本文選題：光纖預警系統(tǒng) + 檢測識別算法�。� 參考：《北方工業(yè)大學》2017年碩士論文

【摘要】：本文圍繞相位光時域反射(ΦOTDR)體制下的光纖入侵檢測識別算法理論基礎研究展開。主要通過設計出ΦOTDR光纖預警系統(tǒng)的檢測識別算法實現(xiàn)有害入侵信號的定位和類型識別。首先,在檢測算法研究方面,本文深入研究了典型的恒虛警率(CFAR)檢測方法并設計出了新的空間維度CFAR檢測方法。并且在時間維度進行非參數(shù)檢驗方法設計,實現(xiàn)了無害干擾的去除。其次,在識別算法研究方面,本文研究了基音周期(PP),占空比(DC),過零率(ZCR)等特征的提取方法,為有效識別入侵類型提供基礎。最后,通過運用經(jīng)典的視覺注意架構,使整體算法結構合理。鑒于此,本文設計出了基于視覺注意架構的光纖預警檢測識別算法,并進行了該算法的實驗驗證。首先,對光纖預警系統(tǒng)的檢測算法進行研究。在空間維度檢測中,本文提出一種新的自適應背景勻質性CFAR檢測方法,該方法能夠在保證檢測性能的同時能夠盡可能的減少算法的時間消耗,保證噪聲被剔除;在時間維度檢測中,本文提出了針對無害干擾信號的頻繁程度選擇進行序貫似然比(SPRT)或K-S檢測的處理,保證無害干擾信號被剔除。其次,對光纖預警系統(tǒng)的識別算法進行研究。發(fā)現(xiàn)機械入侵信號存在PP,人工挖掘信號存在較小的DC,過車信號存在較小的ZCR,并且實驗證明不同類型的實測數(shù)據(jù)能夠提取到相應特征。最后將檢測識別算法融合到視覺注意架構中,將算法分為數(shù)據(jù)驅動和任務驅動兩部分。并且實驗證明數(shù)據(jù)驅動更能夠有效地減小后續(xù)處理的數(shù)據(jù)量,任務驅動能夠使有害入侵類型識別率明顯提升。
[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.
【學位授予單位】：北方工業(yè)大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP277

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本文編號：2016727