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Long-term health monitoring of in-service bridge deck by covariance of covariance matrix of acceleration responses

机译:通过加速度响应协方差矩阵的协方差对在役桥面进行长期健康监测

摘要

The covariance of covariance (CoC) matrix is formed from the auto/crosscorrelation function of acceleration responses of a structure under white noise ambient excitation. The components are function of the modal parameters of the structure and contain more information on the vibration modes of the structure compared to the general existing methods for extracting the modal parameters. This paper makes use of the CoC matrix and a new pattern match criterion for long-term health monitoring, damage localization and quantification of a five-bay three-dimensional frame structure. A large amount of measured data from an in-service suspension bridge is also analyzed. Only the acceleration responses are required to compute the covariance of covariance matrix. The components of the matrix are analyzed and the effects of the traffic flow and environmental temperature are studied. Finally, a strategy to identify the abnormal state of the bridge is presented based on the properties of the CoC components of the bridge. The CoC matrix is shown suitable for analyzing huge amount of measured data for the output-only structural damage detection without need of an analytical model.
机译:协方差(CoC)矩阵的协方差由结构在白噪声环境激励下的加速度响应的自/互相关函数形成。与提取模态参数的一般现有方法相比,这些组件是结构的模态参数的函数,并且包含有关结构振动模式的更多信息。本文利用CoC矩阵和新的模式匹配标准来进行长期健康监测,损伤定位和量化五托架三维框架结构。还分析了来自在役吊桥的大量测量数据。仅需要加速度响应来计算协方差矩阵的协方差。分析了矩阵的组成,并研究了交通流量和环境温度的影响。最后,根据电桥CoC组件的特性,提出了一种识别电桥异常状态的策略。显示的CoC矩阵适用于分析大量测量数据,而无需分析模型即可用于仅输出的结构损伤检测。

著录项

  • 作者

    Wang LX; Li XY; Tan Y; Law SS;

  • 作者单位
  • 年度 2015
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类

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