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    Early Warning Method for Bearing Displacement of Long-Span Bridges Using a Proposed Time-Varying Temperature–Displacement Model

    Source: Journal of Bridge Engineering:;2021:;Volume ( 026 ):;issue: 009::page 04021068-1
    Author:
    Guang-Ming Wu
    ,
    Ting-Hua Yi
    ,
    Dong-Hui Yang
    ,
    Hong-Nan Li
    ,
    Hua Liu
    DOI: 10.1061/(ASCE)BE.1943-5592.0001763
    Publisher: ASCE
    Abstract: Bearing displacement is a necessary monitoring index for a long-span bridge because abnormal bearing displacements could result from structural deterioration or damage. Therefore, an early warning method is established for bearing displacement of long-span bridges. In this study, a novel time-varying temperature–displacement nonlinear model, which can eliminate the model error induced by temperature field simplification, is first proposed to accurately estimate bearing displacement. Then, early warning methods for abnormal displacement and out-of-bounds displacement of bearings are established using estimation errors, and different warning levels are delineated depending on combinations of the two types of early warning, followed by an implementation procedure for the early warning method. Finally, the long-term monitoring data of a large-span bridge are utilized to validate the advantage of the proposed time-varying model and the effectiveness of the early warning method. The results show that the modeling and prediction errors of the time-varying model are smaller than that of the linear model. Additionally, attention needs to be paid to the changes in the warning information for bearings with large modeling errors, which will correspond to a relatively high warning level.
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      Early Warning Method for Bearing Displacement of Long-Span Bridges Using a Proposed Time-Varying Temperature–Displacement Model

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4272537
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    contributor authorGuang-Ming Wu
    contributor authorTing-Hua Yi
    contributor authorDong-Hui Yang
    contributor authorHong-Nan Li
    contributor authorHua Liu
    date accessioned2022-02-01T22:03:47Z
    date available2022-02-01T22:03:47Z
    date issued9/1/2021
    identifier other%28ASCE%29BE.1943-5592.0001763.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4272537
    description abstractBearing displacement is a necessary monitoring index for a long-span bridge because abnormal bearing displacements could result from structural deterioration or damage. Therefore, an early warning method is established for bearing displacement of long-span bridges. In this study, a novel time-varying temperature–displacement nonlinear model, which can eliminate the model error induced by temperature field simplification, is first proposed to accurately estimate bearing displacement. Then, early warning methods for abnormal displacement and out-of-bounds displacement of bearings are established using estimation errors, and different warning levels are delineated depending on combinations of the two types of early warning, followed by an implementation procedure for the early warning method. Finally, the long-term monitoring data of a large-span bridge are utilized to validate the advantage of the proposed time-varying model and the effectiveness of the early warning method. The results show that the modeling and prediction errors of the time-varying model are smaller than that of the linear model. Additionally, attention needs to be paid to the changes in the warning information for bearings with large modeling errors, which will correspond to a relatively high warning level.
    publisherASCE
    titleEarly Warning Method for Bearing Displacement of Long-Span Bridges Using a Proposed Time-Varying Temperature–Displacement Model
    typeJournal Paper
    journal volume26
    journal issue9
    journal titleJournal of Bridge Engineering
    identifier doi10.1061/(ASCE)BE.1943-5592.0001763
    journal fristpage04021068-1
    journal lastpage04021068-14
    page14
    treeJournal of Bridge Engineering:;2021:;Volume ( 026 ):;issue: 009
    contenttypeFulltext
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