中国物理B ›› 2023, Vol. 32 ›› Issue (5): 50202-050202.doi: 10.1088/1674-1056/aca4bd
Shangbin Jiao(焦尚彬)1, Rui Gao(高蕊)1,2,†, Qiongjie Xue(薛琼婕)1, and Jiaqiang Shi(史佳强)1
Shangbin Jiao(焦尚彬)1, Rui Gao(高蕊)1,2,†, Qiongjie Xue(薛琼婕)1, and Jiaqiang Shi(史佳强)1
摘要: The weak signal detection method based on stochastic resonance is usually used to extract and identify the weak characteristic signal submerged in strong noise by using the noise energy transfer mechanism. We propose a novel composite multistable stochastic-resonance (NCMSR) model combining the Gaussian potential model and an improved bistable model. Compared with the traditional multistable stochastic resonance method, all the parameters in the novel model have no symmetry, the output signal-to-noise ratio can be optimized and the output amplitude can be improved by adjusting the system parameters. The model retains the advantages of continuity and constraint of the Gaussian potential model and the advantages of the improved bistable model without output saturation, the NCMSR model has a higher utilization of noise. Taking the output signal-to-noise ratio as the index, weak periodic signal is detected based on the NCMSR model in Gaussian noise and α noise environment respectively, and the detection effect is good. The application of NCMSR to the actual detection of bearing fault signals can realize the fault detection of bearing inner race and outer race. The outstanding advantages of this method in weak signal detection are verified, which provides a theoretical basis for industrial practical applications.
中图分类号: (Numerical simulation; solution of equations)