other two different configurations. This proposed configuration works as a node in the contaminant distributed wireless sensor monitoring network. The corresponding measurement error models of integrated sensors are also proposed by using the Kalman consensus filter to estimate states and conduct data fusion in order to regulate the single sensor measurement results. The paper develops the sufficient proof of the Kalman consensus filter stability when considering the system and the observation noises and compares the mean estimation and the mean consensus errors between Kalman consensus filter and local Kalman filter. The numerical example analyses show the effectiveness of the algorithm. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Spatial Variability of Co On The Scale of The Street According To Street Morphology, Car Traffic and Local Climate In Paris

NASA Astrophysics Data System (ADS)

Quenol, H.; Bridier, S.; Beltrando, G.; Frangi, J. P.

The purpose of this study is to observe CO distribution on street level according to variations of car traffic, weather situation and street morphology. The experimentation use an electronical CO sensor connected to a data logger. Two kinds of observations are carried out : - measurements along an itinerary from the n´ butte de Montmartre z to the n´ Seine z highlights the spatial variability of CO distribution according to car traffic and weather characteristics (radiativ, advectiv, cloudy, rainy) ; - measurements in fixed stations underlines the differences in concentration according the situation (in or out of buildings) and according to level of the vertical measure (from 1.5 to 10 m). This approach of pollution distribution at the street and the district scale is made possible by using low cost sensors. They allow an very fine approach of CO distribution by multiplying measurements points. All of these data are integrated in a GIS with a DEM, a cartography of building implantation and width of the streets. This study shows that the CO concentration is in relation to street morphology (width, height, topography), intensity of car traffic and local meteorology (breezes and wind channeled by street network). This method leads to the constitution of a mobil network used to produce data on horizontal and vertical CO distribution inside the n´ meshs z of the present network of pollution observation.

Analysis of Global Ultrasonic Sensor Data from a Full Scale Wing Panel Test

NASA Astrophysics Data System (ADS)

Michaels, Jennifer E.; Michaels, Thomas E.; Martin, Ramaldo S.

2009-03-01

A full scale wing panel fatigue test was undertaken in 2007 as a part of the DARPA Structural Integrity Prognosis System (SIPS) program. Both local and global ultrasonic sensors were installed on the wing panel and data were recorded periodically over a period of about seven weeks. The local ultrasonic sensors interrogated a small number of selected fastener holes, and the global ultrasonic sensors were arranged in a spatially distributed array surrounding an area encompassing multiple fastener holes of interest. The global ultrasonic sensor data is the focus of the work reported here. Waveforms were recorded from all pitch-catch sensor pairs as a function of static load while fatiguing was paused. The time windows over which the waveforms were recorded were long enough to include most of the reverberating energy. Partway through the test simulated defects were temporarily introduced by gluing masses onto the surface of the wing panel, and waveforms were recorded immediately before their attachment and after their removal. The overall fatigue test was terminated while cracks originating from the fastener holes were still relatively small and before they reached the surface of the wing panel. Both detection and localization results are shown for the artificial damage, and the overall repeatability and stability of the signals are analyzed. Also shown is an analysis of how the reverberating signals change as a function of applied load. The fastener hole fatigue cracks were not detected by the global transducer array, which is not surprising given the final sizes of the cracks as determined by later destructive analysis. However, signals were stable throughout the entire fatigue test, and effects of load on the received signals were significant, both in the short-time and long-time signal regimes.

Technical report: The design and evaluation of a basin-scale wireless sensor network for mountain hydrology

NASA Astrophysics Data System (ADS)

Zhang, Ziran; Glaser, Steven D.; Bales, Roger C.; Conklin, Martha; Rice, Robert; Marks, Danny G.

2017-05-01

A network of sensors for spatially representative water-balance measurements was developed and deployed across the 2000 km2 snow-dominated portion of the upper American River basin, primarily to measure changes in snowpack and soil-water storage, air temperature, and humidity. This wireless sensor network (WSN) consists of 14 sensor clusters, each with 10 measurement nodes that were strategically placed within a 1 km2 area, across different elevations, aspects, slopes, and canopy covers. Compared to existing operational sensor installations, the WSN reduces hydrologic uncertainty in at least three ways. First, redundant measurements improved estimation of lapse rates for air and dew-point temperature. Second, distributed measurements captured local variability and constrained uncertainty in air and dew-point temperature, snow accumulation, and derived hydrologic attributes important for modeling and prediction. Third, the distributed relative-humidity measurements offer a unique capability to monitor upper-basin patterns in dew-point temperature and characterize elevation gradient of water vapor-pressure deficit across steep, variable topography. Network statistics during the first year of operation demonstrated that the WSN was robust for cold, wet, and windy conditions in the basin. The electronic technology used in the WSN-reduced adverse effects, such as high current consumption, multipath signal fading, and clock drift, seen in previous remote WSNs.

A Distributed Data Acquisition System for the Sensor Network of the TAWARA_RTM Project

NASA Astrophysics Data System (ADS)

Fontana, Cristiano Lino; Donati, Massimiliano; Cester, Davide; Fanucci, Luca; Iovene, Alessandro; Swiderski, Lukasz; Moretto, Sandra; Moszynski, Marek; Olejnik, Anna; Ruiu, Alessio; Stevanato, Luca; Batsch, Tadeusz; Tintori, Carlo; Lunardon, Marcello

This paper describes a distributed Data Acquisition System (DAQ) developed for the TAWARA_RTM project (TAp WAter RAdioactivity Real Time Monitor). The aim is detecting the presence of radioactive contaminants in drinking water; in order to prevent deliberate or accidental threats. Employing a set of detectors, it is possible to detect alpha, beta and gamma radiations, from emitters dissolved in water. The Sensor Network (SN) consists of several heterogeneous nodes controlled by a centralized server. The SN cyber-security is guaranteed in order to protect it from external intrusions and malicious acts. The nodes were installed in different locations, along the water treatment processes, in the waterworks plant supplying the aqueduct of Warsaw, Poland. Embedded computers control the simpler nodes, and are directly connected to the SN. Local-PCs (LPCs) control the more complex nodes that consist signal digitizers acquiring data from several detectors. The DAQ in the LPC is split in several processes communicating with sockets in a local sub-network. Each process is dedicated to a very simple task (e.g. data acquisition, data analysis, hydraulics management) in order to have a flexible and fault-tolerant system. The main SN and the local DAQ networks are separated by data routers to ensure the cyber-security.

Using Integer Clocks to Verify the Timing-Sync Sensor Network Protocol

NASA Technical Reports Server (NTRS)

Huang, Xiaowan; Singh, Anu; Smolka, Scott A.

2010-01-01

We use the UPPAAL model checker for Timed Automata to verify the Timing-Sync time-synchronization protocol for sensor networks (TPSN). The TPSN protocol seeks to provide network-wide synchronization of the distributed clocks in a sensor network. Clock-synchronization algorithms for sensor networks such as TPSN must be able to perform arithmetic on clock values to calculate clock drift and network propagation delays. They must be able to read the value of a local clock and assign it to another local clock. Such operations are not directly supported by the theory of Timed Automata. To overcome this formal-modeling obstacle, we augment the UPPAAL specification language with the integer clock derived type. Integer clocks, which are essentially integer variables that are periodically incremented by a global pulse generator, greatly facilitate the encoding of the operations required to synchronize clocks as in the TPSN protocol. With this integer-clock-based model of TPSN in hand, we use UPPAAL to verify that the protocol achieves network-wide time synchronization and is devoid of deadlock. We also use the UPPAAL Tracer tool to illustrate how integer clocks can be used to capture clock drift and resynchronization during protocol execution

Kelvin probe microscopy and electronic transport measurements in reduced graphene oxide chemical sensors

NASA Astrophysics Data System (ADS)

Kehayias, Christopher E.; MacNaughton, Samuel; Sonkusale, Sameer; Staii, Cristian

2013-06-01

Reduced graphene oxide (RGO) is an electronically hybrid material that displays remarkable chemical sensing properties. Here, we present a quantitative analysis of the chemical gating effects in RGO-based chemical sensors. The gas sensing devices are patterned in a field-effect transistor geometry, by dielectrophoretic assembly of RGO platelets between gold electrodes deposited on SiO2/Si substrates. We show that these sensors display highly selective and reversible responses to the measured analytes, as well as fast response and recovery times (tens of seconds). We use combined electronic transport/Kelvin probe microscopy measurements to quantify the amount of charge transferred to RGO due to chemical doping when the device is exposed to electron-acceptor (acetone) and electron-donor (ammonia) analytes. We demonstrate that this method allows us to obtain high-resolution maps of the surface potential and local charge distribution both before and after chemical doping, to identify local gate-susceptible areas on the RGO surface, and to directly extract the contact resistance between the RGO and the metallic electrodes. The method presented is general, suggesting that these results have important implications for building graphene and other nanomaterial-based chemical sensors.

Kelvin probe microscopy and electronic transport measurements in reduced graphene oxide chemical sensors.

PubMed

Kehayias, Christopher E; MacNaughton, Samuel; Sonkusale, Sameer; Staii, Cristian

2013-06-21

Reduced graphene oxide (RGO) is an electronically hybrid material that displays remarkable chemical sensing properties. Here, we present a quantitative analysis of the chemical gating effects in RGO-based chemical sensors. The gas sensing devices are patterned in a field-effect transistor geometry, by dielectrophoretic assembly of RGO platelets between gold electrodes deposited on SiO2/Si substrates. We show that these sensors display highly selective and reversible responses to the measured analytes, as well as fast response and recovery times (tens of seconds). We use combined electronic transport/Kelvin probe microscopy measurements to quantify the amount of charge transferred to RGO due to chemical doping when the device is exposed to electron-acceptor (acetone) and electron-donor (ammonia) analytes. We demonstrate that this method allows us to obtain high-resolution maps of the surface potential and local charge distribution both before and after chemical doping, to identify local gate-susceptible areas on the RGO surface, and to directly extract the contact resistance between the RGO and the metallic electrodes. The method presented is general, suggesting that these results have important implications for building graphene and other nanomaterial-based chemical sensors.

3D reconstruction from non-uniform point clouds via local hierarchical clustering

NASA Astrophysics Data System (ADS)

Yang, Jiaqi; Li, Ruibo; Xiao, Yang; Cao, Zhiguo

2017-07-01

Raw scanned 3D point clouds are usually irregularly distributed due to the essential shortcomings of laser sensors, which therefore poses a great challenge for high-quality 3D surface reconstruction. This paper tackles this problem by proposing a local hierarchical clustering (LHC) method to improve the consistency of point distribution. Specifically, LHC consists of two steps: 1) adaptive octree-based decomposition of 3D space, and 2) hierarchical clustering. The former aims at reducing the computational complexity and the latter transforms the non-uniform point set into uniform one. Experimental results on real-world scanned point clouds validate the effectiveness of our method from both qualitative and quantitative aspects.

Distributed Prognostics and Health Management with a Wireless Network Architecture

NASA Technical Reports Server (NTRS)

Goebel, Kai; Saha, Sankalita; Sha, Bhaskar

2013-01-01

A heterogeneous set of system components monitored by a varied suite of sensors and a particle-filtering (PF) framework, with the power and the flexibility to adapt to the different diagnostic and prognostic needs, has been developed. Both the diagnostic and prognostic tasks are formulated as a particle-filtering problem in order to explicitly represent and manage uncertainties in state estimation and remaining life estimation. Current state-of-the-art prognostic health management (PHM) systems are mostly centralized in nature, where all the processing is reliant on a single processor. This can lead to a loss in functionality in case of a crash of the central processor or monitor. Furthermore, with increases in the volume of sensor data as well as the complexity of algorithms, traditional centralized systems become for a number of reasons somewhat ungainly for successful deployment, and efficient distributed architectures can be more beneficial. The distributed health management architecture is comprised of a network of smart sensor devices. These devices monitor the health of various subsystems or modules. They perform diagnostics operations and trigger prognostics operations based on user-defined thresholds and rules. The sensor devices, called computing elements (CEs), consist of a sensor, or set of sensors, and a communication device (i.e., a wireless transceiver beside an embedded processing element). The CE runs in either a diagnostic or prognostic operating mode. The diagnostic mode is the default mode where a CE monitors a given subsystem or component through a low-weight diagnostic algorithm. If a CE detects a critical condition during monitoring, it raises a flag. Depending on availability of resources, a networked local cluster of CEs is formed that then carries out prognostics and fault mitigation by efficient distribution of the tasks. It should be noted that the CEs are expected not to suspend their previous tasks in the prognostic mode. When the prognostics task is over, and after appropriate actions have been taken, all CEs return to their original default configuration. Wireless technology-based implementation would ensure more flexibility in terms of sensor placement. It would also allow more sensors to be deployed because the overhead related to weights of wired systems is not present. Distributed architectures are furthermore generally robust with regard to recovery from node failures.

Decentralized Dimensionality Reduction for Distributed Tensor Data Across Sensor Networks.

PubMed

Liang, Junli; Yu, Guoyang; Chen, Badong; Zhao, Minghua

2016-11-01

This paper develops a novel decentralized dimensionality reduction algorithm for the distributed tensor data across sensor networks. The main contributions of this paper are as follows. First, conventional centralized methods, which utilize entire data to simultaneously determine all the vectors of the projection matrix along each tensor mode, are not suitable for the network environment. Here, we relax the simultaneous processing manner into the one-vector-by-one-vector (OVBOV) manner, i.e., determining the projection vectors (PVs) related to each tensor mode one by one. Second, we prove that in the OVBOV manner each PV can be determined without modifying any tensor data, which simplifies corresponding computations. Third, we cast the decentralized PV determination problem as a set of subproblems with consensus constraints, so that it can be solved in the network environment only by local computations and information communications among neighboring nodes. Fourth, we introduce the null space and transform the PV determination problem with complex orthogonality constraints into an equivalent hidden convex one without any orthogonality constraint, which can be solved by the Lagrange multiplier method. Finally, experimental results are given to show that the proposed algorithm is an effective dimensionality reduction scheme for the distributed tensor data across the sensor networks.

Twitter as Information Source for Rapid Damage Estimation after Major Earthquakes

NASA Astrophysics Data System (ADS)

Eggert, Silke; Fohringer, Joachim

2014-05-01

Natural disasters like earthquakes require a fast response from local authorities. Well trained rescue teams have to be available, equipment and technology has to be ready set up, information have to be directed to the right positions so the head quarter can manage the operation precisely. The main goal is to reach the most affected areas in a minimum of time. But even with the best preparation for these cases, there will always be the uncertainty of what really happened in the affected area. Modern geophysical sensor networks provide high quality data. These measurements, however, are only mapping disjoint values from their respective locations for a limited amount of parameters. Using observations of witnesses represents one approach to enhance measured values from sensors ("humans as sensors"). These observations are increasingly disseminated via social media platforms. These "social sensors" offer several advantages over common sensors, e.g. high mobility, high versatility of captured parameters as well as rapid distribution of information. Moreover, the amount of data offered by social media platforms is quite extensive. We analyze messages distributed via Twitter after major earthquakes to get rapid information on what eye-witnesses report from the epicentral area. We use this information to (a) quickly learn about damage and losses to support fast disaster response and to (b) densify geophysical networks in areas where there is sparse information to gain a more detailed insight on felt intensities. We present a case study from the Mw 7.1 Philippines (Bohol) earthquake that happened on Oct. 15 2013. We extract Twitter messages, so called tweets containing one or more specified keywords from the semantic field of "earthquake" and use them for further analysis. For the time frame of Oct. 15 to Oct 18 we get a data base of in total 50.000 tweets whereof 2900 tweets are geo-localized and 470 have a photo attached. Analyses for both national level and locally for the City of Cebu show that Twitter is an important and useful piece to the situational awareness of the earthquake's impact.

PADF RF localization experiments with multi-agent caged-MAV platforms

NASA Astrophysics Data System (ADS)

Barber, Christopher; Gates, Miguel; Selmic, Rastko; Al-Issa, Huthaifa; Ordonez, Raul; Mitra, Atindra

2011-06-01

This paper provides a summary of preliminary RF direction finding results generated within an AFOSR funded testbed facility recently developed at Louisiana Tech University. This facility, denoted as the Louisiana Tech University Micro- Aerial Vehicle/Wireless Sensor Network (MAVSeN) Laboratory, has recently acquired a number of state-of-the-art MAV platforms that enable us to analyze, design, and test some of our recent results in the area of multiplatform position-adaptive direction finding (PADF) [1] [2] for localization of RF emitters in challenging embedded multipath environments. Discussions within the segmented sections of this paper include a description of the MAVSeN Laboratory and the preliminary results from the implementation of mobile platforms with the PADF algorithm. This novel approach to multi-platform RF direction finding is based on the investigation of iterative path-loss based (i.e. path loss exponent) metrics estimates that are measured across multiple platforms in order to develop a control law that robotically/intelligently positionally adapt (i.e. self-adjust) the location of each distributed/cooperative platform. The body of this paper provides a summary of our recent results on PADF and includes a discussion on state-of-the-art Sensor Mote Technologies as applied towards the development of sensor-integrated caged-MAV platform for PADF applications. Also, a discussion of recent experimental results that incorporate sample approaches to real-time singleplatform data pruning is included as part of a discussion on potential approaches to refining a basic PADF technique in order to integrate and perform distributed self-sensitivity and self-consistency analysis as part of a PADF technique with distributed robotic/intelligent features. These techniques are extracted in analytical form from a parallel study denoted as "PADF RF Localization Criteria for Multi-Model Scattering Environments". The focus here is on developing and reporting specific approaches to self-sensitivity and self-consistency within this experimental PADF framework via the exploitation of specific single-agent caged-MAV trajectories that are unique to this experiment set.

Adaptive multi-sensor biomimetics for unsupervised submarine hunt (AMBUSH): Early results

NASA Astrophysics Data System (ADS)

Blouin, Stéphane

2014-10-01

Underwater surveillance is inherently difficult because acoustic wave propagation and transmission are limited and unpredictable when targets and sensors move around in the communication-opaque undersea environment. Today's Navy underwater sensors enable the collection of a massive amount of data, often analyzed offtine. The Navy of tomorrow will dominate by making sense of that data in real-time. DRDC's AMBUSH project proposes a new undersea-surveillance network paradigm that will enable such a real-time operation. Nature abounds with examples of collaborative tasks taking place despite limited communication and computational capabilities. This publication describes a year's worth of research efforts finding inspiration in Nature's collaborative tasks such as wolves hunting in packs. This project proposes the utilization of a heterogeneous network combining both static and mobile network nodes. The military objective is to enable an unsupervised surveillance capability while maximizing target localization performance and endurance. The scientific objective is to develop the necessary technology to acoustically and passively localize a noise-source of interest in shallow waters. The project fulfills these objectives via distributed computing and adaptation to changing undersea conditions. Specific research interests discussed here relate to approaches for performing: (a) network self-discovery, (b) network connectivity self-assessment, (c) opportunistic network routing, (d) distributed data-aggregation, and (e) simulation of underwater acoustic propagation. We present early results then followed by a discussion about future work.

In-plane vibration of FG micro/nano-mass sensor based on nonlocal theory under various thermal loading via differential transformation method

NASA Astrophysics Data System (ADS)

Rahmani, O.; Mohammadi Niaei, A.; Hosseini, S. A. H.; Shojaei, M.

2017-01-01

In the present study, free vibration model of a cantilever functionally graded (FG) nanobeam with an attached mass at tip and under various thermal loading and two types of material distribution is introduced. The vibration performance is considered using nonlocal Euler-Bernoulli beam theory. Two types of thermal loading, namely, uniform and nonlinear temperature rises through the thickness direction are considered. Thermo-mechanical properties of FG nano mass sensor are supposed to vary smoothly and continuously throughout the thickness based on power-law and Mori Tanaka distributions of material properties. Eringen non-local elasticity theory is exploited to describe the size dependency of FG nanobeam. The governing equations of the system with both axial and transverse displacements are derived based on Hamilton's principle and solved utilizing the differential transformation method (DTM) to find the non-dimensional natural frequencies. The results have good agreements with those discussing in the literature. After validation of the present model, the effect of various parameters such as mass and position of the attached nano particle, FG power-law exponent, thermal load type, material distribution type and nonlocal parameter on the frequency of nano sensor are studied. It is shown that the present model produces results of high accuracy, and it can be used as a benchmark in future studies of the free vibration of FG Nano-Mass Sensors.

Geometric scaling of artificial hair sensors for flow measurement under different conditions

NASA Astrophysics Data System (ADS)

Su, Weihua; Reich, Gregory W.

2017-03-01

Artificial hair sensors (AHSs) have been developed for prediction of the local flow speed and aerodynamic force around an airfoil and subsequent application in vibration control of the airfoil. Usually, a specific sensor design is only sensitive to the flow speeds within its operating flow measurement region. This paper aims at expanding this flow measurement concept of using AHSs to different flow speed conditions by properly sizing the parameters of the sensors, including the dimensions of the artificial hair, capillary, and carbon nanotubes (CNTs) that make up the sensor design, based on a baseline sensor design and its working flow condition. In doing so, the glass fiber hair is modeled as a cantilever beam with an elastic foundation, subject to the distributed aerodynamic drag over the length of the hair. Hair length and diameter, capillary depth, and CNT height are scaled by keeping the maximum compressive strain of the CNTs constant for different sensors under different speed conditions. Numerical studies will demonstrate the feasibility of the geometric scaling methodology by designing AHSs for aircraft with different dimensions and flight conditions, starting from the same baseline sensor. Finally, the operating bandwidth of the scaled sensors are explored.

Video sensor architecture for surveillance applications.

PubMed

Sánchez, Jordi; Benet, Ginés; Simó, José E

2012-01-01

This paper introduces a flexible hardware and software architecture for a smart video sensor. This sensor has been applied in a video surveillance application where some of these video sensors are deployed, constituting the sensory nodes of a distributed surveillance system. In this system, a video sensor node processes images locally in order to extract objects of interest, and classify them. The sensor node reports the processing results to other nodes in the cloud (a user or higher level software) in the form of an XML description. The hardware architecture of each sensor node has been developed using two DSP processors and an FPGA that controls, in a flexible way, the interconnection among processors and the image data flow. The developed node software is based on pluggable components and runs on a provided execution run-time. Some basic and application-specific software components have been developed, in particular: acquisition, segmentation, labeling, tracking, classification and feature extraction. Preliminary results demonstrate that the system can achieve up to 7.5 frames per second in the worst case, and the true positive rates in the classification of objects are better than 80%.

Video Sensor Architecture for Surveillance Applications

PubMed Central

Sánchez, Jordi; Benet, Ginés; Simó, José E.

2012-01-01

This paper introduces a flexible hardware and software architecture for a smart video sensor. This sensor has been applied in a video surveillance application where some of these video sensors are deployed, constituting the sensory nodes of a distributed surveillance system. In this system, a video sensor node processes images locally in order to extract objects of interest, and classify them. The sensor node reports the processing results to other nodes in the cloud (a user or higher level software) in the form of an XML description. The hardware architecture of each sensor node has been developed using two DSP processors and an FPGA that controls, in a flexible way, the interconnection among processors and the image data flow. The developed node software is based on pluggable components and runs on a provided execution run-time. Some basic and application-specific software components have been developed, in particular: acquisition, segmentation, labeling, tracking, classification and feature extraction. Preliminary results demonstrate that the system can achieve up to 7.5 frames per second in the worst case, and the true positive rates in the classification of objects are better than 80%. PMID:22438723

Propagation Modeling and Defending of a Mobile Sensor Worm in Wireless Sensor and Actuator Networks.

PubMed

Wang, Tian; Wu, Qun; Wen, Sheng; Cai, Yiqiao; Tian, Hui; Chen, Yonghong; Wang, Baowei

2017-01-13

WSANs (Wireless Sensor and Actuator Networks) are derived from traditional wireless sensor networks by introducing mobile actuator elements. Previous studies indicated that mobile actuators can improve network performance in terms of data collection, energy supplementation, etc. However, according to our experimental simulations, the actuator's mobility also causes the sensor worm to spread faster if an attacker launches worm attacks on an actuator and compromises it successfully. Traditional worm propagation models and defense strategies did not consider the diffusion with a mobile worm carrier. To address this new problem, we first propose a microscopic mathematical model to describe the propagation dynamics of the sensor worm. Then, a two-step local defending strategy (LDS) with a mobile patcher (a mobile element which can distribute patches) is designed to recover the network. In LDS, all recovering operations are only taken in a restricted region to minimize the cost. Extensive experimental results demonstrate that our model estimations are rather accurate and consistent with the actual spreading scenario of the mobile sensor worm. Moreover, on average, the LDS outperforms other algorithms by approximately 50% in terms of the cost.

Optical Electronic Bragg Reflection Sensor System with Hydrodynamic Flow Applications

NASA Technical Reports Server (NTRS)

Lyons, D. R.

2003-01-01

This project, as described in the following report, involved design and fabrication of fiber optic sensors for the detection and measurement of dynamic fluid density variations. These devices are created using UV (ultraviolet) ablation and generally modified transverse holographic fiber grating techniques. The resulting phase gratings created on or immediately underneath the flat portion of D-shaped optical waveguides are characterized as evanescent field sensing devices. The primary applications include the sensor portion of a real-time localized or distributed measurement system for hydrodynamic flow, fluid density measurements, and phase change phenomena. Several design modifications were implemented in an attempt to accomplish the tasks specified in our original proposal. In addition, we have established key collaborative relationships with numerous people and institutions.

Recent progress in distributed optical fiber Raman photon sensors at China Jiliang University

NASA Astrophysics Data System (ADS)

Zhang, Zaixuan; Wang, Jianfeng; Li, Yi; Gong, Huaping; Yu, Xiangdong; Liu, Honglin; Jin, Yongxing; Kang, Juan; Li, Chenxia; Zhang, Wensheng; Zhang, Wenping; Niu, Xiaohui; Sun, Zhongzhou; Zhao, Chunliu; Dong, Xinyong; Jin, Shangzhong

2012-06-01

A brief review of recent progress in researches, productions and applications of full distributed fiber Raman photon sensors at China Jiliang University (CJLU) is presented. In order to improve the measurement distance, the accuracy, the space resolution, the ability of multi-parameter measurements, and the intelligence of full distributed fiber sensor systems, a new generation fiber sensor technology based on the optical fiber nonlinear scattering fusion principle is proposed. A series of new generation full distributed fiber sensors are investigated and designed, which consist of new generation ultra-long distance full distributed fiber Raman and Rayleigh scattering photon sensors integrated with a fiber Raman amplifier, auto-correction full distributed fiber Raman photon temperature sensors based on Raman correlation dual sources, full distributed fiber Raman photon temperature sensors based on a pulse coding source, full distributed fiber Raman photon temperature sensors using a fiber Raman wavelength shifter, a new type of Brillouin optical time domain analyzers (BOTDAs) integrated with a fiber Raman amplifier for replacing a fiber Brillouin amplifier, full distributed fiber Raman and Brillouin photon sensors integrated with a fiber Raman amplifier, and full distributed fiber Brillouin photon sensors integrated with a fiber Brillouin frequency shifter. The Internet of things is believed as one of candidates of the next technological revolution, which has driven hundreds of millions of class markets. Sensor networks are important components of the Internet of things. The full distributed optical fiber sensor network (Rayleigh, Raman, and Brillouin scattering) is a 3S (smart materials, smart structure, and smart skill) system, which is easy to construct smart fiber sensor networks. The distributed optical fiber sensor can be embedded in the power grids, railways, bridges, tunnels, roads, constructions, water supply systems, dams, oil and gas pipelines and other facilities, and can be integrated with wireless networks.

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

PubMed

Berkvens, Rafael; Peremans, Herbert; Weyn, Maarten

2016-10-02

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

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

PubMed Central

Berkvens, Rafael; Peremans, Herbert; Weyn, Maarten

2016-01-01

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

Lightweight filter architecture for energy efficient mobile vehicle localization based on a distributed acoustic sensor network.

PubMed

Kim, Keonwook

2013-08-23

The generic properties of an acoustic signal provide numerous benefits for localization by applying energy-based methods over a deployed wireless sensor network (WSN). However, the signal generated by a stationary target utilizes a significant amount of bandwidth and power in the system without providing further position information. For vehicle localization, this paper proposes a novel proximity velocity vector estimator (PVVE) node architecture in order to capture the energy from a moving vehicle and reject the signal from motionless automobiles around the WSN node. A cascade structure between analog envelope detector and digital exponential smoothing filter presents the velocity vector-sensitive output with low analog circuit and digital computation complexity. The optimal parameters in the exponential smoothing filter are obtained by analytical and mathematical methods for maximum variation over the vehicle speed. For stationary targets, the derived simulation based on the acoustic field parameters demonstrates that the system significantly reduces the communication requirements with low complexity and can be expected to extend the operation time considerably.

Dual Segment Glocal Model Based Capacitive Level Sensor (CLS) for Adhesive Material and Level Detection

NASA Astrophysics Data System (ADS)

Khan, F. A.; Yousaf, A.; Reindl, L. M.

2018-04-01

This paper presents a multi segment capacitive level monitoring sensor based on distributed E-fields approach Glocal. This approach has an advantage to analyze build-up problem by the local E-fields as well the fluid level monitoring by the global E-fields. The multi segment capacitive approach presented within this work addresses the main problem of unwanted parasitic capacitance generated from Copper (Cu) strips by applying active shielding concept. Polyvinyl chloride (PVC) is used for isolation and parafilm is used for creating artificial build-up on a CLS.

Large-Scale Wireless Temperature Monitoring System for Liquefied Petroleum Gas Storage Tanks.

PubMed

Fan, Guangwen; Shen, Yu; Hao, Xiaowei; Yuan, Zongming; Zhou, Zhi

2015-09-18

Temperature distribution is a critical indicator of the health condition for Liquefied Petroleum Gas (LPG) storage tanks. In this paper, we present a large-scale wireless temperature monitoring system to evaluate the safety of LPG storage tanks. The system includes wireless sensors networks, high temperature fiber-optic sensors, and monitoring software. Finally, a case study on real-world LPG storage tanks proves the feasibility of the system. The unique features of wireless transmission, automatic data acquisition and management, local and remote access make the developed system a good alternative for temperature monitoring of LPG storage tanks in practical applications.

Strain features and condition assessment of orthotropic steel deck cable-supported bridges subjected to vehicle loads by using dense FBG strain sensors

NASA Astrophysics Data System (ADS)

Wei, Shiyin; Zhang, Zhaohui; Li, Shunlong; Li, Hui

2017-10-01

Strain is a direct indicator of structural safety. Therefore, strain sensors have been used in most structural health monitoring systems for bridges. However, until now, the investigation of strain response has been insufficient. This paper conducts a comprehensive study of the strain features of the U ribs and transverse diaphragm on an orthotropic steel deck and proposes a statistical paradigm for crack detection based on the features of vehicle-induced strain response by using the densely distributed optic fibre Bragg grating (FBG) strain sensors. The local feature of strain under vehicle load is highlighted, which enables the use of measurement data to determine the vehicle loading event and to make a decision regarding the health status of a girder near the strain sensors via technical elimination of the load information. Time-frequency analysis shows that the strain contains three features: the long-term trend item, the short-term trend item, and the instantaneous vehicle-induced item (IVII). The IVII is the wheel-induced strain with a remarkable local feature, and the measured wheel-induced strain is only influenced by the vehicle near the FBG sensor, while other vehicles slightly farther away have no effect on the wheel-induced strain. This causes the local strain series, among the FBG strain sensors in the same transverse locations of different cross-sections, to present similarities in shape to some extent and presents a time delay in successive order along the driving direction. Therefore, the strain series induced by an identical vehicle can be easily tracked and compared by extracting the amplitude and calculating the mutual ratio to eliminate vehicle loading information, leaving the girder information alone. The statistical paradigm for crack detection is finally proposed, and the detection accuracy is then validated by using dense FBG strain sensors on a long-span suspension bridge in China.

Automatic Suppression of Intense Monochromatic Light in Electro-Optical Sensors

PubMed Central

Ritt, Gunnar; Eberle, Bernd

2012-01-01

Electro-optical imaging sensors are widely distributed and used for many different tasks. Due to technical improvements, their pixel size has been steadily decreasing, resulting in a reduced saturation capacity. As a consequence, this progress makes them susceptible to intense point light sources. Developments in laser technology have led to very compact and powerful laser sources of any wavelength in the visible and near infrared spectral region, offered as laser pointers. The manifold of wavelengths makes it difficult to encounter sensor saturation over the complete operating waveband by conventional measures like absorption or interference filters. We present a concept for electro-optical sensors to suppress overexposure in the visible spectral region. The key element of the concept is a spatial light modulator in combination with wavelength multiplexing. This approach allows spectral filtering within a localized area in the field of view of the sensor. The system offers the possibility of automatic reduction of overexposure by monochromatic laser radiation. PMID:23202039

Air Temperature Distribution Measurement Using Asynchronous-Type Sound Probe

NASA Astrophysics Data System (ADS)

Katano, Yosuke; Wakatsuki, Naoto; Mizutani, Koichi

2009-07-01

In conventional temperature measurement using a sound probe, the operation beginnings of two acoustic sensors must be completely synchronized to measure time of flight (TOF), tf, because the precision of synchronization determines TOF measurement accuracy. A wireless local area network (LAN) is convenient for constructing a sensing grid; however, it causes a fluctuation in the delay of millisecond order. Therefore, it cannot provide sufficient precision for synchronizing acoustic sensors. In previous studies, synchronization was achieved by a trigger line using a coaxial cable; however, the cable reduces the flexibility of a wireless sensing grid especially in larger-scale measurement. In this study, an asynchronous-type sound probe is devised to compensate for the effect of the delay of millisecond order caused by the network. The validity of the probe was examined, and the air temperature distribution was measured using this means. A matrix method is employed to obtain the distribution. Similar results were observed using both asynchronous-type sound probes and thermocouples. This shows the validity of the use of a sensing grid with an asynchronous-type sound probe for temperature distribution measurement even if the trigger line is omitted.

Cross-correlation focus method with an electrostatic sensor array for local particle velocity measurement in dilute gas-solid two-phase flow

NASA Astrophysics Data System (ADS)

Wang, Chao; Zhang, Jingyu; Gao, Wenbin; Ding, Hongbing; Wu, Weiping

2015-11-01

The gas-solid two-phase flow has been widely applied in the power, chemical and metallurgical industries. It is of great significance in the research of gas-solid two-phase flow to measure particle velocity at different locations in the pipeline. Thus, an electrostatic sensor array comprising eight arc-shaped electrodes was designed. The relationship between the cross-correlation (CC) velocity and the distribution of particle velocity, charge density and electrode spatial sensitivity was analysed. Then the CC sensitivity and its calculation method were proposed. According to the distribution of CC sensitivity, it was found that, between different electrode pairs, it had different focus areas. The CC focus method was proposed for particle velocity measurement at different locations and validated by a belt-style electrostatic induction experiment facility. Finally, the particle velocities at different locations with different flow conditions were measured to research the particle velocity distribution in a dilute horizontal pneumatic conveying pipeline.

Maturation of Structural Health Management Systems for Solid Rocket Motors

NASA Technical Reports Server (NTRS)

Quing, Xinlin; Beard, Shawn; Zhang, Chang

2011-01-01

Concepts of an autonomous and automated space-compliant diagnostic system were developed for conditioned-based maintenance (CBM) of rocket motors for space exploration vehicles. The diagnostic system will provide real-time information on the integrity of critical structures on launch vehicles, improve their performance, and greatly increase crew safety while decreasing inspection costs. Using the SMART Layer technology as a basis, detailed procedures and calibration techniques for implementation of the diagnostic system were developed. The diagnostic system is a distributed system, which consists of a sensor network, local data loggers, and a host central processor. The system detects external impact to the structure. The major functions of the system include an estimate of impact location, estimate of impact force at impacted location, and estimate of the structure damage at impacted location. This system consists of a large-area sensor network, dedicated multiple local data loggers with signal processing and data analysis software to allow for real-time, in situ monitoring, and longterm tracking of structural integrity of solid rocket motors. Specifically, the system could provide easy installation of large sensor networks, onboard operation under harsh environments and loading, inspection of inaccessible areas without disassembly, detection of impact events and impact damage in real-time, and monitoring of a large area with local data processing to reduce wiring.

Strain transfer analysis of optical fiber based sensors embedded in an asphalt pavement structure

NASA Astrophysics Data System (ADS)

Wang, Huaping; Xiang, Ping

2016-07-01

Asphalt pavement is vulnerable to random damage, such as cracking and rutting, which can be proactively identified by distributed optical fiber sensing technology. However, due to the material nature of optical fibers, a bare fiber is apt to be damaged during the construction process of pavements. Thus, a protective layer is needed for this application. Unfortunately, part of the strain of the host material is absorbed by the protective layer when transferring the strain to the sensing fiber. To account for the strain transfer error, in this paper a theoretical analysis of the strain transfer of a three-layered general model has been carried out by introducing Goodman’s hypothesis to describe the interfacial shear stress relationship. The model considers the viscoelastic behavior of the host material and protective layer. The effects of one crack in the host material and the sensing length on strain transfer relationship are been discussed. To validate the effectiveness of the strain transfer analysis, a flexible asphalt-mastic packaged distributed optical fiber sensor was designed and tested in a laboratory environment to monitor the distributed strain and appearance of cracks in an asphalt concrete beam at two different temperatures. The experimental results indicated that the developed strain transfer formula can significantly reduce the strain transfer error, and that the asphalt-mastic packaged optical fiber sensor can successfully monitor the distributed strain and identify local cracks.

Global Network Connectivity Assessment via Local Data Exchange for Underwater Acoustic Sensor Networks

DTIC Science & Technology

2014-03-31

Network Connectivity Assessment via Local Data Exchange for Underwater Acoustic Sensor Networks M.M. Asadi H. Mahboubi A...2014 Global Network Connectivity Assessment via Local Data Exchange for Underwater Acoustic Sensor Networks Contract Report # AMBUSH.1.1 Contract...pi j /= 0. The sensor network considered in this work is composed of underwater sensors , which use acoustic waves for

Collaborative Localization and Location Verification in WSNs

PubMed Central

Miao, Chunyu; Dai, Guoyong; Ying, Kezhen; Chen, Qingzhang

2015-01-01

Localization is one of the most important technologies in wireless sensor networks. A lightweight distributed node localization scheme is proposed by considering the limited computational capacity of WSNs. The proposed scheme introduces the virtual force model to determine the location by incremental refinement. Aiming at solving the drifting problem and malicious anchor problem, a location verification algorithm based on the virtual force mode is presented. In addition, an anchor promotion algorithm using the localization reliability model is proposed to re-locate the drifted nodes. Extended simulation experiments indicate that the localization algorithm has relatively high precision and the location verification algorithm has relatively high accuracy. The communication overhead of these algorithms is relative low, and the whole set of reliable localization methods is practical as well as comprehensive. PMID:25954948

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

Location-Aware Dynamic Session-Key Management for Grid-Based Wireless Sensor Networks

PubMed Central

Chen, Chin-Ling; Lin, I-Hsien

2010-01-01

Security is a critical issue for sensor networks used in hostile environments. When wireless sensor nodes in a wireless sensor network are distributed in an insecure hostile environment, the sensor nodes must be protected: a secret key must be used to protect the nodes transmitting messages. If the nodes are not protected and become compromised, many types of attacks against the network may result. Such is the case with existing schemes, which are vulnerable to attacks because they mostly provide a hop-by-hop paradigm, which is insufficient to defend against known attacks. We propose a location-aware dynamic session-key management protocol for grid-based wireless sensor networks. The proposed protocol improves the security of a secret key. The proposed scheme also includes a key that is dynamically updated. This dynamic update can lower the probability of the key being guessed correctly. Thus currently known attacks can be defended. By utilizing the local information, the proposed scheme can also limit the flooding region in order to reduce the energy that is consumed in discovering routing paths. PMID:22163606

Location-aware dynamic session-key management for grid-based Wireless Sensor Networks.

PubMed

Chen, Chin-Ling; Lin, I-Hsien

2010-01-01

Security is a critical issue for sensor networks used in hostile environments. When wireless sensor nodes in a wireless sensor network are distributed in an insecure hostile environment, the sensor nodes must be protected: a secret key must be used to protect the nodes transmitting messages. If the nodes are not protected and become compromised, many types of attacks against the network may result. Such is the case with existing schemes, which are vulnerable to attacks because they mostly provide a hop-by-hop paradigm, which is insufficient to defend against known attacks. We propose a location-aware dynamic session-key management protocol for grid-based wireless sensor networks. The proposed protocol improves the security of a secret key. The proposed scheme also includes a key that is dynamically updated. This dynamic update can lower the probability of the key being guessed correctly. Thus currently known attacks can be defended. By utilizing the local information, the proposed scheme can also limit the flooding region in order to reduce the energy that is consumed in discovering routing paths.

Weighted Optimization-Based Distributed Kalman Filter for Nonlinear Target Tracking in Collaborative Sensor Networks.

PubMed

Chen, Jie; Li, Jiahong; Yang, Shuanghua; Deng, Fang

2017-11-01

The identification of the nonlinearity and coupling is crucial in nonlinear target tracking problem in collaborative sensor networks. According to the adaptive Kalman filtering (KF) method, the nonlinearity and coupling can be regarded as the model noise covariance, and estimated by minimizing the innovation or residual errors of the states. However, the method requires large time window of data to achieve reliable covariance measurement, making it impractical for nonlinear systems which are rapidly changing. To deal with the problem, a weighted optimization-based distributed KF algorithm (WODKF) is proposed in this paper. The algorithm enlarges the data size of each sensor by the received measurements and state estimates from its connected sensors instead of the time window. A new cost function is set as the weighted sum of the bias and oscillation of the state to estimate the "best" estimate of the model noise covariance. The bias and oscillation of the state of each sensor are estimated by polynomial fitting a time window of state estimates and measurements of the sensor and its neighbors weighted by the measurement noise covariance. The best estimate of the model noise covariance is computed by minimizing the weighted cost function using the exhaustive method. The sensor selection method is in addition to the algorithm to decrease the computation load of the filter and increase the scalability of the sensor network. The existence, suboptimality and stability analysis of the algorithm are given. The local probability data association method is used in the proposed algorithm for the multitarget tracking case. The algorithm is demonstrated in simulations on tracking examples for a random signal, one nonlinear target, and four nonlinear targets. Results show the feasibility and superiority of WODKF against other filtering algorithms for a large class of systems.

Just-in-Time Correntropy Soft Sensor with Noisy Data for Industrial Silicon Content Prediction.

PubMed

Chen, Kun; Liang, Yu; Gao, Zengliang; Liu, Yi

2017-08-08

Development of accurate data-driven quality prediction models for industrial blast furnaces encounters several challenges mainly because the collected data are nonlinear, non-Gaussian, and uneven distributed. A just-in-time correntropy-based local soft sensing approach is presented to predict the silicon content in this work. Without cumbersome efforts for outlier detection, a correntropy support vector regression (CSVR) modeling framework is proposed to deal with the soft sensor development and outlier detection simultaneously. Moreover, with a continuous updating database and a clustering strategy, a just-in-time CSVR (JCSVR) method is developed. Consequently, more accurate prediction and efficient implementations of JCSVR can be achieved. Better prediction performance of JCSVR is validated on the online silicon content prediction, compared with traditional soft sensors.

Just-in-Time Correntropy Soft Sensor with Noisy Data for Industrial Silicon Content Prediction

PubMed Central

Chen, Kun; Liang, Yu; Gao, Zengliang; Liu, Yi

2017-01-01

Development of accurate data-driven quality prediction models for industrial blast furnaces encounters several challenges mainly because the collected data are nonlinear, non-Gaussian, and uneven distributed. A just-in-time correntropy-based local soft sensing approach is presented to predict the silicon content in this work. Without cumbersome efforts for outlier detection, a correntropy support vector regression (CSVR) modeling framework is proposed to deal with the soft sensor development and outlier detection simultaneously. Moreover, with a continuous updating database and a clustering strategy, a just-in-time CSVR (JCSVR) method is developed. Consequently, more accurate prediction and efficient implementations of JCSVR can be achieved. Better prediction performance of JCSVR is validated on the online silicon content prediction, compared with traditional soft sensors. PMID:28786957

Forecasting Global Horizontal Irradiance Using the LETKF and a Combination of Advected Satellite Images and Sparse Ground Sensors

NASA Astrophysics Data System (ADS)

Harty, T. M.; Lorenzo, A.; Holmgren, W.; Morzfeld, M.

