基于小波分析的滚动轴承故障诊断  

Rolling Bearing Fault Diagnosis Based on Wavelet Analysis

作　　者：刘正平[1] 王彦强[1] 

机构地区：[1]华东交通大学机电工程学院,南昌330013

出　　处：《煤矿机械》2011年第8期266-268,共3页Coal Mine Machinery

摘　　要：通过典型信号的MATLAB仿真讨论了小波在检测信号突变点时的选取原则。针对滚动轴承故障振动信号,先进行小波消噪,再进行小波分解与重构,对重构后的细节信号作Hilbert包络并进行谱分析,从功率谱中可清晰地识别出滚动轴承故障特征频率。The selecting principle of which wavelet in detection signal mutation was discussed by MATLAB simulation to typical signal. According to fault vibration signals of rolling bearing, adopting wavelet de-noising firstly, then carring on wavelet decomposition and reconstruction, and Hilbert envelope and spectral analysis are carried out to reconstructed detail signals. Fault characteristic frequency of rolling bearing can be clearly identified from the power spectrum.

关 键 词：小波变换 突变点 滚动轴承 

分 类 号：TH133.23[机械工程—机械制造及自动化]