Fault diagnosis of ball bearing based on EEMD morphological spectrum and support vector machine

Aiming at fault diagnosis of inner race,outer race and rolling element of ball bearing,a fusion method based on ensemble empirical mode decomposition(EEMD),morphological spectrum,and support vector machine(SVM) was proposed. Firstly,the vibration signal was decomposed by EEMD to get several intrinsic mode functions(IMFs) which have physical meanings. Secondly,the IMF which was rich in fault features was selected as the data source based on power maximum of IMFs. Thirdly,morphological spectrums in some scales of the IMF were extracted,and then they were adopted as the fault eigenvectors. Lastly,the three faults of ball bearing faults were diagnosed by the use of SVM. The conclusion is that the proposed method can diagnosis the faults of the ball bearing with high accuracy.