Multi-stages helical gearbox fault detection using vibration signal and Morlet wavelet transform adapted by information entropy difference

Although the wavelet analysis is a powerful tool and has been widely used for the vibration signal based gearbox fault diagnosis, there are some limitations that undermine its application. The results of the wavelet transform do not possess time invariant property, which may result in the loss of useful information and decrease the accuracy of fault diagnosis. Other limitations in wavelet transform are the selection of the suitable threshold and the wavelet function. A main challenge of wavelet analysis is the adaptability of the parameters of the mother wavelet to the time variance of the given signal. To overcome this deficiency, an adaptive Morlet wavelet transform method based on the information entropy optimization is proposed in this study. The proposed wavelet transform method is applied for analyzing the vibration signals to detect and diagnose the faults of a helical gearbox. A comparative study which used the kurtosis maximization to adapt the wavelet parameters are also carried out to evaluate the proposed method.