A Compound fault diagnosis for rolling bearings method based on blind source separation and ensemble empirical mode decomposition.

ABSTRACT: A Compound fault signal usually contains multiple characteristic signals and strong confusion noise, which makes it difficult to separate week fault signals from them through conventional ways, such as FFT-based envelope detection, wavelet transform or empirical mode decomposition individually. In order to improve the compound faults diagnose of rolling bearings via signals' separation, the present paper proposes a new method to identify compound faults from measured mixed-signals, which is based on ensemble empirical mode decomposition (EEMD) method and independent component analysis (ICA) technique. With the approach, a vibration signal is firstly decomposed into intrinsic mode functions (IMF) by EEMD method to obtain multichannel signals. Then, according to a cross correlation criterion

SUBMITTER: Wang H 

PROVIDER: S-EPMC4188612 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature