Fault diagnosis of direct-driven electromechanical actuator based on ensemble empirical mode decomposition

Based on the ensemble empirical mode decomposition(EEMD), an fault diagnosis method was proposed to diagnose complex faults of the direct-driven dual-redundancy electromechanical actuator (DDDR-EMA). By adding different finite amplitude Gaussian white noises to the signal, EEMD keep the signal continuous in different time span. EEMD well solved the problem of mode mixing involved in the empirical mode decomposition, as well as kept adaptation. The vibration signal from the fault diagnosis experiment of air-borne DDDR-EMA was decomposed by EEMD, a group of the intrinsic mode functions were obtained, and several methods were used to extract fault features from different signal frequency bands. The experimental result verified that EEMD can improve the analysis precision of fault signal, and can diagnose complex faults of airborne DDDR-EMA more accurately comparing with EMD.