基于小波分析和Hilbert变换的滚动轴承故障诊断

Fault diagnosis of rolling bearings based on wavelet analysis and Hilbert transform

针对滚动轴承故障信号的非平稳和调制特点,使用小波分析对包含故障信息的信号进行分解、重构。应用Hilbert变换进行解调和细化频谱分析,提取了故障特征频率,判断轴承故障模式。小波分析和希尔伯特(Hilbert)变换结合对滚动轴承局部损伤故障的检测是有效的。

For the unstable and modulation features of rolling bearing fault signals, the signal containing fault information is decomposed and reconstructed by using wavelet analysis. Hilbert transform was applied to demodulate and subdivide the frequency analysis, extracting the characteristic frequency of fault signals, and judging the mode of the bearing fault. It is found that the combination of wavelet analysis and Hilbert transform is effective in detecting local damage of rolling bearings.