基于经验小波变换的结构损伤特征提取

Feature Extraction of Structural Damage Based on Empirical Wavelet Transform

为了更好地提取结构损伤特征信息,提出了基于经验小波变换(EWT)和希尔伯特变换的振动信号分析方法。首先,用EWT对结构损伤加速度振动信号的频谱进行自适应分割,然后提取不同的调幅-调频(A M-AF)分量,最后对其进行希尔伯特变换,获取瞬时频率。仿真和工程实验结果表明:经验小波变换相对于经验模态分解(E MD)可以更好地提取信号的各个特征分量,为信号时频处理奠定基础,且分解的模态少,不存在虚假模态。同时,EWT与Hilbert的结合更进一步验证了该方法的有效性。

In order to extract the structural damage characteristic signals better,a vibration signal analysis method based on the empirical wavelet transform(EWT)and Hilbert transform is proposed.Firstly,the frequency spectrum of the acceleration vibra tion signal of the damaged structure is segmented adaptively with EWT,then to extract the different AM-AF components,a nd last Hilbert transform is performed to obtain instantaneous frequency.Simulation and engineering experiment results show that compared with empirical mode decomposition(EMD),the empirical wavelet transform can extract each characteristic component of the signal better,w hich lays a foundation for signal time-frequency processing and analysis,and the mode of decomposition is less,and there is no false mode.Meanwhile,the effectiveness of this method is verified by the combination of EWT and Hilbert.