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大跨径斜拉桥长期健康监测数据的性能分析与应用

Performance Analysis and Application of Long-Term Health Monitoring Data for a Large-Span Cable-Stayed Bridge
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摘要 为了充分剖析和挖掘桥梁长期健康监测数据内部蕴含的桥梁性能的变化规律,从而为未来对结构性能变化评估提供支持数据和判断依据,以主桥跨度为776 m的闵浦大桥为例,收集了该桥10余年的健康监测数据,并利用编程软件编写程序代码进行数据处理及分析,包括数据预处理、模态识别、数据拟合等多种方法,开展了桥梁运营期结构性能变化规律的相关研究,并通过数据拟合、数据全局分析等手段分析了主跨挠度、结构应变、斜拉索索力的数据特征,通过快速贝叶斯FFT模态识别方法,对10余年间加速度数据进行阶段性模态识别研究,从而提取了桥梁长期振动响应数据特征。最后,基于动、静力特性分析的结果及不同分析过程和路径,结合得到的规律和结论,以养护运营者的角度合理规划运营期SHM数据的分析方式、关注重点、建议的长期数据存储和特征提取的参数,以及最终长期数据合理利用模式。 In order to fully analyze and excavate the variation rules of bridge performance embedded within the long-term bridge health monitoring data,so as to be used in the future assessment of structural performance variation to provide supportive data and judgmental basis,this paper selected the Minpu Bridge,which has a main bridge span of 776 m,as an example,and collected the health monitoring data of the bridge for more than 10 years.We wrote the program code using the software to carry out data processing and analysis,which includes data preprocessing,modal identification,data fitting and other approaches,carried out a related study on the variation rule of structural performance of the bridge during the operation period,and analyzed the data characteristics of the main span deflection,structural strain,and cable-stayed cable force by means of data fitting and global analysis of the data,and carried out a study on the periodic modal identification of the acceleration data during the period of more than 10 years by means of a fast Bayesian FFT modal identification method,in order to extract the bridge long-term vibration response data characteristics.Finally,based on the results of dynamic and static force characterization and different analysis processes and paths,combined with the obtained laws and conclusions,the analysis mode,focus of attention,and suggested parameters for long-term data storage and feature extraction,as well as the final long-term data reasonable utilization mode of SHM data during the operation period are rationally scheduled from the perspective of the maintenance operator.
作者 倪艳春 蔡永谊 张启伟 NI Yanchun;CAI Yongyi;ZHANG Qiwei(Department of Bridge Engineering,College of Civil Engineering,Tongji University,Shanghai 200092,China;Shanghai Urban Construction City Operation(Group)Co.,Ltd.,Shanghai 200010,China)
出处 《结构工程师》 2024年第5期19-27,共9页 Structural Engineers
基金 国家自然科学基金(52378312)。
关键词 健康监测 数据分析 数据挖掘 长期数据 health monitoring data analysis data mining long-term data
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