基于小波变换在线结构损伤检测分析研究

传统的傅立叶变换只能确定一个函数奇异性的整体性质，而难以确定奇异点在空间的位置及分布情况，小波变换具有空间局部化性质，利用小波变换来分析信号的奇异性及奇异性位置和奇异度的大小是比较有效的，在结构发生损伤时，结构的刚度发生了变化，因此结构动力响应的在线监测信号相应的发生了间断点，由于小波分析具有刻划信号局部特征的作用，通过对结构响应进行小波分解以后可以确定结构是否出现损伤以及确定损伤发生的时刻。

ANALYSES OF ONLINE STRUCTURAL DAMAGE DETECTION BASED ON WAVELET TRANSFORM

Traditional Fourier transform is almost impossible to point out the singularity location and distribution of a function with singularity. However, wavelet transform has the characteristic to pick out the singularity from the whole signal with singular property. A wavelet-based approach is proposed for online structural damage detection. In the case of abrupt damage, occurrence of the damage and the moment when it occurs can be determined by the wavelet decomposition of those data. It shows that structural damage or a change in system stiffness may be detected by spikes in the details of the wavelet decomposition of the response data, and the locations of these spikes may accurately indicate the moments when the structural damage occurred.