A Novel Hyperbolic Unsaturated Bistable Stochastic Resonance System and Its Application in Weak Signal Detection

Stochastic resonance (SR) systems possess the remarkable ability to enhance weak signals by transferring noise energy into the signal, and thus have significant application prospects in weak signal detection. However, the classic bistable SR (CBSR) system suffers from the output saturation problem, which limits its weak signal enhancement ability. To address this limitation, this paper proposes an under-damped unsaturated SR system called the UDHQSR system. This SR system overcomes the output saturation problem through a piecewise potential function constructed by combining hyperbolic sine functions and quadratic functions. Additionally, by introducing a damping term, its weak signal detection performance is further improved. Furthermore, the theoretical output SNR of this proposed SR system is derived to quantitatively represent its weak signal detection performance. The particle swarm optimization (PSO) algorithm is used to dynamically optimize the parameters of the UDHQSR system. Finally, the simulated signal and different real bearing fault signals from public datasets are used to verify the effectiveness of the proposed UDHQSR system. Experimental results demonstrate that this UDHQSR system has better abilities for both weak signal enhancement and noise suppression compared with the CBSR system.