Abstract: Aiming at the analysis of the vibration characteristics of aeroengine rotor, an improved blind source separation algorithm based on cumulant independent component analysis (ICA) is proposed. The new algorithm is used to separate the rotor vibration signal and identify the rotor fault types. The effectiveness of this algorithm is verified by the aeroengine rotor vibration signal simulation. Comparing with the existing algorithms based on second-order cumulants and high-order cumulants, the new method improves the performance index and the signal similarity coefficient. This algorithm is used to separate the vibration signal collected by the engine rotor platform and the rotor fault is set as the outer ring fault. The vibration signal measured by this algorithm has a higher recognition, and the fault types of rotor vibration can be identified.

Key words: aeroengine, blind source separation, rotor vibration, cumulant