رزونانس تصادفی در یک سیستم بازپخش بازخورد زمانی و کاربرد آن در تشخیص خطا

Stochastic resonance (SR) phenomena in a time-delayed feedback tristable system driven by Gaussian white noise are investigated by simulating the potential function, mean first-passage time (MFPT), and signal-to-noise ratio (SNR) of the system. Through the use of a short delay time, the generalized potential function and stationary probability density function (PDF) are obtained. The delay feedback term has a significant effect on both equations, and that the parameters b, c, and d have different effects on the three wells of the potential function. The MFPT is calculated, which plays an extremely important role in research on particles escape rates. We find that the delay feedback term can affect the noise enhanced stability (NES). In addition, the SR characteristics are studied by the index of SNR. The simulation demonstrates that SNR is a non-monotonic distributed and that the peak SNR value can be attained by adjusting the appropriate parameters. Finally, the proposed theory is combined with a variable step method and applied to the detection of high frequencies in experiments. The result indicates that the fault frequency can be identified, and that the energy of the fault signal can be enhanced under suitable delay feedback parameters.