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Bridge identification and damage detection using contact point response difference of moving vehicle
Structural Control and Health Monitoring ( IF 4.6 ) Pub Date : 2021-08-27 , DOI: 10.1002/stc.2837
Ying Zhan 1 , Francis T. K. Au 1 , Jing Zhang 1, 2
Affiliation  

This paper presents the use of a moving vehicle to identify the bridge mode shapes and detect possible damage in the presence of bridge surface roughness. The method utilises the contact point responses at the contact between the wheel and bridge surface, which can be obtained from the vehicle responses and has a direct relation with the bridge responses and surface roughness. A double-pass mass-addition technique is proposed to obtain the contact point response difference using a test vehicle installed with sensors. Then the bridge frequencies can be identified from its spectrum, while the mode shapes can be further obtained by signal filtering and Hilbert transform. Simulation results show that the adverse effect of surface roughness on the contact point acceleration difference is largely reduced. The first three frequencies and mode shapes can be extracted with satisfactory accuracy. Multiple damage locations can be identified by performing wavelet transform on the contact point displacement difference and applying coordinate modal assurance criterion to the mode shapes constructed. The factors that may affect the performance of the proposed method are also investigated, including the distribution of added mass, measurement noise, speed of the test vehicle and co-existing traffic. Experimental validation is conducted on a simply supported aluminium channel beam with artificial roughness carrying a moving model vehicle. The results show that the proposed methodology for bridge identification works in the presence of road surface roughness.

中文翻译:

基于移动车辆接触点响应差异的桥梁识别与损伤检测

本文介绍了使用移动车辆来识别桥梁模式形状并检测存在桥梁表面粗糙度时可能的损坏。该方法利用车轮和桥梁表面接触处的接触点响应,该响应可以从车辆响应中获得,并且与桥梁响应和表面粗糙度有直接关系。提出了一种双通道质量相加技术,以使用安装有传感器的测试车辆获得接触点响应差异。然后可以从其频谱中识别出桥频率,而通过信号滤波和希尔伯特变换可以进一步获得模态形状。仿真结果表明,表面粗糙度对接触点加速度差的不利影响大大降低。可以以令人满意的精度提取前三个频率和模式形状。通过对接触点位移差进行小波变换并将坐标模态保证准则应用于构造的模态振型,可以识别多个损伤位置。还研究了可能影响所提出方法性能的因素,包括附加质量的分布、测量噪声、测试车辆的速度和共存交通。实验验证是在带有人工粗糙度的简支铝槽梁上进行的,该梁带有移动模型车辆。结果表明,所提出的桥梁识别方法适用于存在路面粗糙度的情况。通过对接触点位移差进行小波变换并将坐标模态保证准则应用于构造的模态振型,可以识别多个损伤位置。还研究了可能影响所提出方法性能的因素,包括附加质量的分布、测量噪声、测试车辆的速度和共存交通。实验验证是在一个带有运动模型车辆的具有人工粗糙度的简支铝槽梁上进行的。结果表明,所提出的桥梁识别方法适用于存在路面粗糙度的情况。通过对接触点位移差进行小波变换并将坐标模态保证准则应用于构造的模态振型,可以识别多个损伤位置。还研究了可能影响所提出方法性能的因素,包括附加质量的分布、测量噪声、测试车辆的速度和共存交通。实验验证是在带有人工粗糙度的简支铝槽梁上进行的,该梁带有移动模型车辆。结果表明,所提出的桥梁识别方法适用于存在路面粗糙度的情况。还研究了可能影响所提出方法性能的因素,包括附加质量的分布、测量噪声、测试车辆的速度和共存交通。实验验证是在带有人工粗糙度的简支铝槽梁上进行的,该梁带有移动模型车辆。结果表明,所提出的桥梁识别方法适用于存在路面粗糙度的情况。还研究了可能影响所提出方法性能的因素,包括附加质量的分布、测量噪声、测试车辆的速度和共存交通。实验验证是在带有人工粗糙度的简支铝槽梁上进行的,该梁带有移动模型车辆。结果表明,所提出的桥梁识别方法适用于存在路面粗糙度的情况。
更新日期:2021-11-05
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