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

来源：计算机测量与控制杂志2023年第9期北京时间：

作者：崔伟成,刘林密,杨诗寓,宗富强

单位：海军航空大学

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.

关键词：自相关函数，局部特征尺度分解，有效分量，齿轮故障检测