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首页|期刊导航|东南大学学报(自然科学版)|可考虑温致位移时滞的大跨桥梁支座劣化预警技术

可考虑温致位移时滞的大跨桥梁支座劣化预警技术OA北大核心CSTPCD

Early warning technology of long-span bridge bearing deterioration considering time lag effects of thermal-induced displacement

中文摘要英文摘要

为实现对大跨桥梁支座性能劣化的准确判别,提出了一种考虑温致位移时滞的大跨桥梁支座性能劣化预警方法.首先,分析了温度效应下支座滑动的力学行为,揭示了支座性能劣化前后温致位移的变化特征;其次,建立了可考虑温致位移时滞的门控循环单元GRU网络模型,对支座温致位移进行预测,并提出了可剔除温度效应影响、凸显支座性能劣化的温致位移预测残差TDPE预警指标;最后,基于某大跨桥梁的监测数据,验证所提方法的有效性.结果表明:GRU网络模型可以自适应剔除支座温致位移的时滞效应,对支座位移具有较高的预测精度,预测误差在5 mm以内;TDPE预警指标可以实现支座温致位移4 mm以上的异常增量预警.

To realize the accurate identification of the performance deterioration of long-span bridge bearing,an early warning method of long-span bridge bearing performance deterioration considering the time lag of the thermal-induced displacement was proposed.Firstly,the mechanical behaviors of bearing sliding under the temperature effect was analyzed,and the variation characteristics of the thermal-induced displacement before and after bearing performance degradation were revealed.Secondly,a gated recurrent unit(GRU)network model considering the time lag effect of the thermal-induced displacement was established to predict the bearing thermal-induced displacement.A warning indicator of the thermal-induced displacement prediction residual er-ror(TDPE)that can eliminate the influence of the temperature effect and highlight the performance degrada-tion of the bearing was proposed.Finally,the effectiveness of the proposed method was verified based on the monitoring data of a long-span bridge.The results show that the GRU network model can eliminate adaptively the time lag effect of the bearing thermal-induced displacement.The bearing displacement can be predicted with high accuracy and the prediction error is within 5 mm.The warning indicator of the TDPE can realize the abnormal incremental warning of the bearing thermal-induced displacement more than 4 mm.

杨东辉;孙家正;伊廷华;李宏男;李冲;李文杰

大连理工大学建设工程学院,大连 116024中交公路长大桥建设国家工程研究中心有限公司,北京 100120中国交通集团建设有限公司,北京 100088

交通运输

桥梁健康监测桥梁支座支座损伤温度效应神经网络模型

bridge health monitoringbridge bearingbearing damagetemperature effectneural network model

《东南大学学报(自然科学版)》 2024 (002)

基于空间响应特征反演的装配式板梁桥接缝损伤量化辨识研究

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国家自然科学基金资助项目(52078102,52250011,52322807).

10.3969/j.issn.1001-0505.2024.02.003

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