Feature Extraction of Nonstationarity Vibration Signal Based on Wavelet Decomposition

Nonstationarity feature representation and extraction method based on the wavelet decomposition and demodulation techniques are studied. Some component in special frequency band included faulty information is selected to reconstruct by wavelet analysis. The mono-components with fault feature in different frequency band would be captured and separated out. The demodulated and spectrally signals are analyzed by Hilbert transform, and it presents an approach to get the characteristic frequency of fault signals. So what kind of the fault mode is can be estimated. For the nonstationarity and modulation feature of rolling bearing fault signals, wavelet decomposition combined with Hilbert transform is effective in identifying the localized defects of rolling bearings.