【摘要】：本論文研究的內(nèi)容得到了國家自然科學基金“機械故障診斷中基于非線性理論的微弱信號檢測與處理技術(shù)研究（50875070）”項目的資助。論文在研究隨機共振理論的基礎(chǔ)上，設(shè)計出了參數(shù)可調(diào)的分段隨機共振系統(tǒng)。通過對該系統(tǒng)進行建模、仿真、計算和電路設(shè)計，驗證了該系統(tǒng)對淹沒在強噪聲背景下的中低頻微弱信號檢測的有效性。以及基于DSP技術(shù)設(shè)計出一種可實現(xiàn)自動調(diào)節(jié)參數(shù)的自適應(yīng)分段雙穩(wěn)態(tài)隨機共振硬件電路。 全文主要內(nèi)容如下： 第1章介紹了隨機共振理論在國內(nèi)外發(fā)展動態(tài)和研究現(xiàn)狀，提出了本課題需要解決的問題，確定本課題主要研究內(nèi)容、方法及其創(chuàng)新點。 第2章概括性地介紹了隨機共振基本理論，分析了具有代表性的隨機共振系統(tǒng)的動態(tài)特性、產(chǎn)生隨機共振現(xiàn)象的原因和條件以及利用隨機共振原理的測量方法。 第3章針對經(jīng)典的連續(xù)雙穩(wěn)態(tài)隨機共振模型只適用于小參數(shù)條件，而對于工程中常見的中低頻微弱信號的測量容易出現(xiàn)飽和而難以測量的問題，提出了一種分段雙穩(wěn)態(tài)隨機共振模型，對該系統(tǒng)進行了理論分析、頻帶檢測及信噪比SNR（signal-to-noise ratio）論證，并進行了驗證性的計算和仿真�？梢钥吹皆撃Ｐ蛯υ肼暫皖l率變化具有更好的適應(yīng)性。 第4章主要針對機械故障中常見的中低頻微弱信號檢測，，討論了基于分段雙穩(wěn)態(tài)隨機共振模型的調(diào)制隨機共振方法并對該方法進行了驗證性的計算和仿真。 第5章介紹了自適應(yīng)隨機共振理論的相關(guān)概念，然后結(jié)合自適應(yīng)參數(shù)調(diào)節(jié)原理設(shè)計出基于DSP技術(shù)的自適應(yīng)調(diào)制隨機共振系統(tǒng)。通過對DSP芯片特性的綜合分析，設(shè)計出了基于TMS320F2812芯片的自適應(yīng)調(diào)制隨機共振系統(tǒng)的硬件電路和軟件系統(tǒng)。 第6章對比本文所設(shè)計的分段雙穩(wěn)態(tài)隨機共振檢測技術(shù)與其它一些經(jīng)典微弱信號檢測技術(shù)，分析了本文所設(shè)計的檢測系統(tǒng)的優(yōu)勢與不足，為進一步的研究作了一些展望。 本文的創(chuàng)新之處在于針對工程中常見的中低頻率的微弱信號難以測量的問題，提出了一種分段雙穩(wěn)態(tài)隨機共振模型，并進行了相關(guān)的理論分析和仿真試驗。該模型改善了絕熱近似理論下隨機共振只能滿足小參數(shù)下測試的條件，應(yīng)用該模型和基于調(diào)制隨機共振的跟蹤掃頻方法相結(jié)合，可以提高檢測效率，有效地從強噪聲背景中提取工程實際中的中低頻率微弱信號，從而達到了機械故障信號的檢測。同時本文對該模型做了驗證性的計算、編程仿真和電路設(shè)計，并在此基礎(chǔ)上探討了基于DSP技術(shù)TMS320F2812芯片的自適應(yīng)檢測。
[Abstract]:This paper is supported by the National Natural Science Foundation of China "Research on weak signal Detection and processing Technology based on nonlinear Theory in Mechanical Fault diagnosis (50875070)". Based on the study of stochastic resonance theory, a piecewise stochastic resonance system with adjustable parameters is designed. Through modeling, simulation, calculation and circuit design of the system, the effectiveness of the system for detecting the weak and middle frequency signals submerged in the background of strong noise is verified. An adaptive bistable stochastic resonance hardware circuit is designed based on DSP technology. The main contents of this paper are as follows: in Chapter 1, the development and research status of stochastic resonance theory at home and abroad are introduced, the problems to be solved are put forward, and the main research contents, methods and innovations of this subject are determined. In chapter 2, the basic theory of stochastic resonance is introduced, the dynamic characteristics of the representative stochastic resonance system, the causes and conditions of the stochastic resonance phenomenon and the measurement method using the stochastic resonance principle are analyzed. In chapter 3, the classical continuous bistable stochastic resonance model is only suitable for small parameter conditions, but the measurement of weak signals in middle and low frequency is easy to be saturated and difficult to measure. A piecewise bistable stochastic resonance model is proposed. The theoretical analysis, frequency band detection and SNR (signal-to-noise ratio) demonstration of signal-to-noise ratio (SNR) of the system are carried out, and the verifiability calculation and simulation are carried out. It can be seen that the model has better adaptability to noise and frequency change. In chapter 4, the modulation stochastic resonance (MSRM) method based on piecewise bistable stochastic resonance model is discussed for the detection of weak signals of middle and low frequency, which is common in mechanical faults, and the method is verified by calculation and simulation. In chapter 5, the concepts of adaptive stochastic resonance theory are introduced, and then the adaptive modulation stochastic resonance system based on DSP technology is designed based on the adaptive parameter regulation principle. By synthetically analyzing the characteristics of DSP chip, the hardware circuit and software system of adaptive modulation stochastic resonance system based on TMS320F2812 chip are designed. Chapter 6 compares the segmented bistable stochastic resonance detection technique and some other classical weak signal detection techniques, analyzes the advantages and disadvantages of the detection system designed in this paper, and makes some prospects for further research. The innovation of this paper is that a piecewise bistable stochastic resonance model is proposed to solve the problem that weak signals at low and medium frequencies are difficult to measure in engineering, and relevant theoretical analysis and simulation experiments are carried out. The model improves the condition that stochastic resonance can only satisfy the test condition under small parameters in adiabatic approximation theory. The detection efficiency can be improved by combining the model with the tracking frequency sweep method based on modulation stochastic resonance. The weak signals with low and medium frequencies are extracted from the background of strong noise effectively, and the detection of mechanical fault signals is achieved. At the same time, this paper has done the verification calculation, the programming simulation and the circuit design to this model, and has discussed the adaptive detection based on the DSP technology TMS320F2812 chip.
【學位授予單位】：杭州電子科技大學
【學位級別】：碩士
【學位授予年份】：2012
【分類號】：TH165.3

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