Deploying Wireless Sensor Networks with Fault-Tolerance for Structural Health Monitoring

Structural health monitoring (SHM) systems are implemented for structures (e.g., bridges, buildings) to monitor their operations and health status. Wireless sensor networks (WSNs) are becoming an enabling technology for SHM applications that are more prevalent and more easily deployable than traditi...

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Published inIEEE transactions on computers Vol. 64; no. 2; pp. 382 - 395
Main Authors Bhuiyan, Md Zakirul Alam, Wang, Guojun, Cao, Jiannong, Wu, Jie
Format Journal Article
LanguageEnglish
Published New York IEEE 01.02.2015
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Online AccessGet full text
ISSN0018-9340
1557-9956
DOI10.1109/TC.2013.195

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Abstract Structural health monitoring (SHM) systems are implemented for structures (e.g., bridges, buildings) to monitor their operations and health status. Wireless sensor networks (WSNs) are becoming an enabling technology for SHM applications that are more prevalent and more easily deployable than traditional wired networks. However, SHM brings new challenges to WSNs: engineering-driven optimal deployment, a large volume of data, sophisticated computing, and so forth. In this paper, we address two important challenges: sensor deployment and decentralized computing. We propose a solution, to deploy wireless sensors at strategic locations to achieve the best estimates of structural health (e.g., damage) by following the widely used wired sensor system deployment approach from civil/structural engineering. We found that faults (caused by communication errors, unstable connectivity, sensor faults, etc.) in such a deployed WSN greatly affect the performance of SHM. To make the WSN resilient to the faults, we present an approach, called {\tt FTSHM} (fault-tolerance in SHM), to repair the WSN and guarantee a specified degree of fault tolerance. {\tt FTSHM} searches the repairing points in clusters in a distributed manner, and places a set of backup sensors at those points in such a way that still satisfies the engineering requirements. {\tt FTSHM} also includes an SHM algorithm suitable for decentralized computing in the energy-constrained WSN, with the objective of guaranteeing that the WSN for SHM remains connected in the event of a fault, thus prolonging the WSN lifetime under connectivity and data delivery constraints. We demonstrate the advantages of {\tt FTSHM} through extensive simulations and real experimental settings on a physical structure.
AbstractList Structural health monitoring (SHM) systems are implemented for structures (e.g., bridges, buildings) to monitor their operations and health status. Wireless sensor networks (WSNs) are becoming an enabling technology for SHM applications that are more prevalent and more easily deployable than traditional wired networks. However, SHM brings new challenges to WSNs: engineering-driven optimal deployment, a large volume of data, sophisticated computing, and so forth. In this paper, we address two important challenges: sensor deployment and decentralized computing. We propose a solution, to deploy wireless sensors at strategic locations to achieve the best estimates of structural health (e.g., damage) by following the widely used wired sensor system deployment approach from civil/structural engineering. We found that faults (caused by communication errors, unstable connectivity, sensor faults, etc.) in such a deployed WSN greatly affect the performance of SHM. To make the WSN resilient to the faults, we present an approach, called ttFTSHM (fault-tolerance in SHM), to repair the WSN and guarantee a specified degree of fault tolerance. ttFTSHM searches the repairing points in clusters in a distributed manner, and places a set of backup sensors at those points in such a way that still satisfies the engineering requirements. ttFTSHM also includes an SHM algorithm suitable for decentralized computing in the energy-constrained WSN, with the objective of guaranteeing that the WSN for SHM remains connected in the event of a fault, thus prolonging the WSN lifetime under connectivity and data delivery constraints. We demonstrate the advantages of ttFTSHM through extensive simulations and real experimental settings on a physical structure.
Structural health monitoring (SHM) systems are implemented for structures (e.g., bridges, buildings) to monitor their operations and health status. Wireless sensor networks (WSNs) are becoming an enabling technology for SHM applications that are more prevalent and more easily deployable than traditional wired networks. However, SHM brings new challenges to WSNs: engineering-driven optimal deployment, a large volume of data, sophisticated computing, and so forth. In this paper, we address two important challenges: sensor deployment and decentralized computing. We propose a solution, to deploy wireless sensors at strategic locations to achieve the best estimates of structural health (e.g., damage) by following the widely used wired sensor system deployment approach from civil/structural engineering. We found that faults (caused by communication errors, unstable connectivity, sensor faults, etc.) in such a deployed WSN greatly affect the performance of SHM. To make the WSN resilient to the faults, we present an approach, called {\tt FTSHM} (fault-tolerance in SHM), to repair the WSN and guarantee a specified degree of fault tolerance. {\tt FTSHM} searches the repairing points in clusters in a distributed manner, and places a set of backup sensors at those points in such a way that still satisfies the engineering requirements. {\tt FTSHM} also includes an SHM algorithm suitable for decentralized computing in the energy-constrained WSN, with the objective of guaranteeing that the WSN for SHM remains connected in the event of a fault, thus prolonging the WSN lifetime under connectivity and data delivery constraints. We demonstrate the advantages of {\tt FTSHM} through extensive simulations and real experimental settings on a physical structure.
Structural health monitoring (SHM) systems are implemented for structures (e.g., bridges, buildings) to monitor their operations and health status. Wireless sensor networks (WSNs) are becoming an enabling technology for SHM applications that are more prevalent and more easily deployable than traditional wired networks. However, SHM brings new challenges to WSNs: engineering-driven optimal deployment, a large volume of data, sophisticated computing, and so forth. In this paper, we address two important challenges: sensor deployment and decentralized computing. We propose a solution, to deploy wireless sensors at strategic locations to achieve the best estimates of structural health (e.g., damage) by following the widely used wired sensor system deployment approach from civil/structural engineering. We found that faults (caused by communication errors, unstable connectivity, sensor faults, etc.) in such a deployed WSN greatly affect the performance of SHM. To make the WSN resilient to the faults, we present an approach, called [Formula Omitted] (fault-tolerance in SHM), to repair the WSN and guarantee a specified degree of fault tolerance. [Formula Omitted] searches the repairing points in clusters in a distributed manner, and places a set of backup sensors at those points in such a way that still satisfies the engineering requirements. [Formula Omitted] also includes an SHM algorithm suitable for decentralized computing in the energy-constrained WSN, with the objective of guaranteeing that the WSN for SHM remains connected in the event of a fault, thus prolonging the WSN lifetime under connectivity and data delivery constraints. We demonstrate the advantages of [Formula Omitted] through extensive simulations and real experimental settings on a physical structure.
Author Wu, Jie
Cao, Jiannong
Bhuiyan, Md Zakirul Alam
Wang, Guojun
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  givenname: Jie
  surname: Wu
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Snippet Structural health monitoring (SHM) systems are implemented for structures (e.g., bridges, buildings) to monitor their operations and health status. Wireless...
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SubjectTerms Bridges
Computation
Computer simulation
deployment
energy-efficiency
Fault tolerance
Fault tolerant systems
Faults
Health
Health monitoring (engineering)
Monitoring
Remote sensors
Sensors
Shape
structural health monitoring
Vibrations
Wireless networks
Wireless sensor networks
Title Deploying Wireless Sensor Networks with Fault-Tolerance for Structural Health Monitoring
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Volume 64
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