Study on the optimal stochastic resonance of different bistable potential models based on output saturation characteristic and application

Stochastic resonance (SR) is a kind of physical phenomenon that makes use of noise energy to enhance the signal, but the problem of output saturation generally exists in classcial bistable stochastic resonance (CBSR). To overcome this shortcoming, a few unsaturation models have been established. In view of this, the present study is committed to analyzing and comparing the unsaturation ability of different models more systematically and comprehensively. Firstly, several new piecewise bistable potential models are constructed to supplement the existing unsaturation models and their unsaturation is proved. Then, the higher output signal-to-noise ratio (SNR) of simulated signals shows that the models with linear sides have better unsaturation characteristic and frequency adaptability. Finally, the output SNR and amplitude are chosen as the comprehensive index for evaluating the enhancement performance. Each mod el is applied to process analog and fault signals. The results show that unsaturation capability of piecewise linear bistable stochastic resonance system is best, which is demonstrated again from the optimal output SNR of particle swarm optimization (PSO) algorithm. (C) 2020 Elsevier Ltd. All rights reserved.