Abstract: The vibration signals generated by the gear partial failure show non-stationary and non-periodic.The sideband spectrum near the gear mesh frequency,the second and the third harmonics of the corresponding frequency spectrum all grow significantly.Because principles of prediction and update are closely related to the fault information,the vibration signals are first analyzed and preprocessed by lift wavelet,and the wavelet basis function selection is replaced by designing the predictor and updater during the signal decomposition process,which can significantly raise the feature extraction efficiency.The high frequency signal is demodulated by Hilbert transformation,the conventional vibration components are removed but only fault information retained in its envelope spectrum,and the faults are located after the fault feature frequency can be identified effectively.An illustration verifies that the Hilbert modulation technology based on lifting wavelet transform is fully competent for gear fault diagnosis.