[논문]Full-scale experimental validation of decentralized damage identification using wireless smart sensors

doi:10.1088/0964-1726/21/11/115019

Full-scale experimental validation of decentralized damage identification using wireless smart sensors

Smart materials & structures, v.21 no.11, 2012년, pp.115019 -

Abstract ▼ AI-Helper

Wireless smart sensor networks (WSSN) facilitate a new paradigm for structural health monitoring (SHM) of civil infrastructure. Conventionally, SHM systems employing wired sensors and centralized data acquisition have been used to characterize the state of a structure; however, widespread implementation has been limited due to high costs and difficulties in installation. WSSN offer a unique opportunity to overcome such difficulties. Recent developments have realized low-cost, smart sensors with on-board computation and wireless communication capabilities, making deployment of a dense array of sensors on large civil structures both economical and feasible. Wireless smart sensors (WSS) have shown their tremendous potential for SHM in recent full-scale bridge monitoring examples. However, structural damage identification using on-board computation capability in a WSSN, a primary objective of SHM, has yet to reach its full potential. This paper presents full-scale validation of a damage identification strategy using a decentralized network of Imote2 nodes on a historic steel truss bridge. A total of 24 WSS nodes with 144 sensor channels are deployed on the bridge to validate the developed damage identification software. The performance of this decentralized damage identification strategy is demonstrated on the WSSN by comparing its results with those from the traditional centralized approach, as well as visual inspection.

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표제어: PCR

동의어: Packet Collision Rate

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용어 설명: PCR은 세균 특이성이 있는 primer를 이용하여 적은 수의 세균이 있을지라도 쉽게 검출할 수 있는 유용한 방법이며, 이를 이용하여 구강 내 치면세균막이나 타액에서 직접 세균을 검출할 수 있게 되었다[8].

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Full-scale experimental validation of decentralized damage identification using wireless smart sensors

Abstract ▼ AI-Helper

참고문헌 (34)

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