Stochastic resonance in a single-well potential and its application in rolling bearing fault diagnosis

In this paper, a single-well model based on the piecewise function and classical bistable stochastic resonance (CBSR) is proposed. The steady state probability density of particles and mean first passage time in the model are calculated. The output characteristics and performance of the proposed model are analyzed through numerical simulation. On the basis of CBSR and the proposed model, an adaptive system is established (ACSSR) to generate the highest gain of signal-to-noise ratio (SNR_g). Finally, the effectiveness of ACSSR in weak signal detection is verified with both simulated and experimental input signals. The results indicate that the ACSSR could detect the defect signal correctly and improve the SNR_g.