张 刚,毕璐洁,蒋忠均.Levy 噪声下欠阻尼指数型三稳随机共振系统研究[J].电子测量与仪器学报,2023,37(1):177-190
Levy 噪声下欠阻尼指数型三稳随机共振系统研究
Underdamped exponential tri-stable stochasticresonance system under Levy noise
  
DOI:10.13382/j.issn.1000-7105.2023.01.020
中文关键词:  故障诊断  随机共振  指数型三稳系统  Levy 噪声
英文关键词:fault diagnosis  stochastic resonance  exponential tri-stable system  Levy noise
基金项目:国家自然科学基金 ( 61771085)、 重庆市自然科学基金面 上 项 目 ( cstc2021jcyj-msxmX0836)、 重 庆 市 教 育 委 员 会 科 研 项 目(KJQN201900601)资助
作者单位
张 刚 1. 重庆邮电大学通信与信息工程学院 
毕璐洁 1. 重庆邮电大学通信与信息工程学院 
蒋忠均 2. 中共贵州省委网络安全和信息化委员会办公室 
AuthorInstitution
Zhang Gang 1. School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications (CQUPT) 
Bi Lujie 1. School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications (CQUPT) 
Jiang Zhongjun 2. Cyberspace Administration of Guizhou Province 
摘要点击次数: 494
全文下载次数: 43620
中文摘要:
      针对经典双稳随机共振(CBSR)系统在微弱信号放大检测方面的困难,提出了 Levy 噪声下的欠阻尼指数型三稳随机共 振(UETSR)系统。 将双稳态和指数势函数相结合,利用非高斯噪声可有效提升信噪比的特性,构造出 UETSR 系统。 首先推导 该系统的稳态概率密度函数,以平均信噪比增益为衡量指标,采用量子粒子群算法进行参数寻优,研究在 Levy 噪声的不同参数 α 与 β 下,系统各参数对 UETSR 输出变化规律的影响。 最后将 UETSR、CBSR 和经典三稳系统(CTSR)应用于轴承故障诊断中, 系统输出后的内外圈故障频率处的幅值较输入信号分别增长了 197. 58,1. 153,18. 81 和 238. 87,26. 63,39. 72,最高峰与次高峰 的谱级比分别为 5. 44,4. 03,3. 85 和 5. 10,3. 79,5. 05。 实验结果表明,不同系统参数均可诱导产生 SR 现象,且 UETSR 系统的 性能明显优于 CBSR 和 CTSR,具有良好的工程应用价值。
英文摘要:
      For the difficulties of classical bi-stable stochastic resonance (CBSR) system in amplification and detection of weak signals, an underdamped exponential tri-stable stochastic resonance (UETSR) system in a Levy noise background is proposed. The UETSR system is constructed by combining the bi-stable potential and exponential potential function, and using the property that non-Gaussian noise can effectively improve the signal-to-noise ratio. Firstly, the steady-state probability density function of the system is derived. The mean signal-to-noise ratio improvement (MSNRI) is adopted as an index to measure the stochastic resonance performance. The quantum particle swarm algorithm is used on parameters optimization. The effect of each parameter of the system on the output variation pattern of the UETSR system with different parameters α and β of Levy noise is investigated. Finally, the UETSR, CBSR and classical tri-stable stochastic resonance system (CTSR) are applied to the bearing fault diagnosis, and the amplitudes at the inner and outer ring fault frequencies after the system output increased by 197. 58, 1. 153, 18. 81 and 238. 87, 26. 63, 39. 72, respectively, compared to the input signal. The spectral level ratios of the highest peak to the second highest peak were 5. 44, 4. 03, 3. 85 and 5. 10, 3. 79, 5. 05. The experimental results show that SR phenomena can be induced by different system parameters, and the UETSR system outperformed the CBSR system and the CTSR system. The above conclusions prove that the system has excellent performance and strong practical significance
查看全文  查看/发表评论  下载PDF阅读器