Gear fault pattern identification and diagnosis using Time-Frequency Analysis and wavelet threshold de-noising based on EMD

The testing equipment of a fault gear system was established.By measuring vibration signals of a gear system at different rotating speed for different faults,the test was conducted.The features were extracted from four kinds of signals including signals with no fault,those with tooth root crack,those with pitch circle crack and those with tooth face abrasion.As the signals of the transmission system were often corrupted by noise,so they were preprocessed using the wavelet threshold de-noising based on empirical mode decomposition(EMD).The preprocessed signals were investigated using time-frequency analysis.The results showed that the wavelet threshold de-noising based on EMD is better than the wavelet threshold de-noising,and the former can improve the signal-to-noise ratio(SNR) to extract fault features better.After signal preprocessing based on EMD,the results of time-frequency analysis showed that the proposed method is effective for diagnosis of different fault kinds,such as,tooth root crack,pitch circle crack and tooth face abrasion.