基于EEMD、度量因子和快速峭度图的滚动轴承故障诊断方法

Fault diagnosis method of rolling element bearings based on EEMD,measure-factor and fast kurtogram

基于EMD、谱峭度以及包络分析的滚动轴承故障诊断方法,提出了改进的基于EEMD、度量因子和快速峭度图的诊断方法。该方法首先将故障信号进行EEMD分解得到一组IMFs,然后用度量因子筛选出最能表征故障信息的IMF分量重构信号,再用快速峭度图构造最优带通滤波器,最后将滤波后的重构信号进行包络分析并将包络谱与轴承故障特征频率进行比较,从而诊断出具体故障。滚动轴承的内圈故障仿真数据以及工程实测数据均很好地验证了提出的改进方法的有效性,说明其具有良好的应用前景。

On the basis of fault diagnosis of rolling element bearings with signal processing methods,such as,EMD,spectral kurtosis and envelope analysis,an improved methodology based on EEMD,measure-factor and fast kurtogram was proposed.Firstly,fault signals were decomposed into a group of intrinsic mode functions（IMFs） with ensemble empirical mode decomposition（EEMD）.Secondly,the IMF best representing the fault information was selected to reconstruct signals using the measure-factor based on distance.Thirdly,an optimal band-pass filter was constructed with the central frequency and bandwidth generated using the fast kurtogram.Finally,the specific fault was determined by comparing the envelope spectrum of the filtered signals with the fault characteristic frequency of rolling element bearings.The effectiveness of the proposed methodology was demonstrated with the simulated data and the actual signals measured of inner races,and the improved method had a good prospect for its application in rolling element bearing diagnosis.