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    Tracking Dynamic Characteristics of Structures Using Output-Only Recursive Combined Subspace Identification Technique

    Source: Journal of Engineering Mechanics:;2020:;Volume ( 146 ):;issue: 005
    Author:
    Kaihui Zhong
    ,
    C. C. Chang
    DOI: 10.1061/(ASCE)EM.1943-7889.0001742
    Publisher: ASCE
    Abstract: Identifying the dynamic characteristics of structures under ambient conditions is very important for heath monitoring and damage assessment. In this study, an output-only recursive combined subspace identification technique is proposed for tracking the modal parameters of a time-varying structure under unknown and unmeasured nonstationary input. The technique consists of two parts: initial input estimation and online tracking. For initial input estimation, a short-duration input is first reconstructed through an iterative oblique projection and an orthogonal projection. The reconstructed input and the measured output are then used to form a cross-correlation matrix for initial estimation of modal parameters. An orthogonal projection and an instrumental variable approach are then incorporated in order to eliminate the effects of nonstationary input and measurement noise, respectively. A bi-iteration subspace tracker is applied to extract the unknown input and the structural modal parameters. The proposed technique was validated numerically on a four-degree-of-freedom structure and experimentally on a three-degree-of-freedom building model. Both results showed that the proposed technique can simultaneously reconstruct the unknown input and track the time-varying structural modal parameters using only output measurements.
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      Tracking Dynamic Characteristics of Structures Using Output-Only Recursive Combined Subspace Identification Technique

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4265470
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    contributor authorKaihui Zhong
    contributor authorC. C. Chang
    date accessioned2022-01-30T19:31:28Z
    date available2022-01-30T19:31:28Z
    date issued2020
    identifier other%28ASCE%29EM.1943-7889.0001742.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4265470
    description abstractIdentifying the dynamic characteristics of structures under ambient conditions is very important for heath monitoring and damage assessment. In this study, an output-only recursive combined subspace identification technique is proposed for tracking the modal parameters of a time-varying structure under unknown and unmeasured nonstationary input. The technique consists of two parts: initial input estimation and online tracking. For initial input estimation, a short-duration input is first reconstructed through an iterative oblique projection and an orthogonal projection. The reconstructed input and the measured output are then used to form a cross-correlation matrix for initial estimation of modal parameters. An orthogonal projection and an instrumental variable approach are then incorporated in order to eliminate the effects of nonstationary input and measurement noise, respectively. A bi-iteration subspace tracker is applied to extract the unknown input and the structural modal parameters. The proposed technique was validated numerically on a four-degree-of-freedom structure and experimentally on a three-degree-of-freedom building model. Both results showed that the proposed technique can simultaneously reconstruct the unknown input and track the time-varying structural modal parameters using only output measurements.
    publisherASCE
    titleTracking Dynamic Characteristics of Structures Using Output-Only Recursive Combined Subspace Identification Technique
    typeJournal Paper
    journal volume146
    journal issue5
    journal titleJournal of Engineering Mechanics
    identifier doi10.1061/(ASCE)EM.1943-7889.0001742
    page04020035
    treeJournal of Engineering Mechanics:;2020:;Volume ( 146 ):;issue: 005
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian