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    Wear Detection of Bridge Sliding Bearing Based on Temporal Variation of Thermally Induced Daily Displacement Amplitude

    Source: Journal of Bridge Engineering:;2024:;Volume ( 029 ):;issue: 006::page 04024037-1
    Author:
    Dong-Hui Yang
    ,
    Jia-Zheng Sun
    ,
    Ting-Hua Yi
    ,
    Hong-Nan Li
    ,
    Hua Liu
    DOI: 10.1061/JBENF2.BEENG-6622
    Publisher: American Society of Civil Engineers
    Abstract: Sliding bearings are a vulnerable component of bridges. Bearing wear will affect the free expansion of the bridge structure and produce greater temperature stress, resulting in damage to the main girder and other components of the bridge. In the process of bridge operation, the timely detection of bearing wear is very important for ensuring structural safety. Therefore, this paper proposes a wear detection method for bridge sliding bearings based on displacement amplitude by eliminating the effects of daily temperature variations. First, the bearing mechanical behavior under temperature effects and the correlation between temperature and bearing friction force are analyzed. The bearing displacement hysteresis model under temperature effects is established, and the variation in thermally induced bearing displacement after wear is obtained. Then, the correlation between temperature and thermally induced bearing displacement is analyzed and, based on the particle swarm optimization (PSO) algorithm and long short-term memory (LSTM) neural network, a multivariate temperature–displacement correlation model is established to achieve the accurate prediction of thermally induced bearing displacement and the elimination of temperature effects. According to the variation in the thermally induced displacement of the bearing after wear, the indicator of thermally induced displacement amplitude errors (TDAE) is proposed, and the cumulative sum (CUSUM) control chart is used to detect the bearing anomaly. Finally, a long-span bridge is analyzed as an example. The results show that the proposed TDAE detection indicator can effectively reflect the sliding friction force of the bridge bearing, and the proposed detection method can accurately detect the sliding bearing wear, which can provide effective information for the bridge caretakers to monitor the occurrence of bearing wear and replace the bearing slide plate in a timely manner.
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      Wear Detection of Bridge Sliding Bearing Based on Temporal Variation of Thermally Induced Daily Displacement Amplitude

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4298624
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    • Journal of Bridge Engineering

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    contributor authorDong-Hui Yang
    contributor authorJia-Zheng Sun
    contributor authorTing-Hua Yi
    contributor authorHong-Nan Li
    contributor authorHua Liu
    date accessioned2024-12-24T10:16:47Z
    date available2024-12-24T10:16:47Z
    date copyright6/1/2024 12:00:00 AM
    date issued2024
    identifier otherJBENF2.BEENG-6622.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4298624
    description abstractSliding bearings are a vulnerable component of bridges. Bearing wear will affect the free expansion of the bridge structure and produce greater temperature stress, resulting in damage to the main girder and other components of the bridge. In the process of bridge operation, the timely detection of bearing wear is very important for ensuring structural safety. Therefore, this paper proposes a wear detection method for bridge sliding bearings based on displacement amplitude by eliminating the effects of daily temperature variations. First, the bearing mechanical behavior under temperature effects and the correlation between temperature and bearing friction force are analyzed. The bearing displacement hysteresis model under temperature effects is established, and the variation in thermally induced bearing displacement after wear is obtained. Then, the correlation between temperature and thermally induced bearing displacement is analyzed and, based on the particle swarm optimization (PSO) algorithm and long short-term memory (LSTM) neural network, a multivariate temperature–displacement correlation model is established to achieve the accurate prediction of thermally induced bearing displacement and the elimination of temperature effects. According to the variation in the thermally induced displacement of the bearing after wear, the indicator of thermally induced displacement amplitude errors (TDAE) is proposed, and the cumulative sum (CUSUM) control chart is used to detect the bearing anomaly. Finally, a long-span bridge is analyzed as an example. The results show that the proposed TDAE detection indicator can effectively reflect the sliding friction force of the bridge bearing, and the proposed detection method can accurately detect the sliding bearing wear, which can provide effective information for the bridge caretakers to monitor the occurrence of bearing wear and replace the bearing slide plate in a timely manner.
    publisherAmerican Society of Civil Engineers
    titleWear Detection of Bridge Sliding Bearing Based on Temporal Variation of Thermally Induced Daily Displacement Amplitude
    typeJournal Article
    journal volume29
    journal issue6
    journal titleJournal of Bridge Engineering
    identifier doi10.1061/JBENF2.BEENG-6622
    journal fristpage04024037-1
    journal lastpage04024037-13
    page13
    treeJournal of Bridge Engineering:;2024:;Volume ( 029 ):;issue: 006
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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