2017-12-01

The irradiance incident on a solar panel is the main factor in determining the power output of that panel. For this reason, accurate global horizontal irradiance (GHI) estimates and forecasts are critical when determining the optimal location for a solar power plant, forecasting utility scale solar power production, or forecasting distributed, behind the meter rooftop solar power production. Satellite images provide a basis for producing the GHI estimates needed to undertake these objectives. The focus of this work is to combine satellite derived GHI estimates with ground sensor measurements and an advection model. The idea is to use accurate but sparsely distributed ground sensors to improve satellite derived GHI estimates which can cover large areas (the size of a city or a region of the United States). We use a Bayesian framework to perform the data assimilation, which enables us to produce irradiance forecasts and associated uncertainties which incorporate both satellite and ground sensor data. Within this framework, we utilize satellite images taken from the GOES-15 geostationary satellite (available every 15-30 minutes) as well as ground data taken from irradiance sensors and rooftop solar arrays (available every 5 minutes). The advection model, driven by wind forecasts from a numerical weather model, simulates cloud motion between measurements. We use the Local Ensemble Transform Kalman Filter (LETKF) to perform the data assimilation. We present preliminary results towards making such a system useful in an operational context. We explain how localization and inflation in the LETKF, perturbations of wind-fields, and random perturbations of the advection model, affect the accuracy of our estimates and forecasts. We present experiments showing the accuracy of our forecasted GHI over forecast-horizons of 15 mins to 1 hr. The limitations of our approach and future improvements are also discussed.

Localization Algorithms of Underwater Wireless Sensor Networks: A Survey

PubMed Central

Han, Guangjie; Jiang, Jinfang; Shu, Lei; Xu, Yongjun; Wang, Feng

2012-01-01

In Underwater Wireless Sensor Networks (UWSNs), localization is one of most important technologies since it plays a critical role in many applications. Motivated by widespread adoption of localization, in this paper, we present a comprehensive survey of localization algorithms. First, we classify localization algorithms into three categories based on sensor nodes’ mobility: stationary localization algorithms, mobile localization algorithms and hybrid localization algorithms. Moreover, we compare the localization algorithms in detail and analyze future research directions of localization algorithms in UWSNs. PMID:22438752

Mobile Wireless Sensor Networks for Advanced Soil Sensing and Ecosystem Monitoring

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

A method for atomic-level noncontact thermometry with electron energy distribution

NASA Astrophysics Data System (ADS)

Kinoshita, Ikuo; Tsukada, Chiharu; Ouchi, Kohei; Kobayashi, Eiichi; Ishii, Juntaro

2017-04-01

We devised a new method of determining the temperatures of materials with their electron-energy distributions. The Fermi-Dirac distribution convoluted with a linear combination of Gaussian and Lorentzian distributions was fitted to the photoelectron spectrum measured for the Au(110) single-crystal surface at liquid N2-cooled temperature. The fitting successfully determined the surface-local thermodynamic temperature and the energy resolution simultaneously from the photoelectron spectrum, without any preliminary results of other measurements. The determined thermodynamic temperature was 99 ± 2.1 K, which was in good agreement with the reference temperature of 98.5 ± 0.5 K measured using a silicon diode sensor attached to the sample holder.

Shape Sensing a Morphed Wing with an Optical Fiber Bragg Grating

NASA Technical Reports Server (NTRS)

Tai, Hsiang

2005-01-01

We suggest using distributed fiber Bragg sensors systems which were developed locally at Langley Research Center carefully placed on the wing surface to collect strain component information at each location. Then we used the fact that the rate change of slope in the definition of linear strain is very small and can be treated as a constant. Thereby the strain distribution information of a morphed surface can be reduced into a distribution of local slope information of a flat surface. In other words a morphed curve surface is replaced by the collection of individual flat surface of different slope. By assembling the height of individual flat surface, the morphed curved surface can be approximated. A more sophisticated graphic routine can be utilized to restore the curved morphed surface. With this information, the morphed wing can be further adjusted and controlled. A numerical demonstration is presented.

Propagation Modeling and Defending of a Mobile Sensor Worm in Wireless Sensor and Actuator Networks

PubMed Central

Wang, Tian; Wu, Qun; Wen, Sheng; Cai, Yiqiao; Tian, Hui; Chen, Yonghong; Wang, Baowei

2017-01-01

WSANs (Wireless Sensor and Actuator Networks) are derived from traditional wireless sensor networks by introducing mobile actuator elements. Previous studies indicated that mobile actuators can improve network performance in terms of data collection, energy supplementation, etc. However, according to our experimental simulations, the actuator’s mobility also causes the sensor worm to spread faster if an attacker launches worm attacks on an actuator and compromises it successfully. Traditional worm propagation models and defense strategies did not consider the diffusion with a mobile worm carrier. To address this new problem, we first propose a microscopic mathematical model to describe the propagation dynamics of the sensor worm. Then, a two-step local defending strategy (LDS) with a mobile patcher (a mobile element which can distribute patches) is designed to recover the network. In LDS, all recovering operations are only taken in a restricted region to minimize the cost. Extensive experimental results demonstrate that our model estimations are rather accurate and consistent with the actual spreading scenario of the mobile sensor worm. Moreover, on average, the LDS outperforms other algorithms by approximately 50% in terms of the cost. PMID:28098748

Omni-Directional Scanning Localization Method of a Mobile Robot Based on Ultrasonic Sensors.

PubMed

Mu, Wei-Yi; Zhang, Guang-Peng; Huang, Yu-Mei; Yang, Xin-Gang; Liu, Hong-Yan; Yan, Wen

2016-12-20

Improved ranging accuracy is obtained by the development of a novel ultrasonic sensor ranging algorithm, unlike the conventional ranging algorithm, which considers the divergence angle and the incidence angle of the ultrasonic sensor synchronously. An ultrasonic sensor scanning method is developed based on this algorithm for the recognition of an inclined plate and to obtain the localization of the ultrasonic sensor relative to the inclined plate reference frame. The ultrasonic sensor scanning method is then leveraged for the omni-directional localization of a mobile robot, where the ultrasonic sensors are installed on a mobile robot and follow the spin of the robot, the inclined plate is recognized and the position and posture of the robot are acquired with respect to the coordinate system of the inclined plate, realizing the localization of the robot. Finally, the localization method is implemented into an omni-directional scanning localization experiment with the independently researched and developed mobile robot. Localization accuracies of up to ±3.33 mm for the front, up to ±6.21 for the lateral and up to ±0.20° for the posture are obtained, verifying the correctness and effectiveness of the proposed localization method.

Large-Scale Wireless Temperature Monitoring System for Liquefied Petroleum Gas Storage Tanks

PubMed Central

Fan, Guangwen; Shen, Yu; Hao, Xiaowei; Yuan, Zongming; Zhou, Zhi

2015-01-01

Temperature distribution is a critical indicator of the health condition for Liquefied Petroleum Gas (LPG) storage tanks. In this paper, we present a large-scale wireless temperature monitoring system to evaluate the safety of LPG storage tanks. The system includes wireless sensors networks, high temperature fiber-optic sensors, and monitoring software. Finally, a case study on real-world LPG storage tanks proves the feasibility of the system. The unique features of wireless transmission, automatic data acquisition and management, local and remote access make the developed system a good alternative for temperature monitoring of LPG storage tanks in practical applications. PMID:26393596

Physical-mathematical model of optical radiation interaction with biological tissues

NASA Astrophysics Data System (ADS)

Kozlovska, Tetyana I.; Kolisnik, Peter F.; Zlepko, Sergey M.; Titova, Natalia V.; Pavlov, Volodymyr S.; Wójcik, Waldemar; Omiotek, Zbigniew; Kozhambardiyeva, Miergul; Zhanpeisova, Aizhan

2017-08-01

Remote photoplethysmography (PPG) imaging is an optical technique to remotely assess the local coetaneous microcirculation. In this paper, we present a model and supporting experiments confirming the contribution of skin inhomogeneity to the morphology of PPG waveforms. The physical-mathematical model of distribution of optical radiation in biological tissues was developed. It allows determining the change of intensity of optical radiation depending on such parameters as installation angle of the sensor, biological tissue thickness and the wavelength. We obtained graphics which represent changes of the optical radiation intensity that is registered by photodetector depending on installation angle of the sensor, biological tissue thickness and the extinction coefficient.

Wearable Sensor Localization Considering Mixed Distributed Sources in Health Monitoring Systems

PubMed Central

Wan, Liangtian; Han, Guangjie; Wang, Hao; Shu, Lei; Feng, Nanxing; Peng, Bao

2016-01-01

In health monitoring systems, the base station (BS) and the wearable sensors communicate with each other to construct a virtual multiple input and multiple output (VMIMO) system. In real applications, the signal that the BS received is a distributed source because of the scattering, reflection, diffraction and refraction in the propagation path. In this paper, a 2D direction-of-arrival (DOA) estimation algorithm for incoherently-distributed (ID) and coherently-distributed (CD) sources is proposed based on multiple VMIMO systems. ID and CD sources are separated through the second-order blind identification (SOBI) algorithm. The traditional estimating signal parameters via the rotational invariance technique (ESPRIT)-based algorithm is valid only for one-dimensional (1D) DOA estimation for the ID source. By constructing the signal subspace, two rotational invariant relationships are constructed. Then, we extend the ESPRIT to estimate 2D DOAs for ID sources. For DOA estimation of CD sources, two rational invariance relationships are constructed based on the application of generalized steering vectors (GSVs). Then, the ESPRIT-based algorithm is used for estimating the eigenvalues of two rational invariance matrices, which contain the angular parameters. The expressions of azimuth and elevation for ID and CD sources have closed forms, which means that the spectrum peak searching is avoided. Therefore, compared to the traditional 2D DOA estimation algorithms, the proposed algorithm imposes significantly low computational complexity. The intersecting point of two rays, which come from two different directions measured by two uniform rectangle arrays (URA), can be regarded as the location of the biosensor (wearable sensor). Three BSs adopting the smart antenna (SA) technique cooperate with each other to locate the wearable sensors using the angulation positioning method. Simulation results demonstrate the effectiveness of the proposed algorithm. PMID:26985896

Wearable Sensor Localization Considering Mixed Distributed Sources in Health Monitoring Systems.

PubMed

Wan, Liangtian; Han, Guangjie; Wang, Hao; Shu, Lei; Feng, Nanxing; Peng, Bao

2016-03-12

In health monitoring systems, the base station (BS) and the wearable sensors communicate with each other to construct a virtual multiple input and multiple output (VMIMO) system. In real applications, the signal that the BS received is a distributed source because of the scattering, reflection, diffraction and refraction in the propagation path. In this paper, a 2D direction-of-arrival (DOA) estimation algorithm for incoherently-distributed (ID) and coherently-distributed (CD) sources is proposed based on multiple VMIMO systems. ID and CD sources are separated through the second-order blind identification (SOBI) algorithm. The traditional estimating signal parameters via the rotational invariance technique (ESPRIT)-based algorithm is valid only for one-dimensional (1D) DOA estimation for the ID source. By constructing the signal subspace, two rotational invariant relationships are constructed. Then, we extend the ESPRIT to estimate 2D DOAs for ID sources. For DOA estimation of CD sources, two rational invariance relationships are constructed based on the application of generalized steering vectors (GSVs). Then, the ESPRIT-based algorithm is used for estimating the eigenvalues of two rational invariance matrices, which contain the angular parameters. The expressions of azimuth and elevation for ID and CD sources have closed forms, which means that the spectrum peak searching is avoided. Therefore, compared to the traditional 2D DOA estimation algorithms, the proposed algorithm imposes significantly low computational complexity. The intersecting point of two rays, which come from two different directions measured by two uniform rectangle arrays (URA), can be regarded as the location of the biosensor (wearable sensor). Three BSs adopting the smart antenna (SA) technique cooperate with each other to locate the wearable sensors using the angulation positioning method. Simulation results demonstrate the effectiveness of the proposed algorithm.

A Local Scalable Distributed Expectation Maximization Algorithm for Large Peer-to-Peer Networks

NASA Technical Reports Server (NTRS)

Bhaduri, Kanishka; Srivastava, Ashok N.

2009-01-01

This paper offers a local distributed algorithm for expectation maximization in large peer-to-peer environments. The algorithm can be used for a variety of well-known data mining tasks in a distributed environment such as clustering, anomaly detection, target tracking to name a few. This technology is crucial for many emerging peer-to-peer applications for bioinformatics, astronomy, social networking, sensor networks and web mining. Centralizing all or some of the data for building global models is impractical in such peer-to-peer environments because of the large number of data sources, the asynchronous nature of the peer-to-peer networks, and dynamic nature of the data/network. The distributed algorithm we have developed in this paper is provably-correct i.e. it converges to the same result compared to a similar centralized algorithm and can automatically adapt to changes to the data and the network. We show that the communication overhead of the algorithm is very low due to its local nature. This monitoring algorithm is then used as a feedback loop to sample data from the network and rebuild the model when it is outdated. We present thorough experimental results to verify our theoretical claims.

Game theoretic sensor management for target tracking

NASA Astrophysics Data System (ADS)

Shen, Dan; Chen, Genshe; Blasch, Erik; Pham, Khanh; Douville, Philip; Yang, Chun; Kadar, Ivan

2010-04-01

This paper develops and evaluates a game-theoretic approach to distributed sensor-network management for target tracking via sensor-based negotiation. We present a distributed sensor-based negotiation game model for sensor management for multi-sensor multi-target tacking situations. In our negotiation framework, each negotiation agent represents a sensor and each sensor maximizes their utility using a game approach. The greediness of each sensor is limited by the fact that the sensor-to-target assignment efficiency will decrease if too many sensor resources are assigned to a same target. It is similar to the market concept in real world, such as agreements between buyers and sellers in an auction market. Sensors are willing to switch targets so that they can obtain their highest utility and the most efficient way of applying their resources. Our sub-game perfect equilibrium-based negotiation strategies dynamically and distributedly assign sensors to targets. Numerical simulations are performed to demonstrate our sensor-based negotiation approach for distributed sensor management.

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.

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.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

I-DWRL: Improved Dual Wireless Radio Localization Using Magnetometer.

PubMed

Aziz, Abdul; Kumar, Ramesh; Joe, Inwhee

2017-11-15

In the dual wireless radio localization (DWRL) technique each sensor node is equipped with two ultra-wide band (UWB) radios; the distance between the two radios is a few tens of centimeters. For localization, the DWRL technique must use at least two pre-localized nodes to fully localize an unlocalized node. Moreover, in the DWRL technique it is also not possible for two sensor nodes to properly communicate location information unless each of the four UWB radios of two communicating sensor nodes cannot approach the remaining three radios. In this paper, we propose an improved DWRL (I-DWRL) algorithm along with mounting a magnetometer sensor on one of the UWB radios of all sensor nodes. This addition of a magnetometer helps to improve DWRL algorithm such that only one localized sensor node is required for the localization of an unlocalized sensor node, and localization can also be achieved even when some of the four radios of two nodes are unable to communicate with the remaining three radios. The results show that with the use of a magnetometer a greater number of nodes can be localized with a smaller transmission range, less energy and a shorter period of time. In comparison with the conventional DWRL algorithm, our I-DWRL not only maintains the localization error but also requires around half of semi-localizations, 60% of the time, 70% of the energy and a shorter communication range to fully localize an entire network. Moreover, I-DWRL can even localize more nodes while transmission range is not sufficient for DWRL algorithm.

I-DWRL: Improved Dual Wireless Radio Localization Using Magnetometer

PubMed Central

Aziz, Abdul; Kumar, Ramesh; Joe, Inwhee

2017-01-01

In the dual wireless radio localization (DWRL) technique each sensor node is equipped with two ultra-wide band (UWB) radios; the distance between the two radios is a few tens of centimeters. For localization, the DWRL technique must use at least two pre-localized nodes to fully localize an unlocalized node. Moreover, in the DWRL technique it is also not possible for two sensor nodes to properly communicate location information unless each of the four UWB radios of two communicating sensor nodes cannot approach the remaining three radios. In this paper, we propose an improved DWRL (I-DWRL) algorithm along with mounting a magnetometer sensor on one of the UWB radios of all sensor nodes. This addition of a magnetometer helps to improve DWRL algorithm such that only one localized sensor node is required for the localization of an unlocalized sensor node, and localization can also be achieved even when some of the four radios of two nodes are unable to communicate with the remaining three radios. The results show that with the use of a magnetometer a greater number of nodes can be localized with a smaller transmission range, less energy and a shorter period of time. In comparison with the conventional DWRL algorithm, our I-DWRL not only maintains the localization error but also requires around half of semi-localizations, 60% of the time, 70% of the energy and a shorter communication range to fully localize an entire network. Moreover, I-DWRL can even localize more nodes while transmission range is not sufficient for DWRL algorithm. PMID:29140291

Lightweight Filter Architecture for Energy Efficient Mobile Vehicle Localization Based on a Distributed Acoustic Sensor Network

PubMed Central

Kim, Keonwook

2013-01-01

The generic properties of an acoustic signal provide numerous benefits for localization by applying energy-based methods over a deployed wireless sensor network (WSN). However, the signal generated by a stationary target utilizes a significant amount of bandwidth and power in the system without providing further position information. For vehicle localization, this paper proposes a novel proximity velocity vector estimator (PVVE) node architecture in order to capture the energy from a moving vehicle and reject the signal from motionless automobiles around the WSN node. A cascade structure between analog envelope detector and digital exponential smoothing filter presents the velocity vector-sensitive output with low analog circuit and digital computation complexity. The optimal parameters in the exponential smoothing filter are obtained by analytical and mathematical methods for maximum variation over the vehicle speed. For stationary targets, the derived simulation based on the acoustic field parameters demonstrates that the system significantly reduces the communication requirements with low complexity and can be expected to extend the operation time considerably. PMID:23979482

Multisite Testing of the Discrete Address Beacon System (DABS).

DTIC Science & Technology

1981-07-01

downlink messages from an airborne distributed computer system containing , transponder in addition to performing 36 minicomputers, most of which are...the lockout function. organized into groups (or ensembles) of four computers interfaced to a local Each sensor may provide surveillance and data bus...position and velocity. Depending upon computer subsystem, which monitors the means used for scenario generation, in real time all communication and aircraft

ARO PECASE: Information Assurance for Energy-Constrained Wireless Sensor Networks

DTIC Science & Technology

2011-12-21

Distribution, 18th Annual IEEE International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), September 2007. 2. 2010 IEEE...received the following awards: Student Best Paper Award at the IEEE International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC...Localization in Wireless Ad Hoc Networks – Many current and future appli- cations of mobile ad hoc networks, including disaster response and event

Research on the strategy of underwater united detection fusion and communication using multi-sensor

NASA Astrophysics Data System (ADS)

Xu, Zhenhua; Huang, Jianguo; Huang, Hai; Zhang, Qunfei

2011-09-01

In order to solve the distributed detection fusion problem of underwater target detection, when the signal to noise ratio (SNR) of the acoustic channel is low, a new strategy for united detection fusion and communication using multiple sensors was proposed. The performance of detection fusion was studied and compared based on the Neyman-Pearson principle when the binary phase shift keying (BPSK) and on-off keying (OOK) modes were used by the local sensors. The comparative simulation and analysis between the optimal likelihood ratio test and the proposed strategy was completed, and both the theoretical analysis and simulation indicate that using the proposed new strategy could improve the detection performance effectively. In theory, the proposed strategy of united detection fusion and communication is of great significance to the establishment of an underwater target detection system.

A General theory of Signal Integration for Fault-Tolerant Dynamic Distributed Sensor Networks

DTIC Science & Technology

1993-10-01

related to a) the architecture and fault- tolerance of the distributed sensor network, b) the proper synchronisation of sensor signals, c) the...Computational complexities of the problem of distributed detection. 5) Issues related to recording of events and synchronization in distributed sensor...Intervals for Synchronization in Real Time Distributed Systems", Submitted to Electronic Encyclopedia. 3. V. G. Hegde and S. S. Iyengar "Efficient

Flexible distributed architecture for semiconductor process control and experimentation

NASA Astrophysics Data System (ADS)

Gower, Aaron E.; Boning, Duane S.; McIlrath, Michael B.

1997-01-01

Semiconductor fabrication requires an increasingly expensive and integrated set of tightly controlled processes, driving the need for a fabrication facility with fully computerized, networked processing equipment. We describe an integrated, open system architecture enabling distributed experimentation and process control for plasma etching. The system was developed at MIT's Microsystems Technology Laboratories and employs in-situ CCD interferometry based analysis in the sensor-feedback control of an Applied Materials Precision 5000 Plasma Etcher (AME5000). Our system supports accelerated, advanced research involving feedback control algorithms, and includes a distributed interface that utilizes the internet to make these fabrication capabilities available to remote users. The system architecture is both distributed and modular: specific implementation of any one task does not restrict the implementation of another. The low level architectural components include a host controller that communicates with the AME5000 equipment via SECS-II, and a host controller for the acquisition and analysis of the CCD sensor images. A cell controller (CC) manages communications between these equipment and sensor controllers. The CC is also responsible for process control decisions; algorithmic controllers may be integrated locally or via remote communications. Finally, a system server images connections from internet/intranet (web) based clients and uses a direct link with the CC to access the system. Each component communicates via a predefined set of TCP/IP socket based messages. This flexible architecture makes integration easier and more robust, and enables separate software components to run on the same or different computers independent of hardware or software platform.

Performance of an untethered micro-optical pressure sensor

NASA Astrophysics Data System (ADS)

Ioppolo, Tindaro; Manzo, Maurizio; Krueger, Paul

2012-11-01

We present analytical and computational studies of the performance of a novel untethered micro-optical pressure sensor for fluid dynamics measurements. In particular, resolution and dynamic range will be presented. The sensor concept is based on the whispering galley mode (WGM) shifts that are observed in micro-scale dielectric optical cavities. A micro-spherical optical cavity (liquid or solid) is embedded in a thin polymeric sheet. The applied external pressure perturbs the morphology of the optical cavity leading to a shift in its optical resonances. The optical sensors are interrogated remotely, by embedding quantum dots or fluorescent dye in the micro-optical cavity. This allows a free space coupling of excitation and monitoring of the optical modes without the need of optical fibers or other cabling. With appropriate excitation and monitoring equipment, the micro-scale sensors can be distributed over a surface (e.g., including flexible biological surfaces) to monitor the local pressure field. We acknowledge the financial support from the National Science Foundation through grant CBET-1133876 with Dr. Horst Henning Winter as the program director.

Sensor Web for Spatio-Temporal Monitoring of a Hydrological Environment

NASA Technical Reports Server (NTRS)

Delin, K. A.; Jackson, S. P.; Johnson, D. W.; Burleigh, S. C.; Woodrow, R. R.; McAuley, M.; Britton, J. T.; Dohm, J. M.; Ferre, T. P. A.; Ip, Felipe

2004-01-01

The Sensor Web is a macroinstrument concept that allows for the spatio-temporal understanding of an environment through coordinated efforts between multiple numbers and types of sensing platforms, including, in its most general form, both orbital and terrestrial and both fixed and mobile. Each of these platforms, or pods, communicates within its local neighborhood and thus distributes information to the instrument as a whole. The result of sharing and continual processing of this information among all the Sensor Web elements will result in an information flow and a global perception of and reactive capability to the environment. As illustrated, the Sensor Web concept also allows for the recursive notion of a web of webs with individual distributed instruments possibly playing the role of a single node point on a larger Sensor Web instrument. In particular, the fusion of inexpensive, yet sophisticated, commercial technology from both the computation and telecommunication revolutions has enabled the development of practical, fielded, and embedded in situ systems that have been the focus of the NASA/JPL Sensor Webs Project (http://sensorwebs.jpl.nasa.gov/). These Sensor Webs are complete systems consisting of not only the pod elements that wirelessly communicate among themselves, but also interfacing and archiving software that allows for easy use by the end-user. Previous successful deployments have included environments as diverse as coastal regions, Antarctica, and desert areas. The Sensor Web has broad implications for Earth and planetary science and will revolutionize the way experiments and missions are conceived and performed. As part of our current efforts to develop a macrointelligence within the system, we have deployed a Sensor Web at the Central Avra Valley Storage and Recovery Project (CAVSARP) facility located west of Tucson, AZ. This particular site was selected because it is ideal for studying spatio-temporal phenomena and for providing a test site for more sophisticated hydrological studies in the future.

Design architecture for multi-zone HVAC control systems from existing single-zone systems using wireless sensor networks

NASA Astrophysics Data System (ADS)

Redfern, Andrew; Koplow, Michael; Wright, Paul

2007-01-01

Most residential heating, ventilating, and air-conditioning (HVAC) systems utilize a single zone for conditioning air throughout the entire house. While inexpensive, these systems lead to wide temperature distributions and inefficient cooling due to the difference in thermal loads in different rooms. The end result is additional cost to the end user because the house is over conditioned. To reduce the total amount of energy used in a home and to increase occupant comfort there is a need for a better control system using multiple temperature zones. Typical multi-zone systems are costly and require extensive infrastructure to function. Recent advances in wireless sensor networks (WSNs) have enabled a low cost drop-in wireless vent register control system. The register control system is controlled by a master controller unit, which collects sensor data from a distributed wireless sensor network. Each sensor node samples local settings (occupancy, light, humidity and temperature) and reports the data back to the master control unit. The master control unit compiles the incoming data and then actuates the vent resisters to control the airflow throughout the house. The control system also utilizes a smart thermostat with a movable set point to enable the user to define their given comfort levels. The new system can reduce the run time of the HVAC system and thus decreasing the amount of energy used and increasing the comfort of the home occupations.

On distributed wavefront reconstruction for large-scale adaptive optics systems.

PubMed

de Visser, Cornelis C; Brunner, Elisabeth; Verhaegen, Michel

2016-05-01

The distributed-spline-based aberration reconstruction (D-SABRE) method is proposed for distributed wavefront reconstruction with applications to large-scale adaptive optics systems. D-SABRE decomposes the wavefront sensor domain into any number of partitions and solves a local wavefront reconstruction problem on each partition using multivariate splines. D-SABRE accuracy is within 1% of a global approach with a speedup that scales quadratically with the number of partitions. The D-SABRE is compared to the distributed cumulative reconstruction (CuRe-D) method in open-loop and closed-loop simulations using the YAO adaptive optics simulation tool. D-SABRE accuracy exceeds CuRe-D for low levels of decomposition, and D-SABRE proved to be more robust to variations in the loop gain.

Particle Filter-Based Recursive Data Fusion With Sensor Indexing for Large Core Neutron Flux Estimation

NASA Astrophysics Data System (ADS)

Tamboli, Prakash Kumar; Duttagupta, Siddhartha P.; Roy, Kallol

2017-06-01

We introduce a sequential importance sampling particle filter (PF)-based multisensor multivariate nonlinear estimator for estimating the in-core neutron flux distribution for pressurized heavy water reactor core. Many critical applications such as reactor protection and control rely upon neutron flux information, and thus their reliability is of utmost importance. The point kinetic model based on neutron transport conveniently explains the dynamics of nuclear reactor. The neutron flux in the large core loosely coupled reactor is sensed by multiple sensors measuring point fluxes located at various locations inside the reactor core. The flux values are coupled to each other through diffusion equation. The coupling facilitates redundancy in the information. It is shown that multiple independent data about the localized flux can be fused together to enhance the estimation accuracy to a great extent. We also propose the sensor anomaly handling feature in multisensor PF to maintain the estimation process even when the sensor is faulty or generates data anomaly.

The spectral positioning algorithm of new spectrum vehicle based on convex programming in wireless sensor network

NASA Astrophysics Data System (ADS)

Zhang, Yongjun; Lu, Zhixin

2017-10-01

Spectrum resources are very precious, so it is increasingly important to locate interference signals rapidly. Convex programming algorithms in wireless sensor networks are often used as localization algorithms. But in view of the traditional convex programming algorithm is too much overlap of wireless sensor nodes that bring low positioning accuracy, the paper proposed a new algorithm. Which is mainly based on the traditional convex programming algorithm, the spectrum car sends unmanned aerial vehicles (uses) that can be used to record data periodically along different trajectories. According to the probability density distribution, the positioning area is segmented to further reduce the location area. Because the algorithm only increases the communication process of the power value of the unknown node and the sensor node, the advantages of the convex programming algorithm are basically preserved to realize the simple and real-time performance. The experimental results show that the improved algorithm has a better positioning accuracy than the original convex programming algorithm.

Localization Strategies in WSNs as applied to Landslide Monitoring (Invited)

NASA Astrophysics Data System (ADS)

Massa, A.; Robol, F.; Polo, A.; Giarola, E.; Viani, F.

2013-12-01

In the last years, heterogeneous integrated smart systems based on wireless sensor network (WSN) technology have been developed at the ELEDIA Research Center of the University of Trento [1]. One of the key features of WSNs as applied to distributed monitoring is that, while the capabilities of each single sensor node is limited, the implementation of cooperative schemes throughout the whole network enables the solution of even complex tasks, as the landslide monitoring. The capability of localizing targets respect to the position of the sensor nodes turns out to be fundamental in those application fields where relative movements arise. The main properties like the target typology, the movement characteristics, and the required localization resolution are different changing the reference scenario. However, the common key issue is still the localization of moving targets within the area covered by the sensor network. Many experiences were preparatory for the challenging activities in the field of landslide monitoring where the basic idea is mostly that of detecting slight soil movements. Among them, some examples of WSN-based systems experimentally applied to the localization of people [2] and wildlife [3] have been proposed. More recently, the WSN backbone as well as the investigated sensing technologies have been customized for monitoring superficial movements of the soil. The relative positions of wireless sensor nodes deployed where high probability of landslide exists is carefully monitored to forecast dangerous events. Multiple sensors like ultrasound, laser, high precision GPS, for the precise measurement of relative distances between the nodes of the network and the absolute positions respect to reference targets have been integrated in a prototype system. The millimeter accuracy in the position estimation enables the detection of small soil modifications and to infer the superficial evolution profile of the landslide. This information locally acquired also represent a fine tuning of large scale satellite acquisitions, usually adopted for remote sensing of landslides. The integration of dense and frequent WSN data within satellite image analysis will enhance the sensing capabilities leading to a multi-resolution and an highly space-time calibrated system. The WSN-based system has been preliminary tested in controlled environments in the ELEDIA laboratories and is now installed in a real test site where an active landslide is evolving. Preliminary data are here presented to assess the feasibility of the investigated solution in landslide monitoring and event forecasting. REFERENCES [1] M. Benedetti, L. Ioriatti, M. Martinelli, and F. Viani, 'Wireless sensor network: a pervasive technology for earth observation,' in IEEE Journal of Selected Topics in App. Earth Obs. And Remote Sens., vol. 3, no. 4, pp. 488-497, 2010. [2] F. Viani, M. Donelli, P. Rocca, G. Oliveri, D. Trinchero, and A. Massa, 'Localization, tracking and imaging of targets in wireless sensor networks,' Radio Science, vol. 46, no. 5, 2011. [3] F. Viani, F. Robol, M. Salucci, E. Giarola, S. De Vigili, M. Rocca, F. Boldrini, G. Benedetti, and A. Massa, 'WSN-based early alert system for preventing wildlife-vehicle collisions in Alps regions - From the laboratory test to the real-world implementation,' 7th European Conference on Antennas and Propagation 2013 (EUCAP2013), Gothenburg, Sweden, April 8-12, 2013.

Integration of piezo-capacitive and piezo-electric nanoweb based pressure sensors for imaging of static and dynamic pressure distribution.

PubMed

Jeong, Y J; Oh, T I; Woo, E J; Kim, K J

2017-07-01

Recently, highly flexible and soft pressure distribution imaging sensor is in great demand for tactile sensing, gait analysis, ubiquitous life-care based on activity recognition, and therapeutics. In this study, we integrate the piezo-capacitive and piezo-electric nanowebs with the conductive fabric sheets for detecting static and dynamic pressure distributions on a large sensing area. Electrical impedance tomography (EIT) and electric source imaging are applied for reconstructing pressure distribution images from measured current-voltage data on the boundary of the hybrid fabric sensor. We evaluated the piezo-capacitive nanoweb sensor, piezo-electric nanoweb sensor, and hybrid fabric sensor. The results show the feasibility of static and dynamic pressure distribution imaging from the boundary measurements of the fabric sensors.

Collaborative localization in wireless sensor networks via pattern recognition in radio irregularity using omnidirectional antennas.

PubMed

Jiang, Joe-Air; Chuang, Cheng-Long; Lin, Tzu-Shiang; Chen, Chia-Pang; Hung, Chih-Hung; Wang, Jiing-Yi; Liu, Chang-Wang; Lai, Tzu-Yun

2010-01-01

In recent years, various received signal strength (RSS)-based localization estimation approaches for wireless sensor networks (WSNs) have been proposed. RSS-based localization is regarded as a low-cost solution for many location-aware applications in WSNs. In previous studies, the radiation patterns of all sensor nodes are assumed to be spherical, which is an oversimplification of the radio propagation model in practical applications. In this study, we present an RSS-based cooperative localization method that estimates unknown coordinates of sensor nodes in a network. Arrangement of two external low-cost omnidirectional dipole antennas is developed by using the distance-power gradient model. A modified robust regression is also proposed to determine the relative azimuth and distance between a sensor node and a fixed reference node. In addition, a cooperative localization scheme that incorporates estimations from multiple fixed reference nodes is presented to improve the accuracy of the localization. The proposed method is tested via computer-based analysis and field test. Experimental results demonstrate that the proposed low-cost method is a useful solution for localizing sensor nodes in unknown or changing environments.

Simultaneous measurement of sensor-protein dynamics and motility of a single cell by on-chip microcultivation system

PubMed Central

Inoue, Ippei; Shiomi, Daisuke; Kawagishi, Ikuro; Yasuda, Kenji

2004-01-01

Measurement of the correlation between sensor-protein expression, motility and environmental change is important for understanding the adaptation process of cells during their change of generation. We have developed a novel assay exploiting the on-chip cultivation system, which enabled us to observe the change of the localization of expressed sensor-protein and the motility for generations. Localization of the aspartate sensitive sensor protein at two poles in Escherichia coli decreased quickly after the aspartate was added into the cultivation medium. However, it took more than three generations for recovering the localization after the removal of aspartate from the medium. Moreover, the tumbling frequency was strongly related to the localization of the sensor protein in a cell. The results indicate that the change of the spatial localization of sensor protein, which was inherited for more than three generations, may contribute to cells, motility as the inheritable information. PMID:15119953

Design Optimization and Fabrication of a Novel Structural SOI Piezoresistive Pressure Sensor with High Accuracy

PubMed Central

Li, Chuang; Cordovilla, Francisco; Jagdheesh, R.

2018-01-01

This paper presents a novel structural piezoresistive pressure sensor with four-grooved membrane combined with rood beam to measure low pressure. In this investigation, the design, optimization, fabrication, and measurements of the sensor are involved. By analyzing the stress distribution and deflection of sensitive elements using finite element method, a novel structure featuring high concentrated stress profile (HCSP) and locally stiffened membrane (LSM) is built. Curve fittings of the mechanical stress and deflection based on FEM simulation results are performed to establish the relationship between mechanical performance and structure dimension. A combination of FEM and curve fitting method is carried out to determine the structural dimensions. The optimized sensor chip is fabricated on a SOI wafer by traditional MEMS bulk-micromachining and anodic bonding technology. When the applied pressure is 1 psi, the sensor achieves a sensitivity of 30.9 mV/V/psi, a pressure nonlinearity of 0.21% FSS and an accuracy of 0.30%, and thereby the contradiction between sensitivity and linearity is alleviated. In terms of size, accuracy and high temperature characteristic, the proposed sensor is a proper choice for measuring pressure of less than 1 psi. PMID:29393916

Control of the Intrinsic Sensor Response to Volatile Organic Compounds with Fringing Electric Fields.

PubMed

Henning, Alex; Swaminathan, Nandhini; Vaknin, Yonathan; Jurca, Titel; Shimanovich, Klimentiy; Shalev, Gil; Rosenwaks, Yossi

2018-01-26

The ability to control surface-analyte interaction allows tailoring chemical sensor sensitivity to specific target molecules. By adjusting the bias of the shallow p-n junctions in the electrostatically formed nanowire (EFN) chemical sensor, a multiple gate transistor with an exposed top dielectric layer allows tuning of the fringing electric field strength (from 0.5 × 10 7 to 2.5 × 10 7 V/m) above the EFN surface. Herein, we report that the magnitude and distribution of this fringing electric field correlate with the intrinsic sensor response to volatile organic compounds. The local variations of the surface electric field influence the analyte-surface interaction affecting the work function of the sensor surface, assessed by Kelvin probe force microscopy on the nanometer scale. We show that the sensitivity to fixed vapor analyte concentrations can be nullified and even reversed by varying the fringing field strength, and demonstrate selectivity between ethanol and n-butylamine at room temperature using a single transistor without any extrinsic chemical modification of the exposed SiO 2 surface. The results imply an electric-field-controlled analyte reaction with a dielectric surface extremely compelling for sensitivity and selectivity enhancement in chemical sensors.

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

PubMed

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

2013-08-12

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

A Support Vector Learning-Based Particle Filter Scheme for Target Localization in Communication-Constrained Underwater Acoustic Sensor Networks

PubMed Central

Zhang, Chenglin; Yan, Lei; Han, Song; Guan, Xinping

2017-01-01

Target localization, which aims to estimate the location of an unknown target, is one of the key issues in applications of underwater acoustic sensor networks (UASNs). However, the constrained property of an underwater environment, such as restricted communication capacity of sensor nodes and sensing noises, makes target localization a challenging problem. This paper relies on fractional sensor nodes to formulate a support vector learning-based particle filter algorithm for the localization problem in communication-constrained underwater acoustic sensor networks. A node-selection strategy is exploited to pick fractional sensor nodes with short-distance pattern to participate in the sensing process at each time frame. Subsequently, we propose a least-square support vector regression (LSSVR)-based observation function, through which an iterative regression strategy is used to deal with the distorted data caused by sensing noises, to improve the observation accuracy. At the same time, we integrate the observation to formulate the likelihood function, which effectively update the weights of particles. Thus, the particle effectiveness is enhanced to avoid “particle degeneracy” problem and improve localization accuracy. In order to validate the performance of the proposed localization algorithm, two different noise scenarios are investigated. The simulation results show that the proposed localization algorithm can efficiently improve the localization accuracy. In addition, the node-selection strategy can effectively select the subset of sensor nodes to improve the communication efficiency of the sensor network. PMID:29267252

A Support Vector Learning-Based Particle Filter Scheme for Target Localization in Communication-Constrained Underwater Acoustic Sensor Networks.

PubMed

Li, Xinbin; Zhang, Chenglin; Yan, Lei; Han, Song; Guan, Xinping

2017-12-21

Target localization, which aims to estimate the location of an unknown target, is one of the key issues in applications of underwater acoustic sensor networks (UASNs). However, the constrained property of an underwater environment, such as restricted communication capacity of sensor nodes and sensing noises, makes target localization a challenging problem. This paper relies on fractional sensor nodes to formulate a support vector learning-based particle filter algorithm for the localization problem in communication-constrained underwater acoustic sensor networks. A node-selection strategy is exploited to pick fractional sensor nodes with short-distance pattern to participate in the sensing process at each time frame. Subsequently, we propose a least-square support vector regression (LSSVR)-based observation function, through which an iterative regression strategy is used to deal with the distorted data caused by sensing noises, to improve the observation accuracy. At the same time, we integrate the observation to formulate the likelihood function, which effectively update the weights of particles. Thus, the particle effectiveness is enhanced to avoid "particle degeneracy" problem and improve localization accuracy. In order to validate the performance of the proposed localization algorithm, two different noise scenarios are investigated. The simulation results show that the proposed localization algorithm can efficiently improve the localization accuracy. In addition, the node-selection strategy can effectively select the subset of sensor nodes to improve the communication efficiency of the sensor network.

Distributed-effect optical fiber sensors for trusses and plates

NASA Technical Reports Server (NTRS)

Reichard, Karl; Lindner, Douglas K.

1991-01-01

Modal domain optical fiber sensors, or distributed effect sensors, for active vibration suppression in flexible structures are considered. Preliminary modeling results indicate that these sensors can be used to sense vibrations in a flexible beam and the signal can be used to damp vibrations in the beam. Weighted distributed-effect sensors can be used to implement high order compensators with low order functional observers.

Compressed sampling and dictionary learning framework for wavelength-division-multiplexing-based distributed fiber sensing.

PubMed

Weiss, Christian; Zoubir, Abdelhak M

2017-05-01

We propose a compressed sampling and dictionary learning framework for fiber-optic sensing using wavelength-tunable lasers. A redundant dictionary is generated from a model for the reflected sensor signal. Imperfect prior knowledge is considered in terms of uncertain local and global parameters. To estimate a sparse representation and the dictionary parameters, we present an alternating minimization algorithm that is equipped with a preprocessing routine to handle dictionary coherence. The support of the obtained sparse signal indicates the reflection delays, which can be used to measure impairments along the sensing fiber. The performance is evaluated by simulations and experimental data for a fiber sensor system with common core architecture.

Fiber optic distributed chemical sensor for the real time detection of hydrocarbon fuel leaks

NASA Astrophysics Data System (ADS)

Mendoza, Edgar; Kempen, C.; Esterkin, Yan; Sun, Sunjian

2015-09-01

With the increase worldwide demand for hydrocarbon fuels and the vast development of new fuel production and delivery infrastructure installations around the world, there is a growing need for reliable hydrocarbon fuel leak detection technologies to provide safety and reduce environmental risks. Hydrocarbon leaks (gas or liquid) pose an extreme danger and need to be detected very quickly to avoid potential disasters. Gas leaks have the greatest potential for causing damage due to the explosion risk from the dispersion of gas clouds. This paper describes progress towards the development of a fast response, high sensitivity, distributed fiber optic fuel leak detection (HySense™) system based on the use of an optical fiber that uses a hydrocarbon sensitive fluorescent coating to detect the presence of fuel leaks present in close proximity along the length of the sensor fiber. The HySense™ system operates in two modes, leak detection and leak localization, and will trigger an alarm within seconds of exposure contact. The fast and accurate response of the sensor provides reliable fluid leak detection for pipelines, storage tanks, airports, pumps, and valves to detect and minimize any potential catastrophic damage.

Sensor/Transducer Bus Alternatives for Space derived from Automotive Networks

NASA Astrophysics Data System (ADS)

Heyer, H.-V.

2004-06-01

Both automotive and space industry have major constraints concerning cable and harness. As in a satellite, the dry mass of the harness in the empty car is about 3.3% of the total car mass and the harness costs are about 12% of the total production cost. So a lot of new architectural communication and power distribution concepts are needed to reduce these drawbacks. One of the possible solutions is the use of distributed bus systems which contains in a decentralized topology busses such as CAN, TTCAN or FLEX-RAY for hard-real-time applications, MOST for fast video communication via optical fiber cabling and fire wire IEEE1394 as backbone.For the general purpose sensor/actuator tasks a simple robust one-wire bus has been defined, the Local Interconnect Network (LIN) bus. This bus is an open standard which is supported by several semiconductor manufactures. The bus was firstly introduced in 1999 and has now reached an acceptable maturity with version 2.0 turning out to be quite interesting as sensor / transducer bus for space applications.This presentation will focus on the LIN Bus and present an overview of that bus.

Respiration and heartbeat monitoring using a distributed pulsed MIMO radar.

PubMed

Walterscheid, Ingo; Smith, Graeme E

2017-07-01

This paper addresses non-contact monitoring of physiological signals induced by respiration and heartbeat. To detect the tiny physiological movements of the chest or other parts of the torso, a Mulitple-Input Multiple-Output (MIMO) radar is used. The spatially distributed transmitters and receivers are able to detect the chest surface movements of one or multiple persons in a room. Due to several bistatic measurements at the same time a robust detection and measuring of the breathing and heartbeat rate is possible. Using an appropriate geometrical configuration of the sensors even a localization of the person is feasible.

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

PubMed

Luo, Junhai; Fan, Liying

2017-03-30

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

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

PubMed Central

Luo, Junhai; Fan, Liying

2017-01-01

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

Numerical and experimental study on vorticity measurement in liquid metal using local Lorentz force velocimetry

NASA Astrophysics Data System (ADS)

Hernández, Daniel; Marangoni, Rafael; Schleichert, Jan; Karcher, Christian; Fröhlich, Thomas; Wondrak, Thomas

2018-03-01

Local Lorentz force velocimetry (local LFV) is a contactless velocity measurement technique for liquid metals. Due to the relative movement between an electrically conductive fluid and a static applied magnetic field, eddy currents and a flow-braking Lorentz force are generated inside the metal melt. This force is proportional to the flow rate or to the local velocity, depending on the volume subset of the flow spanned by the magnetic field. By using small-size magnets, a localized magnetic field distribution is achieved allowing a local velocity assessment in the region adjacent to the wall. In the present study, we describe a numerical model of our experiments at a continuous caster model where the working fluid is GaInSn in eutectic composition. Our main goal is to demonstrate that this electromagnetic technique can be applied to measure vorticity distributions, i.e. to resolve velocity gradients as well. Our results show that by using a cross-shaped magnet system, the magnitude of the torque perpendicular to the surface of the mold significantly increases improving its measurement in a liquid metal flow. According to our numerical model, this torque correlates with the vorticity of the velocity in this direction. Before validating our numerical predictions, an electromagnetic dry calibration of the measurement system composed of a multicomponent force and torque sensor and a cross-shaped magnet was done using a rotating disk made of aluminum. The sensor is able to measure simultaneously all three components of force and torque, respectively. This calibration step cannot be avoided and it is used for an accurate definition of the center of the magnet with respect to the sensor’s coordinate system for torque measurements. Finally, we present the results of the experiments at the mini-LIMMCAST facility showing a good agreement with the numerical model.

