本文選題：混沌 + 微弱信號(hào)��； 參考：《東北大學(xué)》2013年碩士論文

【摘要】：微弱信號(hào)的檢測(cè)在雷達(dá)、聲納、振動(dòng)測(cè)量、故障診斷等領(lǐng)域有著非常廣泛的應(yīng)用。國(guó)際上,隨著微電子技術(shù)和非線性檢測(cè)理論的發(fā)展,故障診斷技術(shù)也得到了快速的發(fā)展,但在國(guó)內(nèi)關(guān)于微故障信號(hào)檢測(cè)研究尚需大量投入,加強(qiáng)具有自主知識(shí)產(chǎn)權(quán)技術(shù)的創(chuàng)新開發(fā)及科研成果的轉(zhuǎn)化已成為迫在眉睫的問題。本文針對(duì)化工流體管道微泄漏檢測(cè)、機(jī)械疲勞振動(dòng)故障預(yù)報(bào)等問題,利用混沌系統(tǒng)相軌跡狀態(tài)從混沌態(tài)到大尺度周期態(tài)的躍遷對(duì)于輸入微弱信號(hào)的敏感特性,提出了針對(duì)頻率未知微弱信號(hào)的分段測(cè)頻檢測(cè)方法以及基于復(fù)合系統(tǒng)的微弱信號(hào)檢測(cè)方法,實(shí)現(xiàn)了對(duì)淹沒在強(qiáng)噪聲中的頻率未知的微弱信號(hào)的檢測(cè),為保障工業(yè)過程的高效穩(wěn)定運(yùn)行提供基礎(chǔ)理論與技術(shù)支持。本文做了如下研究：首先,詳細(xì)研究了單Duffing系統(tǒng)和雙耦合Duffing系統(tǒng)的檢測(cè)原理,并對(duì)比分析了在不同噪聲等級(jí)下兩個(gè)系統(tǒng)能夠檢測(cè)的微弱信號(hào)的信噪比門限。仿真結(jié)果證明雙耦合Duffing系統(tǒng)比單Duffing系統(tǒng)具有較強(qiáng)的抗噪性能。然后,針對(duì)微弱信號(hào)檢測(cè)的難點(diǎn)問題,利用混沌系統(tǒng)的間歇混沌特性,提出了一種基于雙耦合Duffing振子的未知頻率的微弱信號(hào)的分段測(cè)頻檢測(cè)方法,并詳細(xì)闡述了該方法的定義以及檢測(cè)原理。通過一系列仿真實(shí)驗(yàn)證明該方法在不同噪聲等級(jí)下能夠準(zhǔn)確的檢測(cè)出任意周期信號(hào)的頻率。最后,詳細(xì)研究了相關(guān)方法和雙耦合Duffing系統(tǒng)在微弱信號(hào)檢測(cè)方面的優(yōu)勢(shì)和劣勢(shì),并結(jié)合這兩種方法提出一種針對(duì)未知頻率微弱信號(hào)檢測(cè)的復(fù)合系統(tǒng),將互相關(guān)方法和基于雙耦合Duffing振子的分段測(cè)頻檢測(cè)方法結(jié)合起來,充分發(fā)揮各自的優(yōu)勢(shì)。仿真實(shí)驗(yàn)證明該方法能夠更好的將待測(cè)周期信號(hào)從強(qiáng)噪聲中提取出來,大大的降低了待測(cè)信號(hào)的信噪比門限。
[Abstract]:Weak signal detection is widely used in radar, sonar, vibration measurement, fault diagnosis and so on. In the world, with the development of microelectronic technology and nonlinear detection theory, fault diagnosis technology has also been rapidly developed, but the research on micro-fault signal detection still needs a lot of investment in our country. It has become an urgent problem to strengthen the innovation and development of independent intellectual property technology and the transformation of scientific research results. In this paper, aiming at the problems of micro-leakage detection and mechanical fatigue vibration fault prediction in chemical fluid pipeline, the sensitive characteristics of phase locus state transition from chaotic state to large-scale periodic state for input weak signal are used in this paper. In this paper, a frequency detection method for unknown weak frequency signals and a weak signal detection method based on composite system are proposed to detect weak signals with unknown frequency submerged in strong noise. It provides basic theory and technical support for ensuring the efficient and stable operation of industrial process. This paper has done the following research: firstly, the detection principle of single Duffing system and double coupling Duffing system is studied in detail, and the signal-to-noise ratio threshold of weak signal can be detected by two systems under different noise levels is compared and analyzed. The simulation results show that the dual coupling Duffing system has better noise resistance than the single Duffing system. Then, aiming at the difficult problem of weak signal detection, using the intermittent chaos characteristic of chaotic system, a frequency detection method of weak signal based on the unknown frequency of dual-coupling Duffing oscillator is proposed. The definition and detection principle of this method are described in detail. Through a series of simulation experiments, it is proved that the method can accurately detect the frequency of arbitrary periodic signals under different noise levels. Finally, the advantages and disadvantages of correlation method and double coupling Duffing system in weak signal detection are studied in detail, and a composite system for weak signal detection with unknown frequency is proposed combining these two methods. The cross-correlation method and the segmented frequency measurement method based on dual-coupling Duffing oscillator are combined to give full play to their respective advantages. The simulation results show that the proposed method can extract the periodic signal from the strong noise and reduce the signal-to-noise ratio (SNR) threshold of the signal to be measured.
【學(xué)位授予單位】：東北大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：TN911.23;O415.5

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本文編號(hào)：1783851