小波和EMD的滤波特性在轴承故障诊断中的比较

Comparison of Wave Filtering by Wavelet Transform and EMD in Fault Diagnosis of Rolling Bearings

通过仿真实验将小波变换和经验模态分解(EMD)方法分解信号的能力进行了比较,并将这种滤波特性应用于旋转机械的故障诊断中,结合包络谱分析,比较了两者对于滚动轴承内圈故障的诊断效果.仿真及轴承实验结果表明EMD方法在滤波的自适应性、分解结果的准确性以及诊断效果等方面均具有优势,更重要的是它分离出的主要分量物理意义明确,反映了信号的真实内涵.

Wavelet transform and empirical mode decomposition method were compared on the ability of decomposing signals by a simulation experiment first, and then were used in fault diagnosis of rotating machinery as well as envelope spectrum analysis method to compare the diagnosis effect of inner race faults of roiling bearings. The results of the two experiments show that EMD is superior to the Wavelet in the fields of filtering adaptability, accuracy and diagnosis effect, and more importantly the main components decomposed by it are full of real meanings