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 in | IEEE transactions on computers Vol. 64; no. 2; pp. 382 - 395 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
IEEE
01.02.2015
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0018-9340 1557-9956 |
| DOI | 10.1109/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. |
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| 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 |
| Author_xml | – sequence: 1 givenname: Md Zakirul Alam surname: Bhuiyan fullname: Bhuiyan, Md Zakirul Alam email: zakirulalam@gmail.com organization: School of Information Science and Engineering, Central South University, Changsha, China – sequence: 2 givenname: Guojun surname: Wang fullname: Wang, Guojun email: csgjwang@mail.csu.edu.cn organization: School of Information Science and Engineering, Central South University, Changsha, China – sequence: 3 givenname: Jiannong surname: Cao fullname: Cao, Jiannong email: csjcao@comp.polyu.edu.hk organization: Department of Computing, The Hong Kong Polytechnic University, Hong Kong – sequence: 4 givenname: Jie surname: Wu fullname: Wu, Jie email: jiewu@temple.edu organization: Department of Computer and Information Sciences, Temple University, Philadelphia |
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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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