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An indirect method for bridge mode shapes identification based on wavelet analysis
Structural Control and Health Monitoring ( IF 4.6 ) Pub Date : 2020-09-02 , DOI: 10.1002/stc.2630
Xudong Jian 1 , Ye Xia 2 , Limin Sun 1
Affiliation  

Mode shapes have been playing a vital role in the research and application of bridge structural health monitoring. This paper presents a novel indirect method identifying bridge mode shapes using dynamic responses of a tractor–trailer vehicle model, which consists of one tractor and three instrumented trailers. In an effort to eliminate the road roughness effect, accelerations of adjacent trailers are firstly subtracted. Wavelet analysis is then employed to identify bridge mode shapes from the subtracted accelerations in an iterative manner. Furthermore, wavelet denoising algorithm is adopted to improve the identification accuracy in the presence of measurement noise. Systematic numerical simulations, in which a tractor–trailer model passes over an expressway bridge, are conducted in order to investigate the performance of the proposed method. Sensitivity analysis including vehicle speed, class of road roughness, and noise level are studied in this numerical investigation. Results demonstrate that the proposed method is able to identify bridge modal frequencies and mode shapes with satisfactory resolution, accuracy, and robustness.

中文翻译:

基于小波分析的桥梁形态识别方法

模式形状在桥梁结构健康监测的研究和应用中一直起着至关重要的作用。本文提出了一种新颖的间接方法,该方法利用拖拉机-挂车模型的动态响应来识别桥模形状,该模型由一个牵引车和三个挂车组成。为了消除道路不平整的影响,首先减去相邻拖车的加速度。然后,采用小波分析以迭代方式从减去的加速度中识别桥模形状。此外,在存在测量噪声的情况下,采用小波去噪算法提高识别精度。为了研究提出的方法的性能,进行了系统的数值模拟,其中牵引车-拖车模型经过高速公路的桥梁。在此数值研究中,研究了包括车速,路面不平度和噪声水平在内的灵敏度分析。结果表明,所提出的方法能够以令人满意的分辨率,准确性和鲁棒性来识别桥模态频率和模态形状。
更新日期:2020-11-04
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