Early detection of defects in gear systems using autocorrelation of morlet wavelet transforms

english

2022

volume 68, issue 1

autocorrelation   early fault diagnosis   gear systems   morlet wavelet transforms   scalograms   vibration analysis

Univerza v Ljubljani, Fakulteta za strojništvo
(Obvezni izvod spletne publikacije)

In recent days, supervision task of industrial systems is vital and the prediction of damages avoids many problems. If any system' defects are not detected in early stage, this system will continue in degradation and may be causing serious economic loss. In the industrial systems, the defects change the behavior and characteristics of the vibration signal. This change is the signature of the presence of the defect. The challenge is the early detection of this signature. The difficulty of the vibration signal is that the signal is very noisy, non-stationary and non-linear. In this study, a new method for early defect detection of a gear system is proposed. This approach is based on vibration analysis by trying to find defect's signature in the vibration signal. This approach has used the Autocorrelation of Morlet Wavelet Transforms (AMWT). Firstly, the simulation validation is introduced. The validation of the approach on real system is given in the second validation part.

23.02.2022