Fiber-Optic Ultrasound Sensors for Smart Structures Applications

DTIC Science & Technology

2000-01-25

Introduction 1 1.1 Objectives 1 1.2 Relevance to Air Force 1 1.3 Fiber Optics Ultrasound Sensors 2 2. Research Accomplishments 2 2.1 Fabry - Perot ...fiber-optic ultrasound receivers: - Fabry - Perot (FOFP) sensors, - Sagnac Ultrasound Sensor (SUS), and - Bragg-Grating Ultrasound (BGU) sensors. We...ultrasound receivers with excellent normal-incidence response can be configured as local ( Fabry - Perot ) or non-local (Sagnac) sensors. The Sagnac

Distributed Detection with Collisions in a Random, Single-Hop Wireless Sensor Network

DTIC Science & Technology

2013-05-26

public release; distribution is unlimited. Distributed detection with collisions in a random, single-hop wireless sensor network The views, opinions...1274 2 ABSTRACT Distributed detection with collisions in a random, single-hop wireless sensor network Report Title We consider the problem of... WIRELESS SENSOR NETWORK Gene T. Whipps?† Emre Ertin† Randolph L. Moses† ?U.S. Army Research Laboratory, Adelphi, MD 20783 †The Ohio State University

Affordable multisensor digital video architecture for 360° situational awareness displays

NASA Astrophysics Data System (ADS)

Scheiner, Steven P.; Khan, Dina A.; Marecki, Alexander L.; Berman, David A.; Carberry, Dana

2011-06-01

One of the major challenges facing today's military ground combat vehicle operations is the ability to achieve and maintain full-spectrum situational awareness while under armor (i.e. closed hatch). Thus, the ability to perform basic tasks such as driving, maintaining local situational awareness, surveillance, and targeting will require a high-density array of real time information be processed, distributed, and presented to the vehicle operators and crew in near real time (i.e. low latency). Advances in display and sensor technologies are providing never before seen opportunities to supply large amounts of high fidelity imagery and video to the vehicle operators and crew in real time. To fully realize the advantages of these emerging display and sensor technologies, an underlying digital architecture must be developed that is capable of processing these large amounts of video and data from separate sensor systems and distributing it simultaneously within the vehicle to multiple vehicle operators and crew. This paper will examine the systems and software engineering efforts required to overcome these challenges and will address development of an affordable, integrated digital video architecture. The approaches evaluated will enable both current and future ground combat vehicle systems the flexibility to readily adopt emerging display and sensor technologies, while optimizing the Warfighter Machine Interface (WMI), minimizing lifecycle costs, and improve the survivability of the vehicle crew working in closed-hatch systems during complex ground combat operations.

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

PubMed

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

2011-01-01

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

Imagining CO2: development and assessment of interactive visualizations for high resolution greenhouse gas observations collected by BEACO2N

NASA Astrophysics Data System (ADS)

Raheja, G.; Shusterman, A.; Martin, S.; Shahar, E.; Laughner, J.; Turner, A. J.; Miller, M. K.; Cohen, R. C.

2016-12-01

The Berkeley Atmospheric CO2 Observation Network (BEACO2N) is a high-density network of 28 carbon dioxide sensors distributed around the San Francisco Bay Area that serve to enhance understanding of intra-city variations in CO2 concentrations that are not necessarily captured by sparser networks maintained by local and national air quality management agencies. We partner with designers at the San Francisco Exploratorium to create a suite of interactive exhibits and hands-on activities that creatively visualize data from BEACO2N for general audiences. Museum goers can manipulate a light-up "bar graph" of live CO2 concentrations by exhaling on an in-room sensor, query the current readings of rooftop sensors using a scale model of the Wired Pier observation system, scroll through the data from other BEACO2N sites projected on a 3-D "topographic table" of the Bay Area, and view interpolated CO2 fields driven by research-grade weather models on a nine-screen LCD display. We present lessons learned from these initial installations, from layperson audience feedback to details of the Stochastic Time-Inverted Lagrangian Transport (STILT) model coupled to Weather Research and Forecasting (WRF) weather fields used to generate intuitive concentration maps. We propose that compelling visual demonstrations of elevated CO2 concentrations due to routine small-scale high-emission anthropogenic activities (e.g. rush hour) and/or special events (such as fireworks or factory fires) generate deeper engagement in local environmental issues and interest in undertaking personal actions that can become part of the broader climate solution. While global means and other large-scale aggregate climate metrics can lead to feelings of disconnect and subsequent ambivalence, via such exhibitions, distributed network instruments like BEACO2N can provide the local sensitivity needed to "personalize" greenhouse gas concentrations to a given individual or community and incite the drive toward understanding, education, and action.

Metabolic Biofouling of Glucose Sensors in Vivo: Role of Tissue Microhemorrhages

PubMed Central

Klueh, Ulrike; Liu, Zenghe; Feldman, Ben; Henning, Timothy P; Cho, Brian; Ouyang, Tianmei; Kreutzer, Don

2011-01-01

Objective: Based on our in vitro study that demonstrated the adverse effects of blood clots on glucose sensor function, we hypothesized that in vivo local tissue hemorrhages, induced as a consequence of sensor implantation or sensor movement post-implantation, are responsible for unreliable readings or an unexplained loss of functionality shortly after implantation. Research Design and Methods: To investigate this issue, we utilized real-time continuous monitoring of blood glucose levels in a mouse model. Direct injection of blood at the tissue site of sensor implantation was utilized to mimic sensor-induced local tissue hemorrhages. Results: It was found that blood injections, proximal to the sensor, consistently caused lowered sensor glucose readings, designated temporary signal reduction, in vivo in our mouse model, while injections of plasma or saline did not have this effect. Conclusion: These results support our hypothesis that tissue hemorrhage and resulting blood clots near the sensor can result in lowered local blood glucose concentrations due to metabolism of glucose by the clot. The lowered local blood glucose concentration led to low glucose readings from the still functioning sensor that did not reflect the systemic glucose level. PMID:21722574

Solar microclimatology. [tables (data) on insolation for application to solar energy conversion by electric power plants

NASA Technical Reports Server (NTRS)

Mckenney, D. B.; Beauchamp, W. T.

1975-01-01

It has become apparent in recent years that solar energy can be used for electric power production by several methods. Because of the diffuse nature of the solar insolation, the area involved in any central power plant design can encompass several square miles. A detailed design of these large area collection systems will require precise knowledge of the local solar insolation. Detailed information will also be needed concerning the temporal nature of the insolation and the local spatial distribution. Therefore, insolation data was collected and analyzed for a network of sensors distributed over an area of several square kilometers in Arizona. The analyses of this data yielded probability distributions of cloud size, velocity, and direction of motion which were compared with data obtained from the National Weather Service. Microclimatological analyses were also performed for suitable modeling parameters pertinent to large scale electric power plant design. Instrumentation used to collect the data is described.

A Reverse Localization Scheme for Underwater Acoustic Sensor Networks

PubMed Central

Moradi, Marjan; Rezazadeh, Javad; Ismail, Abdul Samad

2012-01-01

Underwater Wireless Sensor Networks (UWSNs) provide new opportunities to observe and predict the behavior of aquatic environments. In some applications like target tracking or disaster prevention, sensed data is meaningless without location information. In this paper, we propose a novel 3D centralized, localization scheme for mobile underwater wireless sensor network, named Reverse Localization Scheme or RLS in short. RLS is an event-driven localization method triggered by detector sensors for launching localization process. RLS is suitable for surveillance applications that require very fast reactions to events and could report the location of the occurrence. In this method, mobile sensor nodes report the event toward the surface anchors as soon as they detect it. They do not require waiting to receive location information from anchors. Simulation results confirm that the proposed scheme improves the energy efficiency and reduces significantly localization response time with a proper level of accuracy in terms of mobility model of water currents. Major contributions of this method lie on reducing the numbers of message exchange for localization, saving the energy and decreasing the average localization response time. PMID:22666034

A reverse localization scheme for underwater acoustic sensor networks.

PubMed

Moradi, Marjan; Rezazadeh, Javad; Ismail, Abdul Samad

2012-01-01

Underwater Wireless Sensor Networks (UWSNs) provide new opportunities to observe and predict the behavior of aquatic environments. In some applications like target tracking or disaster prevention, sensed data is meaningless without location information. In this paper, we propose a novel 3D centralized, localization scheme for mobile underwater wireless sensor network, named Reverse Localization Scheme or RLS in short. RLS is an event-driven localization method triggered by detector sensors for launching localization process. RLS is suitable for surveillance applications that require very fast reactions to events and could report the location of the occurrence. In this method, mobile sensor nodes report the event toward the surface anchors as soon as they detect it. They do not require waiting to receive location information from anchors. Simulation results confirm that the proposed scheme improves the energy efficiency and reduces significantly localization response time with a proper level of accuracy in terms of mobility model of water currents. Major contributions of this method lie on reducing the numbers of message exchange for localization, saving the energy and decreasing the average localization response time.

Multipoint dynamically reconfigure adaptive distributed fiber optic acoustic emission sensor (FAESense) system for condition based maintenance

NASA Astrophysics Data System (ADS)

Mendoza, Edgar; Prohaska, John; Kempen, Connie; Esterkin, Yan; Sun, Sunjian; Krishnaswamy, Sridhar

2010-09-01

This paper describes preliminary results obtained under a Navy SBIR contract by Redondo Optics Inc. (ROI), in collaboration with Northwestern University towards the development and demonstration of a next generation, stand-alone and fully integrated, dynamically reconfigurable, adaptive fiber optic acoustic emission sensor (FAESense™) system for the in-situ unattended detection and localization of shock events, impact damage, cracks, voids, and delaminations in new and aging critical infrastructures found in ships, submarines, aircraft, and in next generation weapon systems. ROI's FAESense™ system is based on the integration of proven state-of-the-art technologies: 1) distributed array of in-line fiber Bragg gratings (FBGs) sensors sensitive to strain, vibration, and acoustic emissions, 2) adaptive spectral demodulation of FBG sensor dynamic signals using two-wave mixing interferometry on photorefractive semiconductors, and 3) integration of all the sensor system passive and active optoelectronic components within a 0.5-cm x 1-cm photonic integrated circuit microchip. The adaptive TWM demodulation methodology allows the measurement of dynamic high frequnency acoustic emission events, while compensating for passive quasi-static strain and temperature drifts. It features a compact, low power, environmentally robust 1-inch x 1-inch x 4-inch small form factor (SFF) package with no moving parts. The FAESense™ interrogation system is microprocessor-controlled using high data rate signal processing electronics for the FBG sensors calibration, temperature compensation and the detection and analysis of acoustic emission signals. Its miniaturized package, low power operation, state-of-the-art data communications, and low cost makes it a very attractive solution for a large number of applications in naval and maritime industries, aerospace, civil structures, the oil and chemical industry, and for homeland security applications.

Gust prediction via artificial hair sensor array and neural network

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

University of Pennsylvania MAGIC 2010 Final Report

DTIC Science & Technology

2011-01-10

and mapping ( SLAM ) techniques are employed to build a local map of the environment surrounding the robot. Readings from the two complementary LIDAR sen...IMU, LIDAR , Cameras Localization Disrupter UGV Local Navigation Sensors: GPS, IMU, LIDAR , Cameras Laser Control Localization Task Planner Strategy/Plan...various components shown in Figure 2. This is comprised of the following subsystems: • Sensor UGV: Mobile UGVs with LIDAR and camera sensors, GPS, and

An All-Silk-Derived Dual-Mode E-skin for Simultaneous Temperature-Pressure Detection.

PubMed

Wang, Chunya; Xia, Kailun; Zhang, Mingchao; Jian, Muqiang; Zhang, Yingying

2017-11-15

Flexible skin-mimicking electronics are highly desired for development of smart human-machine interfaces and wearable human-health monitors. Human skins are able to simultaneously detect different information, such as touch, friction, temperature, and humidity. However, due to the mutual interferences of sensors with different functions, it is still a big challenge to fabricate multifunctional electronic skins (E-skins). Herein, a combo temperature-pressure E-skin is reported through assembling a temperature sensor and a strain sensor in both of which flexible and transparent silk-nanofiber-derived carbon fiber membranes (SilkCFM) are used as the active material. The temperature sensor presents high temperature sensitivity of 0.81% per centigrade. The strain sensor shows an extremely high sensitivity with a gauge factor of ∼8350 at 50% strain, enabling the detection of subtle pressure stimuli that induce local strain. Importantly, the structure of the SilkCFM in each sensor is designed to be passive to other stimuli, enabling the integrated E-skin to precisely detect temperature and pressure at the same time. It is demonstrated that the E-skin can detect and distinguish exhaling, finger pressing, and spatial distribution of temperature and pressure, which cannot be realized using single mode sensors. The remarkable performance of the silk-based combo temperature-pressure sensor, together with its green and large-scalable fabrication process, promising its applications in human-machine interfaces and soft electronics.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Reducing Sensor Noise in MEG and EEG Recordings Using Oversampled Temporal Projection.

PubMed

Larson, Eric; Taulu, Samu

2018-05-01

Here, we review the theory of suppression of spatially uncorrelated, sensor-specific noise in electro- and magentoencephalography (EEG and MEG) arrays, and introduce a novel method for suppression. Our method requires only that the signals of interest are spatially oversampled, which is a reasonable assumption for many EEG and MEG systems. Our method is based on a leave-one-out procedure using overlapping temporal windows in a mathematical framework to project spatially uncorrelated noise in the temporal domain. This method, termed "oversampled temporal projection" (OTP), has four advantages over existing methods. First, sparse channel-specific artifacts are suppressed while limiting mixing with other channels, whereas existing linear, time-invariant spatial operators can spread such artifacts to other channels with a spatial distribution which can be mistaken for one produced by an electrophysiological source. Second, OTP minimizes distortion of the spatial configuration of the data. During source localization (e.g., dipole fitting), many spatial methods require corresponding modification of the forward model to avoid bias, while OTP does not. Third, noise suppression factors at the sensor level are maintained during source localization, whereas bias compensation removes the denoising benefit for spatial methods that require such compensation. Fourth, OTP uses a time-window duration parameter to control the tradeoff between noise suppression and adaptation to time-varying sensor characteristics. OTP efficiently optimizes noise suppression performance while controlling for spatial bias of the signal of interest. This is important in applications where sensor noise significantly limits the signal-to-noise ratio, such as high-frequency brain oscillations.

Networked gamma radiation detection system for tactical deployment

NASA Astrophysics Data System (ADS)

Mukhopadhyay, Sanjoy; Maurer, Richard; Wolff, Ronald; Smith, Ethan; Guss, Paul; Mitchell, Stephen

2015-08-01

A networked gamma radiation detection system with directional sensitivity and energy spectral data acquisition capability is being developed by the National Security Technologies, LLC, Remote Sensing Laboratory to support the close and intense tactical engagement of law enforcement who carry out counterterrorism missions. In the proposed design, three clusters of 2″ × 4″ × 16″ sodium iodide crystals (4 each) with digiBASE-E (for list mode data collection) would be placed on the passenger side of a minivan. To enhance localization and facilitate rapid identification of isotopes, advanced smart real-time localization and radioisotope identification algorithms like WAVRAD (wavelet-assisted variance reduction for anomaly detection) and NSCRAD (nuisance-rejection spectral comparison ratio anomaly detection) will be incorporated. We will test a collection of algorithms and analysis that centers on the problem of radiation detection with a distributed sensor network. We will study the basic characteristics of a radiation sensor network and focus on the trade-offs between false positive alarm rates, true positive alarm rates, and time to detect multiple radiation sources in a large area. Empirical and simulation analyses of critical system parameters, such as number of sensors, sensor placement, and sensor response functions, will be examined. This networked system will provide an integrated radiation detection architecture and framework with (i) a large nationally recognized search database equivalent that would help generate a common operational picture in a major radiological crisis; (ii) a robust reach back connectivity for search data to be evaluated by home teams; and, finally, (iii) a possibility of integrating search data from multi-agency responders.

System identification of a tied arch bridge using reference-based wireless sensor networks

NASA Astrophysics Data System (ADS)

Hietbrink, Colby; Whelan, Matthew J.

2012-04-01

Vibration-based methods of structural health monitoring are generally founded on the principle that localized damage to a structure would exhibit changes within the global dynamic response. Upon this basis, accelerometers provide a unique health monitoring strategy in that a distributed network of sensors provides the technical feasibility to isolate the onset of damage without requiring that any sensor be located exactly on or in close proximity to the damage. While in theory this may be sufficient, practical experience has shown significant improvement in the application of damage diagnostic routines when mode shapes characterized by strongly localized behavior of specific elements are captured by the instrumentation array. In traditional applications, this presents a challenge since the cost and complexity of cable-based systems often effectively limits the number of instrumented locations thereby constraining the modal parameter extraction to only global modal responses. The advent of the low-cost RF chip transceiver with wireless networking capabilities has afforded a means by which a substantial number of output locations can be measured through referencebased testing using large-scale wireless sensor networks. In the current study, this approach was applied to the Prairie du Chien Bridge over the Mississippi River to extract operational mode shapes with high spatial reconstruction, including strongly localized modes. The tied arch bridge was instrumented at over 230 locations with single-axis accelerometers conditioned and acquired over a high-rate lossless wireless sensor network with simultaneous sampling capabilities. Acquisition of the dynamic response of the web plates of the arch rib was specifically targeted within the instrumentation array for diagnostic purposes. Reference-based operational modal analysis of the full structure through data-driven stochastic subspace identification is presented alongside finite element analysis results for confirmation of modal parameter plausibility. Particular emphasis is placed on the identification and reconstruction of modal response with large contribution from the arch rib web plates.

Harmony: EEG/MEG Linear Inverse Source Reconstruction in the Anatomical Basis of Spherical Harmonics

PubMed Central

Petrov, Yury

2012-01-01

EEG/MEG source localization based on a “distributed solution” is severely underdetermined, because the number of sources is much larger than the number of measurements. In particular, this makes the solution strongly affected by sensor noise. A new way to constrain the problem is presented. By using the anatomical basis of spherical harmonics (or spherical splines) instead of single dipoles the dimensionality of the inverse solution is greatly reduced without sacrificing the quality of the data fit. The smoothness of the resulting solution reduces the surface bias and scatter of the sources (incoherency) compared to the popular minimum-norm algorithms where single-dipole basis is used (MNE, depth-weighted MNE, dSPM, sLORETA, LORETA, IBF) and allows to efficiently reduce the effect of sensor noise. This approach, termed Harmony, performed well when applied to experimental data (two exemplars of early evoked potentials) and showed better localization precision and solution coherence than the other tested algorithms when applied to realistically simulated data. PMID:23071497

Characterizing the correlations between local phase fractions of gas-liquid two-phase flow with wire-mesh sensor.

PubMed

Tan, C; Liu, W L; Dong, F

2016-06-28

Understanding of flow patterns and their transitions is significant to uncover the flow mechanics of two-phase flow. The local phase distribution and its fluctuations contain rich information regarding the flow structures. A wire-mesh sensor (WMS) was used to study the local phase fluctuations of horizontal gas-liquid two-phase flow, which was verified through comparing the reconstructed three-dimensional flow structure with photographs taken during the experiments. Each crossing point of the WMS is treated as a node, so the measurement on each node is the phase fraction in this local area. An undirected and unweighted flow pattern network was established based on connections that are formed by cross-correlating the time series of each node under different flow patterns. The structure of the flow pattern network reveals the relationship of the phase fluctuations at each node during flow pattern transition, which is then quantified by introducing the topological index of the complex network. The proposed analysis method using the WMS not only provides three-dimensional visualizations of the gas-liquid two-phase flow, but is also a thorough analysis for the structure of flow patterns and the characteristics of flow pattern transition. This article is part of the themed issue 'Supersensing through industrial process tomography'. © 2016 The Author(s).

Characterizing the correlations between local phase fractions of gas–liquid two-phase flow with wire-mesh sensor

PubMed Central

Liu, W. L.; Dong, F.

2016-01-01

Understanding of flow patterns and their transitions is significant to uncover the flow mechanics of two-phase flow. The local phase distribution and its fluctuations contain rich information regarding the flow structures. A wire-mesh sensor (WMS) was used to study the local phase fluctuations of horizontal gas–liquid two-phase flow, which was verified through comparing the reconstructed three-dimensional flow structure with photographs taken during the experiments. Each crossing point of the WMS is treated as a node, so the measurement on each node is the phase fraction in this local area. An undirected and unweighted flow pattern network was established based on connections that are formed by cross-correlating the time series of each node under different flow patterns. The structure of the flow pattern network reveals the relationship of the phase fluctuations at each node during flow pattern transition, which is then quantified by introducing the topological index of the complex network. The proposed analysis method using the WMS not only provides three-dimensional visualizations of the gas–liquid two-phase flow, but is also a thorough analysis for the structure of flow patterns and the characteristics of flow pattern transition. This article is part of the themed issue ‘Supersensing through industrial process tomography’. PMID:27185959

Bayes Node Energy Polynomial Distribution to Improve Routing in Wireless Sensor Network

PubMed Central

Palanisamy, Thirumoorthy; Krishnasamy, Karthikeyan N.

2015-01-01

Wireless Sensor Network monitor and control the physical world via large number of small, low-priced sensor nodes. Existing method on Wireless Sensor Network (WSN) presented sensed data communication through continuous data collection resulting in higher delay and energy consumption. To conquer the routing issue and reduce energy drain rate, Bayes Node Energy and Polynomial Distribution (BNEPD) technique is introduced with energy aware routing in the wireless sensor network. The Bayes Node Energy Distribution initially distributes the sensor nodes that detect an object of similar event (i.e., temperature, pressure, flow) into specific regions with the application of Bayes rule. The object detection of similar events is accomplished based on the bayes probabilities and is sent to the sink node resulting in minimizing the energy consumption. Next, the Polynomial Regression Function is applied to the target object of similar events considered for different sensors are combined. They are based on the minimum and maximum value of object events and are transferred to the sink node. Finally, the Poly Distribute algorithm effectively distributes the sensor nodes. The energy efficient routing path for each sensor nodes are created by data aggregation at the sink based on polynomial regression function which reduces the energy drain rate with minimum communication overhead. Experimental performance is evaluated using Dodgers Loop Sensor Data Set from UCI repository. Simulation results show that the proposed distribution algorithm significantly reduce the node energy drain rate and ensure fairness among different users reducing the communication overhead. PMID:26426701

Bayes Node Energy Polynomial Distribution to Improve Routing in Wireless Sensor Network.

PubMed

Palanisamy, Thirumoorthy; Krishnasamy, Karthikeyan N

2015-01-01

Wireless Sensor Network monitor and control the physical world via large number of small, low-priced sensor nodes. Existing method on Wireless Sensor Network (WSN) presented sensed data communication through continuous data collection resulting in higher delay and energy consumption. To conquer the routing issue and reduce energy drain rate, Bayes Node Energy and Polynomial Distribution (BNEPD) technique is introduced with energy aware routing in the wireless sensor network. The Bayes Node Energy Distribution initially distributes the sensor nodes that detect an object of similar event (i.e., temperature, pressure, flow) into specific regions with the application of Bayes rule. The object detection of similar events is accomplished based on the bayes probabilities and is sent to the sink node resulting in minimizing the energy consumption. Next, the Polynomial Regression Function is applied to the target object of similar events considered for different sensors are combined. They are based on the minimum and maximum value of object events and are transferred to the sink node. Finally, the Poly Distribute algorithm effectively distributes the sensor nodes. The energy efficient routing path for each sensor nodes are created by data aggregation at the sink based on polynomial regression function which reduces the energy drain rate with minimum communication overhead. Experimental performance is evaluated using Dodgers Loop Sensor Data Set from UCI repository. Simulation results show that the proposed distribution algorithm significantly reduce the node energy drain rate and ensure fairness among different users reducing the communication overhead.

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.

Real-time physiological monitoring with distributed networks of sensors and object-oriented programming techniques

NASA Astrophysics Data System (ADS)

Wiesmann, William P.; Pranger, L. Alex; Bogucki, Mary S.

1998-05-01

Remote monitoring of physiologic data from individual high- risk workers distributed over time and space is a considerable challenge. This is often due to an inadequate capability to accurately integrate large amounts of data into usable information in real time. In this report, we have used the vertical and horizontal organization of the 'fireground' as a framework to design a distributed network of sensors. In this system, sensor output is linked through a hierarchical object oriented programing process to accurately interpret physiological data, incorporate these data into a synchronous model and relay processed data, trends and predictions to members of the fire incident command structure. There are several unique aspects to this approach. The first includes a process to account for variability in vital parameter values for each individual's normal physiologic response by including an adaptive network in each data process. This information is used by the model in an iterative process to baseline a 'normal' physiologic response to a given stress for each individual and to detect deviations that indicate dysfunction or a significant insult. The second unique capability of the system orders the information for each user including the subject, local company officers, medical personnel and the incident commanders. Information can be retrieved and used for training exercises and after action analysis. Finally this system can easily be adapted to existing communication and processing links along with incorporating the best parts of current models through the use of object oriented programming techniques. These modern software techniques are well suited to handling multiple data processes independently over time in a distributed network.

Control systems using modal domain optical fiber sensors for smart structure applications

NASA Technical Reports Server (NTRS)

Lindner, Douglas K.; Reichard, Karl M.

1991-01-01

Recently, a new class of sensors has emerged for structural control which respond to environmental changes over a significant gauge length; these sensors are called distributed-effect sensors. These sensors can be fabricated with spatially varying sensitivity to the distributed measurand, and can be configured to measure a variety of structural parameters which can not be measured directly using point sensors. Examples of distributed-effect sensors include piezoelectric film, holographic sensors, and modal domain optical fiber sensors. Optical fiber sensors are particularly attractive for smart structure applications because they are flexible, have low mass, and can easily be embedded directly into materials. In this paper we describe the implementation of weighted modal domain optical fiber sensors. The mathematical model of the modal domain optical fiber sensor model is described and used to derive an expression for the sensor sensitivity. The effects of parameter variations on the sensor sensitivity are demonstrated to illustrate methods of spatially varying the sensor sensitivity.

GeoTrack: bio-inspired global video tracking by networks of unmanned aircraft systems

NASA Astrophysics Data System (ADS)

Barooah, Prabir; Collins, Gaemus E.; Hespanha, João P.

2009-05-01

Research from the Institute for Collaborative Biotechnologies (ICB) at the University of California at Santa Barbara (UCSB) has identified swarming algorithms used by flocks of birds and schools of fish that enable these animals to move in tight formation and cooperatively track prey with minimal estimation errors, while relying solely on local communication between the animals. This paper describes ongoing work by UCSB, the University of Florida (UF), and the Toyon Research Corporation on the utilization of these algorithms to dramatically improve the capabilities of small unmanned aircraft systems (UAS) to cooperatively locate and track ground targets. Our goal is to construct an electronic system, called GeoTrack, through which a network of hand-launched UAS use dedicated on-board processors to perform multi-sensor data fusion. The nominal sensors employed by the system will EO/IR video cameras on the UAS. When GMTI or other wide-area sensors are available, as in a layered sensing architecture, data from the standoff sensors will also be fused into the GeoTrack system. The output of the system will be position and orientation information on stationary or mobile targets in a global geo-stationary coordinate system. The design of the GeoTrack system requires significant advances beyond the current state-of-the-art in distributed control for a swarm of UAS to accomplish autonomous coordinated tracking; target geo-location using distributed sensor fusion by a network of UAS, communicating over an unreliable channel; and unsupervised real-time image-plane video tracking in low-powered computing platforms.

Bioinspired magnetic reception and multimodal sensing.

PubMed

Taylor, Brian K

2017-08-01

Several animals use Earth's magnetic field in concert with other sensor modes to accomplish navigational tasks ranging from local homing to continental scale migration. However, despite extensive research, animal magnetic reception remains poorly understood. Similarly, the Earth's magnetic field offers a signal that engineered systems can leverage to navigate in environments where man-made positioning systems such as GPS are either unavailable or unreliable. This work uses a behavioral strategy inspired by the migratory behavior of sea turtles to locate a magnetic goal and respond to wind when it is present. Sensing is performed using a number of distributed sensors. Based on existing theoretical biology considerations, data processing is performed using combinations of circles and ellipses to exploit the distributed sensing paradigm. Agent-based simulation results indicate that this approach is capable of using two separate magnetic properties to locate a goal from a variety of initial conditions in both noiseless and noisy sensory environments. The system's ability to locate the goal appears robust to noise at the cost of overall path length.

Cell-like pressure sensors reveal increase of mechanical stress towards the core of multicellular spheroids under compression.

PubMed

Dolega, M E; Delarue, M; Ingremeau, F; Prost, J; Delon, A; Cappello, G

2017-01-27

The surrounding microenvironment limits tumour expansion, imposing a compressive stress on the tumour, but little is known how pressure propagates inside the tumour. Here we present non-destructive cell-like microsensors to locally quantify mechanical stress distribution in three-dimensional tissue. Our sensors are polyacrylamide microbeads of well-defined elasticity, size and surface coating to enable internalization within the cellular environment. By isotropically compressing multicellular spheroids (MCS), which are spherical aggregates of cells mimicking a tumour, we show that the pressure is transmitted in a non-trivial manner inside the MCS, with a pressure rise towards the core. This observed pressure profile is explained by the anisotropic arrangement of cells and our results suggest that such anisotropy alone is sufficient to explain the pressure rise inside MCS composed of a single cell type. Furthermore, such pressure distribution suggests a direct link between increased mechanical stress and previously observed lack of proliferation within the spheroids core.

TU-AB-201-03: A Robot for the Automated Delivery of An Electromagnetic Tracking Sensor for the Localization of Brachytherapy Catheters

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

Don, S; Cormack, R; Viswanathan, A

Purpose: To present a programmable robotic system for the accurate and fast deployment of an electromagnetic (EM) sensor for brachytherapy catheter localization. Methods: A robotic system for deployment of an EM sensor was designed and built. The system was programmed to increment the sensor position at specified time and space intervals. Sensor delivery accuracy was measured in a phantom using the localization of the EM sensor and tested in different environmental conditions. Accuracy was tested by measuring the distance between the physical locations reached by the sensor (measured by the EM tracker) and the intended programmed locations. Results: The systemmore » consisted of a stepper motor connected to drive wheels (that grip the cable to move the sensor) and a series of guides to connect to a brachytherapy transfer tube, all controlled by a programmable Arduino microprocessor. The total cost for parts was <$300. The positional accuracy of the sensor location was within 1 mm of the expected position provided by the motorized guide system. Acquisition speed to localize a brachytherapy catheter with 20 cm of active length was 10 seconds. The current design showed some cable slip and warping depending on environment temperature. Conclusion: The use of EM tracking for the localization of brachytherapy catheters has been previously demonstrated. Efficient data acquisition and artifact reduction requires fast and accurate deployment of an EM sensor in consistent, repeatable patterns, which cannot practically be achieved manually. The design of an inexpensive, programmable robot allowing for the precise deployment of stepping patterns was presented, and a prototype was built. Further engineering is necessary to ensure that the device provides efficient independent localization of brachytherapy catheters. This research was funded by the Kaye Family Award.« less

Achieving Congestion Mitigation Using Distributed Power Control for Spectrum Sensor Nodes in Sensor Network-Aided Cognitive Radio Ad Hoc Networks

PubMed Central

Zhuo, Fan; Duan, Hucai

2017-01-01

The data sequence of spectrum sensing results injected from dedicated spectrum sensor nodes (SSNs) and the data traffic from upstream secondary users (SUs) lead to unpredictable data loads in a sensor network-aided cognitive radio ad hoc network (SN-CRN). As a result, network congestion may occur at a SU acting as fusion center when the offered data load exceeds its available capacity, which degrades network performance. In this paper, we present an effective approach to mitigate congestion of bottlenecked SUs via a proposed distributed power control framework for SSNs over a rectangular grid based SN-CRN, aiming to balance resource load and avoid excessive congestion. To achieve this goal, a distributed power control framework for SSNs from interior tier (IT) and middle tier (MT) is proposed to achieve the tradeoff between channel capacity and energy consumption. In particular, we firstly devise two pricing factors by considering stability of local spectrum sensing and spectrum sensing quality for SSNs. By the aid of pricing factors, the utility function of this power control problem is formulated by jointly taking into account the revenue of power reduction and the cost of energy consumption for IT or MT SSN. By bearing in mind the utility function maximization and linear differential equation constraint of energy consumption, we further formulate the power control problem as a differential game model under a cooperation or noncooperation scenario, and rigorously obtain the optimal solutions to this game model by employing dynamic programming. Then the congestion mitigation for bottlenecked SUs is derived by alleviating the buffer load over their internal buffers. Simulation results are presented to show the effectiveness of the proposed approach under the rectangular grid based SN-CRN scenario. PMID:28914803

Distributed Sensor Fusion for Scalar Field Mapping Using Mobile Sensor Networks.

PubMed

La, Hung Manh; Sheng, Weihua

2013-04-01

In this paper, autonomous mobile sensor networks are deployed to measure a scalar field and build its map. We develop a novel method for multiple mobile sensor nodes to build this map using noisy sensor measurements. Our method consists of two parts. First, we develop a distributed sensor fusion algorithm by integrating two different distributed consensus filters to achieve cooperative sensing among sensor nodes. This fusion algorithm has two phases. In the first phase, the weighted average consensus filter is developed, which allows each sensor node to find an estimate of the value of the scalar field at each time step. In the second phase, the average consensus filter is used to allow each sensor node to find a confidence of the estimate at each time step. The final estimate of the value of the scalar field is iteratively updated during the movement of the mobile sensors via weighted average. Second, we develop the distributed flocking-control algorithm to drive the mobile sensors to form a network and track the virtual leader moving along the field when only a small subset of the mobile sensors know the information of the leader. Experimental results are provided to demonstrate our proposed algorithms.

Energy Harvesting Hybrid Acoustic-Optical Underwater Wireless Sensor Networks Localization.

PubMed

Saeed, Nasir; Celik, Abdulkadir; Al-Naffouri, Tareq Y; Alouini, Mohamed-Slim

2017-12-26

Underwater wireless technologies demand to transmit at higher data rate for ocean exploration. Currently, large coverage is achieved by acoustic sensor networks with low data rate, high cost, high latency, high power consumption, and negative impact on marine mammals. Meanwhile, optical communication for underwater networks has the advantage of the higher data rate albeit for limited communication distances. Moreover, energy consumption is another major problem for underwater sensor networks, due to limited battery power and difficulty in replacing or recharging the battery of a sensor node. The ultimate solution to this problem is to add energy harvesting capability to the acoustic-optical sensor nodes. Localization of underwater sensor networks is of utmost importance because the data collected from underwater sensor nodes is useful only if the location of the nodes is known. Therefore, a novel localization technique for energy harvesting hybrid acoustic-optical underwater wireless sensor networks (AO-UWSNs) is proposed. AO-UWSN employs optical communication for higher data rate at a short transmission distance and employs acoustic communication for low data rate and long transmission distance. A hybrid received signal strength (RSS) based localization technique is proposed to localize the nodes in AO-UWSNs. The proposed technique combines the noisy RSS based measurements from acoustic communication and optical communication and estimates the final locations of acoustic-optical sensor nodes. A weighted multiple observations paradigm is proposed for hybrid estimated distances to suppress the noisy observations and give more importance to the accurate observations. Furthermore, the closed form solution for Cramer-Rao lower bound (CRLB) is derived for localization accuracy of the proposed technique.

Energy Harvesting Hybrid Acoustic-Optical Underwater Wireless Sensor Networks Localization

PubMed Central

Saeed, Nasir; Celik, Abdulkadir; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim

2017-01-01

Underwater wireless technologies demand to transmit at higher data rate for ocean exploration. Currently, large coverage is achieved by acoustic sensor networks with low data rate, high cost, high latency, high power consumption, and negative impact on marine mammals. Meanwhile, optical communication for underwater networks has the advantage of the higher data rate albeit for limited communication distances. Moreover, energy consumption is another major problem for underwater sensor networks, due to limited battery power and difficulty in replacing or recharging the battery of a sensor node. The ultimate solution to this problem is to add energy harvesting capability to the acoustic-optical sensor nodes. Localization of underwater sensor networks is of utmost importance because the data collected from underwater sensor nodes is useful only if the location of the nodes is known. Therefore, a novel localization technique for energy harvesting hybrid acoustic-optical underwater wireless sensor networks (AO-UWSNs) is proposed. AO-UWSN employs optical communication for higher data rate at a short transmission distance and employs acoustic communication for low data rate and long transmission distance. A hybrid received signal strength (RSS) based localization technique is proposed to localize the nodes in AO-UWSNs. The proposed technique combines the noisy RSS based measurements from acoustic communication and optical communication and estimates the final locations of acoustic-optical sensor nodes. A weighted multiple observations paradigm is proposed for hybrid estimated distances to suppress the noisy observations and give more importance to the accurate observations. Furthermore, the closed form solution for Cramer-Rao lower bound (CRLB) is derived for localization accuracy of the proposed technique. PMID:29278405

Ensuring Data Storage Security in Tree cast Routing Architecture for Sensor Networks

NASA Astrophysics Data System (ADS)

Kumar, K. E. Naresh; Sagar, U. Vidya; Waheed, Mohd. Abdul

2010-10-01

In this paper presents recent advances in technology have made low-cost, low-power wireless sensors with efficient energy consumption. A network of such nodes can coordinate among themselves for distributed sensing and processing of certain data. For which, we propose an architecture to provide a stateless solution in sensor networks for efficient routing in wireless sensor networks. This type of architecture is known as Tree Cast. We propose a unique method of address allocation, building up multiple disjoint trees which are geographically inter-twined and rooted at the data sink. Using these trees, routing messages to and from the sink node without maintaining any routing state in the sensor nodes is possible. In contrast to traditional solutions, where the IT services are under proper physical, logical and personnel controls, this routing architecture moves the application software and databases to the large data centers, where the management of the data and services may not be fully trustworthy. This unique attribute, however, poses many new security challenges which have not been well understood. In this paper, we focus on data storage security, which has always been an important aspect of quality of service. To ensure the correctness of users' data in this architecture, we propose an effective and flexible distributed scheme with two salient features, opposing to its predecessors. By utilizing the homomorphic token with distributed verification of erasure-coded data, our scheme achieves the integration of storage correctness insurance and data error localization, i.e., the identification of misbehaving server(s). Unlike most prior works, the new scheme further supports secure and efficient dynamic operations on data blocks, including: data update, delete and append. Extensive security and performance analysis shows that the proposed scheme is highly efficient and resilient against Byzantine failure, malicious data modification attack, and even server colluding attacks.

Path planning in GPS-denied environments via collective intelligence of distributed sensor networks

NASA Astrophysics Data System (ADS)

Jha, Devesh K.; Chattopadhyay, Pritthi; Sarkar, Soumik; Ray, Asok

2016-05-01

This paper proposes a framework for reactive goal-directed navigation without global positioning facilities in unknown dynamic environments. A mobile sensor network is used for localising regions of interest for path planning of an autonomous mobile robot. The underlying theory is an extension of a generalised gossip algorithm that has been recently developed in a language-measure-theoretic setting. The algorithm has been used to propagate local decisions of target detection over a mobile sensor network and thus, it generates a belief map for the detected target over the network. In this setting, an autonomous mobile robot may communicate only with a few mobile sensing nodes in its own neighbourhood and localise itself relative to the communicating nodes with bounded uncertainties. The robot makes use of the knowledge based on the belief of the mobile sensors to generate a sequence of way-points, leading to a possible goal. The estimated way-points are used by a sampling-based motion planning algorithm to generate feasible trajectories for the robot. The proposed concept has been validated by numerical simulation on a mobile sensor network test-bed and a Dubin's car-like robot.

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

NASA Astrophysics Data System (ADS)

Liu, Huanlin; Wang, Chujun; Chen, Yong

2018-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-10-01

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

Pyroelectric Energy Scavenging Techniques for Self-Powered Nuclear Reactor Wireless Sensor Networks

DOE PAGES

Hunter, Scott Robert; Lavrik, Nickolay V; Datskos, Panos G; ...

2014-11-01

Recent advances in technologies for harvesting waste thermal energy from ambient environments present an opportunity to implement truly wireless sensor nodes in nuclear power plants. These sensors could continue to operate during extended station blackouts and during periods when operation of the plant s internal power distribution system has been disrupted. The energy required to power the wireless sensors must be generated using energy harvesting techniques from locally available energy sources, and the energy consumption within the sensor circuitry must therefore be low to minimize power and hence the size requirements of the energy harvester. Harvesting electrical energy from thermalmore » energy sources can be achieved using pyroelectric or thermoelectric conversion techniques. Recent modeling and experimental studies have shown that pyroelectric techniques can be cost competitive with thermoelectrics in self powered wireless sensor applications and, using new temperature cycling techniques, has the potential to be several times as efficient as thermoelectrics under comparable operating conditions. The development of a new thermal energy harvester concept, based on temperature cycled pyroelectric thermal-to-electrical energy conversion, is outlined. This paper outlines the modeling of cantilever and pyroelectric structures and single element devices that demonstrate the potential of this technology for the development of high efficiency thermal-to-electrical energy conversion devices.« less

Pyroelectric Energy Scavenging Techniques for Self-Powered Nuclear Reactor Wireless Sensor Networks

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

Hunter, Scott Robert; Lavrik, Nickolay V; Datskos, Panos G

Recent advances in technologies for harvesting waste thermal energy from ambient environments present an opportunity to implement truly wireless sensor nodes in nuclear power plants. These sensors could continue to operate during extended station blackouts and during periods when operation of the plant s internal power distribution system has been disrupted. The energy required to power the wireless sensors must be generated using energy harvesting techniques from locally available energy sources, and the energy consumption within the sensor circuitry must therefore be low to minimize power and hence the size requirements of the energy harvester. Harvesting electrical energy from thermalmore » energy sources can be achieved using pyroelectric or thermoelectric conversion techniques. Recent modeling and experimental studies have shown that pyroelectric techniques can be cost competitive with thermoelectrics in self powered wireless sensor applications and, using new temperature cycling techniques, has the potential to be several times as efficient as thermoelectrics under comparable operating conditions. The development of a new thermal energy harvester concept, based on temperature cycled pyroelectric thermal-to-electrical energy conversion, is outlined. This paper outlines the modeling of cantilever and pyroelectric structures and single element devices that demonstrate the potential of this technology for the development of high efficiency thermal-to-electrical energy conversion devices.« less

Evaluation of Fiber Bragg Grating and Distributed Optical Fiber Temperature Sensors

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

McCary, Kelly Marie

Fiber optic temperature sensors were evaluated in the High Temperature Test Lab (HTTL) to determine the accuracy of the measurements at various temperatures. A distributed temperature sensor was evaluated up to 550C and a fiber Bragg grating sensor was evaluated up to 750C. HTTL measurements indicate that there is a drift in fiber Bragg sensor over time of approximately -10C with higher accuracy at temperatures above 300C. The distributed sensor produced some bad data points at and above 500C but produced measurements with less than 2% error at increasing temperatures up to 400C

AIRQino, a low-cost air quality mobile platform

NASA Astrophysics Data System (ADS)

Zaldei, Alessandro; Vagnoli, Carolina; Di Lonardo, Sara; Gioli, Beniamino; Gualtieri, Giovanni; Toscano, Piero; Martelli, Francesca; Matese, Alessandro

2015-04-01

Recent air quality regulations (Directive 2008/50/EC) enforce the transition from point-based monitoring networks to new tools that must be capable of mapping and forecasting air quality on the totality of land area, and therefore the totality of citizens. This implies new technologies such as models and additional indicative measurements, are needed in addition to accurate fixed air quality monitoring stations, that until now have been taken as reference by local administrators for the enforcement of various mitigation strategies. However, due to their sporadic spatial distribution, they cannot describe the highly resolved spatial pollutant variations within cities. Integrating additional indicative measurements may provide adequate information on the spatial distribution of the ambient air quality, also allowing for a reduction of the required minimum number of fixed sampling points, whose high cost and complex maintenance still remain a crucial concern for local administrators. New low-cost and small size sensors are becoming available, that could be employed in air quality monitoring including mobile applications. However, accurate assessment of their accuracy and performance both in controlled and real monitoring conditions is crucially needed. Quantifying sensor response is a significant challenge due to the sensitivity to ambient temperature and humidity and the cross-sensitivity to others pollutant species. This study reports the development of an Arduino compatible electronic board (AIRQino) which integrates a series of low-cost metal oxide and NDIR sensors for air quality monitoring, with sensors to measure air temperature, relative humidity, noise, solar radiation and vertical acceleration. A comparative assessment was made for CO2, CO, NO2, CH4, O3, VOCs concentrations, temperature and relative humidity. A controlled climatic chamber study (-80°C / +80°C) was performed to verify temperature and humidity interference using reference gas cylinders and high quality reference sensors. The AIRQino was installed on mobile vectors such as bikes, buses and trams in the cities of Firenze and Siracusa (Italy), that send data real-time to a Web portal. By integrating a microprocessor unit it is capable of directly updating calibration coefficients to provide corrected sensor output as digital string through RS232 serial port. Results from the lab tests and the 'real world' mobile applications are presented and discussed, to assess to what extent this sensor technology might be useful for the development of portable, compact, wireless and cost-effective system for air quality monitoring in urban areas at high spatio-temporal resolution.

