基于时延自相关降噪与局部特征尺度分解的齿轮故障诊断

Gear fault diagnosis based on delayed autocorrelation denoising and local characteristic-scale decomposition

摘要:

In order to detect the gear fault accurately, a mode based on autocorrelation denoising and local characteristic-scale decomposition（LCD） was proposed. The autocorrelation function of the vibration signal of gear box was calculated，and the low delay time of [-20,20] and high delay time of last 20 points of the autocorrelation function were set to zeros. The delayed autocorrelation denoising signal was decomposed into some intrinsic mode components（ISC） by LCD, and the ISC included the mesh frequency were selected as the effective component. The fault was detected by the envelope aptitude spectrum. The analysis of broken tooth of gear fault data shows that the increase of the signal to noise ratio（SNR）can be 8.0963dB，the method can realize the occurrence of the fault effectively, can also detect the type of the gear fault, the method can effectively support fault diagnosis.

Abstract:

In order to diagnose the gear fault accurately, a mode based on autocorrelation denoising and local characteristic-scale decomposition（LCD） was proposed. The autocorrelation function of the vibration signal of gear was calculated，and the low delay time of [-20,20] and high delay time of last 20 points of the autocorrelation function were set to zeros. The delayed autocorrelation denoising signal was decomposed into some intrinsic mode components（ISC） by LCD, and the ISC included the mesh frequency were selected as the effective component. The fault was detected by the envelope aptitude spectrum. The analysis of broken tooth of gear fault data shows that the increase of the signal to noise ratio（SNR）can be 8.0963dB，the method can realize the occurrence of the fault effectively, can also diagnose the type of the gear fault, the method has certain engineering value.