Abstract:
In order to further improve the output signal-to-noise ratio and filtering performance of fault diagnosis, a fault diagnosis method based on Quantum Particle Swarm Optimization (QPSO) algorithm is proposed. The algorithm is based on underdamped
\textFitzHugh-Nagumo potential. The analytical expression of the output signal-to-noise ratio of the two-dimensional double potential well system based on the underdamped
\textFitzHugh-Nagumo potential is firstly studied. It is verified that the signal-to-noise ratio can be further improved by changing the system parameters and damping coefficient. Secondly, in order to further improve the output signal-to-noise ratio, an adaptive bistable stochastic resonance method based on underdamped
\textFitzHugh-Nagumo potential is proposed. The method is used in simulation and actual bearing fault detection. The results show that the method can effectively identify the bearing faults of the inner and outer rings. Compared with the traditional first-order variable step size SR (SCSR), the method proposed in this paper can obtain Higher signal-to-noise ratio and filtering performance.