本文關(guān)鍵詞： 無線傳感器網(wǎng)絡 免疫機理 故障診斷 空間特性　出處：《重慶三峽學院》2017年碩士論文　論文類型：學位論文

【摘要】：無線傳感網(wǎng)絡在信息采集、檢測等方面具有強大的處理功能,在復雜問題求解方面具有最優(yōu)求解能力,但其節(jié)點具有能量受限、路由狀態(tài)多變、通信易受干擾、發(fā)生故障概率較大等特點,如何有效及時診斷出發(fā)生的故障已經(jīng)成為無線傳感器網(wǎng)絡應用的關(guān)鍵問題。本文通過對空間特性下的節(jié)點故障診斷算法研究的基礎上,引入對故障檢測與診斷具有記憶識別、學習能力等優(yōu)點的免疫機理,通過對生物免疫系統(tǒng)的理論、仿生機理和人工免疫系統(tǒng)的理解,利用免疫機理的記憶學習的優(yōu)點,對故障數(shù)據(jù)庫進行實時優(yōu)化,本文圍繞著針對節(jié)點故障診斷開展工作,提出了基于空間特性下的節(jié)點免疫故障診斷算法(Node immune fault diagnosis algorithm,NIFD算法),為無線傳感網(wǎng)絡節(jié)點故障診斷提供了一種新方法。主要研究工作如下:1.通過對無線傳感網(wǎng)絡理論進行系統(tǒng)性的梳理,對人工免疫系統(tǒng)的免疫機理分析,建立了人工免疫機理與無線傳感器網(wǎng)絡故障診斷之間的映射關(guān)系,利用人工免疫機理的記憶學習等優(yōu)點對節(jié)點數(shù)據(jù)故障庫進行優(yōu)化。2.在節(jié)點診斷模型的基礎上,通過對節(jié)點的空間相關(guān)性的研究,在基于空間特性下的節(jié)點故障診斷算法基礎上,對網(wǎng)絡節(jié)點故障進行可靠的檢測,為了提高檢測的準確度,引入免疫機理,建立了免疫故障診斷模型。3.通過對模型中免疫機制進行分析,提出了 NIFD算法,實現(xiàn)對監(jiān)測區(qū)域內(nèi)故障節(jié)點的有效診斷。通過仿真實驗,分析該算法在故障節(jié)點的診斷精確度,虛警率和虛警概率等性能仿真,實現(xiàn)了對節(jié)點故障有效的檢測和診斷,判別出故障類型,提高了診斷的精度。建立的故障診斷模型能夠滿足節(jié)點故障的檢測與診斷要求,實現(xiàn)對故障的可靠性診斷。本文將基于空間特性的節(jié)點免疫診斷算法理論運用到無線傳感網(wǎng)絡的節(jié)點檢測與診斷中,通過仿真驗證該算法在節(jié)點故障檢測與診斷方面具有良好的性能,為解決無線傳感網(wǎng)絡的節(jié)點故障診斷問題提供參考。
[Abstract]:Wireless sensor networks have powerful processing functions in information collection and detection, and optimal solving ability in complex problem solving. However, the nodes of wireless sensor networks are energy limited, routing state is changeable, and communication is vulnerable to interference. How to diagnose the fault effectively and timely has become the key problem in wireless sensor network application. Based on the research of node fault diagnosis algorithm based on spatial characteristics, this paper discusses how to diagnose the fault effectively and in time. This paper introduces the immune mechanism which has the advantages of memory recognition and learning ability in fault detection and diagnosis. By understanding the theory of biological immune system, bionic mechanism and artificial immune system, the advantage of memory learning of immune mechanism is utilized. To optimize the fault database in real time, this paper focuses on node fault diagnosis. A node immune fault diagnosis algorithm named Node immune fault diagnosis algorithm based on spatial characteristics is proposed, which provides a new method for node fault diagnosis in wireless sensor networks. The main research work is as follows: 1. On systematic carding, Based on the analysis of the immune mechanism of the artificial immune system, the mapping relationship between the artificial immune mechanism and the fault diagnosis of the wireless sensor network is established. The memory learning of artificial immune mechanism is used to optimize the node data fault database. 2. Based on the node diagnosis model and the research of node spatial correlation, the node fault diagnosis algorithm based on spatial characteristics is proposed. In order to improve the accuracy of detection, the immune fault diagnosis model .3. is established in order to improve the accuracy of network node fault detection. Through the analysis of immune mechanism in the model, the NIFD algorithm is proposed. Through simulation experiments, this paper analyzes the performance simulation of the algorithm in fault node diagnosis accuracy, false alarm rate and false alarm probability, and realizes the effective detection and diagnosis of node fault. The fault diagnosis model can meet the requirements of node fault detection and diagnosis. In this paper, the theory of node immune diagnosis algorithm based on spatial characteristics is applied to node detection and diagnosis of wireless sensor networks. The simulation results show that the algorithm has good performance in node fault detection and diagnosis, and provides a reference for solving the node fault diagnosis problem in wireless sensor networks.
【學位授予單位】：重慶三峽學院
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TN929.5;TP212.9

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