Weak Signal Detection Method Based on Novel Composite Multi-stable Stochastic Resonance

Abstract

Abstract The weak signal detection method based on stochastic resonance (SR) is a method to extract and identify the weak characteristic signal submerged in strong noise by using the noise energy transfer mechanism. A novel composite multi-stable SR(NCMSR) model combining GP model and improved bistable model is proposed in this paper. Compared with the traditional multi-stable SR method, all the parameters in the novel model have no symmetry, the output signal-to-noise ratio (SNR) can be optimized and the output amplitude can be improved by adjusting the system parameters. The model retains the advantages of continuity and constraint of Gaussian potential (GP) model and the advantages of improved bistable model without output saturation, the NCMSR model has a higher utilization of noise. Taking the output SNR ratio as the index, the weak periodic signal is detected based on NCMSR model in Gaussian noise and α noise environment respectively, and the detection effect is good. The application of NCMSR to the actual detection of bearing fault signals can realize the fault detection of bearing inner race and outer race.The outstanding advantages of this method in weak signal detection are verified, which provides a theoretical basis for industrial practical application.