基于随机共振的弱信号提取方法研究

发布时间：2018-05-27 14:35

本文选题：随机共振 + 自适应　；参考：《浙江大学》2014年硕士论文

【摘要】：本文结合国家自然科学基金项目“微弱冲击信号的识别和提取技术研究”(编号：51175466),针对微弱周期信号和微弱冲击信号提取问题,研究了基于随机共振原理的自适应信号提取方法。第一章分析论文的研究背景和意义,阐述常用的弱信号检测理论及其应用,探讨基于随机共振的弱信号检测方法与研究现状,给出论文的章节安排和主要研究内容。第二章阐述随机共振系统理论模型,包括绝热近似条件下的朗之万方程和福克-普朗克方程,研究模型数值求解算法,分析了几种常用的测度指标。第三章提出基于随机共振的弱周期信号提取方法。采用变步长随机共振算法,消除传统随机共振存在对低频信号的局限,分析级联随机共振系统的降噪和整形功能,选取零点间距方差作为模型测度指标,建立针对弱周期信号提取的变步长级联随机共振系统,并通过对比输出信号的峭度值,来识别可能存在的信号类型,最后通过仿真实验验证该方法的有效性。第四章构建基于单稳态随机共振的弱冲击信号提取模型。分析单稳态随机共振的理论模型,构造冲击信号特征系数作为模型测度指标,提出自适应单稳态随机共振提取模型,实现冲击信号提取与识别,并通过仿真实验验证该模型的有效性。第五章利用MATLAB的GUI模块开发基于随机共振的弱信号提取原型系统,并通过仿真实验验证有效性。第六章总结全文所做的研究工作,对随机共振的后续研究进行展望。
[Abstract]:In this paper, according to the project of National Natural Science Foundation of China, "Research on the Identification and extraction Technology of weak Impulse signal" (No. 51175466N), aiming at the problem of weak periodic signal and weak shock signal extraction, An adaptive signal extraction method based on stochastic resonance principle is studied. The first chapter analyzes the research background and significance of the paper, describes the commonly used weak signal detection theory and its application, discusses the methods and research status of weak signal detection based on stochastic resonance, and gives the chapter arrangement and main research content. In the second chapter, the theoretical models of stochastic resonance system, including Langevan equation and Fokk-Planck equation under adiabatic approximation, are described. Numerical algorithms for solving the model are studied, and several commonly used measurement indexes are analyzed. In chapter 3, a weak periodic signal extraction method based on stochastic resonance is proposed. The variable step size stochastic resonance algorithm is used to eliminate the limitation of the traditional stochastic resonance to the low frequency signal. The noise reduction and shaping function of the cascade stochastic resonance system is analyzed. The variance of zero distance is selected as the model measure index. A variable step size cascade stochastic resonance system for weak periodic signal extraction is established, and the kurtosis of the output signal is compared to identify the possible signal types. Finally, the effectiveness of the method is verified by simulation experiments. In chapter 4, a weak impulse signal extraction model based on Monostable Stochastic Resonance (Monostable Stochastic Resonance) is constructed. This paper analyzes the theoretical model of Monostable Stochastic Resonance, constructs the characteristic coefficient of shock signal as the measure index of the model, and puts forward an adaptive Monostable Stochastic Resonance extraction Model to extract and recognize the shock signal. The validity of the model is verified by simulation experiments. In chapter 5, the weak signal extraction prototype system based on stochastic resonance is developed by using the GUI module of MATLAB, and the validity of the system is verified by simulation experiments. Chapter 6 summarizes the research work done in this paper, and looks forward to the future research of stochastic resonance.
【学位授予单位】：浙江大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN911.7

【参考文献】