随机共振参数优化及其应用研究

发布时间：2018-03-16 14:31

本文选题：随机共振　切入点：参数优化　出处：《中国计量学院》2014年硕士论文　论文类型：学位论文

【摘要】：随机共振是以噪声为媒介引起微弱周期信号与非线性系统协同作用的非线性现象，涉及的参数有周期信号的幅值、频率，噪声强度和非线性系统参数。在实际应用中，输入信号和噪声是给定的，只有通过调节非线性系统参数，使非线性系统与输入信号匹配，才能产生随机共振。本文分析了双稳系统参数对随机共振的影响，提出基于人工鱼群算法的自适应随机共振。分析了双稳系统参数对势垒高度的影响以及系统输出信噪比随双稳系统参数的变化，通过调节双稳系统参数实现了随机共振的产生与增强。研究了常用自适应算法的特点，针对线性随机搜索算法采用叠加权值的方法，无法保证全局最优解和遗传算法因为引入随机突变而搜索到错误空间的不足，提出了基于人工鱼群算法的自适应随机共振，利用人工鱼群算法自适应地调节双稳系统参数，实现随机共振；将两个双稳系统经过非线性耦合的方式构成耦合系统，通过耦合的作用控制随机共振的产生，进而对控制参数的优化增强共振效应。将基于人工鱼群算法的自适应随机共振应用于轴承滚动体故障、内圈故障的检测和不同流量的涡街信号的检测，成功地获取了故障特征频率和涡街频率。实验结果表明，利用人工鱼群算法并行优化双稳系统参数，能够增强微弱的特征信号，提高信噪比，有效地实现微弱信号的检测。最后，利用COM技术的LabVIEW与MATLAB的无缝集成，开发了微弱信号智能检测系统，该系统能够根据不同的被测信号特性，自适应地调节双稳系统参数，，实现随机共振。经对涡街信号的检测表明系统能有效地实现微弱特征信号的检测，具有广阔的应用前景。
[Abstract]:Stochastic resonance (SR) is a nonlinear phenomenon in which the weak periodic signal and the nonlinear system interact with each other by using noise as the medium. The parameters involved include amplitude, frequency, noise intensity and nonlinear system parameters of the periodic signal. The input signal and noise are given. Only by adjusting the parameters of the nonlinear system, can the nonlinear system match with the input signal to produce stochastic resonance. In this paper, the influence of the bistable system parameters on the stochastic resonance is analyzed. Adaptive stochastic resonance based on artificial fish swarm algorithm is proposed. The influence of bistable system parameters on the barrier height and the variation of output SNR with bistable system parameters are analyzed. The stochastic resonance is generated and enhanced by adjusting the bistable system parameters. In this paper, the characteristics of common adaptive algorithms are studied. The method of superposition weights is used in linear random search algorithm, which can not guarantee the global optimal solution and the deficiency of genetic algorithm to search the wrong space because of the introduction of random mutation. Adaptive stochastic resonance based on artificial fish swarm algorithm is proposed. The parameters of bistable system are adjusted adaptively by artificial fish swarm algorithm to realize stochastic resonance. The stochastic resonance is controlled by coupling, and the resonance effect is enhanced by optimizing the control parameters. Adaptive stochastic resonance based on artificial fish swarm algorithm is applied to the detection of bearing rolling body fault, inner ring fault and vortex signal with different flow rate. The fault characteristic frequency and vortex frequency are obtained successfully. The experimental results show that, By using artificial fish swarm algorithm to optimize the parameters of bistable system in parallel, the weak characteristic signal can be enhanced, the signal-to-noise ratio (SNR) can be improved, and the weak signal can be detected effectively. Finally, using the seamless integration of LabVIEW and MATLAB of COM technology, a weak signal intelligent detection system is developed. The system can adjust the parameters of bistable system adaptively according to different characteristics of measured signal. The detection of vortex signal shows that the system can detect the weak characteristic signal effectively and has a broad application prospect.
【学位授予单位】：中国计量学院
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TB53;TP18

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