Abstract:The testing equipment of fault gear system was established. By measuring the vibration signals of the gear system at different rotating speed for different faults, the testing signals were obtained. The features were extracted from four kinds of signals: signal with no fault, signal with tooth root crack, signal with pitch circle crack and signal with tooth face abrasion. As the signals of the transmission system are often corrupted by noise, so it take wavelet de-noising by threshold with Empirical Mode Decomposition (EMD) as a signal preprocessing, and the preprocessed signals are investigated by using Time- Frequency Analysis. The results show that wavelet de-noising by threshold with EMD is better than using wavelet de-noising by threshold , and it can improve the SNR(Signal-to-Noise Ratio)to extract fault features better. After signal preprocessing with EMD, the results of time-frequency analysis show that the proposed method is effective for diagnosis of different kinds of fault, such as tooth root crack, pitch circle crack and tooth face abrasion.
邵忍平;曹精明;李永龙. 基于EMD小波阈值去噪和时频分析的齿轮故障模式识别与诊断[J]. , 2012, 31(8): 96-101,.
SHAO Ren-ping;CAO Jing-ming;LI Yong-long. Gear fault pattern identification and diagnosis using Time - Frequency Analysis and wavelet de-noising based on EMD . , 2012, 31(8): 96-101,.