Fault diagnosis method of inter-shaft bearing based on adaptive bistable stochastic resonance

In view of the problem that the aeroengine inter-shaft bearing fault signal is weak and the fault feature extraction is difficult, an adaptive bistable stochastic resonance (BSR) fault diagnosis method based on tolerance genetic algorithm (TAGA) of inter-shaft bearing was proposed. The tolerance theory was introduced into the traditional adaptive genetic algorithm, and a TAGA was established. The structural parameters a and b of the BSR system were optimized by the TAGA. The fault signal was processed by adaptive BSR system. In order to verify the effectiveness of the proposed method, an inter-shaft bearing fault simulation test rig was built, and the inner ring and outer ring fault simulation experiments of the inter-shaft bearing were carried out. The simulation signal and the experimental signal were processed separately by the method established. The results show that the proposed method can enhance the fault signal and the ability of fault feature frequency extraction. After adaptively optimizing the structural parameters, the error between the extracted fault feature frequency and the theoreticalvalue of the fault frequency is less than 0.1%.