Stochastic Resonance Effect in Segmented Underdamped Asymmetric Tristable System and Its Application in Weak Signal Detection Research

This paper proposes a novel segmented underdamped asymmetric tristable stochastic resonance (SUATSR) system. The research involves deriving the equivalent potential function for the underdamped background and analyzing the system’s output saturation. Results demonstrate that the SUATSR system effectively mitigates output saturation issues, enhancing the output amplitude. The study also employs adiabatic approximation theory to derive theoretical expressions for mean first passage time (MFPT) and spectral amplification (SA). The paper discusses the impact of varying system parameters on these performance indicators. Numerical simulations of the classical tristable stochastic resonance (CTSR), segmented underdamped tristable stochastic resonance (SUTSR) and SUATSR systems validate the theoretical derivations. Furthermore, the three systems are applied to different bearing fault tests and optimized using the adaptive genetic algorithm (AGA). The results demonstrate that the SUATSR system outperforms the other two systems, exhibiting higher SA and signal-to-noise ratio (SNR) values at the fault frequency. This highlights the SUATSR system’s superior noise resistance and its effectiveness in detecting and enhancing fault signals.