Distributed fiber optic sensor-enhanced detection and prediction of shrinkage-induced delamination of ultra-high-performance concrete overlay

NASA Astrophysics Data System (ADS)

Bao, Yi; Valipour, Mahdi; Meng, Weina; Khayat, Kamal H.; Chen, Genda

2017-08-01

This study develops a delamination detection system for smart ultra-high-performance concrete (UHPC) overlays using a fully distributed fiber optic sensor. Three 450 mm (length) × 200 mm (width) × 25 mm (thickness) UHPC overlays were cast over an existing 200 mm thick concrete substrate. The initiation and propagation of delamination due to early-age shrinkage of the UHPC overlay were detected as sudden increases and their extension in spatial distribution of shrinkage-induced strains measured from the sensor based on pulse pre-pump Brillouin optical time domain analysis. The distributed sensor is demonstrated effective in detecting delamination openings from microns to hundreds of microns. A three-dimensional finite element model with experimental material properties is proposed to understand the complete delamination process measured from the distributed sensor. The model is validated using the distributed sensor data. The finite element model with cohesive elements for the overlay-substrate interface can predict the complete delamination process.

Acoustic Sensor Network for Relative Positioning of Nodes

PubMed Central

De Marziani, Carlos; Ureña, Jesus; Hernandez, Álvaro; Mazo, Manuel; García, Juan Jesús; Jimenez, Ana; Rubio, María del Carmen Pérez; Álvarez, Fernando; Villadangos, José Manuel

2009-01-01

In this work, an acoustic sensor network for a relative localization system is analyzed by reporting the accuracy achieved in the position estimation. The proposed system has been designed for those applications where objects are not restricted to a particular environment and thus one cannot depend on any external infrastructure to compute their positions. The objects are capable of computing spatial relations among themselves using only acoustic emissions as a ranging mechanism. The object positions are computed by a multidimensional scaling (MDS) technique and, afterwards, a least-square algorithm, based on the Levenberg-Marquardt algorithm (LMA), is applied to refine results. Regarding the position estimation, all the parameters involved in the computation of the temporary relations with the proposed ranging mechanism have been considered. The obtained results show that a fine-grained localization can be achieved considering a Gaussian distribution error in the proposed ranging mechanism. Furthermore, since acoustic sensors require a line-of-sight to properly work, the system has been tested by modeling the lost of this line-of-sight as a non-Gaussian error. A suitable position estimation has been achieved even if it is considered a bias of up to 25 of the line-of-sight measurements among a set of nodes. PMID:22291520

Citizen Science to Support Community-based Flood Early Warning and Resilience Building

NASA Astrophysics Data System (ADS)

Paul, J. D.; Buytaert, W.; Allen, S.; Ballesteros-Cánovas, J. A.; Bhusal, J.; Cieslik, K.; Clark, J.; Dewulf, A.; Dhital, M. R.; Hannah, D. M.; Liu, W.; Nayaval, J. L.; Schiller, A.; Smith, P. J.; Stoffel, M.; Supper, R.

2017-12-01

In Disaster Risk Management, an emerging shift has been noted from broad-scale, top-down assessments towards more participatory, community-based, bottom-up approaches. Combined with technologies for robust and low-cost sensor networks, a citizen science approach has recently emerged as a promising direction in the provision of extensive, real-time information for flood early warning systems. Here we present the framework and initial results of a major new international project, Landslide EVO, aimed at increasing local resilience against hydrologically induced disasters in western Nepal by exploiting participatory approaches to knowledge generation and risk governance. We identify three major technological developments that strongly support our approach to flood early warning and resilience building in Nepal. First, distributed sensor networks, participatory monitoring, and citizen science hold great promise in complementing official monitoring networks and remote sensing by generating site-specific information with local buy-in, especially in data-scarce regions. Secondly, the emergence of open source, cloud-based risk analysis platforms supports the construction of a modular, distributed, and potentially decentralised data processing workflow. Finally, linking data analysis platforms to social computer networks and ICT (e.g. mobile phones, tablets) allows tailored interfaces and people-centred decision- and policy-support systems to be built. Our proposition is that maximum impact is created if end-users are involved not only in data collection, but also over the entire project life-cycle, including the analysis and provision of results. In this context, citizen science complements more traditional knowledge generation practices, and also enhances multi-directional information provision, risk management, early-warning systems and local resilience building.

Fiber optic distributed temperature sensing for fire source localization

NASA Astrophysics Data System (ADS)

Sun, Miao; Tang, Yuquan; Yang, Shuang; Sigrist, Markus W.; Li, Jun; Dong, Fengzhong

2017-08-01

A method for localizing a fire source based on a distributed temperature sensor system is proposed. Two sections of optical fibers were placed orthogonally to each other as the sensing elements. A tray of alcohol was lit to act as a fire outbreak in a cabinet with an uneven ceiling to simulate a real scene of fire. Experiments were carried out to demonstrate the feasibility of the method. Rather large fluctuations and systematic errors with respect to predicting the exact room coordinates of the fire source caused by the uneven ceiling were observed. Two mathematical methods (smoothing recorded temperature curves and finding temperature peak positions) to improve the prediction accuracy are presented, and the experimental results indicate that the fluctuation ranges and systematic errors are significantly reduced. The proposed scheme is simple and appears reliable enough to locate a fire source in large spaces.

Malfunctions in radioactivity sensors' networks

NASA Astrophysics Data System (ADS)

Khalipova, Veronika; Damart, Guillaume; Beauzamy, Bernard; Bruna, Giovanni

2018-01-01

The capacity to promptly and efficiently detect any source of contamination of the environment (a radioactive cloud) at a local and a country scale is mandatory to a safe and secure exploitation of civil nuclear energy. It must rely upon a robust network of measurement devices, to be optimized vs. several parameters, including the overall reliability, the investment, the operation and maintenance costs. We show that a network can be arranged in different ways, but many of them are inadequate. Through simulations, we test the efficiency of several configurations of sensors, in the same domain. The denser arrangement turns out to be the more efficient, but the efficiency is increased when sensors are non-uniformly distributed over the country, with accumulation at the borders. In the case of France, as radioactive threats are most likely to come from the East, the best solution is densifying the sensors close to the eastern border. Our approach differs from previous work because it is "failure oriented": we determine the laws of probability for all types of failures and deduce in this respect the best organization of the network.

A Robot Equipped with a High-Speed LSPR Gas Sensor Module for Collecting Spatial Odor Information from On-Ground Invisible Odor Sources.

PubMed

Yang, Zhongyuan; Sassa, Fumihiro; Hayashi, Kenshi

2018-06-22

Improving the efficiency of detecting the spatial distribution of gas information with a mobile robot is a great challenge that requires rapid sample collection, which is basically determined by the speed of operation of gas sensors. The present work developed a robot equipped with a high-speed gas sensor module based on localized surface plasmon resonance. The sensor module is designed to sample gases from an on-ground odor source, such as a footprint material or artificial odor marker, via a fine sampling tubing. The tip of the sampling tubing was placed close to the ground to reduce the sampling time and the effect of natural gas diffusion. On-ground ethanol odor sources were detected by the robot at high resolution (i.e., 2.5 cm when the robot moved at 10 cm/s), and the reading of gas information was demonstrated experimentally. This work may help in the development of environmental sensing robots, such as the development of odor source mapping and multirobot systems with pheromone tracing.

Distributed Stress Sensing and Non-Destructive Tests Using Mechanoluminescence Materials

NASA Astrophysics Data System (ADS)

Rahimi, Mohammad Reza

Rapid aging of infrastructure systems is currently pervasive in the US and the anticipated cost until 2020 for rehabilitation of aging lifeline will reach 3.6 trillion US dollars (ASCE 2013). Reliable condition or serviceability assessment is critically important in decision-making for economic and timely maintenance of the infrastructure systems. Advanced sensors and nondestructive test (NDT) methods are the key technologies for structural health monitoring (SHM) applications that can provide information on the current state of structures. There are many traditional sensors and NDT methods, for examples, strain gauges, ultrasound, radiography and other X-ray, etc. to detect any defect on the infrastructure. Considering that civil infrastructure is typically large-scale and exhibits complex behavior, estimation of structural conditions by the local sensing and NDT methods is a challenging task. Non-contact and distributed (or full-field) sensing and NDT method are desirable that can provide rich information on the civil infrastructure's state. Materials with the ability of emitting light, especially in the visible range, are named as luminescent materials. Mechanoluminescence (ML) phenomenon is the light emission from luminescent materials as a response of an induced mechanical stress. ML materials offer new opportunities for SHM that can directly visualize the stress and crack distributions on the surface of structures through ML light emission. Although material research for ML phenomena have been made substantially, applications of the ML sensors to full-field stress and crack visualization are still at infant stage and have yet to be full-fledged. Moreover, practical applications of the ML sensors for SHM of civil infrastructure have difficulties since numerous challenging problems (e.g. environmental effect) arise in actual applications. In order to realize a practical SHM system employing ML sensors, more research needs to be conducted, for examples, fundamental understandings of physics of ML phenomenon, method for quantitative stress measurements, calibration method for ML sensors, improvement of sensitivity, optimal manufacturing and design of ML sensors, environmental effects of ML phenomenon (e.g. temperature), image processing and analysis, etc. In this research, fundamental ML phenomena of two most promising ML sensing materials were experimentally studied and a methodology for full-field quantitative strain measurements, for the first time, was proposed along with a standardized calibration method. Characteristics and behavior of ML composites and thin films coated on the structure have been studied under various material tests including compression, tension, pure shear, bending, etc. In addition, ML emission sensitivity to the manufacturing parameters and experimental conditions was addressed in order to find optimal design the ML sensor. A phenomenological stress-optics transduction model for predicting the ML light intensity from a thin-film ML coating sensor subjected to in-plane stresses was proposed. A new full-field quantitative strain measuring methodology by ML thin film sensor was developed, for the first time, in order to visualize and measure the strain field. The results from the ML sensor were compared and verified by finite element simulation results. For NDT applications of ML sensors, experimental tests were conducted to visualize the cracks on structural surfaces and detect damages on structural components. In summary, this research proposes and realizes a new distributed stress sensor and NDT method using ML sensing materials. The proposed method is experimentally validated to be effective for stress measurement and crack visualizations. Successful completion of this research provides a leap toward a commercial light intensity-based optic sensor to be used as a new full-field stress measurement technology and NDT method.

The Pilatus Unmanned Aircraft System for Lower Atmospheric Research

NASA Technical Reports Server (NTRS)

de Boer, Gijs; Palo, Scott; Argrow, Brian; LoDolce, Gabriel; Mack, James; Gao, Ru-shan; Telg, Hagen; Trussel, Cameron; Fromm, Joshua; Long, Charles N.;

The pilatus unmanned aircraft system for lower atmospheric research

NASA Astrophysics Data System (ADS)

de Boer, G.; Palo, S.; Argrow, B.; LoDolce, G.; Mack, J.; Gao, R.-S.; Telg, H.; Trussel, C.; Fromm, J.; Long, C. N.; Bland, G.; Maslanik, J.; Schmid, B.; Hock, T.

2015-11-01

This paper presents details of the University of Colorado (CU) Pilatus unmanned research aircraft, assembled to provide measurements of aerosols, radiation and thermodynamics in the lower troposphere. This aircraft has a wingspan of 3.2 m and a maximum take off weight of 25 kg and is powered by an electric motor to reduce engine exhaust and concerns about carburetor icing. It carries instrumentation to make measurements of broadband up- and downwelling shortwave and longwave radiation, aerosol particle size distribution, atmospheric temperature, relative humidity and pressure and to collect video of flights for subsequent analysis of atmospheric conditions during flight. In order to make the shortwave radiation measurements, care was taken to carefully position a high-quality compact inertial measurement unit (IMU) and characterize the attitude of the aircraft and it's orientation to the upward looking radiation sensor. Using measurements from both of these sensors, a correction is applied to the raw radiometer measurements to correct for aircraft attitude and sensor tilt relative to the sun. The data acquisition system was designed from scratch based on a set of key driving requirements to accommodate the variety of sensors deployed. Initial test flights completed in Colorado provide promising results with measurements from the radiation sensors agreeing with those from a nearby surface site. Additionally, estimates of surface albedo from onboard sensors were consistent with local surface conditions, including melting snow and bright runway surface. Aerosol size distributions collected are internally consistent and have previously been shown to agree well with larger, surface-based instrumentation. Finally the atmospheric state measurements evolve as expected, with the near-surface atmosphere warming over time as the day goes on, and the atmospheric relative humidity decreasing with increased temperature. No directional bias on measured temperature, as might be expected due to uneven heating of the sensor housing over the course of a racetrack pattern, was detected. The results from these flights indicate that the CU Pilatus platform is capable of performing research grade lower tropospheric measurement missions.

The Pilatus unmanned aircraft system for lower atmospheric research

NASA Astrophysics Data System (ADS)

de Boer, Gijs; Palo, Scott; Argrow, Brian; LoDolce, Gabriel; Mack, James; Gao, Ru-Shan; Telg, Hagen; Trussel, Cameron; Fromm, Joshua; Long, Charles N.; Bland, Geoff; Maslanik, James; Schmid, Beat; Hock, Terry

2016-04-01

This paper presents details of the University of Colorado (CU) "Pilatus" unmanned research aircraft, assembled to provide measurements of aerosols, radiation and thermodynamics in the lower troposphere. This aircraft has a wingspan of 3.2 m and a maximum take-off weight of 25 kg, and it is powered by an electric motor to reduce engine exhaust and concerns about carburetor icing. It carries instrumentation to make measurements of broadband up- and downwelling shortwave and longwave radiation, aerosol particle size distribution, atmospheric temperature, relative humidity and pressure and to collect video of flights for subsequent analysis of atmospheric conditions during flight. In order to make the shortwave radiation measurements, care was taken to carefully position a high-quality compact inertial measurement unit (IMU) and characterize the attitude of the aircraft and its orientation to the upward-looking radiation sensor. Using measurements from both of these sensors, a correction is applied to the raw radiometer measurements to correct for aircraft attitude and sensor tilt relative to the sun. The data acquisition system was designed from scratch based on a set of key driving requirements to accommodate the variety of sensors deployed. Initial test flights completed in Colorado provide promising results with measurements from the radiation sensors agreeing with those from a nearby surface site. Additionally, estimates of surface albedo from onboard sensors were consistent with local surface conditions, including melting snow and bright runway surface. Aerosol size distributions collected are internally consistent and have previously been shown to agree well with larger, surface-based instrumentation. Finally the atmospheric state measurements evolve as expected, with the near-surface atmosphere warming over time as the day goes on, and the atmospheric relative humidity decreasing with increased temperature. No directional bias on measured temperature, as might be expected due to uneven heating of the sensor housing over the course of a racetrack pattern, was detected. The results from these flights indicate that the CU Pilatus platform is capable of performing research-grade lower tropospheric measurement missions.

Fiber optic sensors; Proceedings of the Meeting, Cannes, France, November 26, 27, 1985

NASA Technical Reports Server (NTRS)

Arditty, Herve J. (Editor); Jeunhomme, Luc B. (Editor)

1986-01-01

The conference presents papers on distributed sensors and sensor networks, signal processing and detection techniques, temperature measurements, chemical sensors, and the measurement of pressure, strain, and displacements. Particular attention is given to optical fiber distributed sensors and sensor networks, tactile sensing in robotics using an optical network and Z-plane techniques, and a spontaneous Raman temperature sensor. Other topics include coherence in optical fiber gyroscopes, a high bandwidth two-phase flow void fraction fiber optic sensor, and a fiber-optic dark-field microbend sensor.

Looped back fiber mode for reduction of false alarm in leak detection using distributed optical fiber sensor.

PubMed

Chelliah, Pandian; Murgesan, Kasinathan; Samvel, Sosamma; Chelamchala, Babu Rao; Tammana, Jayakumar; Nagarajan, Murali; Raj, Baldev

2010-07-10

Optical-fiber-based sensors have inherent advantages, such as immunity to electromagnetic interference, compared to the conventional sensors. Distributed optical fiber sensor (DOFS) systems, such as Raman and Brillouin distributed temperature sensors are used for leak detection. The inherent noise of fiber-based systems leads to occasional false alarms. In this paper, a methodology is proposed to overcome this. This uses a looped back fiber mode in DOFS and voting logic is employed to considerably reduce the false alarm rate.

Operation of remote mobile sensors for security of drinking water distribution systems.

PubMed

Perelman, By Lina; Ostfeld, Avi

2013-09-01

The deployment of fixed online water quality sensors in water distribution systems has been recognized as one of the key components of contamination warning systems for securing public health. This study proposes to explore how the inclusion of mobile sensors for inline monitoring of various water quality parameters (e.g., residual chlorine, pH) can enhance water distribution system security. Mobile sensors equipped with sampling, sensing, data acquisition, wireless transmission and power generation systems are being designed, fabricated, and tested, and prototypes are expected to be released in the very near future. This study initiates the development of a theoretical framework for modeling mobile sensor movement in water distribution systems and integrating the sensory data collected from stationary and non-stationary sensor nodes to increase system security. The methodology is applied and demonstrated on two benchmark networks. Performance of different sensor network designs are compared for fixed and combined fixed and mobile sensor networks. Results indicate that complementing online sensor networks with inline monitoring can increase detection likelihood and decrease mean time to detection. Copyright © 2013 Elsevier Ltd. All rights reserved.

Multimodal Spatial Calibration for Accurately Registering EEG Sensor Positions

PubMed Central

Chen, Shengyong; Xiao, Gang; Li, Xiaoli

2014-01-01

This paper proposes a fast and accurate calibration method to calibrate multiple multimodal sensors using a novel photogrammetry system for fast localization of EEG sensors. The EEG sensors are placed on human head and multimodal sensors are installed around the head to simultaneously obtain all EEG sensor positions. A multiple views' calibration process is implemented to obtain the transformations of multiple views. We first develop an efficient local repair algorithm to improve the depth map, and then a special calibration body is designed. Based on them, accurate and robust calibration results can be achieved. We evaluate the proposed method by corners of a chessboard calibration plate. Experimental results demonstrate that the proposed method can achieve good performance, which can be further applied to EEG source localization applications on human brain. PMID:24803954

Corrosion monitoring along infrastructures using distributed fiber optic sensing

NASA Astrophysics Data System (ADS)

Alhandawi, Khalil B.; Vahdati, Nader; Shiryayev, Oleg; Lawand, Lydia

2016-04-01

Pipeline Inspection Gauges (PIGs) are used for internal corrosion inspection of oil pipelines every 3-5 years. However, between inspection intervals, rapid corrosion may occur, potentially resulting in major accidents. The motivation behind this research project was to develop a safe distributed corrosion sensor placed inside oil pipelines continuously monitoring corrosion. The intrinsically safe nature of light provided motivation for researching fiber optic sensors as a solution. The sensing fiber's cladding features polymer plastic that is chemically sensitive to hydrocarbons within crude oil mixtures. A layer of metal, used in the oil pipeline's construction, is deposited on the polymer cladding, which upon corrosion, exposes the cladding to surrounding hydrocarbons. The hydrocarbon's interaction with the cladding locally increases the cladding's refractive index in the radial direction. Light intensity of a traveling pulse is reduced due to local reduction in the modal capacity which is interrogated by Optical Time Domain Reflectometery. Backscattered light is captured in real-time while using time delay to resolve location, allowing real-time spatial monitoring of environmental internal corrosion within pipelines spanning large distances. Step index theoretical solutions were used to calculate the power loss due changes in the intensity profile. The power loss is translated into an attenuation coefficient characterizing the expected OTDR trace which was verified against similar experimental results from the literature. A laboratory scale experiment is being developed to assess the validity of the model and the practicality of the solution.

Review of current status of smart structures and integrated systems

NASA Astrophysics Data System (ADS)

Chopra, Inderjit

1996-05-01

A smart structure involves distributed actuators and sensors, and one or more microprocessors that analyze the responses from the sensors and use distributed-parameter control theory to command the actuators to apply localized strains to minimize system response. A smart structure has the capability to respond to a changing external environment (such as loads or shape change) as well as to a changing internal environment (such as damage or failure). It incorporates smart actuators that allow the alteration of system characteristics (such as stiffness or damping) as well as of system response (such as strain or shape) in a controlled manner. Many types of actuators and sensors are being considered, such as piezoelectric materials, shape memory alloys, electrostrictive materials, magnetostrictive materials, electro- rheological fluids and fiber optics. These can be integrated with main load-carrying structures by surface bonding or embedding without causing any significant changes in the mass or structural stiffness of the system. Numerous applications of smart structures technology to various physical systems are evolving to actively control vibration, noise, aeroelastic stability, damping, shape and stress distribution. Applications range from space systems, fixed-wing and rotary-wing aircraft, automotive, civil structures and machine tools. Much of the early development of smart structures methodology was driven by space applications such as vibration and shape control of large flexible space structures, but now wider applications are envisaged for aeronautical and other systems. Embedded or surface-bonded smart actuators on an airplane wing or helicopter blade will induce alteration of twist/camber of airfoil (shape change), that in turn will cause variation of lift distribution and may help to control static and dynamic aeroelastic problems. Applications of smart structures technology to aerospace and other systems are expanding rapidly. Major barriers are: actuator stroke, reliable data base of smart material characteristics, non-availability of robust distributed parameter control strategies, and non-existent mathematical modeling of smart systems. The objective of this paper is to review the state-of-the-art of smart actuators and sensors and integrated systems and point out the needs for future research.

Toward seamless wearable sensing: Automatic on-body sensor localization for physical activity monitoring.

PubMed

Saeedi, Ramyar; Purath, Janet; Venkatasubramanian, Krishna; Ghasemzadeh, Hassan

2014-01-01

Mobile wearable sensors have demonstrated great potential in a broad range of applications in healthcare and wellness. These technologies are known for their potential to revolutionize the way next generation medical services are supplied and consumed by providing more effective interventions, improving health outcomes, and substantially reducing healthcare costs. Despite these potentials, utilization of these sensor devices is currently limited to lab settings and in highly controlled clinical trials. A major obstacle in widespread utilization of these systems is that the sensors need to be used in predefined locations on the body in order to provide accurate outcomes such as type of physical activity performed by the user. This has reduced users' willingness to utilize such technologies. In this paper, we propose a novel signal processing approach that leverages feature selection algorithms for accurate and automatic localization of wearable sensors. Our results based on real data collected using wearable motion sensors demonstrate that the proposed approach can perform sensor localization with 98.4% accuracy which is 30.7% more accurate than an approach without a feature selection mechanism. Furthermore, utilizing our node localization algorithm aids the activity recognition algorithm to achieve 98.8% accuracy (an increase from 33.6% for the system without node localization).

Online Robot Dead Reckoning Localization Using Maximum Relative Entropy Optimization With Model Constraints

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

Urniezius, Renaldas

2011-03-14

The principle of Maximum relative Entropy optimization was analyzed for dead reckoning localization of a rigid body when observation data of two attached accelerometers was collected. Model constraints were derived from the relationships between the sensors. The experiment's results confirmed that accelerometers each axis' noise can be successfully filtered utilizing dependency between channels and the dependency between time series data. Dependency between channels was used for a priori calculation, and a posteriori distribution was derived utilizing dependency between time series data. There was revisited data of autocalibration experiment by removing the initial assumption that instantaneous rotation axis of a rigidmore » body was known. Performance results confirmed that such an approach could be used for online dead reckoning localization.« less

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

An adaptive distributed data aggregation based on RCPC for wireless sensor networks

NASA Astrophysics Data System (ADS)

Hua, Guogang; Chen, Chang Wen

2006-05-01

One of the most important design issues in wireless sensor networks is energy efficiency. Data aggregation has significant impact on the energy efficiency of the wireless sensor networks. With massive deployment of sensor nodes and limited energy supply, data aggregation has been considered as an essential paradigm for data collection in sensor networks. Recently, distributed source coding has been demonstrated to possess several advantages in data aggregation for wireless sensor networks. Distributed source coding is able to encode sensor data with lower bit rate without direct communication among sensor nodes. To ensure reliable and high throughput transmission with the aggregated data, we proposed in this research a progressive transmission and decoding of Rate-Compatible Punctured Convolutional (RCPC) coded data aggregation with distributed source coding. Our proposed 1/2 RSC codes with Viterbi algorithm for distributed source coding are able to guarantee that, even without any correlation between the data, the decoder can always decode the data correctly without wasting energy. The proposed approach achieves two aspects in adaptive data aggregation for wireless sensor networks. First, the RCPC coding facilitates adaptive compression corresponding to the correlation of the sensor data. When the data correlation is high, higher compression ration can be achieved. Otherwise, lower compression ratio will be achieved. Second, the data aggregation is adaptively accumulated. There is no waste of energy in the transmission; even there is no correlation among the data, the energy consumed is at the same level as raw data collection. Experimental results have shown that the proposed distributed data aggregation based on RCPC is able to achieve high throughput and low energy consumption data collection for wireless sensor networks

Network Computing for Distributed Underwater Acoustic Sensors

DTIC Science & Technology

2014-03-31

underwater sensor network with mobility. In preparation. [3] EvoLogics (2013), Underwater Acoustic Modems, (Product Information Guide... Wireless Communications, 9(9), 2934–2944. [21] Pompili, D. and Akyildiz, I. (2010), A multimedia cross-layer protocol for underwater acoustic sensor networks ... Network Computing for Distributed Underwater Acoustic Sensors M. Barbeau E. Kranakis

Parametric Loop Division for 3D Localization in Wireless Sensor Networks

PubMed Central

Ahmad, Tanveer

2017-01-01

Localization in Wireless Sensor Networks (WSNs) has been an active topic for more than two decades. A variety of algorithms were proposed to improve the localization accuracy. However, they are either limited to two-dimensional (2D) space, or require specific sensor deployment for proper operations. In this paper, we proposed a three-dimensional (3D) localization scheme for WSNs based on the well-known parametric Loop division (PLD) algorithm. The proposed scheme localizes a sensor node in a region bounded by a network of anchor nodes. By iteratively shrinking that region towards its center point, the proposed scheme provides better localization accuracy as compared to existing schemes. Furthermore, it is cost-effective and independent of environmental irregularity. We provide an analytical framework for the proposed scheme and find its lower bound accuracy. Simulation results shows that the proposed algorithm provides an average localization accuracy of 0.89 m with a standard deviation of 1.2 m. PMID:28737714

Real-time method for establishing a detection map for a network of sensors

DOEpatents

Nguyen, Hung D; Koch, Mark W; Giron, Casey; Rondeau, Daniel M; Russell, John L

2012-09-11

A method for establishing a detection map of a dynamically configurable sensor network. This method determines an appropriate set of locations for a plurality of sensor units of a sensor network and establishes a detection map for the network of sensors while the network is being set up; the detection map includes the effects of the local terrain and individual sensor performance. Sensor performance is characterized during the placement of the sensor units, which enables dynamic adjustment or reconfiguration of the placement of individual elements of the sensor network during network set-up to accommodate variations in local terrain and individual sensor performance. The reconfiguration of the network during initial set-up to accommodate deviations from idealized individual sensor detection zones improves the effectiveness of the sensor network in detecting activities at a detection perimeter and can provide the desired sensor coverage of an area while minimizing unintentional gaps in coverage.

Implementation of one and three dimensional models for heat transfer coeffcient identification over the plate cooled by the circular water jets

NASA Astrophysics Data System (ADS)

Malinowski, Zbigniew; Cebo-Rudnicka, Agnieszka; Hadała, Beata; Szajding, Artur; Telejko, Tadeusz

2017-10-01

A cooling rate affects the mechanical properties of steel which strongly depend on microstructure evolution processes. The heat transfer boundary condition for the numerical simulation of steel cooling by water jets can be determined from the local one dimensional or from the three dimensional inverse solutions in space and time. In the present study the inconel plate has been heated to about 900 °C and then cooled by six circular water jets. The plate temperature has been measured by 30 thermocouples. The heat transfer coefficient and the heat flux distributions at the plate surface have been determined in time and space. The one dimensional solutions have given a local error to the heat transfer coefficient of about 35%. The three dimensional inverse solution has allowed reducing the local error to about 20%. The uncertainty test has confirmed that a better approximation of the heat transfer coefficient distribution over the cooled surface can be obtained even for limited number of thermocouples. In such a case it was necessary to constrain the inverse solution with the interpolated temperature sensors.

CHAMP: a locally adaptive unmixing-based hyperspectral anomaly detection algorithm

NASA Astrophysics Data System (ADS)

Crist, Eric P.; Thelen, Brian J.; Carrara, David A.

1998-10-01

Anomaly detection offers a means by which to identify potentially important objects in a scene without prior knowledge of their spectral signatures. As such, this approach is less sensitive to variations in target class composition, atmospheric and illumination conditions, and sensor gain settings than would be a spectral matched filter or similar algorithm. The best existing anomaly detectors generally fall into one of two categories: those based on local Gaussian statistics, and those based on linear mixing moles. Unmixing-based approaches better represent the real distribution of data in a scene, but are typically derived and applied on a global or scene-wide basis. Locally adaptive approaches allow detection of more subtle anomalies by accommodating the spatial non-homogeneity of background classes in a typical scene, but provide a poorer representation of the true underlying background distribution. The CHAMP algorithm combines the best attributes of both approaches, applying a linear-mixing model approach in a spatially adaptive manner. The algorithm itself, and teste results on simulated and actual hyperspectral image data, are presented in this paper.

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

Feasibility of approaches combining sensor and source features in brain-computer interface.

PubMed

Ahn, Minkyu; Hong, Jun Hee; Jun, Sung Chan

2012-02-15

Brain-computer interface (BCI) provides a new channel for communication between brain and computers through brain signals. Cost-effective EEG provides good temporal resolution, but its spatial resolution is poor and sensor information is blurred by inherent noise. To overcome these issues, spatial filtering and feature extraction techniques have been developed. Source imaging, transformation of sensor signals into the source space through source localizer, has gained attention as a new approach for BCI. It has been reported that the source imaging yields some improvement of BCI performance. However, there exists no thorough investigation on how source imaging information overlaps with, and is complementary to, sensor information. Information (visible information) from the source space may overlap as well as be exclusive to information from the sensor space is hypothesized. Therefore, we can extract more information from the sensor and source spaces if our hypothesis is true, thereby contributing to more accurate BCI systems. In this work, features from each space (sensor or source), and two strategies combining sensor and source features are assessed. The information distribution among the sensor, source, and combined spaces is discussed through a Venn diagram for 18 motor imagery datasets. Additional 5 motor imagery datasets from the BCI Competition III site were examined. The results showed that the addition of source information yielded about 3.8% classification improvement for 18 motor imagery datasets and showed an average accuracy of 75.56% for BCI Competition data. Our proposed approach is promising, and improved performance may be possible with better head model. Copyright © 2011 Elsevier B.V. All rights reserved.

Integrated multi-sensor fusion for mapping and localization in outdoor environments for mobile robots

NASA Astrophysics Data System (ADS)

Emter, Thomas; Petereit, Janko

2014-05-01

An integrated multi-sensor fusion framework for localization and mapping for autonomous navigation in unstructured outdoor environments based on extended Kalman filters (EKF) is presented. The sensors for localization include an inertial measurement unit, a GPS, a fiber optic gyroscope, and wheel odometry. Additionally a 3D LIDAR is used for simultaneous localization and mapping (SLAM). A 3D map is built while concurrently a localization in a so far established 2D map is estimated with the current scan of the LIDAR. Despite of longer run-time of the SLAM algorithm compared to the EKF update, a high update rate is still guaranteed by sophisticatedly joining and synchronizing two parallel localization estimators.

Field calibration of electrochemical NO2 sensors in a citizen science context

NASA Astrophysics Data System (ADS)

Mijling, Bas; Jiang, Qijun; de Jonge, Dave; Bocconi, Stefano

2018-03-01

In many urban areas the population is exposed to elevated levels of air pollution. However, real-time air quality is usually only measured at few locations. These measurements provide a general picture of the state of the air, but they are unable to monitor local differences. New low-cost sensor technology is available for several years now, and has the potential to extend official monitoring networks significantly even though the current generation of sensors suffer from various technical issues.Citizen science experiments based on these sensors must be designed carefully to avoid generation of data which is of poor or even useless quality. This study explores the added value of the 2016 Urban AirQ campaign, which focused on measuring nitrogen dioxide (NO2) in Amsterdam, the Netherlands. Sixteen low-cost air quality sensor devices were built and distributed among volunteers living close to roads with high traffic volume for a 2-month measurement period. Each electrochemical sensor was calibrated in-field next to an air monitoring station during an 8-day period, resulting in R2 ranging from 0.3 to 0.7. When temperature and relative humidity are included in a multilinear regression approach, the NO2 accuracy is improved significantly, with R2 ranging from 0.6 to 0.9. Recalibration after the campaign is crucial, as all sensors show a significant signal drift in the 2-month measurement period. The measurement series between the calibration periods can be corrected for after the measurement period by taking a weighted average of the calibration coefficients.Validation against an independent air monitoring station shows good agreement. Using our approach, the standard deviation of a typical sensor device for NO2 measurements was found to be 7 µg m-3, provided that temperatures are below 30 °C. Stronger ozone titration on street sides causes an underestimation of NO2 concentrations, which 75 % of the time is less than 2.3 µg m-3.Our findings show that citizen science campaigns using low-cost sensors based on the current generations of electrochemical NO2 sensors may provide useful complementary data on local air quality in an urban setting, provided that experiments are properly set up and the data are carefully analysed.

Localizing on-scalp MEG sensors using an array of magnetic dipole coils.

PubMed

Pfeiffer, Christoph; Andersen, Lau M; Lundqvist, Daniel; Hämäläinen, Matti; Schneiderman, Justin F; Oostenveld, Robert

2018-01-01

Accurate estimation of the neural activity underlying magnetoencephalography (MEG) signals requires co-registration i.e., determination of the position and orientation of the sensors with respect to the head. In modern MEG systems, an array of hundreds of low-Tc SQUID sensors is used to localize a set of small, magnetic dipole-like (head-position indicator, HPI) coils that are attached to the subject's head. With accurate prior knowledge of the positions and orientations of the sensors with respect to one another, the HPI coils can be localized with high precision, and thereby the positions of the sensors in relation to the head. With advances in magnetic field sensing technologies, e.g., high-Tc SQUIDs and optically pumped magnetometers (OPM), that require less extreme operating temperatures than low-Tc SQUID sensors, on-scalp MEG is on the horizon. To utilize the full potential of on-scalp MEG, flexible sensor arrays are preferable. Conventional co-registration is impractical for such systems as the relative positions and orientations of the sensors to each other are subject-specific and hence not known a priori. Herein, we present a method for co-registration of on-scalp MEG sensors. We propose to invert the conventional co-registration approach and localize the sensors relative to an array of HPI coils on the subject's head. We show that given accurate prior knowledge of the positions of the HPI coils with respect to one another, the sensors can be localized with high precision. We simulated our method with realistic parameters and layouts for sensor and coil arrays. Results indicate co-registration is possible with sub-millimeter accuracy, but the performance strongly depends upon a number of factors. Accurate calibration of the coils and precise determination of the positions and orientations of the coils with respect to one another are crucial. Finally, we propose methods to tackle practical challenges to further improve the method.

Localizing on-scalp MEG sensors using an array of magnetic dipole coils

PubMed Central

Andersen, Lau M.; Lundqvist, Daniel; Hämäläinen, Matti; Schneiderman, Justin F.; Oostenveld, Robert

2018-01-01

Accurate estimation of the neural activity underlying magnetoencephalography (MEG) signals requires co-registration i.e., determination of the position and orientation of the sensors with respect to the head. In modern MEG systems, an array of hundreds of low-Tc SQUID sensors is used to localize a set of small, magnetic dipole-like (head-position indicator, HPI) coils that are attached to the subject’s head. With accurate prior knowledge of the positions and orientations of the sensors with respect to one another, the HPI coils can be localized with high precision, and thereby the positions of the sensors in relation to the head. With advances in magnetic field sensing technologies, e.g., high-Tc SQUIDs and optically pumped magnetometers (OPM), that require less extreme operating temperatures than low-Tc SQUID sensors, on-scalp MEG is on the horizon. To utilize the full potential of on-scalp MEG, flexible sensor arrays are preferable. Conventional co-registration is impractical for such systems as the relative positions and orientations of the sensors to each other are subject-specific and hence not known a priori. Herein, we present a method for co-registration of on-scalp MEG sensors. We propose to invert the conventional co-registration approach and localize the sensors relative to an array of HPI coils on the subject’s head. We show that given accurate prior knowledge of the positions of the HPI coils with respect to one another, the sensors can be localized with high precision. We simulated our method with realistic parameters and layouts for sensor and coil arrays. Results indicate co-registration is possible with sub-millimeter accuracy, but the performance strongly depends upon a number of factors. Accurate calibration of the coils and precise determination of the positions and orientations of the coils with respect to one another are crucial. Finally, we propose methods to tackle practical challenges to further improve the method. PMID:29746486

An Expert System And Simulation Approach For Sensor Management & Control In A Distributed Surveillance Network

NASA Astrophysics Data System (ADS)

Leon, Barbara D.; Heller, Paul R.

1987-05-01

A surveillance network is a group of multiplatform sensors cooperating to improve network performance. Network control is distributed as a measure to decrease vulnerability to enemy threat. The network may contain diverse sensor types such as radar, ESM (Electronic Support Measures), IRST (Infrared search and track) and E-0 (Electro-Optical). Each platform may contain a single sensor or suite of sensors. In a surveillance network it is desirable to control sensors to make the overall system more effective. This problem has come to be known as sensor management and control (SM&C). Two major facets of network performance are surveillance and survivability. In a netted environment, surveillance can be enhanced if information from all sensors is combined and sensor operating conditions are controlled to provide a synergistic effect. In contrast, when survivability is the main concern for the network, the best operating status for all sensors would be passive or off. Of course, improving survivability tends to degrade surveillance. Hence, the objective of SM&C is to optimize surveillance and survivability of the network. Too voluminous data of various formats and the quick response time are two characteristics of this problem which make it an ideal application for Artificial Intelligence. A solution to the SM&C problem, presented as a computer simulation, will be presented in this paper. The simulation is a hybrid production written in LISP and FORTRAN. It combines the latest conventional computer programming methods with Artificial Intelligence techniques to produce a flexible state-of-the-art tool to evaluate network performance. The event-driven simulation contains environment models coupled with an expert system. These environment models include sensor (track-while-scan and agile beam) and target models, local tracking, and system tracking. These models are used to generate the environment for the sensor management and control expert system. The expert system, driven by a forward chaining inference engine, makes decisions based on the global database. The global database contains current track and sensor information supplied by the simulation. At present, the rule base emphasizes the surveillance features with rules grouped into three main categories: maintenance and enhancing track on prioritized targets; filling coverage holes and countering jamming; and evaluating sensor status. The paper will describe the architecture used for the expert system and the reasons for selecting the chosen methods. The SM&C simulation produces a graphical representation of sensors and their associated tracks such that the benefits of the sensor management and control expert system are evident. Jammer locations are also part of the display. The paper will describe results from several scenarios that best illustrate the sensor management and control concepts.

All-fiber optoelectronic sensor with Bragg gratings for in-situ cure monitoring

NASA Astrophysics Data System (ADS)

Cusano, Andrea; Breglio, Giovanni; Cutolo, Antonello; Calabro, Antonio M.; Giordano, Michele; Nicolais, Luigi, II

2000-08-01

Real-time, in situ monitoring for quality control of the polymer cure process is of high interest, since thermoset polymer-matrix composite are widely used in large industrial areas: aeronautical, aerospace, automotive and civil due to their low cost/low weight features. However, their final properties are strongly dependence on the processing parameters, such as temperature and pressure sequence. The key-point for advanced composite materials is the possibility to have distributed and simultaneous monitoring of chemoreological and physical properties during the cure process. To this aim, we have developed and tested an optoelectronic fiber optic sensor based on the Fresnel principle able to monitor the variations of the refractive index due to the cure process of an epoxy based resin. Experimental results have been obtained on sensor capability to monitor the cure kinetics by assuming the refractive index as reaction co-ordinate. The integration with in-fiber Bragg grating in order to measure the local temperature has been discussed and tested.

Managed traffic evacuation using distributed sensor processing

NASA Astrophysics Data System (ADS)

Ramuhalli, Pradeep; Biswas, Subir

2005-05-01

This paper presents an integrated sensor network and distributed event processing architecture for managed in-building traffic evacuation during natural and human-caused disasters, including earthquakes, fire and biological/chemical terrorist attacks. The proposed wireless sensor network protocols and distributed event processing mechanisms offer a new distributed paradigm for improving reliability in building evacuation and disaster management. The networking component of the system is constructed using distributed wireless sensors for measuring environmental parameters such as temperature, humidity, and detecting unusual events such as smoke, structural failures, vibration, biological/chemical or nuclear agents. Distributed event processing algorithms will be executed by these sensor nodes to detect the propagation pattern of the disaster and to measure the concentration and activity of human traffic in different parts of the building. Based on this information, dynamic evacuation decisions are taken for maximizing the evacuation speed and minimizing unwanted incidents such as human exposure to harmful agents and stampedes near exits. A set of audio-visual indicators and actuators are used for aiding the automated evacuation process. In this paper we develop integrated protocols, algorithms and their simulation models for the proposed sensor networking and the distributed event processing framework. Also, efficient harnessing of the individually low, but collectively massive, processing abilities of the sensor nodes is a powerful concept behind our proposed distributed event processing algorithms. Results obtained through simulation in this paper are used for a detailed characterization of the proposed evacuation management system and its associated algorithmic components.

Distributed sensor management for space situational awareness via a negotiation game

NASA Astrophysics Data System (ADS)

Jia, Bin; Shen, Dan; Pham, Khanh; Blasch, Erik; Chen, Genshe

2015-05-01

Space situational awareness (SSA) is critical to many space missions serving weather analysis, communications, and navigation. However, the number of sensors used in space situational awareness is limited which hinders collision avoidance prediction, debris assessment, and efficient routing. Hence, it is critical to use such sensor resources efficiently. In addition, it is desired to develop the SSA sensor management algorithm in a distributed manner. In this paper, a distributed sensor management approach using the negotiation game (NG-DSM) is proposed for the SSA. Specifically, the proposed negotiation game is played by each sensor and its neighboring sensors. The bargaining strategies are developed for each sensor based on negotiating for accurately tracking desired targets (e.g., satellite, debris, etc.) . The proposed NG-DSM method is tested in a scenario which includes eight space objects and three different sensor modalities which include a space based optical sensor, a ground radar, or a ground Electro-Optic sensor. The geometric relation between the sensor, the Sun, and the space object is also considered. The simulation results demonstrate the effectiveness of the proposed NG-DSM sensor management methods, which facilitates an application of multiple-sensor multiple-target tracking for space situational awareness.

Localization and Tracking of Implantable Biomedical Sensors

PubMed Central

Umay, Ilknur; Fidan, Barış; Barshan, Billur

2017-01-01

Implantable sensor systems are effective tools for biomedical diagnosis, visualization and treatment of various health conditions, attracting the interest of researchers, as well as healthcare practitioners. These systems efficiently and conveniently provide essential data of the body part being diagnosed, such as gastrointestinal (temperature, pH, pressure) parameter values, blood glucose and pressure levels and electrocardiogram data. Such data are first transmitted from the implantable sensor units to an external receiver node or network and then to a central monitoring and control (computer) unit for analysis, diagnosis and/or treatment. Implantable sensor units are typically in the form of mobile microrobotic capsules or implanted stationary (body-fixed) units. In particular, capsule-based systems have attracted significant research interest recently, with a variety of applications, including endoscopy, microsurgery, drug delivery and biopsy. In such implantable sensor systems, one of the most challenging problems is the accurate localization and tracking of the microrobotic sensor unit (e.g., robotic capsule) inside the human body. This article presents a literature review of the existing localization and tracking techniques for robotic implantable sensor systems with their merits and limitations and possible solutions of the proposed localization methods. The article also provides a brief discussion on the connection and cooperation of such techniques with wearable biomedical sensor systems. PMID:28335384

Structural Anomaly Detection Using Fiber Optic Sensors and Inverse Finite Element Method

NASA Technical Reports Server (NTRS)

Quach, Cuong C.; Vazquez, Sixto L.; Tessler, Alex; Moore, Jason P.; Cooper, Eric G.; Spangler, Jan. L.

