A composite fault diagnosis method of induction motor based on blind signal processing

When the stator winding fault and the roller bearing fault occur simultaneously, only the simultaneous acquisition of the stator current signal and the vibration signal is effective for the diagnosis of the composite faults because the mechanism of fault is different. A composite fault diagnosis method based on blind Least Mean Square was proposed to extract the fault signal from the low frequency vibration signal of the induction motor. Utilizing this method the fault signal was denoised and the characteristic components for fault detection can be identified effectively. The stator phase short circuit fault and the outer raceway fault were simulated in experiment platform. Experimental results show that the proposed method is effective to extract the fault signal and improve the signal-to-noise ratio, and the composite fault diagnosis by using the vibration signal is feasible.