移动荷载作用下时变简支钢桥损伤识别
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TN911.6; TU311.3

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国家自然科学基金青年科学基金资助项目(51608122);福建省自然科学基金青年科技人才创新资助项目(2016J05111);福建农林大学校杰出青年基金资助项目(XJQ201728)


Damage Detection of a Time-Varying Simply Supported Steel Bridge Under Moving Load
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    摘要:

    针对移动荷载作用下桥梁结构振动响应信号呈现非平稳性的特点,构建新的一阶本征函数自功率谱最大值变化比和一阶本征函数小波能量变化率两个指标来识别时变结构的损伤。首先,采用小波阀值去噪法对时变结构响应信号进行去噪处理;其次,运用解析模态分解定理提取响应信号的一阶本征函数并构建一阶本征函数自功率谱最大值变化比指标来识别结构的损伤位置,在识别结构损伤位置的基础上,将损伤位置处的加速度响应信号的一阶和二阶本征函数进行线性混叠后,采用快速独立成分分析进行分离,得到更有效的一阶本征函数;最后,基于连续小波变换和时间窗思想,提出一阶本征函数小波能量变化率指标来预测结构的时变损伤。通过移动荷载作用下的时变简支钢桥试验验证所提出的损伤指标,研究结果表明,提出的两个指标能够有效识别结构的损伤位置和时变损伤。

    Abstract:

    Since response signals of time-varying bridges exhibit non-stationary characteristics, new time-varying damage indexes, including the maximum change ratio of auto power spectrum (MCRAPS) of the first order intrinsic mode function and the wavelet energy change rate (WCR) of the first order intrinsic mode function, are proposed to detect damages. First, the wavelet threshold denoising method is introduced to reduce noises from original response signals. Then, the first two order intrinsic mode functions (IMF1 and IMF2) are extracted by the analytic modal decomposition theorem and the index of MCRAPS is proposed to detect damage locations. Based on the effective detection of damage locations, the decomposed IMF1 and IMF2 are linearly mixed and then separated by fast independent component analysis (FastICA) to obtain more independent IMF1. Aiming to detect time-varying damages, the new independent IMF1 is used to present WCR by continuous wavelet transform and time window. A dynamic test of a time-varying simply supported steel bridge with moving loads is designed to verify the two proposed damage indexes. The results demonstrate that they can effectively detect damage locations and structural time-varying damages, respectively.

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  • 在线发布日期: 2020-03-17
  • 出版日期: 2020-02-28
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