基于局部均值分解和峭度图的滚动轴承包络分析方法

Roller bearing envelope analysis method based on local mean decomposition and kurtogram

提出了基于局部均值分解(local mean decomposition,LMD)和峭度图(kurtogram)的滚动轴承包络分析方法.该方法中,原始滚动轴承故障振动信号通过LMD进行自适应的频率成分分离和初步降噪,包络分析中带通滤波器的参数通过峭度图客观地提供,从而提高滚动轴承包络分析的准确度.通过对滚动轴承仿真信号以及实验信号的分析,结果表明:在低信噪比情况下,LMD可以自适应分离出滚动轴承的固有振动成分,峭度图可以自动确定包络分析中带通滤波器的参数,与传统包络分析比较,所提方法能更加清晰准确地提取滚动轴承的故障特征.

Roller bearing envelope analysis method based on local mean decomposition （LMD） and kurtogram was proposed. In this method, the original roller bearing fault vibra- tion signal was decomposed into a set of frequency components and preliminary reduced noi- ses adaptively by LMD, and the parameters of band-pass filter in envelope analysis were pro- vided objectively by kurtogram, thus the envelope analysis accuracy for roller bearing can be enhanced. The analytical results from roller bearing simulation signals and experiment sig- nals indicate that the natural vibration components of roller bearing can be separated by LMD adaptively and the parameters of band-pass filter in envelope analysis can be determined by kurtogram automatically in low signal-to-noise ratio. Compared with traditional envelope a- nalysis, the proposed method can extract the fault features of roller bearing more clearly and accurately.