Gearbox fault feature detection based on adaptive parameter identification with Morlet wavelet

Localized defects in rotary machinery parts tend to result in impulse response in vibration signal, whose parameters provide a potential approach for localized fault diagnosis. A method combining the Morlet wavelet and Correlation Filtering, named Cyclic Morlet Wavelet Correlation Filtering (CMWCF), is proposed for identifying both the impulse response parameters and the cyclic period. Simulation study on cyclic impulse response signal with different SNR showed that CMWCF is effective in identifying the impulse response parameters and the cyclic period. Applications in gearbox vibration parameter identification for localized fault diagnosis showed that CMWCF is effective in identifying the parameters, and thus provides a feature detection method for gearbox fault diagnosis.