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.
出处
《煤矿机械》
北大核心
2011年第8期266-268,共3页
Coal Mine Machinery
关键词
小波变换
突变点
滚动轴承
wavelet transform
mutation
rolling bearing