UNSYNCHRONIZED INPUT GEAR DAMAGE DIAGNOSIS USING TIME AVARAGING AND COMPLEX SHIFTED MORLET WAVELET

Wavelet analysis is one of the important tools in analyzing and feature extraction of transient and non-stationary signals. Wavelet has been used widely in condition monitoring of mechanical systems and fault diagnosis of gearboxes. In most cases, the signal to noise ratio (SNR) is so low that feature extraction of signal components is very difficult in practical situations and in addition of this. One solution of this problem is applying signal time averaging (TA) techniques in time domain for denoising of signal, but using this method is only possible when gearbox input shaft rotation is constant or synchronized. In this paper a new noise canceling method based on TA method for unsynchronized input, have been developed, then complex Morlet wavelet (CMW) have been implemented for feature extraction and diagnosis of different kind of local gear damages. The proposed method has been implemented on a simulated signal and real test rig of YAMAHA motorcycle gearbox. Both simulation and experimental results have proved that the method is very accurate in analysis of the signal and fault diagnosis of gearbox.

Keywords:

Morlet Wavelet , Time Averaging Method , Gearbox Fault Diagnosis , Unsynchronized Input