指数型随机共振微弱振动信号检测方法

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Abstract The fault signal is difficult to detect and extract in practical engineering because of its characteristic frequency signals submerged in noise. In order to extract the weak signal in strong background noise, a new bistable stochastic resonance system functions called exponential Duffing bistable combining harmonic Potential model and Gaussian Potential model put forward in this paper. Firstly, the escape rate is derived and the effect on the output signal-to-noise ratio by system parameters are studied. Then, simulation harmonic vibration signal and attenuation impulse signal have demonstrated the feasibility detection performance of exponential bistable stochastic resonance system. Finally, the exponential bistable stochastic resonance with empirical mode decomposition method has taken to detect weak multi-frequency signal under heavy noise and this method also useful for the bearing fault signal detection. The experimental analysis and the simulation results show that exponential bistable stochastic resonance model in signal detection is reliable, and multi-frequency harmonic signal through empirical mode decomposition after the stochastic resonance can get accurate detection, the propose united detection method is effective and reliable in the fault signal detection.

Key words： exponential bistable stochastic resonance empirical mode decomposition the fault signal detection

Received: 18 July 2017 Published: 28 April 2019

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	Articles by authors
	ZHANG Gang1
	2
	CAO Li1
	HE Lifang2
	YI Tian2

Cite this article:

ZHANG Gang1,2,CAO Li1, et al. Weak vibration signal detection method for exponential stochastic resonance systems[J]. JOURNAL OF VIBRATION AND SHOCK, 2019, 38(9): 53-61.

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http://jvs.sjtu.edu.cn/EN/ OR http://jvs.sjtu.edu.cn/EN/Y2019/V38/I9/53

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