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Structural Health Monitoring of Arch Dam from Dynamic Measurements

机译:动态测量拱坝的结构健康监测

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This paper presents the system identification of the Fei-Tsui arch dam using the recorded seismic data and ambient vibration data. The modal properties of the dam under different reservoir water level are identified using the recorded seismic data from 84 earthquake events. Considering the spatial variability of input excitation, both multi-input and single-input system models are employed in the input/output subspace identification. The regression curves between the natural frequencies and the reservoir water level are developed from the statistical analysis of identification results. In order to compare the current behavior of the dam to the past, an ambient vibration experiment is performed and the output-only stochastic subspace identification method is used to identify the current modal properties of the dam. Finally, a safety evaluation is made by pointing the current identification result on the developed regression curve. Further more, the comparison between different identification algorithms in this study is made. From the stability diagram of the identification the output-only stochastic subspace identification (using ambient data) provides more clear system characteristics than the input/output subspace identification (using seismic data). Discussion on the single-input model and the multi-input model for subspace identification is also made in this study.
机译:本文介绍了使用记录的地震数据和环境振动数据的Fei-Tsui Arch DAM的系统识别。使用来自84个地震事件的记录的地震数据鉴定了不同贮存水位下的坝的模态性质。考虑到输入激励的空间变化,在输入/输出子空间识别中采用了多输入和单输入系统模型。从鉴定结果的统计分析中显影了自然频率和储层水位之间的回归曲线。为了比较坝的当前行为迄今为止,执行环境振动实验,并使用输出的随机子空间识别方法来识别大坝的当前模态特性。最后,通过指向发布的回归曲线上的当前识别结果进行安全评估。此外,制造了该研究中的不同识别算法之间的比较。从识别的稳定性图,输出的随机子空间识别(使用环境数据)提供比输入/输出子空间识别更清晰的系统特性(使用地震数据)。本研究还提出了关于单输入模型的讨论和子空间识别的多输入模型。

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