Novel Woods-Saxon stochastic resonance system for weak signal detection

We propose a joint exponential function and Woods–Saxon stochastic resonance (EWSSR) model. Because change of a single parameter in the classical stochastic resonance model may cause a great change in the shape of the potential function, it is difficult to obtain the optimal output signal-to-noise ratio by adjusting one parameter. In the novel system, the influence of different parameters on the shape of the potential function has its own emphasis, making it easier for us to adjust the shape of the potential function. The system can obtain different widths of the potential well or barrier height by adjusting one of these parameters, so that the system can match different types of input signals adaptively. By adjusting the system parameters, the potential function model can be transformed between the bistable model and the monostable model. The potential function of EWSSR has richer shapes and geometric characteristics. The effects of parameters, such as the height of the barrier and the width of the potential well, on SNR are studied, and a set of relatively optimal parameters are determined. Moreover, the EWSSR model is compared with other classical stochastic resonance models. Numerical experiments show that the proposed EWSSR model has higher SNR and better noise immunity than other classical stochastic resonance models. Simultaneously, the EWSSR model is applied to the detection of actual bearing fault signals, and the detection effect is also superior to other models.