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。
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 parametersαandβof 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.
作者
张刚
毕璐洁
蒋忠均
Zhang Gang;Bi Lujie;Jiang Zhongjun(School of Communication and Information Engineering,Chongqing University of Posts and Telecommunications(CQUPT),Chongqing 400065,China;Cyberspace Administration of Guizhou Province,Guiyang 550000,China)
出处
《电子测量与仪器学报》
CSCD
北大核心
2023年第1期177-190,共14页
Journal of Electronic Measurement and Instrumentation
基金
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
关键词
故障诊断
随机共振
指数型三稳系统
Levy噪声
fault diagnosis
stochastic resonance
exponential tri-stable system
Levy noise
