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Based on Stochastic Resonance to Enhance Micro-Fault Signal Features

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Abstract

Stochastic resonance (SR) is an effective approach for weak signal detection. Utilizing a single system for cascading has restrictions for conventional SR. To examine the impact of applying various types of SR on the inter-system generation in the same cascade process, the mixed system cascade stochastic resonance (MSCSR) approach is presented in this study. The improved effect is measured in terms of amplitude and signal-to-noise ratio (SNR), on this basis, proposed stochastic weighted particle swarm optimization algorithm to optimize SR system parameters. The results indicate that the collaboration between different systems leads to changes in the potential well of the cascade process. With the proposed approach, MSCSR, the output amplitude is 3.39 times more than that of the bi-stable cascade system, and the SNR is 3.83 dB higher than that of the tri-stable cascade system. The effect of the method described in this study on weak fault characteristics is noticeably stronger than that of the single SR cascade system method. Meanwhile, the method proposed in this paper has important engineering value for micro-fault diagnosis of rolling bearings.

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Acknowledgments

The authors thank Professor Engineer Jian Wang from 7th Academy (China Aerospace Corporation) for his guidance on this work. This work was supported by the Sichuan Youth Fund Project (No: SC20220230), the authors also would like to thank the anonymous reviewers for their valuable comments and suggestions. They help us to improve the work comparatively and fundamentally.

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  1. School of Mechatronic Engineering, Chengdu University of Technology, Chengdu, 610059, China

    Kai Wang, Yuan Cheng, Haowen Zheng, Likai Gao & Zhengyu Feng

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  1. Kai Wang
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Correspondence to Yuan Cheng.

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Wang, K., Cheng, Y., Zheng, H. et al. Based on Stochastic Resonance to Enhance Micro-Fault Signal Features. J Fail. Anal. and Preven. 23, 1203–1215 (2023). https://doi.org/10.1007/s11668-023-01678-9

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