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    Infrasound-Based Noncontact Sensing for Bridge Structural Health Monitoring

    Source: Journal of Bridge Engineering:;2019:;Volume ( 024 ):;issue: 005
    Author:
    Sergio Lobo-Aguilar
    ,
    Zhenyu Zhang
    ,
    Zhaoshuo Jiang
    ,
    Richard Christenson
    DOI: 10.1061/(ASCE)BE.1943-5592.0001385
    Publisher: American Society of Civil Engineers
    Abstract: This study demonstrates the use of infrasound measurements from microphones as a means of noncontact sensing to capture the dynamic properties of structures for structural health monitoring (SHM). A pilot study using an in-service highway bridge in Connecticut is conducted to compare infrasound and accelerometer-based SHM using a frequency domain peak-picking method. A three-dimensional finite-element (FE) model is developed to validate the results. Potential benefits and limitations of infrasound-based SHM are discussed. An attention model from machine learning is further proposed to increase the signal-to-noise ratio of the microphone measurements and provide an unbiased rapid means of identifying the modal frequencies of the bridge.
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      Infrasound-Based Noncontact Sensing for Bridge Structural Health Monitoring

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4259877
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    contributor authorSergio Lobo-Aguilar
    contributor authorZhenyu Zhang
    contributor authorZhaoshuo Jiang
    contributor authorRichard Christenson
    date accessioned2019-09-18T10:39:20Z
    date available2019-09-18T10:39:20Z
    date issued2019
    identifier other%28ASCE%29BE.1943-5592.0001385.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4259877
    description abstractThis study demonstrates the use of infrasound measurements from microphones as a means of noncontact sensing to capture the dynamic properties of structures for structural health monitoring (SHM). A pilot study using an in-service highway bridge in Connecticut is conducted to compare infrasound and accelerometer-based SHM using a frequency domain peak-picking method. A three-dimensional finite-element (FE) model is developed to validate the results. Potential benefits and limitations of infrasound-based SHM are discussed. An attention model from machine learning is further proposed to increase the signal-to-noise ratio of the microphone measurements and provide an unbiased rapid means of identifying the modal frequencies of the bridge.
    publisherAmerican Society of Civil Engineers
    titleInfrasound-Based Noncontact Sensing for Bridge Structural Health Monitoring
    typeJournal Paper
    journal volume24
    journal issue5
    journal titleJournal of Bridge Engineering
    identifier doi10.1061/(ASCE)BE.1943-5592.0001385
    page04019033
    treeJournal of Bridge Engineering:;2019:;Volume ( 024 ):;issue: 005
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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