基于局部均值分解和峭度图的滚动轴承包络分析方法

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 and kurtogram

Roller bearing envelope analysis method based on local mean decomposition (LMD) and kurtogram was proposed. In this method, the original roller bearing fault vibration signal was decomposed into a set of frequency components and preliminary reduced noises adaptively by LMD, and the parameters of band-pass filter in envelope analysis were provided objectively by kurtogram, thus the envelope analysis accuracy for roller bearing can be enhanced. The analytical results from roller bearing simulation signals and experiment signals 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 analysis, the proposed method can extract the fault features of roller bearing more clearly and accurately.