本文選題：隨機(jī)共振 + 自適應(yīng)��； 參考：《浙江大學(xué)》2014年碩士論文

【摘要】：本文結(jié)合國家自然科學(xué)基金項(xiàng)目“微弱沖擊信號的識(shí)別和提取技術(shù)研究”(編號：51175466),針對微弱周期信號和微弱沖擊信號提取問題,研究了基于隨機(jī)共振原理的自適應(yīng)信號提取方法。 第一章分析論文的研究背景和意義,闡述常用的弱信號檢測理論及其應(yīng)用,探討基于隨機(jī)共振的弱信號檢測方法與研究現(xiàn)狀,給出論文的章節(jié)安排和主要研究內(nèi)容。 第二章闡述隨機(jī)共振系統(tǒng)理論模型,包括絕熱近似條件下的朗之萬方程和�？�-普朗克方程,研究模型數(shù)值求解算法,分析了幾種常用的測度指標(biāo)。 第三章提出基于隨機(jī)共振的弱周期信號提取方法。采用變步長隨機(jī)共振算法,消除傳統(tǒng)隨機(jī)共振存在對低頻信號的局限,分析級聯(lián)隨機(jī)共振系統(tǒng)的降噪和整形功能,選取零點(diǎn)間距方差作為模型測度指標(biāo),建立針對弱周期信號提取的變步長級聯(lián)隨機(jī)共振系統(tǒng),并通過對比輸出信號的峭度值,來識(shí)別可能存在的信號類型,最后通過仿真實(shí)驗(yàn)驗(yàn)證該方法的有效性。 第四章構(gòu)建基于單穩(wěn)態(tài)隨機(jī)共振的弱沖擊信號提取模型。分析單穩(wěn)態(tài)隨機(jī)共振的理論模型,構(gòu)造沖擊信號特征系數(shù)作為模型測度指標(biāo),提出自適應(yīng)單穩(wěn)態(tài)隨機(jī)共振提取模型,實(shí)現(xiàn)沖擊信號提取與識(shí)別,并通過仿真實(shí)驗(yàn)驗(yàn)證該模型的有效性。 第五章利用MATLAB的GUI模塊開發(fā)基于隨機(jī)共振的弱信號提取原型系統(tǒng),并通過仿真實(shí)驗(yàn)驗(yàn)證有效性。 第六章總結(jié)全文所做的研究工作,對隨機(jī)共振的后續(xù)研究進(jìn)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.
【學(xué)位授予單位】：浙江大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TN911.7

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