Performance enhancement of ensemble empirical mode decomposition

Ensemble empirical mode decomposition (EEMD) is a newly developed method aimed at eliminating mode mixing present in the original empirical mode decomposition (EMD). To evaluate the performance of this new method, this paper investigates the effect of two parameters pertinent to EEMD: the amplitude of added white noise and the number of ensemble trials. A test signal with mode mixing that mimics realistic bearing vibration signals measured on a bearing test bed was developed to enable quantitative evaluation of the EEMD and provide guidance on how to choose the two parameters appropriately for bearing signal decomposition. Subsequently, a modified EEMD (MEEMD) method is proposed to reduce the computational cost of the original EEMD method as well as improving its performance. Numerical evaluation and systematic study using vibration data measured on an experimental bearing test bed verified the effectiveness and computational efficiency of the proposed MEEMD method for bearing defect diagnosis.