2005-01-01

NASA Langley Research Center is investigating a variety of techniques for mitigating aircraft accidents due to structural component failure. One technique under consideration combines distributed fiber optic strain sensing with an inverse finite element method for detecting and characterizing structural anomalies anomalies that may provide early indication of airframe structure degradation. The technique identifies structural anomalies that result in observable changes in localized strain but do not impact the overall surface shape. Surface shape information is provided by an Inverse Finite Element Method that computes full-field displacements and internal loads using strain data from in-situ fiberoptic sensors. This paper describes a prototype of such a system and reports results from a series of laboratory tests conducted on a test coupon subjected to increasing levels of damage.

Underwater robot society doing internal inspection and leak monitoring of water systems

NASA Astrophysics Data System (ADS)

Halme, Aarne; Vainio, Mika; Appelqvist, Pekka; Jakubik, Peter; Schonberg, Torsten; Visala, Arto

1997-09-01

In the field of civil engineering an effective internal monitoring of pipes and water storage is very problematic. Normally the sensors used for the task are either fixed or manually movable. Thus they will only provide locally and temporally restricted information. As a solution an underwater robotic sensor/actuator society is presented. The system is capable of operating inside a fluid environment as a kind of distributed sensory system. The value of the system emerges from the interactions between the members. Through a communication system the society fuses information from individual members and provides a more reliable estimate of the conditions inside water systems. Tests results in a transparent demo process consisting of tanks and pipes with a volume of 700 liters are presented.

System approach to distributed sensor management

NASA Astrophysics Data System (ADS)

Mayott, Gregory; Miller, Gordon; Harrell, John; Hepp, Jared; Self, Mid

2010-04-01

Since 2003, the US Army's RDECOM CERDEC Night Vision Electronic Sensor Directorate (NVESD) has been developing a distributed Sensor Management System (SMS) that utilizes a framework which demonstrates application layer, net-centric sensor management. The core principles of the design support distributed and dynamic discovery of sensing devices and processes through a multi-layered implementation. This results in a sensor management layer that acts as a System with defined interfaces for which the characteristics, parameters, and behaviors can be described. Within the framework, the definition of a protocol is required to establish the rules for how distributed sensors should operate. The protocol defines the behaviors, capabilities, and message structures needed to operate within the functional design boundaries. The protocol definition addresses the requirements for a device (sensors or processes) to dynamically join or leave a sensor network, dynamically describe device control and data capabilities, and allow dynamic addressing of publish and subscribe functionality. The message structure is a multi-tiered definition that identifies standard, extended, and payload representations that are specifically designed to accommodate the need for standard representations of common functions, while supporting the need for feature-based functions that are typically vendor specific. The dynamic qualities of the protocol enable a User GUI application the flexibility of mapping widget-level controls to each device based on reported capabilities in real-time. The SMS approach is designed to accommodate scalability and flexibility within a defined architecture. The distributed sensor management framework and its application to a tactical sensor network will be described in this paper.

Data center thermal management

DOEpatents

Hamann, Hendrik F.; Li, Hongfei

2016-02-09

Historical high-spatial-resolution temperature data and dynamic temperature sensor measurement data may be used to predict temperature. A first formulation may be derived based on the historical high-spatial-resolution temperature data for determining a temperature at any point in 3-dimensional space. The dynamic temperature sensor measurement data may be calibrated based on the historical high-spatial-resolution temperature data at a corresponding historical time. Sensor temperature data at a plurality of sensor locations may be predicted for a future time based on the calibrated dynamic temperature sensor measurement data. A three-dimensional temperature spatial distribution associated with the future time may be generated based on the forecasted sensor temperature data and the first formulation. The three-dimensional temperature spatial distribution associated with the future time may be projected to a two-dimensional temperature distribution, and temperature in the future time for a selected space location may be forecasted dynamically based on said two-dimensional temperature distribution.

NASA Mars rover: a testbed for evaluating applications of covariance intersection

NASA Astrophysics Data System (ADS)

Uhlmann, Jeffrey K.; Julier, Simon J.; Kamgar-Parsi, Behzad; Lanzagorta, Marco O.; Shyu, Haw-Jye S.

1999-07-01

The Naval Research Laboratory (NRL) has spearheaded the development and application of Covariance Intersection (CI) for a variety of decentralized data fusion problems. Such problems include distributed control, onboard sensor fusion, and dynamic map building and localization. In this paper we describe NRL's development of a CI-based navigation system for the NASA Mars rover that stresses almost all aspects of decentralized data fusion. We also describe how this project relates to NRL's augmented reality, advanced visualization, and REBOT projects.

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.

Mapping Arid Vegetation Species Distributions in the White Mountains, Eastern California, Using AVIRIS, Topography, and Geology

NASA Technical Reports Server (NTRS)

VandeVen, C.; Weiss, S. B.

2001-01-01

Our challenge is to model plant species distributions in complex montane environments using disparate sources of data, including topography, geology, and hyperspectral data. From an ecologist's point of view, species distributions are determined by local environment and disturbance history, while spectral data are 'ancillary.' However, a remote sensor's perspective says that spectral data provide picture of what vegetation is there, topographic and geologic data are ancillary. In order to bridge the gap, all available data should be used to get the best possible prediction of species distributions using complex multivariate techniques implemented on a GIS. Vegetation reflects local climatic and nutrient conditions, both of which can be modeled, allowing predictive mapping of vegetation distributions. Geologic substrate strongly affects chemical, thermal, and physical properties of soils, while climatic conditions are determined by local topography. As elevation increases, precipitation increases and temperature decreases. Aspect, slope, and surrounding topography determine potential insolation, so that south-facing slopes are warmer and north-facing slopes cooler at a given elevation. Topographic position (ridge, slope, canyon, or meadow) and slope angle affect sediment accumulation and soil depth. These factors combine as complex environmental gradients, and underlie many features of plant distributions. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data, digital elevation models, digitized geologic maps, and 378 ground control points were used to predictively map species distributions in the central and southern White Mountains, along the western boundary of the Basin and Range province. Minimum Noise Fraction (MNF) bands were calculated from the visible and near-infrared AVIRIS bands, and combined with digitized geologic maps and topographic variables using Canonical Correspondence Analysis (CCA). CCA allows for modeling species 'envelopes' in multidimensional environmental space, which can then be projected across entire landscapes.

Passive wireless antenna sensors for crack detection and shear/compression sensing

NASA Astrophysics Data System (ADS)

Mohammad, Irshad

Despite the fact that engineering components and structures are carefully designed against fatigue failures, 50 to 90% of mechanical failures are due to fatigue crack development. The severity of the failure depends on both the crack length and its orientation. Many types of sensors are available that can detect fatigue crack propagation. However, crack orientation detection has been rarely reported in the literature. We evaluated a patch antenna sensor capable of detecting crack propagation as well as crack orientation changes. The aim of these sensors would be to evaluate the real-time health condition of metallic structures to avoid catastrophic failures. The proposed crack sensing system consists of a dielectric substrate with a ground plane on one side of the substrate and an antenna patch printed on the other side of the substrate. The ground plane and the antenna patch, both conductive in nature, form an electromagnetic resonant cavity that radiates at distinct frequencies. These frequencies are monitored to evaluate the condition of cracks. A wireless sensor array can be realized by implementing a wireless interrogation unit. The scientific merits of this research are: 1) high sensitivity: it was demonstrated that the antenna sensors can detect crack growth with a sub-millimeter resolution; 2) passive wireless operation: based on microstrip antennas, the antenna sensors encode the sensing information in the backscattered antenna signal and thus can transmit the information without needing a local battery; 3) thin and conformal: the entire sensor unit is less than a millimeter thick and highly conformal; 4) crack orientation detection: the crack orientation on the structure can be precisely evaluated based on a single parameter, which only few sensors can accomplish. In addition to crack detection, the patch antenna sensors are also investigated for measuring shear and pressure forces, with an aim to study the formation, diagnostics and prevention of foot ulcers in diabetic patients. These sensors were vertically integrated and embedded in the insole of shoes for measuring plantar pressure/shear distribution. The scientific merits of this proposed research are: 1) simultaneous shear/pressure measurement : current smart shoe technology can only measure shear and pressure separately due to the size of the shear sensor. The proposed sensor can measure shear and pressure deformation simultaneously; 2) high sensitivity and spatial resolution: these sensors are very sensitive and have compact size that enables measuring stress distribution with fine spatial resolution; 3) passive and un-tethered operation: the sensor transponder was mounted on the top surface of the shoe to facilitate wireless interrogation of the sensor array embedded in the insole of the shoe, eliminating external wiring completely.

Nanotechnology Propellant Health Monitoring Sensors; Success Through Multi-Stakeholder Interests

DTIC Science & Technology

2014-11-01

Passive AgeAlert sensors integrate well with passive (no battery!) RFID technology: • RFID reader provides rf energy to read tag providing tag...be added • Reader access to secure server means real time updates Propellant aging sensor Shock sensor Passive RFID tag RFID reader Polymer Aging...Aging Concepts, Inc., Distribution A: Approved for Public Release; Distribution Unlimited Integration of AgeAlert Sensors and Passive RFID 12

Estimation of Visual Maps with a Robot Network Equipped with Vision Sensors

PubMed Central

Gil, Arturo; Reinoso, Óscar; Ballesta, Mónica; Juliá, Miguel; Payá, Luis

2010-01-01

In this paper we present an approach to the Simultaneous Localization and Mapping (SLAM) problem using a team of autonomous vehicles equipped with vision sensors. The SLAM problem considers the case in which a mobile robot is equipped with a particular sensor, moves along the environment, obtains measurements with its sensors and uses them to construct a model of the space where it evolves. In this paper we focus on the case where several robots, each equipped with its own sensor, are distributed in a network and view the space from different vantage points. In particular, each robot is equipped with a stereo camera that allow the robots to extract visual landmarks and obtain relative measurements to them. We propose an algorithm that uses the measurements obtained by the robots to build a single accurate map of the environment. The map is represented by the three-dimensional position of the visual landmarks. In addition, we consider that each landmark is accompanied by a visual descriptor that encodes its visual appearance. The solution is based on a Rao-Blackwellized particle filter that estimates the paths of the robots and the position of the visual landmarks. The validity of our proposal is demonstrated by means of experiments with a team of real robots in a office-like indoor environment. PMID:22399930

Estimation of visual maps with a robot network equipped with vision sensors.

PubMed

Gil, Arturo; Reinoso, Óscar; Ballesta, Mónica; Juliá, Miguel; Payá, Luis

2010-01-01

In this paper we present an approach to the Simultaneous Localization and Mapping (SLAM) problem using a team of autonomous vehicles equipped with vision sensors. The SLAM problem considers the case in which a mobile robot is equipped with a particular sensor, moves along the environment, obtains measurements with its sensors and uses them to construct a model of the space where it evolves. In this paper we focus on the case where several robots, each equipped with its own sensor, are distributed in a network and view the space from different vantage points. In particular, each robot is equipped with a stereo camera that allow the robots to extract visual landmarks and obtain relative measurements to them. We propose an algorithm that uses the measurements obtained by the robots to build a single accurate map of the environment. The map is represented by the three-dimensional position of the visual landmarks. In addition, we consider that each landmark is accompanied by a visual descriptor that encodes its visual appearance. The solution is based on a Rao-Blackwellized particle filter that estimates the paths of the robots and the position of the visual landmarks. The validity of our proposal is demonstrated by means of experiments with a team of real robots in a office-like indoor environment.

Fiber-connected position localization sensor networks

NASA Astrophysics Data System (ADS)

Pan, Shilong; Zhu, Dan; Fu, Jianbin; Yao, Tingfeng

2014-11-01

Position localization has drawn great attention due to its wide applications in radars, sonars, electronic warfare, wireless communications and so on. Photonic approaches to realize position localization can achieve high-resolution, which also provides the possibility to move the signal processing from each sensor node to the central station, thanks to the low loss, immunity to electromagnetic interference (EMI) and broad bandwidth brought by the photonic technologies. In this paper, we present a review on the recent works of position localization based on photonic technologies. A fiber-connected ultra-wideband (UWB) sensor network using optical time-division multiplexing (OTDM) is proposed to realize high-resolution localization and moving the signal processing to the central station. A 3.9-cm high spatial resolution is achieved. A wavelength-division multiplexed (WDM) fiber-connected sensor network is also demonstrated to realize location which is independent of the received signal format.

Obtaining high-resolution stage forecasts by coupling large-scale hydrologic models with sensor data

NASA Astrophysics Data System (ADS)

Fries, K. J.; Kerkez, B.

2017-12-01

We investigate how "big" quantities of distributed sensor data can be coupled with a large-scale hydrologic model, in particular the National Water Model (NWM), to obtain hyper-resolution forecasts. The recent launch of the NWM provides a great example of how growing computational capacity is enabling a new generation of massive hydrologic models. While the NWM spans an unprecedented spatial extent, there remain many questions about how to improve forecast at the street-level, the resolution at which many stakeholders make critical decisions. Further, the NWM runs on supercomputers, so water managers who may have access to their own high-resolution measurements may not readily be able to assimilate them into the model. To that end, we ask the question: how can the advances of the large-scale NWM be coupled with new local observations to enable hyper-resolution hydrologic forecasts? A methodology is proposed whereby the flow forecasts of the NWM are directly mapped to high-resolution stream levels using Dynamical System Identification. We apply the methodology across a sensor network of 182 gages in Iowa. Of these sites, approximately one third have shown to perform well in high-resolution flood forecasting when coupled with the outputs of the NWM. The quality of these forecasts is characterized using Principal Component Analysis and Random Forests to identify where the NWM may benefit from new sources of local observations. We also discuss how this approach can help municipalities identify where they should place low-cost sensors to most benefit from flood forecasts of the NWM.

Deploying temporary networks for upscaling of sparse network stations

NASA Astrophysics Data System (ADS)

Coopersmith, Evan J.; Cosh, Michael H.; Bell, Jesse E.; Kelly, Victoria; Hall, Mark; Palecki, Michael A.; Temimi, Marouane

2016-10-01

Soil observations networks at the national scale play an integral role in hydrologic modeling, drought assessment, agricultural decision support, and our ability to understand climate change. Understanding soil moisture variability is necessary to apply these measurements to model calibration, business and consumer applications, or even human health issues. The installation of soil moisture sensors as sparse, national networks is necessitated by limited financial resources. However, this results in the incomplete sampling of the local heterogeneity of soil type, vegetation cover, topography, and the fine spatial distribution of precipitation events. To this end, temporary networks can be installed in the areas surrounding a permanent installation within a sparse network. The temporary networks deployed in this study provide a more representative average at the 3 km and 9 km scales, localized about the permanent gauge. The value of such temporary networks is demonstrated at test sites in Millbrook, New York and Crossville, Tennessee. The capacity of a single U.S. Climate Reference Network (USCRN) sensor set to approximate the average of a temporary network at the 3 km and 9 km scales using a simple linear scaling function is tested. The capacity of a temporary network to provide reliable estimates with diminishing numbers of sensors, the temporal stability of those networks, and ultimately, the relationship of the variability of those networks to soil moisture conditions at the permanent sensor are investigated. In this manner, this work demonstrates the single-season installation of a temporary network as a mechanism to characterize the soil moisture variability at a permanent gauge within a sparse network.

Fog Computing and Edge Computing Architectures for Processing Data From Diabetes Devices Connected to the Medical Internet of Things.

PubMed

Klonoff, David C

2017-07-01

The Internet of Things (IoT) is generating an immense volume of data. With cloud computing, medical sensor and actuator data can be stored and analyzed remotely by distributed servers. The results can then be delivered via the Internet. The number of devices in IoT includes such wireless diabetes devices as blood glucose monitors, continuous glucose monitors, insulin pens, insulin pumps, and closed-loop systems. The cloud model for data storage and analysis is increasingly unable to process the data avalanche, and processing is being pushed out to the edge of the network closer to where the data-generating devices are. Fog computing and edge computing are two architectures for data handling that can offload data from the cloud, process it nearby the patient, and transmit information machine-to-machine or machine-to-human in milliseconds or seconds. Sensor data can be processed near the sensing and actuating devices with fog computing (with local nodes) and with edge computing (within the sensing devices). Compared to cloud computing, fog computing and edge computing offer five advantages: (1) greater data transmission speed, (2) less dependence on limited bandwidths, (3) greater privacy and security, (4) greater control over data generated in foreign countries where laws may limit use or permit unwanted governmental access, and (5) lower costs because more sensor-derived data are used locally and less data are transmitted remotely. Connected diabetes devices almost all use fog computing or edge computing because diabetes patients require a very rapid response to sensor input and cannot tolerate delays for cloud computing.

Recent Progress in Brillouin Scattering Based Fiber Sensors

PubMed Central

Bao, Xiaoyi; Chen, Liang

2011-01-01

Brillouin scattering in optical fiber describes the interaction of an electro-magnetic field (photon) with a characteristic density variation of the fiber. When the electric field amplitude of an optical beam (so-called pump wave), and another wave is introduced at the downshifted Brillouin frequency (namely Stokes wave), the beating between the pump and Stokes waves creates a modified density change via the electrostriction effect, resulting in so-called the stimulated Brillouin scattering. The density variation is associated with a mechanical acoustic wave; and it may be affected by local temperature, strain, and vibration which induce changes in the fiber effective refractive index and sound velocity. Through the measurement of the static or dynamic changes in Brillouin frequency along the fiber one can realize a distributed fiber sensor for local temperature, strain and vibration over tens or hundreds of kilometers. This paper reviews the progress on improving sensing performance parameters like spatial resolution, sensing length limitation and simultaneous temperature and strain measurement. These kinds of sensors can be used in civil structural monitoring of pipelines, bridges, dams, and railroads for disaster prevention. Analogous to the static Bragg grating, one can write a moving Brillouin grating in fibers, with the lifetime of the acoustic wave. The length of the Brillouin grating can be controlled by the writing pulses at any position in fibers. Such gratings can be used to measure changes in birefringence, which is an important parameter in fiber communications. Applications for this kind of sensor can be found in aerospace, material processing and fine structures. PMID:22163842

Recent progress in Brillouin scattering based fiber sensors.

PubMed

Bao, Xiaoyi; Chen, Liang

2011-01-01

Brillouin scattering in optical fiber describes the interaction of an electro-magnetic field (photon) with a characteristic density variation of the fiber. When the electric field amplitude of an optical beam (so-called pump wave), and another wave is introduced at the downshifted Brillouin frequency (namely Stokes wave), the beating between the pump and Stokes waves creates a modified density change via the electrostriction effect, resulting in so-called the stimulated Brillouin scattering. The density variation is associated with a mechanical acoustic wave; and it may be affected by local temperature, strain, and vibration which induce changes in the fiber effective refractive index and sound velocity. Through the measurement of the static or dynamic changes in Brillouin frequency along the fiber one can realize a distributed fiber sensor for local temperature, strain and vibration over tens or hundreds of kilometers. This paper reviews the progress on improving sensing performance parameters like spatial resolution, sensing length limitation and simultaneous temperature and strain measurement. These kinds of sensors can be used in civil structural monitoring of pipelines, bridges, dams, and railroads for disaster prevention. Analogous to the static Bragg grating, one can write a moving Brillouin grating in fibers, with the lifetime of the acoustic wave. The length of the Brillouin grating can be controlled by the writing pulses at any position in fibers. Such gratings can be used to measure changes in birefringence, which is an important parameter in fiber communications. Applications for this kind of sensor can be found in aerospace, material processing and fine structures.

Marker-Based Multi-Sensor Fusion Indoor Localization System for Micro Air Vehicles.

PubMed

Xing, Boyang; Zhu, Quanmin; Pan, Feng; Feng, Xiaoxue

2018-05-25

A novel multi-sensor fusion indoor localization algorithm based on ArUco marker is designed in this paper. The proposed ArUco mapping algorithm can build and correct the map of markers online with Grubbs criterion and K-mean clustering, which avoids the map distortion due to lack of correction. Based on the conception of multi-sensor information fusion, the federated Kalman filter is utilized to synthesize the multi-source information from markers, optical flow, ultrasonic and the inertial sensor, which can obtain a continuous localization result and effectively reduce the position drift due to the long-term loss of markers in pure marker localization. The proposed algorithm can be easily implemented in a hardware of one Raspberry Pi Zero and two STM32 micro controllers produced by STMicroelectronics (Geneva, Switzerland). Thus, a small-size and low-cost marker-based localization system is presented. The experimental results show that the speed estimation result of the proposed system is better than Px4flow, and it has the centimeter accuracy of mapping and positioning. The presented system not only gives satisfying localization precision, but also has the potential to expand other sensors (such as visual odometry, ultra wideband (UWB) beacon and lidar) to further improve the localization performance. The proposed system can be reliably employed in Micro Aerial Vehicle (MAV) visual localization and robotics control.

Theoretical analyses of localized surface plasmon resonance spectrum with nanoparticles imprinted polymers

NASA Astrophysics Data System (ADS)

Li, Hong; Peng, Wei; Wang, Yanjie; Hu, Lingling; Liang, Yuzhang; Zhang, Xinpu; Yao, Wenjuan; Yu, Qi; Zhou, Xinlei

2011-12-01

Optical sensors based on nanoparticles induced Localized Surface Plasmon Resonance are more sensitive to real-time chemical and biological sensing, which have attracted intensive attentions in many fields. In this paper, we establish a simulation model based on nanoparticles imprinted polymer to increase sensitivity of the LSPR sensor by detecting the changes of Surface Plasmon Resonance signals. Theoretical analysis and numerical simulation of parameters effects to absorption peak and light field distribution are highlighted. Two-dimensional simulated color maps show that LSPR lead to centralization of the light energy around the gold nanoparticles, Transverse Magnetic wave and total reflection become the important factors to enhance the light field in our simulated structure. Fast Fourier Transfer analysis shows that the absorption peak of the surface plasmon resonance signal resulted from gold nanoparticles is sharper while its wavelength is bigger by comparing with silver nanoparticles; a double chain structure make the amplitude of the signals smaller, and make absorption wavelength longer; the absorption peak of enhancement resulted from nanopore arrays has smaller wavelength and weaker amplitude in contrast with nanoparticles. These simulation results of the Localized Surface Plasmon Resonance can be used as an enhanced transduction mechanism for enhancement of sensitivity in recognition and sensing of target analytes in accordance with different requirements.

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.

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

Au-Graphene Hybrid Plasmonic Nanostructure Sensor Based on Intensity Shift

PubMed Central

Alharbi, Raed; Irannejad, Mehrdad; Yavuz, Mustafa

2017-01-01

Integrating plasmonic materials, like gold with a two-dimensional material (e.g., graphene) enhances the light-material interaction and, hence, plasmonic properties of the metallic nanostructure. A localized surface plasmon resonance sensor is an effective platform for biomarker detection. They offer a better bulk surface (local) sensitivity than a regular surface plasmon resonance (SPR) sensor; however, they suffer from a lower figure of merit compared to that one in a propagating surface plasmon resonance sensors. In this work, a decorated multilayer graphene film with an Au nanostructures was proposed as a liquid sensor. The results showed a significant improvement in the figure of merit compared with other reported localized surface plasmon resonance sensors. The maximum figure of merit and intensity sensitivity of 240 and 55 RIU−1 (refractive index unit) at refractive index change of 0.001 were achieved which indicate the capability of the proposed sensor to detect a small change in concentration of liquids in the ng/mL level which is essential in early-stage cancer disease detection. PMID:28106850

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

NASA Astrophysics Data System (ADS)

Zhao, Ming; Han, Baoling

2016-11-01

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

A Research on Low Modulus Distributed Fiber Optical Sensor for Pavement Material Strain Monitoring

PubMed Central

Meng, Lingjian; Wang, Linbing; Hou, Yue; Yan, Guannan

2017-01-01

The accumulated irreversible deformation in pavement under repeated vehicle loadings will cause fatigue failure of asphalt concrete. It is necessary to monitor the mechanical response of pavement under load by using sensors. Previous studies have limitations in modulus accommodation between the sensor and asphalt pavement, and it is difficult to achieve the distributed monitoring goal. To solve these problems, a new type of low modulus distributed optical fiber sensor (DOFS) for asphalt pavement strain monitoring is fabricated. Laboratory experiments have proved the applicability and accuracy of the newly-designed sensor. This paper presents the results of the development. PMID:29048393

A Research on Low Modulus Distributed Fiber Optical Sensor for Pavement Material Strain Monitoring.

PubMed

Meng, Lingjian; Wang, Linbing; Hou, Yue; Yan, Guannan

2017-10-19

The accumulated irreversible deformation in pavement under repeated vehicle loadings will cause fatigue failure of asphalt concrete. It is necessary to monitor the mechanical response of pavement under load by using sensors. Previous studies have limitations in modulus accommodation between the sensor and asphalt pavement, and it is difficult to achieve the distributed monitoring goal. To solve these problems, a new type of low modulus distributed optical fiber sensor (DOFS) for asphalt pavement strain monitoring is fabricated. Laboratory experiments have proved the applicability and accuracy of the newly-designed sensor. This paper presents the results of the development.

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

Real-Time Adaptation of Decision Thresholds in Sensor Networks for Detection of Moving Targets (PREPRINT)

DTIC Science & Technology

2010-01-01

target kinematics for multiple sensor detections is referred to as the track - before - detect strategy, and is commonly adopted in multi-sensor surveillance...of moving targets. Wettergren [4] presented an application of track - before - detect strategies to undersea distributed sensor networks. In de- signing...the deployment of a distributed passive sensor network that employs this track - before - detect procedure, it is impera- tive that the placement of

ADAPTable Sensor Systems Phase 2. Topic 2: Reusable Core Software. Distributed Synchronization Software for the Sensor Nodes

DTIC Science & Technology

2015-03-01

Wireless Sensor Network Using Unreliable GPS Signals Daniel R. Fuhrmann*, Joshua Stomberg§, Saeid Nooshabadi*§ Dustin McIntire†, William Merill... wireless sensor network , when the timing jitter is subject to a empirically determined bimodal non-Gaussian distribution. Specifically, we 1) estimate the...over a nominal 19.2 MHz frequency with an adjustment made every four hours. Index Terms— clock synchronization, GPS, wireless sensor networks , Kalman

Localization of Ferromagnetic Target with Three Magnetic Sensors in the Movement Considering Angular Rotation

PubMed Central

Gao, Xiang; Yan, Shenggang; Li, Bin

2017-01-01

Magnetic detection techniques have been widely used in many fields, such as virtual reality, surgical robotics systems, and so on. A large number of methods have been developed to obtain the position of a ferromagnetic target. However, the angular rotation of the target relative to the sensor is rarely studied. In this paper, a new method for localization of moving object to determine both the position and rotation angle with three magnetic sensors is proposed. Trajectory localization estimation of three magnetic sensors, which are collinear and noncollinear, were obtained by the simulations, and experimental results demonstrated that the position and rotation angle of ferromagnetic target having roll, pitch or yaw in its movement could be calculated accurately and effectively with three noncollinear vector sensors. PMID:28892006

Probability and Statistics in Sensor Performance Modeling

DTIC Science & Technology

2010-12-01

language software program is called Environmental Awareness for Sensor and Emitter Employment. Some important numerical issues in the implementation...3 Statistical analysis for measuring sensor performance...complementary cumulative distribution function cdf cumulative distribution function DST decision-support tool EASEE Environmental Awareness of

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.

Achieving Passive Localization with Traffic Light Schedules in Urban Road Sensor Networks

PubMed Central

Niu, Qiang; Yang, Xu; Gao, Shouwan; Chen, Pengpeng; Chan, Shibing

2016-01-01

Localization is crucial for the monitoring applications of cities, such as road monitoring, environment surveillance, vehicle tracking, etc. In urban road sensor networks, sensors are often sparely deployed due to the hardware cost. Under this sparse deployment, sensors cannot communicate with each other via ranging hardware or one-hop connectivity, rendering the existing localization solutions ineffective. To address this issue, this paper proposes a novel Traffic Lights Schedule-based localization algorithm (TLS), which is built on the fact that vehicles move through the intersection with a known traffic light schedule. We can first obtain the law by binary vehicle detection time stamps and describe the law as a matrix, called a detection matrix. At the same time, we can also use the known traffic light information to construct the matrices, which can be formed as a collection called a known matrix collection. The detection matrix is then matched in the known matrix collection for identifying where sensors are located on urban roads. We evaluate our algorithm by extensive simulation. The results show that the localization accuracy of intersection sensors can reach more than 90%. In addition, we compare it with a state-of-the-art algorithm and prove that it has a wider operational region. PMID:27735871

Distributed Fiber Optic Sensor for Early Detection of Rocky Slopes Movements

NASA Astrophysics Data System (ADS)

Minardo, Aldo; Picarelli, Luciano; Coscetta, Agnese; Zeni, Giovanni; Esposito, Giuseppe; Sacchi, Marco; Matano, Fabio; Caccavale, Mauro; Luigi, Zeni

2014-05-01

Distributed optical fiber sensors have in recent years gained considerable attention in structural and environmental monitoring due to specific advantages that, apart from the classical advantages common to all optical fiber sensors such as immunity to electromagnetic interferences, high sensitivity, small size and possibility to be embedded into the structures, multiplexing and remote interrogation capabilities [1], offer the unique feature of allowing the exploitation of a telecommunication grade optical fiber cable as the sensing element to measure deformation and temperature profiles over very long distances. In particular, distributed optical fiber sensors based on stimulated Brillouin scattering (SBS) through the so-called Brillouin Optical Time Domain Analysis (BOTDA), allow to measure strain and temperature profiles up to tens of kilometers with a strain accuracy of ±10µɛ and a temperature accuracy of ±1°C [2]. They have already been successfully employed in the monitoring of large civil and geotechnical structures such as bridges, tunnels, dams, pipelines allowing to identify and localize any kind of failures that can occur during their construction and operation [3,4]. In this paper we present the application of BOTDA to the monitoring of movements in a rocky slope, showing how the sensing optical fiber cable is able to detect the formation and follow the growth of fractures, and to identify their location along the slope, as well. The experimental results have been achieved on a test field located in the area of Naples (Italy), where a single mode optical fiber sensing cable has been deployed along a yellow tuffs slope, by spot gluing the cable with epoxy adhesive. In order to assess the validity of the proposed approach, a few existing cracks have been artificially enlarged and the magnitude and location of the induced strain peaks have been clearly identified by the sensing device. It should be emphasized that, due to the distributed nature of the sensor, no preliminary information about the possible displacement locations of rocks are required in advance. The sensing cable can be simply deployed in a zig-zag pattern path along the slope, for hundreds of meters, and the system will remotely detect and locate any displacements wherever they occur along the fiber cable path, so representing a powerful tool for early warning against possible rock slides. [1] J. M. López-Higuera, L. R. Cobo, A. Q. Incera, A. Cobo, " Fiber Optic Sensors in Structural Health Monitoring", Journal of Lightwave Technology, Vol. 29, pp.586-608, 2011. [2] A. Minardo, R. Bernini, L. Zeni, "Numerical analysis of single pulse and differential pulse-width pair BOTDA systems in the high spatial resolution regime", Optics Express, vol. 19, pp. 19233-19244, 2011. [3] A. Minardo, R. Bernini, L. Amato, L. Zeni, "Bridge monitoring using Brillouin fiber-optic sensors", IEEE Sensor Journal, Vol. 12 (1), pp. 145-150, 2012. [4] R. Bernini, A. Minardo, S. Ciaramella, V. Minutolo, L. Zeni, "Distributed strain measurement along a concrete beam via stimulated Brillouin scattering in optical fibers", International Journal of Geophysics, Vol. 2011, pp. 1-5, doi:10.1155/2011/710941, 2011.

Role of Vascular Networks in Extending Glucose Sensor Function: Impact of Angiogenesis and Lymphangiogenesis on Continuous Glucose Monitoring in vivo

PubMed Central

Klueh, Ulrike; Antar, Omar; Qiao, Yi; Kreutzer, Donald L.

2014-01-01

The concept of increased blood vessel (BV) density proximal to glucose sensors implanted in the interstitial tissue increases the accuracy and lifespan of sensors is accepted, despite limited existing experimental data. Interestingly, there is no previous data or even conjecture in the literature on the role of lymphatic vessels (LV) alone, or in combination with BV, in enhancing continuous glucose monitoring (CGM) in vivo. To investigate the impact of inducing vascular networks (BV and LV) at sites of glucose sensor implantation, we utilized adenovirus based local gene therapy of vascular endothelial cell growth factor-A (VEGF-A) to induce vessels at sensor implantation sites. The results of these studies demonstrated that 1) VEGF-A based local gene therapy increases vascular networks (blood vessels and lymphatic vessels) at sites of glucose sensor implantation; and 2) this local increase of vascular networks enhances glucose sensor function in vivo from 7 days to greater than 28 days post sensor implantation. This data provides “proof of concept” for the effective usage of local angiogenic factor (AF) gene therapy in mammalian models in an effort to extend CGM in vivo. It also supports the practice of a variety of viral and non-viral vectors as well as gene products (e.g. anti-inflammatory and anti-fibrosis genes) to engineer “implant friendly tissues” for the usage with implantable glucose sensors as well as other implantable devices. PMID:24243850

Low cost self-made pressure distribution sensors for ergonomic chair: Are they suitable for posture monitoring?

PubMed

Martinaitis, Arnas; Daunoraviciene, Kristina

2018-05-18

Long sitting causes many health problems for people. Healthy sitting monitoring systems, like real-time pressure distribution measuring, is in high demand and many methods of posture recognition were developed. Such systems are usually expensive and hardly available for the regular user. The aim of study is to develop low cost but sensitive enough pressure sensors and posture monitoring system. New self-made pressure sensors have been developed and tested, and prototype of pressure distribution measuring system was designed. Sensors measured at average noise amplitude of a = 56 mV (1.12%), average variation in sequential measurements of the same sensor s = 17 mV (0.34%). Signal variability between sensors averaged at 100 mV (2.0%). Weight to signal dependency graph was measured and hysteresis calculated. Results suggested the use of total sixteen sensors for posture monitoring system with accuracy of < 1.5% after relaxation and repeatability of around 2%. Results demonstrate that hand-made sensor sensitivity and repeatability are acceptable for posture monitoring, and it is possible to build low cost pressure distribution measurement system with graphical visualization without expensive equipment or complicated software.

Distributed sensor for water and pH measurements using fiber optics and swellable polymeric systems

NASA Astrophysics Data System (ADS)

Michie, W. C.; Culshaw, B.; McKenzie, I.; Konstantakis, M.; Graham, N. B.; Moran, C.; Santos, F.; Bergqvist, E.; Carlstrom, B.

1995-01-01

We report on the design, construction and test of a generic form of sensor for making distributed measurements of a range of chemical parameters. The technique combines optical time-domain reflectometry with chemically sensitive water-swellable polymers (hydrogels). Initial experiments have concentrated on demonstrating a distributed water detector; however, gels have been developed that enable this sensor to be

Community Seismic Network (CSN)

NASA Astrophysics Data System (ADS)

Clayton, R. W.; Heaton, T. H.; Kohler, M. D.; Cheng, M.; Guy, R.; Chandy, M.; Krause, A.; Bunn, J.; Olson, M.; Faulkner, M.; Liu, A.; Strand, L.

2012-12-01

We report on developments in sensor connectivity, architecture, and data fusion algorithms executed in Cloud computing systems in the Community Seismic Network (CSN), a network of low-cost sensors housed in homes and offices by volunteers in the Pasadena, CA area. The network has over 200 sensors continuously reporting anomalies in local acceleration through the Internet to a Cloud computing service (the Google App Engine) that continually fuses sensor data to rapidly detect shaking from earthquakes. The Cloud computing system consists of data centers geographically distributed across the continent and is likely to be resilient even during earthquakes and other local disasters. The region of Southern California is partitioned in a multi-grid style into sets of telescoping cells called geocells. Data streams from sensors within a geocell are fused to detect anomalous shaking across the geocell. Temporal spatial patterns across geocells are used to detect anomalies across regions. The challenge is to detect earthquakes rapidly with an extremely low false positive rate. We report on two data fusion algorithms, one that tessellates the surface so as to fuse data from a large region around Pasadena and the other, which uses a standard tessellation of equal-sized cells. Since September 2011, the network has successfully detected earthquakes of magnitude 2.5 or higher within 40 Km of Pasadena. In addition to the standard USB device, which connects to the host's computer, we have developed a stand-alone sensor that directly connects to the internet via Ethernet or wifi. This bypasses security concerns that some companies have with the USB-connected devices, and allows for 24/7 monitoring at sites that would otherwise shut down their computers after working hours. In buildings we use the sensors to model the behavior of the structures during weak events in order to understand how they will perform during strong events. Visualization models of instrumented buildings ranging between five and 22 stories tall have been constructed using Google SketchUp. Ambient vibration records are used to identify the first set of horizontal vibrational modal frequencies of the buildings. These frequencies are used to compute the response on every floor of the building, given either observed data or scenario ground motion input at the buildings' base.

Moving multiple sinks through wireless sensor networks for lifetime maximization.

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

Petrioli, Chiara; Carosi, Alessio; Basagni, Stefano

2008-01-01

Unattended sensor networks typically watch for some phenomena such as volcanic events, forest fires, pollution, or movements in animal populations. Sensors report to a collection point periodically or when they observe reportable events. When sensors are too far from the collection point to communicate directly, other sensors relay messages for them. If the collection point location is static, sensor nodes that are closer to the collection point relay far more messages than those on the periphery. Assuming all sensor nodes have roughly the same capabilities, those with high relay burden experience battery failure much faster than the rest of themore » network. However, since their death disconnects the live nodes from the collection point, the whole network is then dead. We consider the problem of moving a set of collectors (sinks) through a wireless sensor network to balance the energy used for relaying messages, maximizing the lifetime of the network. We show how to compute an upper bound on the lifetime for any instance using linear and integer programming. We present a centralized heuristic that produces sink movement schedules that produce network lifetimes within 1.4% of the upper bound for realistic settings. We also present a distributed heuristic that produces lifetimes at most 25:3% below the upper bound. More specifically, we formulate a linear program (LP) that is a relaxation of the scheduling problem. The variables are naturally continuous, but the LP relaxes some constraints. The LP has an exponential number of constraints, but we can satisfy them all by enforcing only a polynomial number using a separation algorithm. This separation algorithm is a p-median facility location problem, which we can solve efficiently in practice for huge instances using integer programming technology. This LP selects a set of good sensor configurations. Given the solution to the LP, we can find a feasible schedule by selecting a subset of these configurations, ordering them via a traveling salesman heuristic, and computing feasible transitions using matching algorithms. This algorithm assumes sinks can get a schedule from a central server or a leader sink. If the network owner prefers the sinks make independent decisions, they can use our distributed heuristic. In this heuristic, sinks maintain estimates of the energy distribution in the network and move greedily (with some coordination) based on local search. This application uses the new SUCASA (Solver Utility for Customization with Automatic Symbol Access) facility within the PICO (Parallel Integer and Combinatorial Optimizer) integer programming solver system. SUCASA allows rapid development of customized math programming (search-based) solvers using a problem's natural multidimensional representation. In this case, SUCASA also significantly improves runtime compared to implementations in the ampl math programming language or in perl.« less

Investigation of dust particles with future Russian lunar missions: achievements of further development of PmL instrument.

NASA Astrophysics Data System (ADS)

Kuznetsov, Ilya; Zakharov, Alexander; Afonin, Valeri; Seran, Elena; Godefroy, Michel; Shashkova, Inna; Lyash, Andrey; Dolnikov, Gennady; Popel, Sergey; Lisin, Evgeny

2016-07-01

One of the complicating factors of the future robotic and human lunar landing missions is the influence of the dust. Meteorites bombardment has accompanied by shock-explosive phenomena, disintegration and mix of the lunar soil in depth and on area simultaneously. As a consequence, the lunar soil has undergone melting, physical and chemical transformations. Recently we have the some reemergence for interest of Moon investigation. The prospects in current century declare USA, China, India, and European Union. In Russia also prepare two missions: Luna-Glob and Luna-Resource. Not last part of investigation of Moon surface is reviewing the dust condition near the ground of landers. Studying the properties of lunar dust is important both for scientific purposes to investigation the lunar exosphere component and for the technical safety of lunar robotic and manned missions. The absence of an atmosphere on the Moon's surface is leading to greater compaction and sintering. Properties of regolith and dust particles (density, temperature, composition, etc.) as well as near-surface lunar exosphere depend on solar activity, lunar local time and position of the Moon relative to the Earth's magneto tail. Upper layers of regolith are an insulator, which is charging as a result of solar UV radiation and the constant bombardment of charged particles, creates a charge distribution on the surface of the moon: positive on the illuminated side and negative on the night side. Charge distribution depends on the local lunar time, latitude and the electrical properties of the regolith (the presence of water in the regolith can influence the local distribution of charge). On the day side of Moon near surface layer there exists possibility formation dusty plasma system. Altitude of levitation is depending from size of dust particle and Moon latitude. The distribution of dust particles by size and altitude has estimated with taking into account photoelectrons, electrons and ions of solar wind, solar emission. Dust analyzer instrument PmL for future Russian lander missions intends for investigation the dynamics of dusty plasma near lunar surface. PmL consists of three parts in the case of Luna-Glob: Impact Sensor and two Electric Field Sensors (EFC). There are 9 parts of PmL instrument for Luna-Resource mission: two Impact Sensors, 5 EFC (three on the Boom and two on the lander) and 2 Solar Wind and Dust Analyzers. These days the engineering model of PmL for LG-mission is finished. We obtained first practical results from the simulating chambers with dust particles injectors and plasma inside. All the important achievements are presented in this report as well as the roadmap for further development of PmL instruments in both of Russian lunar missions.

Vehicle autonomous localization in local area of coal mine tunnel based on vision sensors and ultrasonic sensors

PubMed Central

Yang, Wei; You, Kaiming; Li, Wei; Kim, Young-il

2017-01-01

This paper presents a vehicle autonomous localization method in local area of coal mine tunnel based on vision sensors and ultrasonic sensors. Barcode tags are deployed in pairs on both sides of the tunnel walls at certain intervals as artificial landmarks. The barcode coding is designed based on UPC-A code. The global coordinates of the upper left inner corner point of the feature frame of each barcode tag deployed in the tunnel are uniquely represented by the barcode. Two on-board vision sensors are used to recognize each pair of barcode tags on both sides of the tunnel walls. The distance between the upper left inner corner point of the feature frame of each barcode tag and the vehicle center point can be determined by using a visual distance projection model. The on-board ultrasonic sensors are used to measure the distance from the vehicle center point to the left side of the tunnel walls. Once the spatial geometric relationship between the barcode tags and the vehicle center point is established, the 3D coordinates of the vehicle center point in the tunnel’s global coordinate system can be calculated. Experiments on a straight corridor and an underground tunnel have shown that the proposed vehicle autonomous localization method is not only able to quickly recognize the barcode tags affixed to the tunnel walls, but also has relatively small average localization errors in the vehicle center point’s plane and vertical coordinates to meet autonomous unmanned vehicle positioning requirements in local area of coal mine tunnel. PMID:28141829

Vehicle autonomous localization in local area of coal mine tunnel based on vision sensors and ultrasonic sensors.

PubMed

Xu, Zirui; Yang, Wei; You, Kaiming; Li, Wei; Kim, Young-Il

2017-01-01

This paper presents a vehicle autonomous localization method in local area of coal mine tunnel based on vision sensors and ultrasonic sensors. Barcode tags are deployed in pairs on both sides of the tunnel walls at certain intervals as artificial landmarks. The barcode coding is designed based on UPC-A code. The global coordinates of the upper left inner corner point of the feature frame of each barcode tag deployed in the tunnel are uniquely represented by the barcode. Two on-board vision sensors are used to recognize each pair of barcode tags on both sides of the tunnel walls. The distance between the upper left inner corner point of the feature frame of each barcode tag and the vehicle center point can be determined by using a visual distance projection model. The on-board ultrasonic sensors are used to measure the distance from the vehicle center point to the left side of the tunnel walls. Once the spatial geometric relationship between the barcode tags and the vehicle center point is established, the 3D coordinates of the vehicle center point in the tunnel's global coordinate system can be calculated. Experiments on a straight corridor and an underground tunnel have shown that the proposed vehicle autonomous localization method is not only able to quickly recognize the barcode tags affixed to the tunnel walls, but also has relatively small average localization errors in the vehicle center point's plane and vertical coordinates to meet autonomous unmanned vehicle positioning requirements in local area of coal mine tunnel.

