Fault diagnosis for rolling bearing based on EEMD and complexity dimension

Aiming at the nonlinear characteristics of the rolling bearing operation, a method based on the combination of EEMD and complexity is proposed to analyze the bearing fault. Firstly, EEMD decomposition is performed on the vibration signals under different operating states such as normal rolling bearing, inner ring fault, outer ring fault, and cage fault. Next, the kurtosis theory is used to filter out effective IMF under various operating conditions. Finally, the complexity analysis and comparison of the corresponding layer IMF in each operating state are performed in turn. The experimental results show that complexity is a characteristic parameter of the state of the system represented by the signal. This method can accurately and effectively identify the running state of the rolling bearing.