分段非对称随机共振系统微弱信号检测

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摘要作为一种重要的信号处理方法,随机共振(SR)能够利用噪声能量增强微弱信号,有效降低噪声信号对特征提取的影响。针对分段对称系统模型随机共振幅值增益不够明显及噪声利用率较低等不足,提出一种分段非线性系统模型。该系统参数独立,易于调节,可通过调节参数诱导最佳随机共振。在双稳态模型下,推导了克莱默斯（Kramers）逃逸率和输出信噪比,同时在模型公式仿真和数值仿真两方面与分段对称系统进行对比分析,用于说明该方法的有效性。结果表明该方法能够有效地提取特征频率,具有良好的放大性能和抗噪声能力。最后将系统应用于不同型号的轴承故障检测,并用自适应智能算法最优化系统参数。结果显示,非对称系统的输出幅值分别为对称系统的8倍，3倍和6倍。数据表明,非对称系统能更有效地实现微弱特征检测与早期故障诊断。该研究进一步对系统在实际工程应用提供了理论指导与依据。

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	贺利芳
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关键词 ：非对称系统, 随机共振, 遗传算法, 平均信噪比增益

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

收稿日期: 2020-11-09 出版日期: 2022-03-15

引用本文:

贺利芳，朱伟，张天骐. 分段非对称随机共振系统微弱信号检测[J]. 振动与冲击, 2022, 41(5): 114-122.
HE Lifang, ZHU Wei, ZHANG Tianqi. Detection of weak signals in piecewise asymmetric stochastic resonance system. JOURNAL OF VIBRATION AND SHOCK, 2022, 41(5): 114-122.

链接本文:

http://jvs.sjtu.edu.cn/CN/ 或 http://jvs.sjtu.edu.cn/CN/Y2022/V41/I5/114

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