中文摘要：

根据滚动轴承的振动故障特征,介绍了一种新的基于经验模态分解（Empirical Mode Decomposition,EMD）与同态滤波解调相结合的滚动轴承故障诊断方法.EMD可将轴承故障信号分解成若干个IMFs（Intrinsic Mode Functions）,各个IMF突出了原始信号的某些局部特征.再对某些IMFs有针对性地进行同态滤波解调,提取了轴承内圈故障特征频率,诊断出轴承内圈严重磨损故障.同时,为更突出同态滤波解调方法的优越性,与Hilbert包络进行了对比分析.仿真与应用结果表明,同态滤波解调方法要优于Hilbert包络法.

英文摘要：

According to the vibration fault characteristics of rolling elements bearing, a fault diagnosis method based on empirical mode decomposition （EMD） and homomorphic filtering demodulation was introduced. The vibration signal of a rolling element bearing was decomposed into several intrinsic mode functions （IMFs） with EMD method,and every IMF highlights some local features of the original signal. Then, the characteristic frequency of bearing inner ring was extracted from some IMFs by using homomorphie filtering demodulation,and inner race severe wear was diagnosed. At the same time, in order to give prominence to the superiority of the homomorphic filtering demodulation method, a comparison with the Hilbert envelope method was completed. The simulative and experimental results indicate that the effect of homomorphie filtering demodulation is superior to Hilbert envelope demodulation.