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    Development and Application of High-Sensitivity Wireless Smart Sensors for Decentralized Stochastic Modal Identification

    Source: Journal of Engineering Mechanics:;2012:;Volume ( 138 ):;issue: 006
    Author:
    Hongki Jo
    ,
    Sung-Han Sim
    ,
    Tomonori Nagayama
    ,
    B. F. Spencer Jr.
    DOI: 10.1061/(ASCE)EM.1943-7889.0000352
    Publisher: American Society of Civil Engineers
    Abstract: State-of-the-art smart sensor technology enables deployment of dense arrays of sensors, which is critical for structural health monitoring (SHM) of complicated and large-scale civil structures. Despite recent successful implementation of various wireless smart sensor networks (WSSNs) for full-scale SHM, the low-cost micro-electro-mechanical systems (MEMS) sensors commonly used in smart sensors cannot readily measure low-level ambient vibrations because of their relatively low resolution. Combined use of conventional wired high-sensitivity sensors with low-cost wireless smart sensors has been shown to provide improved spectral estimates of response that can lead to improved experimental modal analysis. However, such a heterogeneous network of wired and wireless sensors requires central collection of an enormous amount of raw data and off-network processing to achieve global time synchronization; consequently, many of the advantages of WSSNs for SHM are lost. In this paper, the development of a new high-sensitivity accelerometer board (SHM-H) for the Imote2 wireless smart sensor (WSS) platform is presented. The use of a small number of these high-sensitivity WSSs, composed of the SHM-H and Imote2, as reference sensors in the Natural Excitation Technique—based decentralized WSSN strategy is explored and is shown to provide a cost-effective means of improving modal feature extraction in the decentralized WSSN for SHM.
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      Development and Application of High-Sensitivity Wireless Smart Sensors for Decentralized Stochastic Modal Identification

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    contributor authorHongki Jo
    contributor authorSung-Han Sim
    contributor authorTomonori Nagayama
    contributor authorB. F. Spencer Jr.
    date accessioned2017-05-08T21:43:44Z
    date available2017-05-08T21:43:44Z
    date copyrightJune 2012
    date issued2012
    identifier other%28asce%29em%2E1943-7889%2E0000361.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/60823
    description abstractState-of-the-art smart sensor technology enables deployment of dense arrays of sensors, which is critical for structural health monitoring (SHM) of complicated and large-scale civil structures. Despite recent successful implementation of various wireless smart sensor networks (WSSNs) for full-scale SHM, the low-cost micro-electro-mechanical systems (MEMS) sensors commonly used in smart sensors cannot readily measure low-level ambient vibrations because of their relatively low resolution. Combined use of conventional wired high-sensitivity sensors with low-cost wireless smart sensors has been shown to provide improved spectral estimates of response that can lead to improved experimental modal analysis. However, such a heterogeneous network of wired and wireless sensors requires central collection of an enormous amount of raw data and off-network processing to achieve global time synchronization; consequently, many of the advantages of WSSNs for SHM are lost. In this paper, the development of a new high-sensitivity accelerometer board (SHM-H) for the Imote2 wireless smart sensor (WSS) platform is presented. The use of a small number of these high-sensitivity WSSs, composed of the SHM-H and Imote2, as reference sensors in the Natural Excitation Technique—based decentralized WSSN strategy is explored and is shown to provide a cost-effective means of improving modal feature extraction in the decentralized WSSN for SHM.
    publisherAmerican Society of Civil Engineers
    titleDevelopment and Application of High-Sensitivity Wireless Smart Sensors for Decentralized Stochastic Modal Identification
    typeJournal Paper
    journal volume138
    journal issue6
    journal titleJournal of Engineering Mechanics
    identifier doi10.1061/(ASCE)EM.1943-7889.0000352
    treeJournal of Engineering Mechanics:;2012:;Volume ( 138 ):;issue: 006
    contenttypeFulltext
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