Abstract: The fault feature extraction based on wavelet transform technique is studied in depth，which is applied to fault diagnosis of rotary machine.A new fault feature extraction method based on singularity detection and the modular maximum using continuous wavelet transform analysis is put forward.Research on combining the resolution method and singularity theory can find that wavelet transform is very propitious to depict the whole and local signal.Utilizing the characteristics of wavelet transform resolving and constructing the signal，the information about frequency band pointedly can be chosen and the noise interference can be reduced.At the same time，the typical characteristics of crack faults can be effectively extracted through frequency spectrum analysis of constructing signals.The results show that it is effective to diagnose the non-steady of rotor by wavelet transform.

摘要： 就小波分析技术在旋转机械故障诊断应用中的故障特征提取问题进行了深入研究，提出了基于小波奇异性及小波变换模极大值的故障特征提取方法，通过对故障信号与小波变换的多分辨率方法以及奇异性理论相结合进行研究，发现小波分析便于对信号的总体和局部进行刻画；利用小波变换对信号的分解和重构特性，可有针对性地选取有关频带的信息以及降低噪声干扰，通过对重构信号的频谱分析能更有效地提取裂纹故障的典型特征。结果表明，对于旋转机械的非平稳信号来说，利用小波变换方法进行故障诊断是行之有效的。