基于EMD与对数能量的滚动轴承故障诊断方法

Rolling element bearing diagnostics based on EMD and logarithm of short-time energy

滚动轴承在发生损伤时,产生周期性脉冲振动,提取冲击振动的周期特征是故障诊断的关键。为了提取滚动轴承的故障特征频率,根据滚动轴承的振动响应信号特征,提出基于经验模态分解(EMD)和对数能量的故障特征频率提取方法。首先通过经验模态分解找到包含故障信息的本征模态函数(IMF),然后对IMF的短时能量进行积分并取自然对数,获得信号的对数能量变化曲线,最后通过对曲线的谱分析,找到轴承的故障特征频率。仿真和实验数据验证了该方法的有效性,并和Hilbert包络法与能量算子法进行了对比,表明该方法能更显著地突出故障特征频率。

Studies show that defected rolling element bearing brings out periodic impact force.Therefore,extracting the cyclic characteristics of the impact force is of significant importance for the bearing diagnosis.In the present study,a novel fault characteristic frequency extraction method is proposed based on the empirical mode decomposition(EMD)and the logarithm of the short-time energy.Firstly,the intrinsic mode function(IMF)containing the fault is sifted by the empirical mode decomposition and correlation coefficient.Then the short-time energy of the IMF is integrated and the natural logarithm is considered to obtain the energy curve.Finally,the fault characteristic frequency of the bearing is found by the spectral analysis of the energy curve.The effectiveness of the proposed method is verified by simulation and experiments.Comparison of the proposed method with Hilbert envelope method and energy operator method shows that the proposed method can highlight the fault characteristic frequency.