摘要
通过典型信号的MATLAB仿真,针对滚动轴承故障信号的非平稳性特点,结合峭度直方图和小波函数的时-频分析方法,对包含滚动轴承故障信息的信号进行了小波分解和重构,对重构后的细节信号作Hilbert包络并进行谱分析,从而有效地把轴承中的故障信息成分识别出来。
Combined with the kurtosis of the histogram and wavelet time-frequency analysis,MATLAB simulation of a typical signal for rolling bearing fault signal of non-stationary characteristics is used to decompose and reconstruct the signal contains the information on the bearing fault with the wavelet.Hilbert envelope and spectral analysis are carried out to reconstructed detail signals,which identifies bearing fault information elements effectively.
出处
《机械工程师》
2012年第2期30-32,共3页
Mechanical Engineer
关键词
小波分析
滚动轴承
故障诊断
wavelet analysis
rolling bearing
fault diagnosis
