Abstract

Various structural health monitoring strategies have been proposed recently that can be implemented in the decentralized computing environment intrinsic to wireless smart sensor networks (WSSN). Many are based on changes in the experimentally determined flexibility matrix for the structure under consideration. However, the flexibility matrix contains only static information; much richer information is available by considering the dynamic flexibility, or receptance, of the structure. Recently, the stochastic dynamic damage locating vector (SDDLV) method was proposed based on changes of dynamic flexibility matrices employing centrally collected output-only measurements. This paper investigates the potential of the SDDLV method for implementation on a network of wireless smart sensors, where a decentralized, hierarchical, in-network processing approach is used to address issues of scalability of the SDDLV algorithm. Two approaches to aggregate results are proposed that provide robust estimates of damage locations. The efficacy of the developed strategy is first verified using wired sensors emulating a wireless sensor network. Subsequently, the decentralized damage detection strategy is implemented on MEMSIC’s Imote2 smart sensor platform and validated experimentally on a laboratory scale truss bridge.

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