Collaborative emitter tracking using Rao-Blackwellized random exchange diffusion particle filtering

NASA Astrophysics Data System (ADS)

Bruno, Marcelo G. S.; Dias, Stiven S.

2014-12-01

We introduce in this paper the fully distributed, random exchange diffusion particle filter (ReDif-PF) to track a moving emitter using multiple received signal strength (RSS) sensors. We consider scenarios with both known and unknown sensor model parameters. In the unknown parameter case, a Rao-Blackwellized (RB) version of the random exchange diffusion particle filter, referred to as the RB ReDif-PF, is introduced. In a simulated scenario with a partially connected network, the proposed ReDif-PF outperformed a PF tracker that assimilates local neighboring measurements only and also outperformed a linearized random exchange distributed extended Kalman filter (ReDif-EKF). Furthermore, the novel ReDif-PF matched the tracking error performance of alternative suboptimal distributed PFs based respectively on iterative Markov chain move steps and selective average gossiping with an inter-node communication cost that is roughly two orders of magnitude lower than the corresponding cost for the Markov chain and selective gossip filters. Compared to a broadcast-based filter which exactly mimics the optimal centralized tracker or its equivalent (exact) consensus-based implementations, ReDif-PF showed a degradation in steady-state error performance. However, compared to the optimal consensus-based trackers, ReDif-PF is better suited for real-time applications since it does not require iterative inter-node communication between measurement arrivals.

Monitoring of Concrete Structures Using Ofdr Technique

NASA Astrophysics Data System (ADS)

Henault, J. M.; Salin, J.; Moreau, G.; Delepine-Lesoille, S.; Bertand, J.; Taillade, F.; Quiertant, M.; Benzarti, K.

2011-06-01

Structural health monitoring is a key factor in life cycle management of infrastructures. Truly distributed fiber optic sensors are able to provide relevant information on large structures, such as bridges, dikes, nuclear power plants or nuclear waste disposal facilities. The sensing chain includes an optoelectronic unit and a sensing cable made of one or more optical fibers. A new instrument based on Optical Frequency Domain Reflectometry (OFDR), enables to perform temperature and strain measurements with a centimeter scale spatial resolution over hundred of meters and with a level of precision equal to 1 μstrain and 0.1 °C. Several sensing cables are designed with different materials targeting to last for decades in a concrete aggressive environment and to ensure an optimal transfer of temperature and strain from the concrete matrix to the optical fiber. Tests were carried out by embedding various sensing cables into plain concrete specimens and representative-scale reinforced concrete structural elements. Measurements were performed with an OFDR instrument; meanwhile, mechanical solicitations were imposed to the concrete element. Preliminary experiments are very promising since measurements performed with distributed sensing system are comparable to values obtained with conventional sensors used in civil engineering and with the Strength of Materials Modelling. Moreover, the distributed sensing system makes it possible to detect and localize cracks appearing in concrete during the mechanical loading.

Modeling of the Through-the-Thickness Electric Potentials of a Piezoelectric Bimorph Using the Spectral Element Method

PubMed Central

Dong, Xingjian; Peng, Zhike; Hua, Hongxing; Meng, Guang

2014-01-01

An efficient spectral element (SE) with electric potential degrees of freedom (DOF) is proposed to investigate the static electromechanical responses of a piezoelectric bimorph for its actuator and sensor functions. A sublayer model based on the piecewise linear approximation for the electric potential is used to describe the nonlinear distribution of electric potential through the thickness of the piezoelectric layers. An equivalent single layer (ESL) model based on first-order shear deformation theory (FSDT) is used to describe the displacement field. The Legendre orthogonal polynomials of order 5 are used in the element interpolation functions. The validity and the capability of the present SE model for investigation of global and local responses of the piezoelectric bimorph are confirmed by comparing the present solutions with those obtained from coupled 3-D finite element (FE) analysis. It is shown that, without introducing any higher-order electric potential assumptions, the current method can accurately describe the distribution of the electric potential across the thickness even for a rather thick bimorph. It is revealed that the effect of electric potential is significant when the bimorph is used as sensor while the effect is insignificant when the bimorph is used as actuator, and therefore, the present study may provide a better understanding of the nonlinear induced electric potential for bimorph sensor and actuator. PMID:24561399

A distributed automatic target recognition system using multiple low resolution sensors

NASA Astrophysics Data System (ADS)

Yue, Zhanfeng; Lakshmi Narasimha, Pramod; Topiwala, Pankaj

2008-04-01

In this paper, we propose a multi-agent system which uses swarming techniques to perform high accuracy Automatic Target Recognition (ATR) in a distributed manner. The proposed system can co-operatively share the information from low-resolution images of different looks and use this information to perform high accuracy ATR. An advanced, multiple-agent Unmanned Aerial Vehicle (UAV) systems-based approach is proposed which integrates the processing capabilities, combines detection reporting with live video exchange, and swarm behavior modalities that dramatically surpass individual sensor system performance levels. We employ real-time block-based motion analysis and compensation scheme for efficient estimation and correction of camera jitter, global motion of the camera/scene and the effects of atmospheric turbulence. Our optimized Partition Weighted Sum (PWS) approach requires only bitshifts and additions, yet achieves a stunning 16X pixel resolution enhancement, which is moreover parallizable. We develop advanced, adaptive particle-filtering based algorithms to robustly track multiple mobile targets by adaptively changing the appearance model of the selected targets. The collaborative ATR system utilizes the homographies between the sensors induced by the ground plane to overlap the local observation with the received images from other UAVs. The motion of the UAVs distorts estimated homography frame to frame. A robust dynamic homography estimation algorithm is proposed to address this, by using the homography decomposition and the ground plane surface estimation.

A Dual-Mode Large-Arrayed CMOS ISFET Sensor for Accurate and High-Throughput pH Sensing in Biomedical Diagnosis.

PubMed

Huang, Xiwei; Yu, Hao; Liu, Xu; Jiang, Yu; Yan, Mei; Wu, Dongping

2015-09-01

The existing ISFET-based DNA sequencing detects hydrogen ions released during the polymerization of DNA strands on microbeads, which are scattered into microwell array above the ISFET sensor with unknown distribution. However, false pH detection happens at empty microwells due to crosstalk from neighboring microbeads. In this paper, a dual-mode CMOS ISFET sensor is proposed to have accurate pH detection toward DNA sequencing. Dual-mode sensing, optical and chemical modes, is realized by integrating a CMOS image sensor (CIS) with ISFET pH sensor, and is fabricated in a standard 0.18-μm CIS process. With accurate determination of microbead physical locations with CIS pixel by contact imaging, the dual-mode sensor can correlate local pH for one DNA slice at one location-determined microbead, which can result in improved pH detection accuracy. Moreover, toward a high-throughput DNA sequencing, a correlated-double-sampling readout that supports large array for both modes is deployed to reduce pixel-to-pixel nonuniformity such as threshold voltage mismatch. The proposed CMOS dual-mode sensor is experimentally examined to show a well correlated pH map and optical image for microbeads with a pH sensitivity of 26.2 mV/pH, a fixed pattern noise (FPN) reduction from 4% to 0.3%, and a readout speed of 1200 frames/s. A dual-mode CMOS ISFET sensor with suppressed FPN for accurate large-arrayed pH sensing is proposed and demonstrated with state-of-the-art measured results toward accurate and high-throughput DNA sequencing. The developed dual-mode CMOS ISFET sensor has great potential for future personal genome diagnostics with high accuracy and low cost.

Passive-quadrature demodulated localized-Michelson fiber-optic strain sensor embedded in composite materials

NASA Astrophysics Data System (ADS)

Valis, Tomas; Tapanes, Edward; Liu, Kexing; Measures, Raymond M.

1991-04-01

A strain sensor embedded in composite materials that is intrinsic, all fiber, local, and phase demodulated is described. It is the combination of these necessary elements that represents an advance in the state of the art. Sensor localization is achieved by using a pair of mirror-ended optical fibers of different lengths that are mechanically coupled up until the desired gauge length for common-mode suppression has been reached. This fiber-optic sensor has been embedded in both thermoset (Kevlar/epoxy and graphite/epoxy) and thermoplastic (graphite/PEEK) composite materials in order to make local strain measurements at the lamina level. The all-fiber system uses a 3 x 3 coupler for phase demodulation. Parameters such as strain sensitivity, transverse strain sensitivity, failure strain, and frequency response are discussed, along with applications.

Evaluation of Food Freshness and Locality by Odor Sensor

NASA Astrophysics Data System (ADS)

Koike, Takayuki; Shimada, Koji; Kamimura, Hironobu; Kaneki, Noriaki

The aim of this study was to investigate whether food freshness and locality can be classified using a food evaluation system consisting four SnO2-semiconductor gas sensors and a solid phase column, into which collecting aroma materials. The temperature of sensors was periodically changed to be in unsteady state and thus, the sensor information was increased. The parameters (in quefrency band) were extracted from sensor information using cepstrum analysis that enable to separate superimposed information on sinusoidal wave. The quefrency was used as parameters for principal component and discriminant analyses (PCA and DCA) to detect food freshness and food localities. We used three kinds of strawberries, people can perceive its odors, passed from one to three days after harvest, and kelps and Ceylon tea, people are hardly to perceive its odor, corrected from five areas as sample. Then, the deterioration of strawberries and localities of kelps and Ceylon teas were visually evaluated using the numerical analyses. While the deteriorations were classified using PCA or DCA, the localities were classified only by DCA. The findings indicate that, although odorant intensity influenced the method detecting food quality, the quefrency obtained from odorant information using cepstrum analysis were available to detect the difference in the freshness and the localities of foods.

Peer-to-peer model for the area coverage and cooperative control of mobile sensor networks

NASA Astrophysics Data System (ADS)

Tan, Jindong; Xi, Ning

2004-09-01

This paper presents a novel model and distributed algorithms for the cooperation and redeployment of mobile sensor networks. A mobile sensor network composes of a collection of wireless connected mobile robots equipped with a variety of sensors. In such a sensor network, each mobile node has sensing, computation, communication, and locomotion capabilities. The locomotion ability enhances the autonomous deployment of the system. The system can be rapidly deployed to hostile environment, inaccessible terrains or disaster relief operations. The mobile sensor network is essentially a cooperative multiple robot system. This paper first presents a peer-to-peer model to define the relationship between neighboring communicating robots. Delaunay Triangulation and Voronoi diagrams are used to define the geometrical relationship between sensor nodes. This distributed model allows formal analysis for the fusion of spatio-temporal sensory information of the network. Based on the distributed model, this paper discusses a fault tolerant algorithm for autonomous self-deployment of the mobile robots. The algorithm considers the environment constraints, the presence of obstacles and the nonholonomic constraints of the robots. The distributed algorithm enables the system to reconfigure itself such that the area covered by the system can be enlarged. Simulation results have shown the effectiveness of the distributed model and deployment algorithms.

Implementation of Fiber Optic Sensing System on Sandwich Composite Cylinder Buckling Test

NASA Technical Reports Server (NTRS)

Pena, Francisco; Richards, W. Lance; Parker, Allen R.; Piazza, Anthony; Schultz, Marc R.; Rudd, Michelle T.; Gardner, Nathaniel W.; Hilburger, Mark W.

2018-01-01

The National Aeronautics and Space Administration (NASA) Engineering and Safety Center Shell Buckling Knockdown Factor Project is a multicenter project tasked with developing new analysis-based shell buckling design guidelines and design factors (i.e., knockdown factors) through high-fidelity buckling simulations and advanced test technologies. To validate these new buckling knockdown factors for future launch vehicles, the Shell Buckling Knockdown Factor Project is carrying out structural testing on a series of large-scale metallic and composite cylindrical shells at the NASA Marshall Space Flight Center (Marshall Space Flight Center, Alabama). A fiber optic sensor system was used to measure strain on a large-scale sandwich composite cylinder that was tested under multiple axial compressive loads up to more than 850,000 lb, and equivalent bending loads over 22 million in-lb. During the structural testing of the composite cylinder, strain data were collected from optical cables containing distributed fiber Bragg gratings using a custom fiber optic sensor system interrogator developed at the NASA Armstrong Flight Research Center. A total of 16 fiber-optic strands, each containing nearly 1,000 fiber Bragg gratings, measuring strain, were installed on the inner and outer cylinder surfaces to monitor the test article global structural response through high-density real-time and post test strain measurements. The distributed sensing system provided evidence of local epoxy failure at the attachment-ring-to-barrel interface that would not have been detected with conventional instrumentation. Results from the fiber optic sensor system were used to further refine and validate structural models for buckling of the large-scale composite structures. This paper discusses the techniques employed for real-time structural monitoring of the composite cylinder for structural load introduction and distributed bending-strain measurements over a large section of the cylinder by utilizing unique sensing capabilities of fiber optic sensors.

Design and development of a probe-based multiplexed multi-species absorption spectroscopy sensor for characterizing transient gas-parameter distributions in the intake systems of I.C. engines

DOE PAGES

Jatana, Gurneesh; Geckler, Sam; Koeberlein, David; ...

2016-09-01

We designed and developed a 4-probe multiplexed multi-species absorption spectroscopy sensor system for gas property measurements on the intake side of commercial multi-cylinder internal-combustion (I.C.) engines; the resulting cycle- and cylinder-resolved concentration, temperature and pressure measurements are applicable for assessing spatial and temporal variations in the recirculated exhaust gas (EGR) distribution at various locations along the intake gas path, which in turn is relevant to assessing cylinder charge uniformity, control strategies, and CFD models. Furthermore, the diagnostic is based on absorption spectroscopy and includes an H 2O absorption system (utilizing a 1.39 m distributed feedback (DFB) diode laser) for measuringmore » gas temperature, pressure, and H 2O concentration, and a CO 2 absorption system (utilizing a 2.7 m DFB laser) for measuring CO 2 concentration. The various lasers, optical components and detectors were housed in an instrument box, and the 1.39- m and 2.7- m lasers were guided to and from the engine-mounted probes via optical fibers and hollow waveguides, respectively. The 5kHz measurement bandwidth allows for near-crank angle resolved measurements, with a resolution of 1.2 crank angle degrees at 1000 RPM. Our use of compact stainless steel measurement probes enables simultaneous multi-point measurements at various locations on the engine with minimal changes to the base engine hardware; in addition to resolving large-scale spatial variations via simultaneous multi-probe measurements, local spatial gradients can be resolved by translating individual probes. Along with details of various sensor design features and performance, we also demonstrate validation of the spectral parameters of the associated CO 2 absorption transitions using both a multi-pass heated cell and the sensor probes.« less

Seismic damage identification for steel structures using distributed fiber optics.

PubMed

Hou, Shuang; Cai, C S; Ou, Jinping

2009-08-01

A distributed fiber optic monitoring methodology based on optic time domain reflectometry technology is developed for seismic damage identification of steel structures. Epoxy with a strength closely associated to a specified structure damage state is used for bonding zigzagged configured optic fibers on the surfaces of the structure. Sensing the local deformation of the structure, the epoxy modulates the signal change within the optic fiber in response to the damage state of the structure. A monotonic loading test is conducted on a steel specimen installed with the proposed sensing system using selected epoxy that will crack at the designated strain level, which indicates the damage of the steel structure. Then, using the selected epoxy, a varying degree of cyclic loading amplitudes, which is associated with different damage states, is applied on a second specimen. The test results show that the specimen's damage can be identified by the optic sensors, and its maximum local deformation can be recorded by the sensing system; moreover, the damage evolution can also be identified.

Distributed Fiber-Optic Sensors for Vibration Detection

PubMed Central

Liu, Xin; Jin, Baoquan; Bai, Qing; Wang, Yu; Wang, Dong; Wang, Yuncai

2016-01-01

Distributed fiber-optic vibration sensors receive extensive investigation and play a significant role in the sensor panorama. Optical parameters such as light intensity, phase, polarization state, or light frequency will change when external vibration is applied on the sensing fiber. In this paper, various technologies of distributed fiber-optic vibration sensing are reviewed, from interferometric sensing technology, such as Sagnac, Mach–Zehnder, and Michelson, to backscattering-based sensing technology, such as phase-sensitive optical time domain reflectometer, polarization-optical time domain reflectometer, optical frequency domain reflectometer, as well as some combinations of interferometric and backscattering-based techniques. Their operation principles are presented and recent research efforts are also included. Finally, the applications of distributed fiber-optic vibration sensors are summarized, which mainly include structural health monitoring and perimeter security, etc. Overall, distributed fiber-optic vibration sensors possess the advantages of large-scale monitoring, good concealment, excellent flexibility, and immunity to electromagnetic interference, and thus show considerable potential for a variety of practical applications. PMID:27472334

Distributed Fiber-Optic Sensors for Vibration Detection.

PubMed

Liu, Xin; Jin, Baoquan; Bai, Qing; Wang, Yu; Wang, Dong; Wang, Yuncai

2016-07-26

Distributed fiber-optic vibration sensors receive extensive investigation and play a significant role in the sensor panorama. Optical parameters such as light intensity, phase, polarization state, or light frequency will change when external vibration is applied on the sensing fiber. In this paper, various technologies of distributed fiber-optic vibration sensing are reviewed, from interferometric sensing technology, such as Sagnac, Mach-Zehnder, and Michelson, to backscattering-based sensing technology, such as phase-sensitive optical time domain reflectometer, polarization-optical time domain reflectometer, optical frequency domain reflectometer, as well as some combinations of interferometric and backscattering-based techniques. Their operation principles are presented and recent research efforts are also included. Finally, the applications of distributed fiber-optic vibration sensors are summarized, which mainly include structural health monitoring and perimeter security, etc. Overall, distributed fiber-optic vibration sensors possess the advantages of large-scale monitoring, good concealment, excellent flexibility, and immunity to electromagnetic interference, and thus show considerable potential for a variety of practical applications.

Research on sensor design for internet of things and laser manufacturing

NASA Astrophysics Data System (ADS)

Wang, Tao; Yao, Jianquan; Guo, Ling; Zhang, Yanchun

2010-12-01

In this paper, we will introduce the research on sensor design for IOT (Internet of Things) and laser manufacturing, and supporting the establishment of local area IOT. The main contents include studying on the structure designing of silicon micro tilt sensor, data acquisition and processing, addressing implanted and building Local Area IOT with wireless sensor network technology. At last, it is discussed the status and trends of the Internet of Things from the promoters, watchers, pessimists and doers.

Two-Dimensional Automatic Measurement for Nozzle Flow Distribution Using Improved Ultrasonic Sensor

PubMed Central

Zhai, Changyuan; Zhao, Chunjiang; Wang, Xiu; Wang, Ning; Zou, Wei; Li, Wei

2015-01-01

Spray deposition and distribution are affected by many factors, one of which is nozzle flow distribution. A two-dimensional automatic measurement system, which consisted of a conveying unit, a system control unit, an ultrasonic sensor, and a deposition collecting dish, was designed and developed. The system could precisely move an ultrasonic sensor above a pesticide deposition collecting dish to measure the nozzle flow distribution. A sensor sleeve with a PVC tube was designed for the ultrasonic sensor to limit its beam angle in order to measure the liquid level in the small troughs. System performance tests were conducted to verify the designed functions and measurement accuracy. A commercial spray nozzle was also used to measure its flow distribution. The test results showed that the relative error on volume measurement was less than 7.27% when the liquid volume was 2 mL in trough, while the error was less than 4.52% when the liquid volume was 4 mL or more. The developed system was also used to evaluate the flow distribution of a commercial nozzle. It was able to provide the shape and the spraying width of the flow distribution accurately. PMID:26501288

The Pilatus unmanned aircraft system for lower atmospheric research

DOE PAGES

de Boer, Gijs; Palo, Scott; Argrow, Brian; ...

2016-04-28

This study presents details of the University of Colorado (CU) “Pilatus” unmanned research aircraft, assembled to provide measurements of aerosols, radiation and thermodynamics in the lower troposphere. This aircraft has a wingspan of 3.2 m and a maximum take-off weight of 25 kg, and it is powered by an electric motor to reduce engine exhaust and concerns about carburetor icing. It carries instrumentation to make measurements of broadband up- and downwelling shortwave and longwave radiation, aerosol particle size distribution, atmospheric temperature, relative humidity and pressure and to collect video of flights for subsequent analysis of atmospheric conditions during flight. Inmore » order to make the shortwave radiation measurements, care was taken to carefully position a high-quality compact inertial measurement unit (IMU) and characterize the attitude of the aircraft and its orientation to the upward-looking radiation sensor. Using measurements from both of these sensors, a correction is applied to the raw radiometer measurements to correct for aircraft attitude and sensor tilt relative to the sun. The data acquisition system was designed from scratch based on a set of key driving requirements to accommodate the variety of sensors deployed. Initial test flights completed in Colorado provide promising results with measurements from the radiation sensors agreeing with those from a nearby surface site. Additionally, estimates of surface albedo from onboard sensors were consistent with local surface conditions, including melting snow and bright runway surface. Aerosol size distributions collected are internally consistent and have previously been shown to agree well with larger, surface-based instrumentation. Finally the atmospheric state measurements evolve as expected, with the near-surface atmosphere warming over time as the day goes on, and the atmospheric relative humidity decreasing with increased temperature. No directional bias on measured temperature, as might be expected due to uneven heating of the sensor housing over the course of a racetrack pattern, was detected. The results from these flights indicate that the CU Pilatus platform is capable of performing research-grade lower tropospheric measurement missions.« less

The Pilatus unmanned aircraft system for lower atmospheric research

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

de Boer, Gijs; Palo, Scott; Argrow, Brian

This study presents details of the University of Colorado (CU) “Pilatus” unmanned research aircraft, assembled to provide measurements of aerosols, radiation and thermodynamics in the lower troposphere. This aircraft has a wingspan of 3.2 m and a maximum take-off weight of 25 kg, and it is powered by an electric motor to reduce engine exhaust and concerns about carburetor icing. It carries instrumentation to make measurements of broadband up- and downwelling shortwave and longwave radiation, aerosol particle size distribution, atmospheric temperature, relative humidity and pressure and to collect video of flights for subsequent analysis of atmospheric conditions during flight. Inmore » order to make the shortwave radiation measurements, care was taken to carefully position a high-quality compact inertial measurement unit (IMU) and characterize the attitude of the aircraft and its orientation to the upward-looking radiation sensor. Using measurements from both of these sensors, a correction is applied to the raw radiometer measurements to correct for aircraft attitude and sensor tilt relative to the sun. The data acquisition system was designed from scratch based on a set of key driving requirements to accommodate the variety of sensors deployed. Initial test flights completed in Colorado provide promising results with measurements from the radiation sensors agreeing with those from a nearby surface site. Additionally, estimates of surface albedo from onboard sensors were consistent with local surface conditions, including melting snow and bright runway surface. Aerosol size distributions collected are internally consistent and have previously been shown to agree well with larger, surface-based instrumentation. Finally the atmospheric state measurements evolve as expected, with the near-surface atmosphere warming over time as the day goes on, and the atmospheric relative humidity decreasing with increased temperature. No directional bias on measured temperature, as might be expected due to uneven heating of the sensor housing over the course of a racetrack pattern, was detected. The results from these flights indicate that the CU Pilatus platform is capable of performing research-grade lower tropospheric measurement missions.« less

Engineering of Sensor Network Structure for Dependable Fusion

DTIC Science & Technology

2014-08-15

Lossy Wireless Sensor Networks , IEEE/ACM Transactions on Networking , (04 2013): 0. doi: 10.1109/TNET.2013.2256795 Soumik Sarkar, Kushal Mukherjee...Phoha, Bharat B. Madan, Asok Ray. Distributed Network Control for Mobile Multi-Modal Wireless Sensor Networks , Journal of Parallel and Distributed...Deadline Constraints, IEEE Transactions on Automatic Control special issue on Wireless Sensor and Actuator Networks , (01 2011): 1. doi: Eric Keller

Measurement of cosmic-ray muons with the Distributed Electronic Cosmic-ray Observatory, a network of smartphones

NASA Astrophysics Data System (ADS)

Vandenbroucke, J.; BenZvi, S.; Bravo, S.; Jensen, K.; Karn, P.; Meehan, M.; Peacock, J.; Plewa, M.; Ruggles, T.; Santander, M.; Schultz, D.; Simons, A. L.; Tosi, D.

2016-04-01

Solid-state camera image sensors can be used to detect ionizing radiation in addition to optical photons. We describe the Distributed Electronic Cosmic-ray Observatory (DECO), an app and associated public database that enables a network of consumer devices to detect cosmic rays and other ionizing radiation. In addition to terrestrial background radiation, cosmic-ray muon candidate events are detected as long, straight tracks passing through multiple pixels. The distribution of track lengths can be related to the thickness of the active (depleted) region of the camera image sensor through the known angular distribution of muons at sea level. We use a sample of candidate muon events detected by DECO to measure the thickness of the depletion region of the camera image sensor in a particular consumer smartphone model, the HTC Wildfire S. The track length distribution is fit better by a cosmic-ray muon angular distribution than an isotropic distribution, demonstrating that DECO can detect and identify cosmic-ray muons despite a background of other particle detections. Using the cosmic-ray distribution, we measure the depletion thickness to be 26.3 ± 1.4 μm. With additional data, the same method can be applied to additional models of image sensor. Once measured, the thickness can be used to convert track length to incident polar angle on a per-event basis. Combined with a determination of the incident azimuthal angle directly from the track orientation in the sensor plane, this enables direction reconstruction of individual cosmic-ray events using a single consumer device. The results simultaneously validate the use of cell phone camera image sensors as cosmic-ray muon detectors and provide a measurement of a parameter of camera image sensor performance which is not otherwise publicly available.

Probabilistic #D data fusion for multiresolution surface generation

NASA Technical Reports Server (NTRS)

Manduchi, R.; Johnson, A. E.

2002-01-01

In this paper we present an algorithm for adaptive resolution integration of 3D data collected from multiple distributed sensors. The input to the algorithm is a set of 3D surface points and associated sensor models. Using a probabilistic rule, a surface probability function is generated that represents the probability that a particular volume of space contains the surface. The surface probability function is represented using an octree data structure; regions of space with samples of large conariance are stored at a coarser level than regions of space containing samples with smaller covariance. The algorithm outputs an adaptive resolution surface generated by connecting points that lie on the ridge of surface probability with triangles scaled to match the local discretization of space given by the algorithm, we present results from 3D data generated by scanning lidar and structure from motion.

Determination of hot carrier energy distributions from inversion of ultrafast pump-probe reflectivity measurements.

PubMed

Heilpern, Tal; Manjare, Manoj; Govorov, Alexander O; Wiederrecht, Gary P; Gray, Stephen K; Harutyunyan, Hayk

2018-05-10

Developing a fundamental understanding of ultrafast non-thermal processes in metallic nanosystems will lead to applications in photodetection, photochemistry and photonic circuitry. Typically, non-thermal and thermal carrier populations in plasmonic systems are inferred either by making assumptions about the functional form of the initial energy distribution or using indirect sensors like localized plasmon frequency shifts. Here we directly determine non-thermal and thermal distributions and dynamics in thin films by applying a double inversion procedure to optical pump-probe data that relates the reflectivity changes around Fermi energy to the changes in the dielectric function and in the single-electron energy band occupancies. When applied to normal incidence measurements our method uncovers the ultrafast excitation of a non-Fermi-Dirac distribution and its subsequent thermalization dynamics. Furthermore, when applied to the Kretschmann configuration, we show that the excitation of propagating plasmons leads to a broader energy distribution of electrons due to the enhanced Landau damping.

Development of the cloud sharing system for residential earthquake responses using smartphones

NASA Astrophysics Data System (ADS)

Shohei, N.; Fujiwara, H.; Azuma, H.; Hao, K. X.

2015-12-01

Earthquake responses at residential depends on its building structure, site amplification, epicenter distance, and etc. Until recently, it was impossible to obtain the individual residential response by conventional seismometer in terms of costs. However, current technology makes it possible with the Micro Electro Mechanical Systems (MEMS) sensors inside mobile terminals like smartphones. We developed the cloud sharing system for residential earthquake response in local community utilizing mobile terminals, such as an iPhone, iPad, iPod touch as a collaboration between NIED and Hakusan Corp. The triggered earthquake acceleration waveforms are recorded at sampling frequencies of 100Hz and stored on their memories once an threshold value was exceeded or ordered information received from the Earthquake Early Warning system. The recorded data is automatically transmitted and archived on the cloud server once the wireless communication is available. Users can easily get the uploaded data by use of a web browser through Internet. The cloud sharing system is designed for residential and only shared in local community internal. Residents can freely add sensors and register information about installation points in each region. And if an earthquake occurs, they can easily view the local distribution of seismic intensities and even analyze waves.To verify this cloud-based seismic wave sharing system, we have performed on site experiments under the cooperation of several local communities, The system and experimental results will be introduced and demonstrated in the presentation.

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).

Comparing bulk electrical conductivities spatial series obtained by Time Domain Reflectometry and Electromagnetic Induction sensors

NASA Astrophysics Data System (ADS)

Saeed, Ali; Ajeel, Ali; dragonetti, giovanna; Comegna, Alessandro; Lamaddalena, Nicola; Coppola, Antonio

2016-04-01

The ability to determine and monitor the effects of salts on soils and plants, are of great importance to agriculture. To control its harmful effects, soil salinity needs to be monitored in space and time. This requires knowledge of its magnitude, temporal dynamics, and spatial variability. Conventional ground survey procedures by direct soil sampling are time consuming, costly and destructive. Alternatively, soil salinity can be evaluated by measuring the bulk electrical conductivity (σb) directly in the field. Time domain reflectometry (TDR) sensors allow simultaneous measurements of water content, θ, and σb. They may be calibrated for estimating the electrical conductivity of the soil solution (σw). However, they have a relatively small observation window and thus they are thought to only provide local-scale measurements. The spatial range of the sensors is limited to tens of centimeters and extension of the information to a large area can be problematic. Also, information on the vertical distribution of the σb soil profile may only be obtained by installing sensors at different depths. In this sense, the TDR may be considered as an invasive technique. Compared to the TDR, other geophysical methods based for example on Electromagnetic Induction (EMI) techniques are non-invasive methods and represent a viable alternative to traditional techniques for soil characterization. The problem is that all these techniques give depth-weighted apparent electrical conductivity (σa) measurements, depending on the specific depth distribution of the σb, as well as on the depth response function of the sensor used. In order to deduce the actual distribution of the bulk electrical conductivity, σb, in the soil profile, one needs to invert the signal coming from EMI. Because of their relatively lower observation window, TDR sensors provide quasi-point values and do not adequately integrate the spatial variability of the chemical concentration distribution in the soil solution (and of the water content) induced by natural soil heterogeneity. Thus, the variability of TDR readings is expected to come from a combination of smaller and larger-scale variations. By contrast, an EMI sensor reading partly smoothes the small-scale variability seen by a TDR probe. As a consequence, the variability revealed by profile-integrated EMI and local (within a given depth interval) TDR readings may have completely different characteristics. In this study, a comparison between the variability patterns of σb revealed by TDR and EMI sensors was carried out. The database came from a field experiment conducted in the Mediterranean Agronomic Institute (MAI) of Valenzano (Bari). The soil was pedologically classified as Colluvic Regosol, consisting of a silty loam with an average depth of 60 cm on a shallow fractured calcareous rock. The experimental field (30m x 15.6 m; for a total area of 468 m2) consisted of three transects of 30 m length and 4.2 width, cultivated with green bean and irrigated with three different salinity levels (1 dS/m, 3dS/m, 6dS/m). Each transect consisted of seven crop rows irrigated by a drip irrigation system (dripper discharge q=2 l/h.). Water salinity was induced by adding CaCl2 to the tap water. All crop-soil measurements were conducted along the middle row at 24 monitoring sites, 1m apart. The spatial and temporal evolution of bulk electrical conductivity (σb) of soil was monitored by i) an Electromagnetic Induction method (EM38-DD) and ii) Time Domain Reflectometry (TDR). Herein we will focus on the methodology we used to elaborate the database of this experiment. Mostly, the data elaboration was devoted to make TDR and EMI data actually comparable. Specifically, we analysed the effect of the different observation windows of TDR and EMI sensors on the different spatial and temporal variability observed in the data series coming from the two sensors. After exploring the different patterns and structures of variability of the original EMI and TDR data series the study assessed the potential of applying a Fourier's analysis to filter the original data series to extract the predominant, high-variance signal after removing the small- scale (high frequency) variance observed in the TDR data series.

A Modified Distributed Bees Algorithm for Multi-Sensor Task Allocation.

PubMed

Tkach, Itshak; Jevtić, Aleksandar; Nof, Shimon Y; Edan, Yael

2018-03-02

Multi-sensor systems can play an important role in monitoring tasks and detecting targets. However, real-time allocation of heterogeneous sensors to dynamic targets/tasks that are unknown a priori in their locations and priorities is a challenge. This paper presents a Modified Distributed Bees Algorithm (MDBA) that is developed to allocate stationary heterogeneous sensors to upcoming unknown tasks using a decentralized, swarm intelligence approach to minimize the task detection times. Sensors are allocated to tasks based on sensors' performance, tasks' priorities, and the distances of the sensors from the locations where the tasks are being executed. The algorithm was compared to a Distributed Bees Algorithm (DBA), a Bees System, and two common multi-sensor algorithms, market-based and greedy-based algorithms, which were fitted for the specific task. Simulation analyses revealed that MDBA achieved statistically significant improved performance by 7% with respect to DBA as the second-best algorithm, and by 19% with respect to Greedy algorithm, which was the worst, thus indicating its fitness to provide solutions for heterogeneous multi-sensor systems.

An iridium oxide microelectrode for monitoring acute local pH changes of endothelial cells.

PubMed

Ng, Shu Rui; O'Hare, Danny

2015-06-21

pH sensors were fabricated by anodically electrodepositing iridium oxide films (AEIROFs) onto microelectrodes on chips and coated with poly(ethyleneimine) (PEI) for mechanical stability. These demonstrate super-Nernstian response to pH from pH 4.0 to 7.7 in chloride-free phosphate buffer. The surface of the chip was coated with fibronectin for the attachment of porcine aortic endothelial cells (PAECs). The working capability of the pH sensor for monitoring acute local pH changes was investigated by stimulating the PAECs with thrombin. Our results show that thrombin induced acute extracellular acidification of PAECs and dissolution of fibronectin, causing the local pH to decrease. The use of PD98059, a mitogen-activated protein kinase (MAPK) inhibitor, reduced extracellular acidification and an increase in local pH was observed. This study shows that our pH sensors can facilitate the investigation of acute cellular responses to stimulation by monitoring the real-time, local pH changes of cells attached to the sensors.

Framework to trade optimality for local processing in large-scale wavefront reconstruction problems.

PubMed

Haber, Aleksandar; Verhaegen, Michel

2016-11-15

We show that the minimum variance wavefront estimation problems permit localized approximate solutions, in the sense that the wavefront value at a point (excluding unobservable modes, such as the piston mode) can be approximated by a linear combination of the wavefront slope measurements in the point's neighborhood. This enables us to efficiently compute a wavefront estimate by performing a single sparse matrix-vector multiplication. Moreover, our results open the possibility for the development of wavefront estimators that can be easily implemented in a decentralized/distributed manner, and in which the estimate optimality can be easily traded for computational efficiency. We numerically validate our approach on Hudgin wavefront sensor geometries, and the results can be easily generalized to Fried geometries.

Jammer Localization Using Wireless Devices with Mitigation by Self-Configuration

PubMed Central

Ashraf, Qazi Mamoon; Habaebi, Mohamed Hadi; Islam, Md. Rafiqul

2016-01-01

Communication abilities of a wireless network decrease significantly in the presence of a jammer. This paper presents a reactive technique, to detect and locate the position of a jammer using a distributed collection of wireless sensor devices. We employ the theory of autonomic computing as a framework to design the same. Upon detection of a jammer, the affected nodes self-configure their power consumption which stops unnecessary waste of battery resources. The scheme then proceeds to determine the approximate location of the jammer by analysing the location of active nodes as well as the affected nodes. This is done by employing a circular curve fitting algorithm. Results indicate a high degree of accuracy in localizing a jammer has been achieved. PMID:27583378

[Peroxisome proliferator activated receptors PPARs: their role in carbohydrate and lipid metabolism].

PubMed

Andrééva-Gatéva, P

2003-01-01

Peroxisome proliferator activated receptors (PPAR) belong to a family of nuclear receptors broadly distributed in the organism. Their pleiotropic role has been recently proved as well as their pathogenic significance in diabetes, obesity, cell cycle controlling, carcinogenesis, inflammation and atherosclerosis. The three types of PPAR identified until today have different tissue localization. PPARgamma, primarily identified in macrophages and adipocytes, play an important role in the expression of proteins essential for lipid metabolism and adipogenesis. PPARalpha are localized predominantly in hepatocytes and have also an important role in lipid metabolism. PPAR are though to be lipid sensors in organism. Carbohydrate metabolism is also under the control of PPAR and their exogenous ligands, (ie: thiasolidinediones), are important antidiabetic drugs.

Real-Time Two-Dimensional Mapping of Relative Local Surface Temperatures with a Thin-Film Sensor Array

PubMed Central

Li, Gang; Wang, Zhenhai; Mao, Xinyu; Zhang, Yinghuang; Huo, Xiaoye; Liu, Haixiao; Xu, Shengyong

2016-01-01

Dynamic mapping of an object’s local temperature distribution may offer valuable information for failure analysis, system control and improvement. In this letter we present a computerized measurement system which is equipped with a hybrid, low-noise mechanical-electrical multiplexer for real-time two-dimensional (2D) mapping of surface temperatures. We demonstrate the performance of the system on a device embedded with 32 pieces of built-in Cr-Pt thin-film thermocouples arranged in a 4 × 8 matrix. The system can display a continuous 2D mapping movie of relative temperatures with a time interval around 1 s. This technique may find applications in a variety of practical devices and systems. PMID:27347969

Real-time sensor validation and fusion for distributed autonomous sensors

NASA Astrophysics Data System (ADS)

Yuan, Xiaojing; Li, Xiangshang; Buckles, Bill P.

2004-04-01

Multi-sensor data fusion has found widespread applications in industrial and research sectors. The purpose of real time multi-sensor data fusion is to dynamically estimate an improved system model from a set of different data sources, i.e., sensors. This paper presented a systematic and unified real time sensor validation and fusion framework (RTSVFF) based on distributed autonomous sensors. The RTSVFF is an open architecture which consists of four layers - the transaction layer, the process fusion layer, the control layer, and the planning layer. This paradigm facilitates distribution of intelligence to the sensor level and sharing of information among sensors, controllers, and other devices in the system. The openness of the architecture also provides a platform to test different sensor validation and fusion algorithms and thus facilitates the selection of near optimal algorithms for specific sensor fusion application. In the version of the model presented in this paper, confidence weighted averaging is employed to address the dynamic system state issue noted above. The state is computed using an adaptive estimator and dynamic validation curve for numeric data fusion and a robust diagnostic map for decision level qualitative fusion. The framework is then applied to automatic monitoring of a gas-turbine engine, including a performance comparison of the proposed real-time sensor fusion algorithms and a traditional numerical weighted average.

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 mobile ferromagnetic shape detection sensor using a Hall sensor array and magnetic imaging.

PubMed

Misron, Norhisam; Shin, Ng Wei; Shafie, Suhaidi; Marhaban, Mohd Hamiruce; Mailah, Nashiren Farzilah

2011-01-01

This paper presents a mobile Hall sensor array system for the shape detection of ferromagnetic materials that are embedded in walls or floors. The operation of the mobile Hall sensor array system is based on the principle of magnetic flux leakage to describe the shape of the ferromagnetic material. Two permanent magnets are used to generate the magnetic flux flow. The distribution of magnetic flux is perturbed as the ferromagnetic material is brought near the permanent magnets and the changes in magnetic flux distribution are detected by the 1-D array of the Hall sensor array setup. The process for magnetic imaging of the magnetic flux distribution is done by a signal processing unit before it displays the real time images using a netbook. A signal processing application software is developed for the 1-D Hall sensor array signal acquisition and processing to construct a 2-D array matrix. The processed 1-D Hall sensor array signals are later used to construct the magnetic image of ferromagnetic material based on the voltage signal and the magnetic flux distribution. The experimental results illustrate how the shape of specimens such as square, round and triangle shapes is determined through magnetic images based on the voltage signal and magnetic flux distribution of the specimen. In addition, the magnetic images of actual ferromagnetic objects are also illustrated to prove the functionality of mobile Hall sensor array system for actual shape detection. The results prove that the mobile Hall sensor array system is able to perform magnetic imaging in identifying various ferromagnetic materials.

A Mobile Ferromagnetic Shape Detection Sensor Using a Hall Sensor Array and Magnetic Imaging

PubMed Central

Misron, Norhisam; Shin, Ng Wei; Shafie, Suhaidi; Marhaban, Mohd Hamiruce; Mailah, Nashiren Farzilah

2011-01-01

This paper presents a Mobile Hall Sensor Array system for the shape detection of ferromagnetic materials that are embedded in walls or floors. The operation of the Mobile Hall Sensor Array system is based on the principle of magnetic flux leakage to describe the shape of the ferromagnetic material. Two permanent magnets are used to generate the magnetic flux flow. The distribution of magnetic flux is perturbed as the ferromagnetic material is brought near the permanent magnets and the changes in magnetic flux distribution are detected by the 1-D array of the Hall sensor array setup. The process for magnetic imaging of the magnetic flux distribution is done by a signal processing unit before it displays the real time images using a netbook. A signal processing application software is developed for the 1-D Hall sensor array signal acquisition and processing to construct a 2-D array matrix. The processed 1-D Hall sensor array signals are later used to construct the magnetic image of ferromagnetic material based on the voltage signal and the magnetic flux distribution. The experimental results illustrate how the shape of specimens such as square, round and triangle shapes is determined through magnetic images based on the voltage signal and magnetic flux distribution of the specimen. In addition, the magnetic images of actual ferromagnetic objects are also illustrated to prove the functionality of Mobile Hall Sensor Array system for actual shape detection. The results prove that the Mobile Hall Sensor Array system is able to perform magnetic imaging in identifying various ferromagnetic materials. PMID:22346653

A Collaborative Secure Localization Algorithm Based on Trust Model in Underwater Wireless Sensor Networks

PubMed Central

Han, Guangjie; Liu, Li; Jiang, Jinfang; Shu, Lei; Rodrigues, Joel J.P.C.

2016-01-01

Localization is one of the hottest research topics in Underwater Wireless Sensor Networks (UWSNs), since many important applications of UWSNs, e.g., event sensing, target tracking and monitoring, require location information of sensor nodes. Nowadays, a large number of localization algorithms have been proposed for UWSNs. How to improve location accuracy are well studied. However, few of them take location reliability or security into consideration. In this paper, we propose a Collaborative Secure Localization algorithm based on Trust model (CSLT) for UWSNs to ensure location security. Based on the trust model, the secure localization process can be divided into the following five sub-processes: trust evaluation of anchor nodes, initial localization of unknown nodes, trust evaluation of reference nodes, selection of reference node, and secondary localization of unknown node. Simulation results demonstrate that the proposed CSLT algorithm performs better than the compared related works in terms of location security, average localization accuracy and localization ratio. PMID:26891300

Aluminum alloy material structure impact localization by using FBG sensors

NASA Astrophysics Data System (ADS)

Zhu, Xiubin

2014-12-01

The aluminum alloy structure impact localization system by using fiber Bragg grating (FBG) sensors and impact localization algorithm was investigated. A four-FBG sensing network was established. And the power intensity demodulation method was initialized employing the narrow-band tunable laser. The wavelet transform was used to weaken the impact signal noise. And the impact signal time difference was extracted to build the time difference localization algorithm. At last, a fiber Bragg grating impact localization system was established and experimentally verified. The experimental results showed that in the aluminum alloy plate with the 500 mm*500 mm*2 mm test area, the maximum and average impact abscissa localization errors were 11 mm and 6.25 mm, and the maximum and average impact ordinate localization errors were 9 mm and 4.25 mm, respectively. The fiber Bragg grating sensors and demodulation system are feasible to realize the aviation aluminum alloy material structure impact localization. The research results provide a reliable method for the aluminum alloy material structure impact localization.

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 Sensor Web Architecture

NASA Astrophysics Data System (ADS)

Bose, P.; Zimdars, A.; Hurlburt, N.; Doug, S.

