一种基于提升小波变换的故障特征提取方法及其应用

FAULT FEATURE EXTRACTION METHOD USING THE LIFTING WAVELET TRANSFORM AND ITS APPLICATIONS

为了实现旋转机械的早期故障诊断和预示,提出一种采用滑动窗提取瞬态冲击故障特征的方法。该方法以提升小波变换为基础,采用提升模式构造具有冲击特征的小波,用来获取振动信号中的冲击故障特征。然后,采用一种基于回转周期的滑动窗处理小波分解的细节信号,提取每个滑动窗的模最大值作为故障的时域特征。该方法在转子早期碰摩故障和齿轮箱滑动轴承的轴瓦损坏故障的应用中取得了较满意的效果。

In order to diagnose and prognose incipient fault of rotating machinery,a new feature extraction method using sliding window is proposed to extract transient impacts from original signals.Firstly,on the basis of the lifting wavelet transform,a wavelet with impact characteristics,constructed by using the lifting scheme,is employed to reveal the impulsive fault feature from the original signals.Then a sliding window,designed according to the revolution cycle of rotating machinery,is applied to process detail signals of decomposition.Modulus maxima obtained from these windows are extracted as expected features in the time domain.An incipient impact malfunction and a bush broken fault of a plain bearing have been successfully detected by using the proposed method.