A Novel Type of Stochastic Resonance Potential Well Model and Its Application

For a stochastic resonance system, the characteristics of the nonlinear model have an important influence on the output. To further improve the enhanced detection of stochastic resonance, a novel potential well stochastic resonance model is constructed to simultaneously solve the problem of the output saturation and high barrier in the classical bistable model. Analytical expressions of the Kramers rate and output signalto-noise ratio are presented, and weak signal detection is theoretically analyzed. The performance of the system based on the novel potential well model is simulated and analyzed. Finally, the proposed model is used for the detection of multiple high-frequency weak signals in an α-stable noise environment and a practical bearing fault signal. The simulation and experimental results demonstrate that the output of the stochastic resonance system proposed in this paper exhibits a large output signal-to-noise ratio and a high spectral peak at the characteristic frequency.