2006-12-01

NASA envisions the development of smart sensor webs, intelligent and integrated observation network that harness distributed sensing assets, their associated continuous and complex data sets, and predictive observation processing mechanisms for timely, collaborative hazard mitigation and enhanced science productivity and reliability. This paper presents Virtual Sensor Web Infrastructure for Collaborative Science (VSICS) Architecture for sustained coordination of (numerical and distributed) model-based processing, closed-loop resource allocation, and observation planning. VSICS's key ideas include i) rich descriptions of sensors as services based on semantic markup languages like OWL and SensorML; ii) service-oriented workflow composition and repair for simple and ensemble models; event-driven workflow execution based on event-based and distributed workflow management mechanisms; and iii) development of autonomous model interaction management capabilities providing closed-loop control of collection resources driven by competing targeted observation needs. We present results from initial work on collaborative science processing involving distributed services (COSEC framework) that is being extended to create VSICS.

Spatially distributed modal signals of free shallow membrane shell structronic system

NASA Astrophysics Data System (ADS)

Yue, H. H.; Deng, Z. Q.; Tzou, H. S.

2008-11-01

Based on the smart material and structronics technology, distributed sensor and control of shell structures have been rapidly developed for the last 20 years. This emerging technology has been utilized in aerospace, telecommunication, micro-electromechanical systems and other engineering applications. However, distributed monitoring technique and its resulting global spatially distributed sensing signals of shallow paraboloidal membrane shells are not clearly understood. In this paper, modeling of free flexible paraboloidal shell with spatially distributed sensor, micro-sensing signal characteristics, and location of distributed piezoelectric sensor patches are investigated based on a new set of assumed mode shape functions. Parametric analysis indicates that the signal generation depends on modal membrane strains in the meridional and circumferential directions in which the latter is more significant than the former, when all bending strains vanish in membrane shells. This study provides a modeling and analysis technique for distributed sensors laminated on lightweight paraboloidal flexible structures and identifies critical components and regions that generate significant signals.

Distributed temperature sensor testing in liquid sodium

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

Gerardi, Craig; Bremer, Nathan; Lisowski, Darius

Rayleigh-backscatter-based distributed fiber optic sensors were immersed in sodium to obtain high-resolution liquid-sodium temperature measurements. Distributed temperature sensors (DTSs) functioned well up to 400°C in a liquid sodium environment. The DTSs measured sodium column temperature and the temperature of a complex geometrical pattern that leveraged the flexibility of fiber optics. A single Ø 360 lm OD sensor registered dozens of temperatures along a length of over one meter at 100 Hz. We also demonstrated the capability to use a single DTS to simultaneously detect thermal interfaces (e.g. sodium level) and measure temperature.

Temperature grid sensor for the measurement of spatial temperature distributions at object surfaces.

PubMed

Schäfer, Thomas; Schubert, Markus; Hampel, Uwe

2013-01-25

This paper presents results of the development and application of a new temperature grid sensor based on the wire-mesh sensor principle. The grid sensor consists of a matrix of 256 Pt1000 platinum chip resistors and an associated electronics that measures the grid resistances with a multiplexing scheme at high speed. The individual sensor elements can be spatially distributed on an object surface and measure transient temperature distributions in real time. The advantage compared with other temperature field measurement approaches such as infrared cameras is that the object under investigation can be thermally insulated and the radiation properties of the surface do not affect the measurement accuracy. The sensor principle is therefore suited for various industrial monitoring applications. Its applicability for surface temperature monitoring has been demonstrated through heating and mixing experiments in a vessel.

Airborne agent concentration analysis

DOEpatents

Gelbard, Fred

2004-02-03

A method and system for inferring airborne contaminant concentrations in rooms without contaminant sensors, based on data collected by contaminant sensors in other rooms of a building, using known airflow interconnectivity data. The method solves a least squares problem that minimizes the difference between measured and predicted contaminant sensor concentrations with respect to an unknown contaminant release time. Solutions are constrained to providing non-negative initial contaminant concentrations in all rooms. The method can be used to identify a near-optimal distribution of sensors within the building, when then number of available sensors is less than the total number of rooms. This is achieved by having a system-sensor matrix that is non-singular, and by selecting that distribution which yields the lowest condition number of all the distributions considered. The method can predict one or more contaminant initial release points from the collected data.

Dust particles investigation for future Russian lunar missions.

NASA Astrophysics Data System (ADS)

Dolnikov, Gennady; Horanyi, Mihaly; Esposito, Francesca; Zakharov, Alexander; Popel, Sergey; Afonin, Valeri; Borisov, Nikolay; Seran, Elena; Godefroy, Michel; Shashkova, Inna; Kuznetsov, Ilya; Lyash, Andrey; Vorobyova, Elena; Petrov, Oleg; Lisin, Evgeny

One of the complicating factors of the future robotic and human lunar landing missions is the influence of the dust. Meteorites bombardment has accompanied by shock-explosive phenomena, disintegration and mix of the lunar soil in depth and on area simultaneously. As a consequence, the lunar soil has undergone melting, physical and chemical transformations. Recently we have the some reemergence for interest of Moon investigation. The prospects in current century declare USA, China, India, and European Union. In Russia also prepare two missions: Luna-Glob and Luna-Resource. Not last part of investigation of Moon surface is reviewing the dust condition near the ground of landers. Studying the properties of lunar dust is important both for scientific purposes to investigation the lunar exosphere component and for the technical safety of lunar robotic and manned missions. The absence of an atmosphere on the Moon's surface is leading to greater compaction and sintering. Properties of regolith and dust particles (density, temperature, composition, etc.) as well as near-surface lunar exosphere depend on solar activity, lunar local time and position of the Moon relative to the Earth's magneto tail. Upper layers of regolith are an insulator, which is charging as a result of solar UV radiation and the constant bombardment of charged particles, creates a charge distribution on the surface of the moon: positive on the illuminated side and negative on the night side. Charge distribution depends on the local lunar time, latitude and the electrical properties of the regolith (the presence of water in the regolith can influence the local distribution of charge). On light side of Moon near surface layer there exists possibility formation dusty plasma system. Altitude of levitation is depending from size of dust particle and Moon latitude. The distribution dust particle by size and altitude has estimated with taking into account photoelectrons, electrons and ions of solar wind, solar emission. Dust analyzer instrument PmL for future Russian lender missons intends for investigation the dynamics of dusty plasma near lunar surface. PmL consist of three blocks: Impact Sensor and two Electric Field Sensors. Dust Experiment goals are: 1) Impact sensor to investigate the dynamics of dust particles near the lunar surface (speed, charge, mass, vectors of a fluxes) a) high speed micrometeorites b) secondary particles after micrometeorites soil bombardment c) levitating dust particles due to electrostatic fields PmL instrument will measure dust particle impulses. In laboratory tests we used - min impulse so as 7•10-11 N•c, by SiO2 dust particles, 20-40 µm with velocity about 0,5 -2,5 m/c, dispersion 0.3, and - max impulse was 10-6 N•c with possibility increased it by particles Pb-Sn 0,7 mm with velocity 1 m/c, dispersion ±0.3. Also Impact Sensor will measure the charge of dust particle as far as 10-15 C ( 1000 electrons). In case the charge and impulse of a dust particle are measured we can obtain velocity and mass of them. 2) Electric field Sensor will measure the value and dynamics of the electric fields the lunar surface. Two Electric Field Sensors both are measured the concentration and temperature of charged particles (electrons, ions, dust particles). Uncertainty of measurements is 10%. Electric Field Sensors contain of Lengmure probe. Using Lengmure probe to dark and light Moon surface we can obtain the energy spectra photoelectrons in different period of time. PmL instrument is developing, working out and manufacturing in IKI. Simultaneously with the PmL dust instrument to study lunar dust it would be very important to use an onboard TV system adjusted for imaging physical properties of dust on the lunar surface (adhesion, albedo, porosity, etc), and to collect dust particles samples from the lunar surface to return these samples to the Earth for measure a number of physic-chemical properties of the lunar dust, e.g. a quantum yield of photoemission, what is very important for modeling physical processes in the lunar exosphere.

State estimation for distributed systems with sensing delay

NASA Astrophysics Data System (ADS)

Alexander, Harold L.

1991-08-01

Control of complex systems such as remote robotic vehicles requires combining data from many sensors where the data may often be delayed by sensory processing requirements. The number and variety of sensors make it desirable to distribute the computational burden of sensing and estimation among multiple processors. Classic Kalman filters do not lend themselves to distributed implementations or delayed measurement data. The alternative Kalman filter designs presented in this paper are adapted for delays in sensor data generation and for distribution of computation for sensing and estimation over a set of networked processors.

Laboratory evaluation of the Sequoia Scientific LISST-ABS acoustic backscatter sediment sensor

USGS Publications Warehouse

Snazelle, Teri T.

2017-12-18

Sequoia Scientific’s LISST-ABS is an acoustic backscatter sensor designed to measure suspended-sediment concentration at a point source. Three LISST-ABS were evaluated at the U.S. Geological Survey (USGS) Hydrologic Instrumentation Facility (HIF). Serial numbers 6010, 6039, and 6058 were assessed for accuracy in solutions with varying particle-size distributions and for the effect of temperature on sensor accuracy. Certified sediment samples composed of different ranges of particle size were purchased from Powder Technology Inc. These sediment samples were 30–80-micron (µm) Arizona Test Dust; less than 22-µm ISO 12103-1, A1 Ultrafine Test Dust; and 149-µm MIL-STD 810E Silica Dust. The sensor was able to accurately measure suspended-sediment concentration when calibrated with sediment of the same particle-size distribution as the measured. Overall testing demonstrated that sensors calibrated with finer sized sediments overdetect sediment concentrations with coarser sized sediments, and sensors calibrated with coarser sized sediments do not detect increases in sediment concentrations from small and fine sediments. These test results are not unexpected for an acoustic-backscatter device and stress the need for using accurate site-specific particle-size distributions during sensor calibration. When calibrated for ultrafine dust with a less than 22-µm particle size (silt) and with the Arizona Test Dust with a 30–80-µm range, the data from sensor 6039 were biased high when fractions of the coarser (149-µm) Silica Dust were added. Data from sensor 6058 showed similar results with an elevated response to coarser material when calibrated with a finer particle-size distribution and a lack of detection when subjected to finer particle-size sediment. Sensor 6010 was also tested for the effect of dissimilar particle size during the calibration and showed little effect. Subsequent testing revealed problems with this sensor, including an inadequate temperature compensation, making this data questionable. The sensor was replaced by Sequoia Scientific with serial number 6039. Results from the extended temperature testing showed proper temperature compensation for sensor 6039, and results from the dissimilar calibration/testing particle-size distribution closely corroborated the results from sensor 6058.

Innovative Embedded Fiber Sensor System for Spacecraft's Health in Situ Monitoring

NASA Astrophysics Data System (ADS)

Haddad, E.; Kruzelecky, R.; Zou, J.; Wong, B.; Mohammad, N.; Thatte, G.; Jamroz, W.; Riendeau, S.

2009-01-01

Monitoring of various parameters in satellites is desirable to provide the necessary information on the condition and status of the spacecraft and its various subsystems (AOCS, thermal, propulsion, power, mechanisms etc.) throughout its lifecycle. Fiber-Optic Bragg Grating (FBG) sensors represent an alternative to current technological approaches, enabling in situ distributed dynamic health monitoring, to provide a mapping of the spacecraft strain and temperature distributions, for varying operating and orbital conditions. In addition, these sensors may be implemented in the very early spacecraft fabrication stages, as built-in testing and diagnostic tools, and then used continuously through the mission phases until the end of the spacecraft mission. This can substantially reduce the cost of ground qualification and facilitate improved spacecraft design. MPBC has developed and ground qualified a demonstrator fiber sensor network, the Fiber Sensor Demonstrator (FSD) that has been successfully integrated with ESA's Proba-2. This is scheduled to launch in the fall of 2008, and will be the first complete fiber-optic sensing system in space. The advantages of the MPBC approach include a central interrogation system that can be used to control a multi-parameter sensing incorporating various types of sensors. Using a combination of both parallel signal distribution and serial wavelength division sensor multiplexing along single strands of optical fiber enables a high sensor capacity. In a continuous effort, MPB Communications (MPBC) is developing an innovative Embedded Distributed Fiber Sensor (EDFOS) within space composite structures. It addresses the challenges of embedding very thin fiber sensors within a selected material matrix, the decoupling of the strain and temperature effects on the fiber, and the sensor distribution. The embedded sensor approach allows the sensor system to follow the status of the space structure through its entire life cycle; from fabrication and assembly, to ground testing, to the space mission itself. By providing a history of the structure, any changes are more readily discernable, and the in situ sensor information can be used to further improve the design and reliability of the structure.

SMART: The Future of Spaceflight Avionics

NASA Technical Reports Server (NTRS)

Alhorn, Dean C.; Howard, David E.

2010-01-01

A novel avionics approach is necessary to meet the future needs of low cost space and lunar missions that require low mass and low power electronics. The current state of the art for avionics systems are centralized electronic units that perform the required spacecraft functions. These electronic units are usually custom-designed for each application and the approach compels avionics designers to have in-depth system knowledge before design can commence. The overall design, development, test and evaluation (DDT&E) cycle for this conventional approach requires long delivery times for space flight electronics and is very expensive. The Small Multi-purpose Advanced Reconfigurable Technology (SMART) concept is currently being developed to overcome the limitations of traditional avionics design. The SMART concept is based upon two multi-functional modules that can be reconfigured to drive and sense a variety of mechanical and electrical components. The SMART units are key to a distributed avionics architecture whereby the modules are located close to or right at the desired application point. The drive module, SMART-D, receives commands from the main computer and controls the spacecraft mechanisms and devices with localized feedback. The sensor module, SMART-S, is used to sense the environmental sensors and offload local limit checking from the main computer. There are numerous benefits that are realized by implementing the SMART system. Localized sensor signal conditioning electronics reduces signal loss and overall wiring mass. Localized drive electronics increase control bandwidth and minimize time lags for critical functions. These benefits in-turn reduce the main processor overhead functions. Since SMART units are standard flight qualified units, DDT&E is reduced and system design can commence much earlier in the design cycle. Increased production scale lowers individual piece part cost and using standard modules also reduces non-recurring costs. The benefit list continues, but the overall message is already evident: the SMART concept is an evolution in spacecraft avionics. SMART devices have the potential to change the design paradigm for future satellites, spacecraft and even commercial applications.

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.

Distributed digital signal processors for multi-body flexible structures

NASA Technical Reports Server (NTRS)

Lee, Gordon K. F.

1992-01-01

Multi-body flexible structures, such as those currently under investigation in spacecraft design, are large scale (high-order) dimensional systems. Controlling and filtering such structures is a computationally complex problem. This is particularly important when many sensors and actuators are located along the structure and need to be processed in real time. This report summarizes research activity focused on solving the signal processing (that is, information processing) issues of multi-body structures. A distributed architecture is developed in which single loop processors are employed for local filtering and control. By implementing such a philosophy with an embedded controller configuration, a supervising controller may be used to process global data and make global decisions as the local devices are processing local information. A hardware testbed, a position controller system for a servo motor, is employed to illustrate the capabilities of the embedded controller structure. Several filtering and control structures which can be modeled as rational functions can be implemented on the system developed in this research effort. Thus the results of the study provide a support tool for many Control/Structure Interaction (CSI) NASA testbeds such as the Evolutionary model and the nine-bay truss structure.

Building and evaluating sensor-based Citizens' Observatories for improving quality of life in cities

NASA Astrophysics Data System (ADS)

Castell, Nuria; Lahoz, William; Schneider, Philipp; Høiskar, Britt Ann; Grossberndt, Sonja; Naderer, Clemens; Robinson, Johanna; Kocman, David; Horvat, Milena; Bartonova, Alena

2014-05-01

Urban air quality, the environmental quality of public spaces and indoor areas such as schools, are areas of great concern to citizens and policymakers. However, access to information addressing these areas is not always available in a user-friendly manner. In particular, the quality and quantity of this information is not consistent across these areas, and does not reflect differences in needs among users. The EU-funded CITI-SENSE project will build on the concept of the Citizens' Observatories to empower citizens to contribute to and participate in environmental governance, and enable them to support and influence decision making by policymakers. To achieve this goal, CITI-SENSE will develop, test, demonstrate and validate a community-based environmental monitoring and information system using low-cost sensors and Earth Observation applications. Key to achieving this goal is the chain "sensors-platforms-products-users" linking providers of technology to users: (i) technologies for distributed monitoring (sensors); (ii) information and communication technologies (platform); (iii) information products and services (products); (iv) and citizen involvement in both monitoring and societal decisions (users). The CITI-SENSE observatories cover three empowerment initiatives: urban air quality; public spaces; and school indoor quality. The empowerment initiatives are being performed at nine locations across Europe. Each location has adapted the generic case study to their local circumstances and has contacted the urban stakeholders needed to run the study. The empowerment initiatives are divided into two phases: a first phase (Pilot Study), and a second phase (Full Implementation). The main goal of the Pilot Study is to test and evaluate the chain "sensors-platform-products-users". To assess the results of the empowerment initiatives, key performance indicators (KPIs) are being developed; these include questionnaires for users. The KPIs will be used to design the full implementation phase of the project. First results from the Pilot Study will be presented for three participating cities: Ljubljana (Slovenia), Vienna (Austria) and Oslo (Norway), which differ in size, environmental conditions and social perception on local air quality. Ljubljana and Oslo empowerment initiatives include urban air quality, and school indoor air quality, while Vienna only includes urban air quality. For the area of urban air quality, the three cities will deploy a wireless network of five static sensor nodes and distribute five personal sensors among people to be carried while performing daily activities in the pilot study. The data will be accessible to users through mobile phones, web services and other devices. For the full implementation phase the sensor network will comprise a total of 20 to 40 static nodes, depending on the size of the city, and 20 personal nodes. For the school indoor air quality three sensors will be allocated inside the school and one outside. The data will be visible provided in school classrooms giving the students a unique and innovative approach to learn about air quality by being involved. Acknowledgements: CITI-SENSE is a Collaborative Project partly funded by the EU FP7-ENV-2012 under grant agreement no 308524. www.citi-sense.eu.

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

Real time thermal imaging for analysis and control of crystal growth by the Czochralski technique

NASA Technical Reports Server (NTRS)

Wargo, M. J.; Witt, A. F.

1992-01-01

A real time thermal imaging system with temperature resolution better than +/- 0.5 C and spatial resolution of better than 0.5 mm has been developed. It has been applied to the analysis of melt surface thermal field distributions in both Czochralski and liquid encapsulated Czochralski growth configurations. The sensor can provide single/multiple point thermal information; a multi-pixel averaging algorithm has been developed which permits localized, low noise sensing and display of optical intensity variations at any location in the hot zone as a function of time. Temperature distributions are measured by extraction of data along a user selectable linear pixel array and are simultaneously displayed, as a graphic overlay, on the thermal image.

Phase-based Bragg intragrating distributed strain sensor

NASA Astrophysics Data System (ADS)

Huang, S.; Ohn, M. M.; Measures, R. M.

1996-03-01

A strain-distribution sensing technique based on the measurement of the phase spectrum of the reflected light from a fiber-optic Bragg grating is described. When a grating is subject to a strain gradient, the grating will experience a chirp and therefore the resonant wavelength will vary along the grating, causing wavelength-dependent penetration depth. Because the group delay for each wavelength component is related to its penetration depth and the resonant wavelength is determined by strain, a measured phase spectrum can then indicate the local strain as a function of location within the grating. This phase-based Bragg grating sensing technique offers a powerful new means for studying some important effects over a few millimeters or centimeters in smart structures.

Distributed multimodal data fusion for large scale wireless sensor networks

NASA Astrophysics Data System (ADS)

Ertin, Emre

2006-05-01

Sensor network technology has enabled new surveillance systems where sensor nodes equipped with processing and communication capabilities can collaboratively detect, classify and track targets of interest over a large surveillance area. In this paper we study distributed fusion of multimodal sensor data for extracting target information from a large scale sensor network. Optimal tracking, classification, and reporting of threat events require joint consideration of multiple sensor modalities. Multiple sensor modalities improve tracking by reducing the uncertainty in the track estimates as well as resolving track-sensor data association problems. Our approach to solving the fusion problem with large number of multimodal sensors is construction of likelihood maps. The likelihood maps provide a summary data for the solution of the detection, tracking and classification problem. The likelihood map presents the sensory information in an easy format for the decision makers to interpret and is suitable with fusion of spatial prior information such as maps, imaging data from stand-off imaging sensors. We follow a statistical approach to combine sensor data at different levels of uncertainty and resolution. The likelihood map transforms each sensor data stream to a spatio-temporal likelihood map ideally suitable for fusion with imaging sensor outputs and prior geographic information about the scene. We also discuss distributed computation of the likelihood map using a gossip based algorithm and present simulation results.

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

PubMed

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

2016-10-27

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

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

PubMed Central

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

2016-01-01

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

Passive Sensor Integration for Vehicle Self-Localization in Urban Traffic Environment †

PubMed Central

Gu, Yanlei; Hsu, Li-Ta; Kamijo, Shunsuke

2015-01-01

This research proposes an accurate vehicular positioning system which can achieve lane-level performance in urban canyons. Multiple passive sensors, which include Global Navigation Satellite System (GNSS) receivers, onboard cameras and inertial sensors, are integrated in the proposed system. As the main source for the localization, the GNSS technique suffers from Non-Line-Of-Sight (NLOS) propagation and multipath effects in urban canyons. This paper proposes to employ a novel GNSS positioning technique in the integration. The employed GNSS technique reduces the multipath and NLOS effects by using the 3D building map. In addition, the inertial sensor can describe the vehicle motion, but has a drift problem as time increases. This paper develops vision-based lane detection, which is firstly used for controlling the drift of the inertial sensor. Moreover, the lane keeping and changing behaviors are extracted from the lane detection function, and further reduce the lateral positioning error in the proposed localization system. We evaluate the integrated localization system in the challenging city urban scenario. The experiments demonstrate the proposed method has sub-meter accuracy with respect to mean positioning error. PMID:26633420

An active acoustic tripwire for simultaneous detection and localization of multiple underwater intruders.

PubMed

Folegot, Thomas; Martinelli, Giovanna; Guerrini, Piero; Stevenson, J Mark

2008-11-01

An algorithm allowing simultaneous detection and localization of multiple submerged targets crossing an acoustic tripwire based on forward scattering is described and then evaluated based upon data collected at sea. This paper quantifies the agreement between the theoretical performance and the results obtained from processing data gathered at sea for crossings at several depths and ranges. Targets crossing the acoustic field produce shadows on each side of the barrier, for specific sensors and for specific acoustic paths. In post-processing, a model is invoked to associate expected paths with the observed shadows. This process allows triangulation of the target's position inside the acoustic field. Precise localization is achieved by taking advantage of the multipath propagation structure of the received signal, together with the diversity of the source and receiver locations. Environmental robustness is demonstrated using simulations and can be explained by the use of an array of sources spatially distributed through the water column.

Investigation of local heterogeneity of hbO2 and hb in working dog heart in situ under isovolemic hemodilution and critical coronary stenosis

NASA Astrophysics Data System (ADS)

Krug, Alfons; Kessler, Manfred D.; Khuri, Raja; Lust, Robert; Chitwood, Randolph

1996-12-01

A tissue spectrophotometer (EMPHO II) working with 70 micrometer micro lightguide sensors enables recording of spectra in the visible wavelength range (500 - 630 nm). During an initial period arterial hypoxia and hyperoxia were induced on working dog heart by mechanical ventilation with oxygen fractions (fiO2) of 0.1 and 0.5. Under these conditions the effects of low and high fiO2 on oxygenation distribution of intracapillary hemoglobin were investigated. In the second part of the experiment the relation between systemic hematocrit, local hemoglobin concentration, local hemoglobin oxygenation and the oxygen regulation mechanism were studied in detail. In the final part of the experiment the effect of critical coronary stenosis on hb and hbO2 was measured. Critical stenosis was achieved by partial clamping of the left anterior coronary artery (LAD).

Local Contributors and Predictability of Flash Drought at the Marena Oklahoma In Situ Sensor Testbed (MOISST) During 2012

NASA Astrophysics Data System (ADS)

Basara, J. B.; Otkin, J.; Mahan, H. R.; Anderson, M. C.; Hain, C.; Wagle, P.; Xiao, X.

2014-12-01

The Marena Oklahoma In Situ Sensor Testbed (MOISST) site was installed in May 2010 as part of the calibration and validation program for the NASA Soil Moisture Active Passive (SMAP) mission. The site includes more than 200 soil, vegetation, and atmospheric sensors installed over an approximately 64 hectare pasture in Central Oklahoma with 4 main stations and multiple sensors installed in profiles. Additional sensors located at the site include a COsmic-ray Soil Moisture Observing System, global position system reflectometers, a passive distributed temperature system, an eddy correlation flux tower, and a phenocam. During 2012, flash drought conditions occurred at the MOISST location as conditions transitioned from no drought in late April to D4 (exceptional drought) in mid August. The array of instruments captured the dramatic transition of land-surface conditions at the MOISST site, in particular during a period spanning approximately six weeks in July and August in whereby drought conditions changed from abnormally dry to exceptional drought and ecosystem collapsed occurred. Results for the analyses demonstrated that both soil moisture and vegetation dynamics were critical components to flash drought development. Further, when the Evaporative Stress Index (ESI) was applied to the MOISST site during 2012, the results demonstrated that the predictability of drought conditions were increased to nearly six weeks prior to flash drought development that began in July.

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

Few-mode fiber based distributed curvature sensor through quasi-single-mode Brillouin frequency shift.

PubMed

Wu, Hao; Wang, Ruoxu; Liu, Deming; Fu, Songnian; Zhao, Can; Wei, Huifeng; Tong, Weijun; Shum, Perry Ping; Tang, Ming

2016-04-01

We proposed and demonstrated a few-mode fiber (FMF) based optical-fiber sensor for distributed curvature measurement through quasi-single-mode Brillouin frequency shift (BFS). By central-alignment splicing FMF and single-mode fiber (SMF) with a fusion taper, a SMF-components-compatible distributed curvature sensor based on FMF is realized using the conventional Brillouin optical time-domain analysis system. The distributed BFS change induced by bending in FMF has been theoretically and experimentally investigated. The precise BFS response to the curvature along the fiber link has been calibrated. A proof-of-concept experiment is implemented to validate its effectiveness in distributed curvature measurement.

Experimental extractions of particle position from inline holograms using single coefficient of Wigner-Ville analysis

NASA Astrophysics Data System (ADS)

Widjaja, Joewono; Dawprateep, Saowaros; Chuamchaitrakool, Porntip

2017-07-01

Extractions of particle positions from inline holograms using a single coefficient of Wigner-Ville distribution (WVD) are experimentally verified. WVD analysis of holograms gives local variation of fringe frequency. Regardless of an axial position of particles, one of the WVD coefficients has the unique characteristics of having the lowest amplitude and being located on a line with a slope inversely proportional to the particle position. Experimental results obtained using two image sensors with different resolutions verify the feasibility of the present method.

Distributed Sensor Nodes Charged by Mobile Charger with Directional Antenna and by Energy Trading for Balancing.

PubMed

Moraes, Celso; Myung, Sunghee; Lee, Sangkeum; Har, Dongsoo

2017-01-10

Provision of energy to wireless sensor networks is crucial for their sustainable operation. Sensor nodes are typically equipped with batteries as their operating energy sources. However, when the sensor nodes are sited in almost inaccessible locations, replacing their batteries incurs high maintenance cost. Under such conditions, wireless charging of sensor nodes by a mobile charger with an antenna can be an efficient solution. When charging distributed sensor nodes, a directional antenna, rather than an omnidirectional antenna, is more energy-efficient because of smaller proportion of off-target radiation. In addition, for densely distributed sensor nodes, it can be more effective for some undercharged sensor nodes to harvest energy from neighboring overcharged sensor nodes than from the remote mobile charger, because this reduces the pathloss of charging signal due to smaller distances. In this paper, we propose a hybrid charging scheme that combines charging by a mobile charger with a directional antenna, and energy trading, e.g., transferring and harvesting, between neighboring sensor nodes. The proposed scheme is compared with other charging scheme. Simulations demonstrate that the hybrid charging scheme with a directional antenna achieves a significant reduction in the total charging time required for all sensor nodes to reach a target energy level.

Distributed Sensor Nodes Charged by Mobile Charger with Directional Antenna and by Energy Trading for Balancing

PubMed Central

Moraes, Celso; Myung, Sunghee; Lee, Sangkeum; Har, Dongsoo

2017-01-01

Provision of energy to wireless sensor networks is crucial for their sustainable operation. Sensor nodes are typically equipped with batteries as their operating energy sources. However, when the sensor nodes are sited in almost inaccessible locations, replacing their batteries incurs high maintenance cost. Under such conditions, wireless charging of sensor nodes by a mobile charger with an antenna can be an efficient solution. When charging distributed sensor nodes, a directional antenna, rather than an omnidirectional antenna, is more energy-efficient because of smaller proportion of off-target radiation. In addition, for densely distributed sensor nodes, it can be more effective for some undercharged sensor nodes to harvest energy from neighboring overcharged sensor nodes than from the remote mobile charger, because this reduces the pathloss of charging signal due to smaller distances. In this paper, we propose a hybrid charging scheme that combines charging by a mobile charger with a directional antenna, and energy trading, e.g., transferring and harvesting, between neighboring sensor nodes. The proposed scheme is compared with other charging scheme. Simulations demonstrate that the hybrid charging scheme with a directional antenna achieves a significant reduction in the total charging time required for all sensor nodes to reach a target energy level. PMID:28075372

Distributed adaptive diagnosis of sensor faults using structural response data

NASA Astrophysics Data System (ADS)

Dragos, Kosmas; Smarsly, Kay

2016-10-01

The reliability and consistency of wireless structural health monitoring (SHM) systems can be compromised by sensor faults, leading to miscalibrations, corrupted data, or even data loss. Several research approaches towards fault diagnosis, referred to as ‘analytical redundancy’, have been proposed that analyze the correlations between different sensor outputs. In wireless SHM, most analytical redundancy approaches require centralized data storage on a server for data analysis, while other approaches exploit the on-board computing capabilities of wireless sensor nodes, analyzing the raw sensor data directly on board. However, using raw sensor data poses an operational constraint due to the limited power resources of wireless sensor nodes. In this paper, a new distributed autonomous approach towards sensor fault diagnosis based on processed structural response data is presented. The inherent correlations among Fourier amplitudes of acceleration response data, at peaks corresponding to the eigenfrequencies of the structure, are used for diagnosis of abnormal sensor outputs at a given structural condition. Representing an entirely data-driven analytical redundancy approach that does not require any a priori knowledge of the monitored structure or of the SHM system, artificial neural networks (ANN) are embedded into the sensor nodes enabling cooperative fault diagnosis in a fully decentralized manner. The distributed analytical redundancy approach is implemented into a wireless SHM system and validated in laboratory experiments, demonstrating the ability of wireless sensor nodes to self-diagnose sensor faults accurately and efficiently with minimal data traffic. Besides enabling distributed autonomous fault diagnosis, the embedded ANNs are able to adapt to the actual condition of the structure, thus ensuring accurate and efficient fault diagnosis even in case of structural changes.

Soft sensor modeling based on variable partition ensemble method for nonlinear batch processes

NASA Astrophysics Data System (ADS)

Wang, Li; Chen, Xiangguang; Yang, Kai; Jin, Huaiping

2017-01-01

Batch processes are always characterized by nonlinear and system uncertain properties, therefore, the conventional single model may be ill-suited. A local learning strategy soft sensor based on variable partition ensemble method is developed for the quality prediction of nonlinear and non-Gaussian batch processes. A set of input variable sets are obtained by bootstrapping and PMI criterion. Then, multiple local GPR models are developed based on each local input variable set. When a new test data is coming, the posterior probability of each best performance local model is estimated based on Bayesian inference and used to combine these local GPR models to get the final prediction result. The proposed soft sensor is demonstrated by applying to an industrial fed-batch chlortetracycline fermentation process.

SCHeMA open and modular in situ sensing solution

NASA Astrophysics Data System (ADS)

Tercier-Waeber, Marie Louise; Novellino, Antonio

2017-04-01

Marine environments are highly vulnerable and influenced by a wide diversity of anthropogenic and natural substances and organisms that may have adverse effects on the ecosystem equilibrium, on living resources and, ultimately, on human health. Identification of relevant types of hazards at the appropriate temporal and spatial scale is crucial to detect their sources and origin, to understand the processes governing their magnitude and distribution, and to ultimately evaluate and manage their risks and consequences preventing economic losses. This can be addressed only by the development of innovative, compact, rugged, automated, sensor networks allowing long-term monitoring. Development of such tools is a challenging task as it requires many analytical and technical innovations. The FP7-OCEAN 2013-SCHeMA project aims to contribute to meet this challenge by providing an open and modular sensing solution for autonomous in situ high resolution mapping of a range of anthropogenic and natural chemical compounds (trace metals, nutrients, anthropogenic organic compounds, toxic algae species and toxins, species relevant to the carbon cycle). To achieve this, SCHeMA activities focus on the development of : 1) an array of miniature sensor probes taking advantage of various innovative solutions, namely: (polymer-based) gel-integrated sensors; solid state ion-selective membrane sensors coupled to an on-line desalination module; mid-infrared optical sensors; optochemical multichannel devices; enOcean technology; 2) dedicated hardware, firmware and software components allowing their plug-and-play integration, localization as well as wireless bidirectional communication via advanced OGC-SWE wired/wireless dedicated interfaces; 3) a web-based front-end system compatible with EU standard requirements and principles (INSPIRE, GEO/GEOSS) and configured to insure easy interoperability with national, regional and local marine observation systems. This lecture will present examples of innovative approaches and devices successfully developed and currently explored. Potentiality of the SCHeMA individual probes and integrated system to provide new type of high-resolution environmental data will be illustrated by examples of field application in selected coastal areas. www.schema-ocean.eu

Nanoparticles based fiber optic SPR sensor

NASA Astrophysics Data System (ADS)

Shah, Kruti; Sharma, Navneet K.

2018-05-01

Localized surface plasmon resonance based fiber optic sensor using platinum nanoparticles is proposed and theoretically analyzed. Increase in thickness of nanoparticles layer increases the sensitivity of sensor. 50 nm thick platinum nanoparticles layer based sensor reveals highest sensitivity.

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.

Wi-Fi/MARG Integration for Indoor Pedestrian Localization.

PubMed

Tian, Zengshan; Jin, Yue; Zhou, Mu; Wu, Zipeng; Li, Ze

2016-12-10

With the wide deployment of Wi-Fi networks, Wi-Fi based indoor localization systems that are deployed without any special hardware have caught significant attention and have become a currently practical technology. At the same time, the Magnetic, Angular Rate, and Gravity (MARG) sensors installed in commercial mobile devices can achieve highly-accurate localization in short time. Based on this, we design a novel indoor localization system by using built-in MARG sensors and a Wi-Fi module. The innovative contributions of this paper include the enhanced Pedestrian Dead Reckoning (PDR) and Wi-Fi localization approaches, and an Extended Kalman Particle Filter (EKPF) based fusion algorithm. A new Wi-Fi/MARG indoor localization system, including an Android based mobile client, a Web page for remote control, and a location server, is developed for real-time indoor pedestrian localization. The extensive experimental results show that the proposed system is featured with better localization performance, with the average error 0.85 m, than the one achieved by using the Wi-Fi module or MARG sensors solely.

Local Area Water Removal Analysis of a Proton Exchange Membrane Fuel Cell under Gas Purge Conditions

PubMed Central

Lee, Chi-Yuan; Lee, Yu-Ming; Lee, Shuo-Jen

2012-01-01

In this study, local area water content distribution under various gas purging conditions are experimentally analyzed for the first time. The local high frequency resistance (HFR) is measured using novel micro sensors. The results reveal that the liquid water removal rate in a membrane electrode assembly (MEA) is non-uniform. In the under-the-channel area, the removal of liquid water is governed by both convective and diffusive flux of the through-plane drying. Thus, almost all of the liquid water is removed within 30 s of purging with gas. However, liquid water that is stored in the under-the-rib area is not easy to remove during 1 min of gas purging. Therefore, the re-hydration of the membrane by internal diffusive flux is faster than that in the under-the-channel area. Consequently, local fuel starvation and membrane degradation can degrade the performance of a fuel cell that is started from cold. PMID:22368495

BreathSens: A Continuous On-Bed Respiratory Monitoring System With Torso Localization Using an Unobtrusive Pressure Sensing Array.

PubMed

Liu, Jason J; Huang, Ming-Chun; Xu, Wenyao; Zhang, Xiaoyi; Stevens, Luke; Alshurafa, Nabil; Sarrafzadeh, Majid

2015-09-01

The ability to continuously monitor respiration rates of patients in homecare or in clinics is an important goal. Past research showed that monitoring patient breathing can lower the associated mortality rates for long-term bedridden patients. Nowadays, in-bed sensors consisting of pressure sensitive arrays are unobtrusive and are suitable for deployment in a wide range of settings. Such systems aim to extract respiratory signals from time-series pressure sequences. However, variance of movements, such as unpredictable extremities activities, affect the quality of the extracted respiratory signals. BreathSens, a high-density pressure sensing system made of e-Textile, profiles the underbody pressure distribution and localizes torso area based on the high-resolution pressure images. With a robust bodyparts localization algorithm, respiratory signals extracted from the localized torso area are insensitive to arbitrary extremities movements. In a study of 12 subjects, BreathSens demonstrated its respiratory monitoring capability with variations of sleep postures, locations, and commonly tilted clinical bed conditions.

Local area water removal analysis of a proton exchange membrane fuel cell under gas purge conditions.

PubMed

Lee, Chi-Yuan; Lee, Yu-Ming; Lee, Shuo-Jen

2012-01-01

In this study, local area water content distribution under various gas purging conditions are experimentally analyzed for the first time. The local high frequency resistance (HFR) is measured using novel micro sensors. The results reveal that the liquid water removal rate in a membrane electrode assembly (MEA) is non-uniform. In the under-the-channel area, the removal of liquid water is governed by both convective and diffusive flux of the through-plane drying. Thus, almost all of the liquid water is removed within 30 s of purging with gas. However, liquid water that is stored in the under-the-rib area is not easy to remove during 1 min of gas purging. Therefore, the re-hydration of the membrane by internal diffusive flux is faster than that in the under-the-channel area. Consequently, local fuel starvation and membrane degradation can degrade the performance of a fuel cell that is started from cold.

Cloud2IR: Infrared thermography and environmental sensors integrated in an autonomoussystem for long term monitoring of structures

NASA Astrophysics Data System (ADS)

Crinière, Antoine; Dumoulin, Jean; Mevel, Laurent; Andrade-Barroso, Guillermo

2016-04-01

Since late 2014, the project Cloud2SM aims to develop a robust information system able to assess the long term monitoring of civil engineering structures as well as interfacing various sensors and data. Cloud2SM address three main goals, the management of distributed data and sensors network, the asynchronous processing of the data through network and the local management of the sensors themselves [1]. Integrated to this project Cloud2IR is an autonomous sensor system dedicated to the long term monitoring of infrastructures. Past experimentations have shown the need as well as usefulness of such system [2]. Before Cloud2IR an initially laboratory oriented system was used, which implied heavy operating system to be used [3]. Based on such system Cloud2IR has benefited of the experimental knowledge acquired to redefine a lighter architecture based on generics standards, more appropriated to autonomous operations on field and which can be later included in a wide distributed architecture such as Cloud2SM. The sensor system can be divided in two parts. The sensor side, this part is mainly composed by the various sensors drivers themselves as the infrared camera, the weather station or the pyranometers and their different fixed configurations. In our case, as infrared camera are slightly different than other kind of sensors, the system implement in addition an RTSP server which can be used to set up the FOV as well as other measurement parameter considerations. The second part can be seen as the data side, which is common to all sensors. It instantiate through a generic interface all the sensors and control the data access loop (not the requesting). This side of the system is weakly coupled (see data coupling) with the sensor side. It can be seen as a general framework able to aggregate any sensor data, type or size and automatically encapsulate them in various generic data format as HDF5 or cloud data as OGC SWE standard. This whole part is also responsible of the acquisition scenario the local storage management and the network management through SFTP or SOAP for the OGC frame. The data side only need an XML configuration file and if a configuration change occurs in time the system is automatically restarted with the new value. Cloud2IR has been deployed on field since several Monthat the SenseCity outdoor test bed in Marne La Vallée (France)[4]. The next step will be the full standardisation of the system and possibly the full separation between the sensor side and the data side which can be seen at term as an external framework. References: [1] A Crinière, J Dumoulin, L Mevel, G Andrade-Barosso, M Simonin. The Cloud2SM Project.European Geosciences Union General Assembly (EGU2015), Apr 2015, Vienne, Austria. 2015. [2] J Dumoulin, A Criniere, and R Averty. The detection and thermal characterization of the inner structure of the 'musmeci' bridge deck by infrared thermography monitoring. Journal Of Geophysics And Engineering doi:10.1088/1742-2132/10/6/064003, Vol 10, 2013. [3] J Dumoulin, R Averty. Development of an infrared system coupled with a weather station for real time atmospheric corrections using GPU computing: Application to bridge monitoring, in Proc of 11 th International Conference on Quantitative InfraRed Thermography, Naples Italy, 2012. [4] F Derkx, B Lebental, T Bourouina, Frédéric B, C Cojocaru, and al..The Sense-City project.XVIIIth Symposium on Vibrations, Shocks and Noise, Jul 2012, France. 9p, 2012.

Compact Tactile Sensors for Robot Fingers

NASA Technical Reports Server (NTRS)

Martin, Toby B.; Lussy, David; Gaudiano, Frank; Hulse, Aaron; Diftler, Myron A.; Rodriguez, Dagoberto; Bielski, Paul; Butzer, Melisa

2004-01-01

Compact transducer arrays that measure spatial distributions of force or pressure have been demonstrated as prototypes of tactile sensors to be mounted on fingers and palms of dexterous robot hands. The pressure- or force-distribution feedback provided by these sensors is essential for the further development and implementation of robot-control capabilities for humanlike grasping and manipulation.

Robot-Beacon Distributed Range-Only SLAM for Resource-Constrained Operation

PubMed Central

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

2017-01-01

This work deals with robot-sensor network cooperation where sensor nodes (beacons) are used as landmarks for Range-Only (RO) Simultaneous Localization and Mapping (SLAM). Most existing RO-SLAM techniques consider beacons as passive devices disregarding the sensing, computational and communication capabilities with which they are actually endowed. SLAM is a resource-demanding task. Besides the technological constraints of the robot and beacons, many applications impose further resource consumption limitations. This paper presents a scalable distributed RO-SLAM scheme for resource-constrained operation. It is capable of exploiting robot-beacon cooperation in order to improve SLAM accuracy while meeting a given resource consumption bound expressed as the maximum number of measurements that are integrated in SLAM per iteration. The proposed scheme combines a Sparse Extended Information Filter (SEIF) SLAM method, in which each beacon gathers and integrates robot-beacon and inter-beacon measurements, and a distributed information-driven measurement allocation tool that dynamically selects the measurements that are integrated in SLAM, balancing uncertainty improvement and resource consumption. The scheme adopts a robot-beacon distributed approach in which each beacon participates in the selection, gathering and integration in SLAM of robot-beacon and inter-beacon measurements, resulting in significant estimation accuracies, resource-consumption efficiency and scalability. It has been integrated in an octorotor Unmanned Aerial System (UAS) and evaluated in 3D SLAM outdoor experiments. The experimental results obtained show its performance and robustness and evidence its advantages over existing methods. PMID:28425946

Robot-Beacon Distributed Range-Only SLAM for Resource-Constrained Operation.

PubMed

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

2017-04-20

This work deals with robot-sensor network cooperation where sensor nodes (beacons) are used as landmarks for Range-Only (RO) Simultaneous Localization and Mapping (SLAM). Most existing RO-SLAM techniques consider beacons as passive devices disregarding the sensing, computational and communication capabilities with which they are actually endowed. SLAM is a resource-demanding task. Besides the technological constraints of the robot and beacons, many applications impose further resource consumption limitations. This paper presents a scalable distributed RO-SLAM scheme for resource-constrained operation. It is capable of exploiting robot-beacon cooperation in order to improve SLAM accuracy while meeting a given resource consumption bound expressed as the maximum number of measurements that are integrated in SLAM per iteration. The proposed scheme combines a Sparse Extended Information Filter (SEIF) SLAM method, in which each beacon gathers and integrates robot-beacon and inter-beacon measurements, and a distributed information-driven measurement allocation tool that dynamically selects the measurements that are integrated in SLAM, balancing uncertainty improvement and resource consumption. The scheme adopts a robot-beacon distributed approach in which each beacon participates in the selection, gathering and integration in SLAM of robot-beacon and inter-beacon measurements, resulting in significant estimation accuracies, resource-consumption efficiency and scalability. It has been integrated in an octorotor Unmanned Aerial System (UAS) and evaluated in 3D SLAM outdoor experiments. The experimental results obtained show its performance and robustness and evidence its advantages over existing methods.

