發(fā)布時(shí)間：2018-06-14 08:21

  本文選題：光纖預(yù)警系統(tǒng) + 檢測(cè)識(shí)別算法　； 參考：《北方工業(yè)大學(xué)》2017年碩士論文

【摘要】：本文圍繞相位光時(shí)域反射(ΦOTDR)體制下的光纖入侵檢測(cè)識(shí)別算法理論基礎(chǔ)研究展開(kāi)。主要通過(guò)設(shè)計(jì)出ΦOTDR光纖預(yù)警系統(tǒng)的檢測(cè)識(shí)別算法實(shí)現(xiàn)有害入侵信號(hào)的定位和類(lèi)型識(shí)別。首先,在檢測(cè)算法研究方面,本文深入研究了典型的恒虛警率(CFAR)檢測(cè)方法并設(shè)計(jì)出了新的空間維度CFAR檢測(cè)方法。并且在時(shí)間維度進(jìn)行非參數(shù)檢驗(yàn)方法設(shè)計(jì),實(shí)現(xiàn)了無(wú)害干擾的去除。其次,在識(shí)別算法研究方面,本文研究了基音周期(PP),占空比(DC),過(guò)零率(ZCR)等特征的提取方法,為有效識(shí)別入侵類(lèi)型提供基礎(chǔ)。最后,通過(guò)運(yùn)用經(jīng)典的視覺(jué)注意架構(gòu),使整體算法結(jié)構(gòu)合理。鑒于此,本文設(shè)計(jì)出了基于視覺(jué)注意架構(gòu)的光纖預(yù)警檢測(cè)識(shí)別算法,并進(jìn)行了該算法的實(shí)驗(yàn)驗(yàn)證。首先,對(duì)光纖預(yù)警系統(tǒng)的檢測(cè)算法進(jìn)行研究。在空間維度檢測(cè)中,本文提出一種新的自適應(yīng)背景勻質(zhì)性CFAR檢測(cè)方法,該方法能夠在保證檢測(cè)性能的同時(shí)能夠盡可能的減少算法的時(shí)間消耗,保證噪聲被剔除;在時(shí)間維度檢測(cè)中,本文提出了針對(duì)無(wú)害干擾信號(hào)的頻繁程度選擇進(jìn)行序貫似然比(SPRT)或K-S檢測(cè)的處理,保證無(wú)害干擾信號(hào)被剔除。其次,對(duì)光纖預(yù)警系統(tǒng)的識(shí)別算法進(jìn)行研究。發(fā)現(xiàn)機(jī)械入侵信號(hào)存在PP,人工挖掘信號(hào)存在較小的DC,過(guò)車(chē)信號(hào)存在較小的ZCR,并且實(shí)驗(yàn)證明不同類(lèi)型的實(shí)測(cè)數(shù)據(jù)能夠提取到相應(yīng)特征。最后將檢測(cè)識(shí)別算法融合到視覺(jué)注意架構(gòu)中,將算法分為數(shù)據(jù)驅(qū)動(dòng)和任務(wù)驅(qū)動(dòng)兩部分。并且實(shí)驗(yàn)證明數(shù)據(jù)驅(qū)動(dòng)更能夠有效地減小后續(xù)處理的數(shù)據(jù)量,任務(wù)驅(qū)動(dòng)能夠使有害入侵類(lèi)型識(shí)別率明顯提升。
[Abstract]:This paper focuses on the theoretical research of optical fiber intrusion detection algorithm based on phase optical time domain reflection (桅 OTDR). The detection and recognition algorithm of 桅 OTDR optical fiber early warning system is designed to locate and identify harmful intrusion signals. Firstly, in the aspect of detection algorithm, this paper deeply studies the typical CFAR detection method and designs a new spatial dimension CFAR detection method. The nonparametric test method is designed in time dimension to remove harmless interference. Secondly, in the research of recognition algorithm, this paper studies the extraction methods of pitch period, duty cycle and ZCRs, which provide the basis for the effective identification of intrusion types. Finally, by using the classical visual attention architecture, the overall algorithm structure is reasonable. In view of this, an optical fiber early warning detection and recognition algorithm based on visual attention architecture is designed and verified by experiments. Firstly, the detection algorithm of optical fiber early warning system is studied. In spatial dimension detection, a new adaptive background homogeneity CFAR detection method is proposed. This method can not only guarantee the detection performance, but also reduce the time consumption of the algorithm as much as possible, and ensure that the noise is eliminated. In time dimension detection, the sequential likelihood ratio (SPRT) or K-S detection is proposed to select the frequency of harmless interference signal to ensure that the harmless interference signal is eliminated. Secondly, the recognition algorithm of optical fiber early warning system is studied. It is found that there are PPPs in mechanical intrusion signals, small DCs in manual mining signals and small ZCRs in vehicle passing signals. The experimental results show that different types of measured data can extract the corresponding features. Finally, the detection and recognition algorithm is integrated into visual attention architecture, and the algorithm is divided into two parts: data driven and task driven. Experimental results show that data drive can reduce the amount of data in subsequent processing more effectively, and task driven can significantly improve the recognition rate of harmful intrusion types.
【學(xué)位授予單位】：北方工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：TP277

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本文編號(hào)：2016727