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Wavelet entropy based structural damage identification under seismic excitation

机译:基于小波熵的地震激励下的结构损伤识别

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摘要

In this work, an entropy based two-step structural damage identification method under seismic excitation is proposed. The measured signals are decomposed by means of wavelet packet transform, and the wavelet entropies are obtained on the basis of the information entropy theory. In the first step, the damage alarming indices, calculated with the wavelet entropies in undamaged and damaged conditions, are used as samples for Shewhart individuals control chart to alarm the structural damage. In the second step, the damage localization indices, constructed by calculating the differences of curvature of wavelet entropies in undamaged and damaged conditions, are fed to the back-propagation neural network to identify structure damage location. The numerical simulation and shaking table model test of an offshore platform under seismic excitation are implemented to verify the feasibility of the proposed two-step structural damage identification method. The results show that the proposed method needs only the non-stationary output data and has low sensitivity to signal noise.
机译:在这项工作中,提出了一种基于熵激励的两步结构损伤识别方法。测量信号通过小波分组变换分解,并且基于信息熵理论获得小波熵。在第一步中,使用无损坏和损坏的条件中的小波熵计算的损坏警报指数用作削减个人控制图表的样本,以报警结构损坏。在第二步中,通过计算在未损坏和损坏的条件下小波熵的曲率差的差异构成的损坏定位指标被馈送到后传播神经网络以识别结构损坏位置。实现了地震激励下的海上平台的数值模拟和振动台模型试验,以验证提出的两步结构损伤识别方法的可行性。结果表明,该方法仅需要非静止输出数据,并且对信号噪声具有低灵敏度。

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