Abstract
A method of Rotating Machinery fault feature extraction based on wavelet transform and Hilbert demodulation is been studied. On the basis of rotating machinery fault mechanism and spectral characteristics, wavelet transform is used to be decompose the vibration acceleration signals of bearing faults into different frequency bands, Which is then used to achieve accurate fault information by Hilbert demodulation. The result shows the method can effectively improve the frequency resolution and realize accurate extraction of fault feature, and it has certain practical value for industrial production of rotating machinery faults diagnosis when applied to the production industry. Key words: Rotating Machinery; bearings; Wavelet algorithm; Hilbert demodulation
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