Energy-efficient sensing in wireless sensor networks using compressed sensing.

PubMed

Razzaque, Mohammad Abdur; Dobson, Simon

2014-02-12

Sensing of the application environment is the main purpose of a wireless sensor network. Most existing energy management strategies and compression techniques assume that the sensing operation consumes significantly less energy than radio transmission and reception. This assumption does not hold in a number of practical applications. Sensing energy consumption in these applications may be comparable to, or even greater than, that of the radio. In this work, we support this claim by a quantitative analysis of the main operational energy costs of popular sensors, radios and sensor motes. In light of the importance of sensing level energy costs, especially for power hungry sensors, we consider compressed sensing and distributed compressed sensing as potential approaches to provide energy efficient sensing in wireless sensor networks. Numerical experiments investigating the effectiveness of compressed sensing and distributed compressed sensing using real datasets show their potential for efficient utilization of sensing and overall energy costs in wireless sensor networks. It is shown that, for some applications, compressed sensing and distributed compressed sensing can provide greater energy efficiency than transform coding and model-based adaptive sensing in wireless sensor networks.

Distributed electrochemical sensors: recent advances and barriers to market adoption.

PubMed

Hoekstra, Rafael; Blondeau, Pascal; Andrade, Francisco J

2018-07-01

Despite predictions of their widespread application in healthcare and environmental monitoring, electrochemical sensors are yet to be distributed at scale, instead remaining largely confined to R&D labs. This contrasts sharply with the situation for physical sensors, which are now ubiquitous and seamlessly embedded in the mature ecosystem provided by electronics and connectivity protocols. Although chemical sensors could be integrated into the same ecosystem, there are fundamental issues with these sensors in the three key areas of analytical performance, usability, and affordability. Nevertheless, advances are being made in each of these fields, leading to hope that the deployment of automated and user-friendly low-cost electrochemical sensors is on the horizon. Here, we present a brief survey of key challenges and advances in the development of distributed electrochemical sensors for liquid samples, geared towards applications in healthcare and wellbeing, environmental monitoring, and homeland security. As will be seen, in many cases the analytical performance of the sensor is acceptable; it is usability that is the major barrier to commercial viability at this moment. Were this to be overcome, the issue of affordability could be addressed. Graphical Abstract ᅟ.

A Modified Distributed Bees Algorithm for Multi-Sensor Task Allocation †

PubMed Central

Nof, Shimon Y.; Edan, Yael

2018-01-01

Multi-sensor systems can play an important role in monitoring tasks and detecting targets. However, real-time allocation of heterogeneous sensors to dynamic targets/tasks that are unknown a priori in their locations and priorities is a challenge. This paper presents a Modified Distributed Bees Algorithm (MDBA) that is developed to allocate stationary heterogeneous sensors to upcoming unknown tasks using a decentralized, swarm intelligence approach to minimize the task detection times. Sensors are allocated to tasks based on sensors’ performance, tasks’ priorities, and the distances of the sensors from the locations where the tasks are being executed. The algorithm was compared to a Distributed Bees Algorithm (DBA), a Bees System, and two common multi-sensor algorithms, market-based and greedy-based algorithms, which were fitted for the specific task. Simulation analyses revealed that MDBA achieved statistically significant improved performance by 7% with respect to DBA as the second-best algorithm, and by 19% with respect to Greedy algorithm, which was the worst, thus indicating its fitness to provide solutions for heterogeneous multi-sensor systems. PMID:29498683

A statistical study of electron butterfly pitch angle distributions using Polar

NASA Astrophysics Data System (ADS)

Fritz, T.; Duguay, R.

As the line of apsides of the orbit of the POLAR spacecraft has precessed, the radial distance at which the orbit of the spacecraft intersects the equatorial plane has steadily increased. Beginning in 1999, the crossing exceeded distances of six Earth radii and a particle distribution exhibiting a deficiency in particles with pitch angles nearly perpendicular to magnetic field lines was frequently observed in the energetic electron measurements made by the POLAR CEPPAD HIST and IES sensors. (Blake, et a , 1995) Such particle distributions, known as "butterfly" distributions,l represent a region in pitch angle space that is shadowed by the magnetopause and can provide information about the location of the magnetopause and its stand off distance. The occurrence of "butterfly" distributions also reflects the configuration and combined influence of the Earth's magnetosphere and the dawn to dusk electric field. In particular, the study observed the occurrence of the minimum at a local pitch angle of 90 degrees for data recorded between the years 1999 and 2001. Information corresponding to the spacecraft entering such regions of particle pitch angle distribution was collected and analyzed. Polar plots of magnetic local time versus radial distance have been generated and are compared to equatorial contours of constant magnetic field, as well as to the theoretical motion of such particles constrained under the 1st adiabatic invariant within realistic magnetic and electric fields. Blake, et al, Space Science Reviews 71: 531-562, 1995

Distributed dual-parameter optical fiber sensor based on cascaded microfiber Fabry-Pérot interferometers

NASA Astrophysics Data System (ADS)

Xiang, Yang; Luo, Yiyang; Zhang, Wei; Liu, Deming; Sun, Qizhen

2017-04-01

We propose and demonstrate a distributed fiber sensor based on cascaded microfiber Fabry-Perot interferometers (MFPI) for simultaneous refractive index (SRI) and temperature measurement. By employing MFPI which is fabricated by taper-drawing the center of a uniform fiber Bragg grating (FBG) on standard fiber into a section of microfiber, dual parameters including SRI and temperature can be detected through demodulating the reflection spectrum of the MFPI. Further, wavelength-division-multiplexing (WDM) is applied to realize distributed dual-parameter fiber sensor by using cascaded MFPIs with different Bragg wavelengths. A prototype sensor system with 5 cascaded MFPIs is constructed to experimentally demonstrate the sensing performance.

High performance architecture design for large scale fibre-optic sensor arrays using distributed EDFAs and hybrid TDM/DWDM

NASA Astrophysics Data System (ADS)

Liao, Yi; Austin, Ed; Nash, Philip J.; Kingsley, Stuart A.; Richardson, David J.

2013-09-01

A distributed amplified dense wavelength division multiplexing (DWDM) array architecture is presented for interferometric fibre-optic sensor array systems. This architecture employs a distributed erbium-doped fibre amplifier (EDFA) scheme to decrease the array insertion loss, and employs time division multiplexing (TDM) at each wavelength to increase the number of sensors that can be supported. The first experimental demonstration of this system is reported including results which show the potential for multiplexing and interrogating up to 4096 sensors using a single telemetry fibre pair with good system performance. The number can be increased to 8192 by using dual pump sources.

Low Noise Infrasonic Sensor System with High Reduction of Natural Background Noise

DTIC Science & Technology

2006-05-01

local processing allows a variety of options both in the array geometry and signal processing. A generic geometry is indicated in Figure 2. Geometric...higher frequency sound detected . Table 1 provides a comparison of piezocable and microbarograph based arrays . Piezocable Sensor Local Signal ...aliasing associated with the current infrasound sensors used at large spacing in the present designs of infrasound monitoring arrays , particularly in the

Design and performance investigation of a highly accurate apodized fiber Bragg grating-based strain sensor in single and quasi-distributed systems.

PubMed

Ali, Taha A; Shehata, Mohamed I; Mohamed, Nazmi A

2015-06-01

In this work, fiber Bragg grating (FBG) strain sensors in single and quasi-distributed systems are investigated, seeking high-accuracy measurement. Since FBG-based strain sensors of small lengths are preferred in medical applications, and that causes the full width at half-maximum (FWHM) to be larger, a new apodization profile is introduced for the first time, to the best of our knowledge, with a remarkable FWHM at small sensor lengths compared to the Gaussian and Nuttall profiles, in addition to a higher mainlobe slope at these lengths. A careful selection of apodization profiles with detailed investigation is performed-using sidelobe analysis and the FWHM, which are primary judgment factors especially in a quasi-distributed configuration. A comparison between the elite selection of apodization profiles (extracted from related literature) and the proposed new profile is carried out covering the reflectivity peak, FWHM, and sidelobe analysis. The optimization process concludes that the proposed new profile with a chosen small length (L) of 10 mm and Δn_ac of 1.4×10^-4 is the optimum choice for single stage and quasi-distributed strain-sensor networks, even better than the Gaussian profile at small sensor lengths. The proposed profile achieves the smallest FWHM of 15 GHz (suitable for UDWDM), and the highest mainlobe slope of 130 dB/nm. For the quasi-distributed scenario, a noteworthy high isolation of 6.953 dB is achieved while applying a high strain value of 1500 μstrain (με) for a five-stage strain-sensing network. Further investigation was undertaken, proving that consistency in choosing the apodization profile in the quasi-distributed network is mandatory. A test was made of the inclusion of a uniform apodized sensor among other apodized sensors with the proposed profile in an FBG strain-sensor network.

Experiment on a feedback control of nonlinear thermocapillary convection in a half-zone liquid bridge

NASA Astrophysics Data System (ADS)

Kudo, M.; Ueno, I.; Shiomi, J.; Amberg, G.; Kawamura, H.

Under microgravity condition, themocapillarity dominates in material processing. In a half-zone method, two co-axial cylindrical rods hold a liquid bridge by the surface tension. By adding a temperature difference Δ T between the rods, thermocapillary flow is induced in the bridge. The convection changes from two-dimensional steady flow to three-dimensional oscillatory one at a critical Δ T in the case of medium to high Prandtl number (Pr) fluid. In our latest study (Shiomi et al., JFM, 2003), complete damping of the temperature oscillation was not achieved at highly nonlinear regions by a simple cancellation scheme. The excitation of unexpected other azimuthal wave numbers prevented the suppression of the oscillation. The present study aimed to develop a new control scheme with taking into account of spatio-temporal azimuthal temperature distribution. The target geometry was a liquid bridge of 5 mm in diameter and of a unit aspect ratio, Γ g(g= H/R=1, where H and R are the height and the radius of the bridge, respectively). At this aspect ratio, a dominant azimuthal mode was wave number of 2 when the control was absent. Silicone oil of 5 cSt (Pr = 68 at 25C) was employed as a test fluid. The flow field was visualized by suspending polystyrene sphere particles (D =17μ m). The present experiments were performed with 4 sensors located at different azimuthal positions for the evaluation of the azimuthal surface temperature distribution as well as with 2 heaters to suppress its non-uniform distribution. All sensors and heaters were located at the mid-height of the bridge. The present algorithm involved two main features; the first one was the time-dependent estimation of the azimuthal surface temperature distribution at the height of the sensors and heaters. Evaluation of the azimuthal temperature distribution enabled us to cancel the temperature oscillation by local heating effectively. The second one was the time-dependent evaluation of a frequency of the dominant mode number. This scheme enabled us to predict the azimuthal temperature distribution properly. The control was applied to a highly nonlinear flow that exhibited a traveling-wave type oscillatory flow (traveling flow) in the absence of the control. Under the control, the amplitude of temperature measured by each sensor attenuated significantly. The flow visualization exhibited a gradual change of the flow structure from the traveling down to the standing flow with less nonlinearity. We realized the reduction of the amplitude less than half of the initial value without amplifying other azimuthal-wave-number oscillations.

Spatial Signal Characteristics of Shallow Paraboloidal Shell Structronic Systems

NASA Astrophysics Data System (ADS)

Yue, H. H.; Deng, Z. Q.; Tzou, H. S.

Based on the smart material and structronics technology, distributed sensor and control of shell structures have been rapidly developed for the last twenty years. This emerging technology has been utilized in aerospace, telecommunication, micro-electromechanical systems and other engineering applications. However, distributed monitoring technique and its resulting global spatially distributed sensing signals of thin flexible membrane shells are not clearly understood. In this paper, modeling of free thin paraboloidal shell with spatially distributed sensor, micro-sensing signal characteristics, and location of distributed piezoelectric sensor patches are investigated based on a new set of assumed mode shape functions. Parametric analysis indicates that the signal generation depends on modal membrane strains in the meridional and circumferential directions in which the latter is more significant than the former, when all bending strains vanish in membrane shells. This study provides a modeling and analysis technique for distributed sensors laminated on lightweight paraboloidal flexible structures and identifies critical components and regions that generate significant signals.

Discrete shaped strain sensors for intelligent structures

NASA Technical Reports Server (NTRS)

Andersson, Mark S.; Crawley, Edward F.

1992-01-01

Design of discrete, highly distributed sensor systems for intelligent structures has been studied. Data obtained indicate that discrete strain-averaging sensors satisfy the functional requirements for distributed sensing of intelligent structures. Bartlett and Gauss-Hanning sensors, in particular, provide good wavenumber characteristics while meeting the functional requirements. They are characterized by good rolloff rates and positive Fourier transforms for all wavenumbers. For the numerical integration schemes, Simpson's rule is considered to be very simple to implement and consistently provides accurate results for five sensors or more. It is shown that a sensor system that satisfies the functional requirements can be applied to a structure that supports mode shapes with purely sinusoidal curvature.

Distributed k-Means Algorithm and Fuzzy c-Means Algorithm for Sensor Networks Based on Multiagent Consensus Theory.

PubMed

Qin, Jiahu; Fu, Weiming; Gao, Huijun; Zheng, Wei Xing

2016-03-03

This paper is concerned with developing a distributed k-means algorithm and a distributed fuzzy c-means algorithm for wireless sensor networks (WSNs) where each node is equipped with sensors. The underlying topology of the WSN is supposed to be strongly connected. The consensus algorithm in multiagent consensus theory is utilized to exchange the measurement information of the sensors in WSN. To obtain a faster convergence speed as well as a higher possibility of having the global optimum, a distributed k-means++ algorithm is first proposed to find the initial centroids before executing the distributed k-means algorithm and the distributed fuzzy c-means algorithm. The proposed distributed k-means algorithm is capable of partitioning the data observed by the nodes into measure-dependent groups which have small in-group and large out-group distances, while the proposed distributed fuzzy c-means algorithm is capable of partitioning the data observed by the nodes into different measure-dependent groups with degrees of membership values ranging from 0 to 1. Simulation results show that the proposed distributed algorithms can achieve almost the same results as that given by the centralized clustering algorithms.

A Localized Surface Plasmon Resonance Sensor Using Double-Metal-Complex Nanostructures and a Review of Recent Approaches

PubMed Central

Ahn, Heesang; Song, Hyerin; Kim, Kyujung

2017-01-01

From active developments and applications of various devices to acquire outside and inside information and to operate based on feedback from that information, the sensor market is growing rapidly. In accordance to this trend, the surface plasmon resonance (SPR) sensor, an optical sensor, has been actively developed for high-sensitivity real-time detection. In this study, the fundamentals of SPR sensors and recent approaches for enhancing sensing performance are reported. In the section on the fundamentals of SPR sensors, a brief description of surface plasmon phenomena, SPR, SPR-based sensing applications, and several configuration types of SPR sensors are introduced. In addition, advanced nanotechnology- and nanofabrication-based techniques for improving the sensing performance of SPR sensors are proposed: (1) localized SPR (LSPR) using nanostructures or nanoparticles; (2) long-range SPR (LRSPR); and (3) double-metal-layer SPR sensors for additional performance improvements. Consequently, a high-sensitivity, high-biocompatibility SPR sensor method is suggested. Moreover, we briefly describe issues (miniaturization and communication technology integration) for future SPR sensors. PMID:29301238

Dominance of debonding defect of CFST on PZT sensor response considering the meso-scale structure of concrete with multi-scale simulation

NASA Astrophysics Data System (ADS)

Xu, Bin; Chen, Hongbing; Mo, Y.-L.; Zhou, Tianmin

2018-07-01

Piezoelectric-lead-zirconate-titanate(PZT)-based interface debonding defects detection for concrete filled steel tubulars (CFSTs) has been proposed and validated through experiments, and numerical study on its mechanism has been carried out recently by assuming that concrete material is homogenous. However, concrete is composed of coarse and fine aggregates, mortar and interface transition zones (ITZs) and even initial defects and is a typical nonhomogeneous material and its mesoscale structure might affect the wave propagation in the concrete core of CFST members. Therefore, it is significantly important to further investigate the influence of mesoscale structure of concrete on the stress wave propagation and the response of embedded PZT sensor for the interface debonding detection. In this study, multi-physical numerical simulation on the wave propagation and embedded PZT sensor response of rectangular CFST members with numerical concrete core considering the randomness in circular aggregate distribution, and coupled with surface-mounted PZT actuator and embedded PZT sensor is carried out. The effect of randomness in the circular aggregates distribution and the existence of ITZs are discussed. Both a local stress wave propagation behavior including transmission, reflection, and diffraction at the interface between concrete core and steel tube under a pulse signal excitation and a global wave field in the cross-section of the rectangular CFST models without and with interface debonding defects under sweep frequency excitation are simulated. The sensitivity of an evaluation index based on wavelet packet analysis on the embedded PZT sensor response on the variation of mesoscale parameters of concrete core without and with different interface debonding defects under sweep frequency voltage signal is investigated in details. The results show that the effect of the interface debondings on the embedded PZT measurement is dominant when compared to the meso-scale structures of concrete core. This study verified the feasibility of the PZT based debonding detection for rectangular CFST members even the meso-scale structure of concrete core is considered.

Laser-based sensors on UAVs for quantifying local emissions of greenhouse gases

NASA Astrophysics Data System (ADS)

Zondlo, Mark; Tao, Lei; O'Brien, Anthony; Ross, Kevin; Khan, Amir; Pan, Da; Golston, Levi; Sun, Kang; DiGangi, Josh

2015-04-01

Small unmanned aerial systems (UAS) provide an ideal platform to sample both locally near an emission source as well as within the atmospheric boundary layer. However, small UAS (those with wingspans or rotors on the order of a meter) place severe constraints on sensor size (~ liter volume), mass (~ kg), and power (10s W). Laser-based sensors employing absorption techniques are ideally suited for such platforms due to their high sensitivity, high selectivity, and compact footprint. We have developed and flown compact sensors for water vapor, carbon dioxide and methane using new advances in open-path, laser-based spectroscopy on a variety of platforms ranging from remote control helicopters to long-duration UAS. Open-path spectroscopy allows for high frequency sampling (10-25 Hz) while avoiding the size/mass/power of sample delays, inlet lines, and pumps. To address the challenges of in-flight stability in changing environmental conditions and any associated flight artifacts on the measurement itself (e.g. vibrations), we use an in-line reference cell at a reduced pressure (10 hPa) to account for systematic drift continuously while in flight. Wavelength modulation spectroscopy is used at different harmonics to isolate the narrow linewidth of the in-line reference signal from the ambient, pressure-broadened absorption lineshape of the trace gas of interest. As a result, a metric of in-flight performance is achieved in real-time on the same optical pathlength as the ambient signal. To demonstrate the great potential of laser-based sensors on UAS, we deployed a 1.65 micron-based methane sensor (4 kg, 50 W, 100 ppbv precision at 10 Hz) on a UT-Dallas remote control aircraft for two weeks around gas/oil extraction activities as part of the EDF Barnett Coordinated Campaign in October 2013. We conducted thirty-four flights around a compressor station to examine the spatial and temporal characteristics of its emissions. Leaks of methane were typically lofted to altitudes well above the surface (up to 100 m). In addition, plumes were very narrow horizontally (10-30 m width) within 200 m of the emission origin. By using a mass balance approach of upwind versus downwind CH4 concentrations, coupled to meteorological wind data, the CH4 emission rate from the compressor station averaged 13 ± 5 g CH4 s-1, consistent with individual, leak surveys measured within the compressor station itself. More recently, we developed a mid-infrared version of the same sensor using an antimonide laser at 3.3 microns. This sensor has a precision of 2 ppbv CH4 at 10 Hz, a mass of 1.3 kg, and consumes 10 W of power. Flight tests show the improved precision is capable of detecting methane leaks from landfills and cattle feedlots at higher altitudes (500 m) and greater distances downwind (several km) than the near infrared CH4 sensor. Sampling strategy is particularly important for not only UAS-based flight patterns but also sensor design. Many tradeoffs exist between the sampling density of the flight pattern, sensor precision, accuracy of wind data, and geographic isolation of the source of interest, and these will be discussed in the context of airborne-based CH4 measurements in the field. The development of compact yet robust trace gas sensors to be deployed on small UAS opens new capabilities for atmospheric sensing such as quantifying local source emissions (e.g. farms, well pads), vertical profiling of trace gases in a forest canopy, and trace gas distributions in complex areas (mountains, urban canyons).

Epidermis Microstructure Inspired Graphene Pressure Sensor with Random Distributed Spinosum for High Sensitivity and Large Linearity.

PubMed

Pang, Yu; Zhang, Kunning; Yang, Zhen; Jiang, Song; Ju, Zhenyi; Li, Yuxing; Wang, Xuefeng; Wang, Danyang; Jian, Muqiang; Zhang, Yingying; Liang, Renrong; Tian, He; Yang, Yi; Ren, Tian-Ling

2018-03-27

Recently, wearable pressure sensors have attracted tremendous attention because of their potential applications in monitoring physiological signals for human healthcare. Sensitivity and linearity are the two most essential parameters for pressure sensors. Although various designed micro/nanostructure morphologies have been introduced, the trade-off between sensitivity and linearity has not been well balanced. Human skin, which contains force receptors in a reticular layer, has a high sensitivity even for large external stimuli. Herein, inspired by the skin epidermis with high-performance force sensing, we have proposed a special surface morphology with spinosum microstructure of random distribution via the combination of an abrasive paper template and reduced graphene oxide. The sensitivity of the graphene pressure sensor with random distribution spinosum (RDS) microstructure is as high as 25.1 kPa -1 in a wide linearity range of 0-2.6 kPa. Our pressure sensor exhibits superior comprehensive properties compared with previous surface-modified pressure sensors. According to simulation and mechanism analyses, the spinosum microstructure and random distribution contribute to the high sensitivity and large linearity range, respectively. In addition, the pressure sensor shows promising potential in detecting human physiological signals, such as heartbeat, respiration, phonation, and human motions of a pushup, arm bending, and walking. The wearable pressure sensor array was further used to detect gait states of supination, neutral, and pronation. The RDS microstructure provides an alternative strategy to improve the performance of pressure sensors and extend their potential applications in monitoring human activities.

Resilient distributed control in the presence of misbehaving agents in networked control systems.

PubMed

Zeng, Wente; Chow, Mo-Yuen

2014-11-01

In this paper, we study the problem of reaching a consensus among all the agents in the networked control systems (NCS) in the presence of misbehaving agents. A reputation-based resilient distributed control algorithm is first proposed for the leader-follower consensus network. The proposed algorithm embeds a resilience mechanism that includes four phases (detection, mitigation, identification, and update), into the control process in a distributed manner. At each phase, every agent only uses local and one-hop neighbors' information to identify and isolate the misbehaving agents, and even compensate their effect on the system. We then extend the proposed algorithm to the leaderless consensus network by introducing and adding two recovery schemes (rollback and excitation recovery) into the current framework to guarantee the accurate convergence of the well-behaving agents in NCS. The effectiveness of the proposed method is demonstrated through case studies in multirobot formation control and wireless sensor networks.

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

EEG source localization: Sensor density and head surface coverage.

PubMed

Song, Jasmine; Davey, Colin; Poulsen, Catherine; Luu, Phan; Turovets, Sergei; Anderson, Erik; Li, Kai; Tucker, Don

2015-12-30

The accuracy of EEG source localization depends on a sufficient sampling of the surface potential field, an accurate conducting volume estimation (head model), and a suitable and well-understood inverse technique. The goal of the present study is to examine the effect of sampling density and coverage on the ability to accurately localize sources, using common linear inverse weight techniques, at different depths. Several inverse methods are examined, using the popular head conductivity. Simulation studies were employed to examine the effect of spatial sampling of the potential field at the head surface, in terms of sensor density and coverage of the inferior and superior head regions. In addition, the effects of sensor density and coverage are investigated in the source localization of epileptiform EEG. Greater sensor density improves source localization accuracy. Moreover, across all sampling density and inverse methods, adding samples on the inferior surface improves the accuracy of source estimates at all depths. More accurate source localization of EEG data can be achieved with high spatial sampling of the head surface electrodes. The most accurate source localization is obtained when the voltage surface is densely sampled over both the superior and inferior surfaces. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

On Prolonging Network Lifetime through Load-Similar Node Deployment in Wireless Sensor Networks

PubMed Central

Li, Qiao-Qin; Gong, Haigang; Liu, Ming; Yang, Mei; Zheng, Jun

2011-01-01

This paper is focused on the study of the energy hole problem in the Progressive Multi-hop Rotational Clustered (PMRC)-structure, a highly scalable wireless sensor network (WSN) architecture. Based on an analysis on the traffic load distribution in PMRC-based WSNs, we propose a novel load-similar node distribution strategy combined with the Minimum Overlapping Layers (MOL) scheme to address the energy hole problem in PMRC-based WSNs. In this strategy, sensor nodes are deployed in the network area according to the load distribution. That is, more nodes shall be deployed in the range where the average load is higher, and then the loads among different areas in the sensor network tend to be balanced. Simulation results demonstrate that the load-similar node distribution strategy prolongs network lifetime and reduces the average packet latency in comparison with existing nonuniform node distribution and uniform node distribution strategies. Note that, besides the PMRC structure, the analysis model and the proposed load-similar node distribution strategy are also applicable to other multi-hop WSN structures. PMID:22163809

Quantitative modeling of coupled piezo-elastodynamic behavior of piezoelectric actuators bonded to an elastic medium for structural health monitoring: a review.

PubMed

Huang, Guoliang; Song, Fei; Wang, Xiaodong

2010-01-01

Elastic waves, especially guided waves, generated by a piezoelectric actuator/sensor network, have shown great potential for on-line health monitoring of advanced aerospace, nuclear, and automotive structures in recent decades. Piezoelectric materials can function as both actuators and sensors in these applications due to wide bandwidth, quick response and low costs. One of the most fundamental issues surrounding the effective use of piezoelectric actuators is the quantitative evaluation of the resulting elastic wave propagation by considering the coupled piezo-elastodynamic behavior between the actuator and the host medium. Accurate characterization of the local interfacial stress distribution between the actuator and the host medium is the key issue for the problem. This paper presents a review of the development of analytical, numerical and hybrid approaches for modeling of the coupled piezo-elastodynamic behavior. The resulting elastic wave propagation for structural health monitoring is also summarized.

Prototyping a Hybrid Cooperative and Tele-robotic Surgical System for Retinal Microsurgery.

PubMed

Balicki, Marcin; Xia, Tian; Jung, Min Yang; Deguet, Anton; Vagvolgyi, Balazs; Kazanzides, Peter; Taylor, Russell

2011-06-01

This paper presents the design of a tele-robotic microsurgical platform designed for development of cooperative and tele-operative control schemes, sensor based smart instruments, user interfaces and new surgical techniques with eye surgery as the driving application. The system is built using the distributed component-based cisst libraries and the Surgical Assistant Workstation framework. It includes a cooperatively controlled EyeRobot2, a da Vinci Master manipulator, and a remote stereo visualization system. We use constrained optimization based virtual fixture control to provide Virtual Remote-Center-of-Motion (vRCM) and haptic feedback. Such system can be used in a hybrid setup, combining local cooperative control with remote tele-operation, where an experienced surgeon can provide hand-over-hand tutoring to a novice user. In another scheme, the system can provide haptic feedback based on virtual fixtures constructed from real-time force and proximity sensor information.

Prototyping a Hybrid Cooperative and Tele-robotic Surgical System for Retinal Microsurgery

PubMed Central

Balicki, Marcin; Xia, Tian; Jung, Min Yang; Deguet, Anton; Vagvolgyi, Balazs; Kazanzides, Peter; Taylor, Russell

2013-01-01

This paper presents the design of a tele-robotic microsurgical platform designed for development of cooperative and tele-operative control schemes, sensor based smart instruments, user interfaces and new surgical techniques with eye surgery as the driving application. The system is built using the distributed component-based cisst libraries and the Surgical Assistant Workstation framework. It includes a cooperatively controlled EyeRobot2, a da Vinci Master manipulator, and a remote stereo visualization system. We use constrained optimization based virtual fixture control to provide Virtual Remote-Center-of-Motion (vRCM) and haptic feedback. Such system can be used in a hybrid setup, combining local cooperative control with remote tele-operation, where an experienced surgeon can provide hand-over-hand tutoring to a novice user. In another scheme, the system can provide haptic feedback based on virtual fixtures constructed from real-time force and proximity sensor information. PMID:24398557

Single-ion microwave near-field quantum sensor

NASA Astrophysics Data System (ADS)

Wahnschaffe, M.; Hahn, H.; Zarantonello, G.; Dubielzig, T.; Grondkowski, S.; Bautista-Salvador, A.; Kohnen, M.; Ospelkaus, C.

2017-01-01

We develop an intuitive model of 2D microwave near-fields in the unusual regime of centimeter waves localized to tens of microns. Close to an intensity minimum, a simple effective description emerges with five parameters that characterize the strength and spatial orientation of the zero and first order terms of the near-field, as well as the field polarization. Such a field configuration is realized in a microfabricated planar structure with an integrated microwave conductor operating near 1 GHz. We use a single 9 Be+ ion as a high-resolution quantum sensor to measure the field distribution through energy shifts in its hyperfine structure. We find agreement with simulations at the sub-micron and few-degree level. Our findings give a clear and general picture of the basic properties of oscillatory 2D near-fields with applications in quantum information processing, neutral atom trapping and manipulation, chip-scale atomic clocks, and integrated microwave circuits.

Smart Building: Decision Making Architecture for Thermal Energy Management.

PubMed

Uribe, Oscar Hernández; Martin, Juan Pablo San; Garcia-Alegre, María C; Santos, Matilde; Guinea, Domingo

2015-10-30

Smart applications of the Internet of Things are improving the performance of buildings, reducing energy demand. Local and smart networks, soft computing methodologies, machine intelligence algorithms and pervasive sensors are some of the basics of energy optimization strategies developed for the benefit of environmental sustainability and user comfort. This work presents a distributed sensor-processor-communication decision-making architecture to improve the acquisition, storage and transfer of thermal energy in buildings. The developed system is implemented in a near Zero-Energy Building (nZEB) prototype equipped with a built-in thermal solar collector, where optical properties are analysed; a low enthalpy geothermal accumulation system, segmented in different temperature zones; and an envelope that includes a dynamic thermal barrier. An intelligent control of this dynamic thermal barrier is applied to reduce the thermal energy demand (heating and cooling) caused by daily and seasonal weather variations. Simulations and experimental results are presented to highlight the nZEB thermal energy reduction.

H2O frost point detection on Mars

NASA Technical Reports Server (NTRS)

Ryan, J. A.; Sharman, R. D.

1981-01-01

The Viking Mars landers contain meteorological instrumentation to measure wind, temperature, and pressure but not atmospheric water content. The landings occurred during local summer, and it was observed that the nocturnal temperature decrease at sensor height (1.6 m) did not exhibit a uniform behavior at either site. It was expected that the rate of decrease would gradually slow, leveling off near sunrise. Instead, a leveling occurred several hours earlier. Temperature subsequently began a more rapid decrease which slowed by sunrise. This suggested that the temperature sensors may be detecting the frost point of water vapor. Analysis of alternative hypotheses demonstrates that none of these are viable candidates. The frost point interpretation is consistent with other lander and orbiter observations, with terrestrial experience, and with modeling of Mars' atmospheric behavior. It thus appears that the meteorology experiment can help provide a basis toward understanding the distribution and dynamics of Martian water vapor.

A Research Program in Computer Technology. Volume 1

DTIC Science & Technology

1981-08-01

rigidity, sensor networks 10. command and control, digital voice communication, graphic input device for terminal, multimedia communications, portable...satellite channel in the internetwork environment; Distributed Sensor Networks - formulation of algorithms and communication protocols to support the...operation of geographically distributed sensors ; Personal Communicator - work intended to result in a demonstration-level portable terminal to test and

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.

Specifically and wash-free labeling of SNAP-tag fused proteins with a hybrid sensor to monitor local micro-viscosity.

PubMed

Wang, Chao; Song, Xinbo; Chen, Lingcheng; Xiao, Yi

2017-05-15

Viscosity, as one of the major factors of intracellular microenvironment, influences the function of proteins. To detect local micro-viscosity of a protein, it is a precondition to apply a viscosity sensor for specifically target to proteins. However, all the reported small-molecule probes are just suitable for sensing/imaging of macro-viscosity in biological fluids of entire cells or organelles. To this end, we developed a hybrid sensor BDP-V BG by connecting a viscosity-sensitive boron-dipyrromethene (BODIPY) molecular rotor (BDP-V) to O 6 -benzylguanine (BG) for specific detection of local micro-viscosity of SNAP-tag fused proteins. We measured and calculated the reaction efficiency between the sensor and SNAP-tag protein in vitro to confirm the high labeling specificity. We also found that the labeling reaction results in a 53-fold fluorescence enhancement for the rotor, which qualifies it as a wash-free sensor with ignorable background fluorescence. The high sensitivity of protein labeled sensor (BDP-V-SNAP) to the changes of local viscosity was evaluated by detecting the enhancement of fluorescence lifetimes. Further, with the sensor BDP-V BG, we achieved high specific labeling of cells expressing two SNAP-tag fused proteins (nuclear histone H2B and mitochondrial COX8A). Two-photon excited fluorescence lifetime imaging revealed that, the micro-viscosities nearby the SNAP-tag fused two proteins are distinct. The different changes of local micro-viscosity of SNAP-tag fused histone protein in apoptosis induced by three nucleus-targeted drugs were also characterized for the first time. Copyright © 2016 Elsevier B.V. All rights reserved.

A Mobile Anchor Assisted Localization Algorithm Based on Regular Hexagon in Wireless Sensor Networks

PubMed Central

Rodrigues, Joel J. P. C.

2014-01-01

Localization is one of the key technologies in wireless sensor networks (WSNs), since it provides fundamental support for many location-aware protocols and applications. Constraints of cost and power consumption make it infeasible to equip each sensor node in the network with a global position system (GPS) unit, especially for large-scale WSNs. A promising method to localize unknown nodes is to use several mobile anchors which are equipped with GPS units moving among unknown nodes and periodically broadcasting their current locations to help nearby unknown nodes with localization. This paper proposes a mobile anchor assisted localization algorithm based on regular hexagon (MAALRH) in two-dimensional WSNs, which can cover the whole monitoring area with a boundary compensation method. Unknown nodes calculate their positions by using trilateration. We compare the MAALRH with HILBERT, CIRCLES, and S-CURVES algorithms in terms of localization ratio, localization accuracy, and path length. Simulations show that the MAALRH can achieve high localization ratio and localization accuracy when the communication range is not smaller than the trajectory resolution. PMID:25133212

An Amplitude-Based Estimation Method for International Space Station (ISS) Leak Detection and Localization Using Acoustic Sensor Networks

NASA Technical Reports Server (NTRS)

Tian, Jialin; Madaras, Eric I.

2009-01-01

The development of a robust and efficient leak detection and localization system within a space station environment presents a unique challenge. A plausible approach includes the implementation of an acoustic sensor network system that can successfully detect the presence of a leak and determine the location of the leak source. Traditional acoustic detection and localization schemes rely on the phase and amplitude information collected by the sensor array system. Furthermore, the acoustic source signals are assumed to be airborne and far-field. Likewise, there are similar applications in sonar. In solids, there are specialized methods for locating events that are used in geology and in acoustic emission testing that involve sensor arrays and depend on a discernable phase front to the received signal. These methods are ineffective if applied to a sensor detection system within the space station environment. In the case of acoustic signal location, there are significant baffling and structural impediments to the sound path and the source could be in the near-field of a sensor in this particular setting.

Localization and Mapping Using Only a Rotating FMCW Radar Sensor

PubMed Central

Vivet, Damien; Checchin, Paul; Chapuis, Roland

2013-01-01

Rotating radar sensors are perception systems rarely used in mobile robotics. This paper is concerned with the use of a mobile ground-based panoramic radar sensor which is able to deliver both distance and velocity of multiple targets in its surrounding. The consequence of using such a sensor in high speed robotics is the appearance of both geometric and Doppler velocity distortions in the collected data. These effects are, in the majority of studies, ignored or considered as noise and then corrected based on proprioceptive sensors or localization systems. Our purpose is to study and use data distortion and Doppler effect as sources of information in order to estimate the vehicle's displacement. The linear and angular velocities of the mobile robot are estimated by analyzing the distortion of the measurements provided by the panoramic Frequency Modulated Continuous Wave (FMCW) radar, called IMPALA. Without the use of any proprioceptive sensor, these estimates are then used to build the trajectory of the vehicle and the radar map of outdoor environments. In this paper, radar-only localization and mapping results are presented for a ground vehicle moving at high speed. PMID:23567523

Localization and mapping using only a rotating FMCW radar sensor.

PubMed

Vivet, Damien; Checchin, Paul; Chapuis, Roland

2013-04-08

Rotating radar sensors are perception systems rarely used in mobile robotics. This paper is concerned with the use of a mobile ground-based panoramic radar sensor which is able to deliver both distance and velocity of multiple targets in its surrounding. The consequence of using such a sensor in high speed robotics is the appearance of both geometric and Doppler velocity distortions in the collected data. These effects are, in the majority of studies, ignored or considered as noise and then corrected based on proprioceptive sensors or localization systems. Our purpose is to study and use data distortion and Doppler effect as sources of information in order to estimate the vehicle's displacement. The linear and angular velocities of the mobile robot are estimated by analyzing the distortion of the measurements provided by the panoramic Frequency Modulated Continuous Wave (FMCW) radar, called IMPALA. Without the use of any proprioceptive sensor, these estimates are then used to build the trajectory of the vehicle and the radar map of outdoor environments. In this paper, radar-only localization and mapping results are presented for a ground vehicle moving at high speed.

Local Positioning System Using Flickering Infrared LEDs

PubMed Central

Raharijaona, Thibaut; Mawonou, Rodolphe; Nguyen, Thanh Vu; Colonnier, Fabien; Boyron, Marc; Diperi, Julien; Viollet, Stéphane

2017-01-01

A minimalistic optical sensing device for the indoor localization is proposed to estimate the relative position between the sensor and active markers using amplitude modulated infrared light. The innovative insect-based sensor can measure azimuth and elevation angles with respect to two small and cheap active infrared light emitting diodes (LEDs) flickering at two different frequencies. In comparison to a previous lensless visual sensor that we proposed for proximal localization (less than 30 cm), we implemented: (i) a minimalistic sensor in terms of small size (10 cm3), light weight (6 g) and low power consumption (0.4 W); (ii) an Arduino-compatible demodulator for fast analog signal processing requiring low computational resources; and (iii) an indoor positioning system for a mobile robotic application. Our results confirmed that the proposed sensor was able to estimate the position at a distance of 2 m with an accuracy as small as 2-cm at a sampling frequency of 100 Hz. Our sensor can be also suitable to be implemented in a position feedback loop for indoor robotic applications in GPS-denied environment. PMID:29099743

A Parameter Communication Optimization Strategy for Distributed Machine Learning in Sensors

PubMed Central

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

2017-01-01

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

Microfluidic Surface Plasmon Resonance Sensors: From Principles to Point-of-Care Applications

PubMed Central

Wang, Da-Shin; Fan, Shih-Kang

2016-01-01

Surface plasmon resonance (SPR) is a label-free, highly-sensitive, and real-time sensing technique. Conventional SPR sensors, which involve a planar thin gold film, have been widely exploited in biosensing; various miniaturized formats have been devised for portability purposes. Another type of SPR sensor which utilizes localized SPR (LSPR), is based on metal nanostructures with surface plasmon modes at the structural interface. The resonance condition is sensitive to the refractive index change of the local medium. The principles of these two types of SPR sensors are reviewed and their integration with microfluidic platforms is described. Further applications of microfluidic SPR sensors to point-of-care (POC) diagnostics are discussed. PMID:27472340

Decentralized control experiments on NASA's flexible grid

NASA Technical Reports Server (NTRS)

Ozguner, U.; Yurkowich, S.; Martin, J., III; Al-Abbass, F.

1986-01-01

Methods arising from the area of decentralized control are emerging for analysis and control synthesis for large flexible structures. In this paper the control strategy involves a decentralized model reference adaptive approach using a variable structure control. Local models are formulated based on desired damping and response time in a model-following scheme for various modal configurations. Variable structure controllers are then designed employing co-located angular rate and position feedback. In this scheme local control forces the system to move on a local sliding mode in some local error space. An important feature of this approach is that the local subsystem is made insensitive to dynamical interactions with other subsystems once the sliding surface is reached. Experiments based on the above have been performed for NASA's flexible grid experimental apparatus. The grid is designed to admit appreciable low-frequency structural dynamics, and allows for implementation of distributed computing components, inertial sensors, and actuation devices. A finite-element analysis of the grid provides the model for control system design and simulation; results of several simulations are reported on here, and a discussion of application experiments on the apparatus is presented.

Distributed Underwater Sensing: A Paradigm Change for the Future

NASA Astrophysics Data System (ADS)

Yang, T. C.

Distributed netted underwater sensors (DNUS) present a paradigm change that has generated high interest all over the world. It utilizes many small spatially distributed, inexpensive sensors, and a certain number of mobile nodes, such as autonomous underwater vehicles (AUVs), forming a wireless acoustic network to relate data and provide real time monitoring of the ocean. Distributed underwater sensors can be used for oceanographic data collection, pollution monitoring, offshore exploration, disaster prevention, assisted navigation and tactical surveillance applications over wide areas. These functions were traditionally accomplished by a cabled system, such as an array of sensors deployed from a platform, or a large number of sensors moored on the ocean bottom, connected by a cable. The cabled systems are not only expensive but often require heavy ocean engineering (e.g., equipment to deploy heavy armored cables). In the future, as fabrication technology advances making low cost sensors a reality, DNUS is expected to be affordable and will become the undersea "OceanNet" for the marine industry like the current "internet" on land. This paper gives a layman view of the system concept, the state of the art, and future challenges. One of challenges, of particular interest to this conference, is to develop technologies for miniature-size sensors that are energy efficient, allowing long time deployment in the ocean.

VLF Source Localization with a Freely Drifting Sensor Array

DTIC Science & Technology

1992-09-01

Simultaneous Measurement of Infra - sonic Acoustic Particle Velocity and Acoustic Pressure in the Ocean by F-ely Drifting Swallow Floats," IEEEJ. Ocean. Eng., vol...Pacific. Marine Physical Laboratory’s set of nine freely drifting, infrasonic sensors, capable of recording ocean ambient noise in the 1- to 25-Hz range...Terms. 15. Number of Pages, Swallow float, matched-field processing, infrasonic sensor, vlf source localization 153 16. Price Code. 17. Seorlity

Summary of the First Network-Centric Sensing Community Workshop, ’Netted Sensors: A Government, Industry and Academia Dialogue’

DTIC Science & Technology

2006-04-01

and Scalability, (2) Sensors and Platforms, (3) Distributed Computing and Processing , (4) Information Management, (5) Fusion and Resource Management...use of the deployed system. 3.3 Distributed Computing and Processing Session The Distributed Computing and Processing Session consisted of three

Numerical Simulation of Dispersion from Urban Greenhouse Gas Sources

NASA Astrophysics Data System (ADS)

Nottrott, Anders; Tan, Sze; He, Yonggang; Winkler, Renato

2017-04-01

Cities are characterized by complex topography, inhomogeneous turbulence, and variable pollutant source distributions. These features create a scale separation between local sources and urban scale emissions estimates known as the Grey-Zone. Modern computational fluid dynamics (CFD) techniques provide a quasi-deterministic, physically based toolset to bridge the scale separation gap between source level dynamics, local measurements, and urban scale emissions inventories. CFD has the capability to represent complex building topography and capture detailed 3D turbulence fields in the urban boundary layer. This presentation discusses the application of OpenFOAM to urban CFD simulations of natural gas leaks in cities. OpenFOAM is an open source software for advanced numerical simulation of engineering and environmental fluid flows. When combined with free or low cost computer aided drawing and GIS, OpenFOAM generates a detailed, 3D representation of urban wind fields. OpenFOAM was applied to model scalar emissions from various components of the natural gas distribution system, to study the impact of urban meteorology on mobile greenhouse gas measurements. The numerical experiments demonstrate that CH4 concentration profiles are highly sensitive to the relative location of emission sources and buildings. Sources separated by distances of 5-10 meters showed significant differences in vertical dispersion of plumes, due to building wake effects. The OpenFOAM flow fields were combined with an inverse, stochastic dispersion model to quantify and visualize the sensitivity of point sensors to upwind sources in various built environments. The Boussinesq approximation was applied to investigate the effects of canopy layer temperature gradients and convection on sensor footprints.