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高速铁路桥梁动力响应监测数据分析方法及其应用 被引量:14

Analysis Method and Its Application of Dynamic Response Monitoring Data of High-Speed Railway Bridges
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摘要 为在桥梁结构健康监测系统中实现监测数据的自动分析,根据高速铁路桥梁上的列车荷载特点,提出了一种简单、有效的数据分析方法。该方法利用主梁跨中竖向变形数据确定列车过桥时刻,提取此时刻前后时间段内高信噪比的加速度数据,进行频谱分析获得结构的自振频率,并将该方法应用在渝利铁路韩家沱长江大桥的健康监测系统中。结果表明:该方法实现了程序化自动分析,因提取了高质量的数据,分析结果的识别率由不到80%提高到超过98%;因避免了列车引起的附加质量对分析结果的影响,分析结果的误差减少了2.97%~4.87%。 To achieve the automatic analysis of the monitoring data in the structural health monitoring systems of bridges,a simple and effective analysis method for the dynamic response monitoring data of the high-speed railway bridges was proposed in regard of the train load characteristics of the bridges.In the method,the midspan vertical deformation data of the main girders of the bridges were used to determine the time the trains passed through the bridges and the acceleration data of the high signal-noise ratios in the time periods before and after the trains passed through were extracted.The related frequency spectrum analysis was implemented,the natural vibration frequencies of the structures were acquired and the method was then applied in reality to the health monitoring system of the Hanjiatuo Changjiang River Bridge on Chongqing-Lichuan Railway.The results show that with the method,the programming automatic analysis of the monitoring data is achieved.Because the high quality data are extracted,the identification rates of the analysis are improved to those greater than 9 8%from those less than 80%and because the influences of the additional mass caused by the trains on the analysis are averted,the errors of the analysis are reduced by 2.9 7%~4.87%.
作者 荆国强 王波 柴小鹏 汪正兴 JING Guo-qiang;WANG Bo;CHAI Xiao-peng;WANG Zheng-xing(China Railway Bridge Science Research Institute,Ltd.,Wuhan 430034,China;State Key Laboratory for Health and Safety of Bridge Structures?Wuhan 430034,China)
出处 《桥梁建设》 EI CSCD 北大核心 2018年第2期31-36,共6页 Bridge Construction
基金 中国中铁股份有限公司科技开发计划项目(2014-重点-07) 武汉市"硚口英才计划"项目
关键词 高速铁路桥 斜拉桥 健康监测 动力响应 自振频率 数据分析 high-speed railway bridge cable-stayed bridge health monitoring dynamic response natural vibration frequency data analysis
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