Journal of Jilin University(Engineering and Technology Edition) ›› 2021, Vol. 51 ›› Issue (3): 1091-1096.doi: 10.13229/j.cnki.jdxbgxb20200260

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Method of enhancing stochastic resonance signal of self⁃adaptive coupled periodic potential system

Wei LI1,2(),Jian CHEN1,2(),Shan-yong TAO1,2   

  1. 1.Institute of Noise and Vibration Engineering，Hefei University of Technology，Hefei 230009，China
    2.Automotive NVH Engineering & Technology Research Center of Anhui Province，Hefei 230009，China
  • Received:2020-04-19 Online:2021-05-01 Published:2021-05-07
  • Contact: Jian CHEN E-mail:jazzlee@mail.hfut.edu.cn;Chenjian@hfut.edu.cn

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Abstract:

Based on the single periodic potential system， a new method of stochastic resonance signal enhancement for coupled periodic potential systems was proposed. The method uses particle swarm optimization to achieve adaptive matching of system parameters， coupling coefficients and step sizes. Using this method the targeting signal and the signal-noice-ratio can be enhanced. Experiments are carried out to verify the ne method. The results show that due to the function of the coupling system， the control system affects the stochastic resonance of the controlled system by adjusting the parameters， so that the adaptive coupling periodic potential system stochastic resonance method performs better than the adaptive first-order periodic potential system stochastic resonance method in the enhancement of weak fault characteristic signal. Due to the synergy between the stochastic resonance of the control system and the stochastic resonance of the controlled system， the stochastic resonance effect of the controlled system is greatly enhanced. Therefore， the adaptive double-input coupling periodic potential system stochastic resonance method is more suitable for the extraction of weak fault characteristic signals in the noise environment than the adaptive single-input coupled periodic potential system stochastic resonance method.

Key words: signal processing, periodic potential function, coupling system, fault diagnosis, signal noise ratio（SNR）, self-adaptation

CLC Number: 

  • TN911.7

Fig.1

Flow chart of input and output"

Fig.2

Three-dimensional graph of potential function a=1, b=1, r=0.02"

Fig.3

Aero engine bearing testing machine"

Fig.4

Inner ring fault status"

Fig.5

Time domain waveform and spectrum of inner ring outer raceway fault vibration signal"

Fig.6

Curve of output SNR of inner ring outer raceway fault vibration signal with iteration times"

Fig.7

output spectrum of inner ring outer raceway fault"

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