In order to solve the problems of output saturation and signal amplification difference of the traditional two-dimensional tri-stable stochastic resonance system driven by dualinput signals (DTDTSR), a novel system, coupled piecewise symmetric tri-stable stochastic resonance system (coupled piecewise symmetric tri-stable stochastic resonance system) driven by dual-input signals, is ingeniously proposed. A novel system is proposed: coupled piecewise symmetric tri-stable stochastic resonance system driven by dual-input signals (DCPSTSR). Firstly, the problem of output saturation of the system is studied in depth, which provides a key theoretical foundation for the optimization of the system performance. Secondly, the output spectral amplification (SA) function of the system is derived within the framework of the adiabatic approximation theory. The influence of system parameters on it is analyzed in detail, which provides theoretical support for deeper understanding. Further, a comprehensive comparison of the DCPSTSR, coupled piecewise symmetric tri-stable stochastic resonance system (CPSTSR) and DTDTSR systems is carried out through numerical simulations, and the results clearly indicate that the DCPSTSR system is significantly superior to the other systems in terms of output spectral amplification function. Finally, the system parameters are precisely optimized by genetic algorithm and successfully applied to bearing fault detection. The experimental results verify the excellent performance of the DCPSTSR system and provide strong theoretical support and feasibility verification for future theoretical research and engineering applications. This design and its successful application in bearing fault detection provide a new direction and example for further research and practical application in the field of resonance systems, which has important scientific and engineering value.