分段非对称随机共振系统微弱信号检测

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Abstract Stochastic resonance (SR), as a potential signal processing tool, can enhance weak signal by transforming noise energy and effectively reduce the influence of noise signal on feature extraction. A piecewise nonlinear system model is proposed for the lack of obvious amplitude gain of spectrum on characteristic frequency and low noise utilization in piecewise linear system. The system parameters are independent and easy to adjust, and the optimal stochastic resonance can be induced by adjusting the parameters. Under the bistable model, its Kramers escape rate and output SNR are deduced. Meanwhile, the model formula simulation and numerical simulation are compared with the piecewise symmetric system to demonstrate the effectiveness of the method. The results show that the method can extract the characteristic frequency and has good enhancement performance and anti-noise ability. Finally, the system is applied to different types of the bearing fault detection and the adaptive intelligent algorithm is used to select the optimal system parameters. The results show that the output amplitude of the asymmetric system is 8 times, 3 times and 6 times that of the symmetric system. The data show that the asymmetric system can realize weak feature detection and early fault diagnosis more effectively. This study provides theoretical guidance and basis for the application of the system in practical engineering.

Key words： asymmetric system Stochastic resonance Genetic algorithm Average SNR gain

Received: 09 November 2020 Published: 15 March 2022

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	Articles by authors
	HE Lifang
	ZHU Wei
	ZHANG Tianqi

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HE Lifang,ZHU Wei,ZHANG Tianqi. Detection of weak signals in piecewise asymmetric stochastic resonance system[J]. JOURNAL OF VIBRATION AND SHOCK, 2022, 41(5): 114-122.

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http://jvs.sjtu.edu.cn/EN/ OR http://jvs.sjtu.edu.cn/EN/Y2022/V41/I5/114

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