Gear tooth health state monitoring based on morphological filtering and Wavelet transition

Gear box is one of the most important transmission components in mechanical systems. Fault diagnosis and state monitoring techniques for gear box have been studied for years. But in practical, gear box usually works under varying work conditions which has not been considered in most studies. In this paper, a novel state monitoring method is proposed for monitor gear box work with varying conditions. The vibration signal is de-nosied by morphological filtering. Then gear-mesh frequency band is extracted by wavelet transform. Dimensionless time indexes are used as state monitoring features. A regularization method is proposed to calculate gear tooth health index. Simulate and experiment signal are presented to illustrate the effectiveness of the method. The result indicates that, morphological filtering is an efficient method to de-nosie the vibration signal; wavelet transform can extract the gear-mesh frequency band; gear tooth health index can monitor gear tooth state based on vibration signal.