【摘要】：故障診斷主要研究如何對系統(tǒng)中出現(xiàn)的故障進行檢測、分離和辨識,即判斷故障是否發(fā)生,定位故障發(fā)生的部位和種類以及確定故障發(fā)生的時間和故障發(fā)生的大小。動態(tài)因果圖基于一些明顯特點(布爾邏輯運算的引入、完全基于概率論等),和有關因果圖推理的算法研究的不斷優(yōu)化,使其在系統(tǒng)的故障診斷中應用得越來越廣泛。針對現(xiàn)實應用中存在的各種不確定性因素,本論文以因果圖理論為基礎,結合灰色系統(tǒng)理論的優(yōu)點,將其應于復雜系統(tǒng)的故障診斷中,提高故障診斷的效率。主要內(nèi)容包括:(1)按預測、分析、提出預防重點的分析步驟,從整體上對系統(tǒng)進行故障診斷分析。首先用灰色災變預測模型對事故多發(fā)年份進行預測,且模型的預測精度較高。其次對系統(tǒng)的檢修可以根據(jù)因果圖故障分析中的基本事件重要度分析方法得到,選擇重要度大的部件進行檢修。但是傳統(tǒng)的基本事件重要度有3種,本文考慮通過引入灰色關聯(lián)理論,得到更為直觀的基本事件排序,實例表明此方法的引入是合理的。最后提出預防重點,制定合理有效的故障應對方案,以減少此類事故的發(fā)生。(2)因果圖的一個最小割集代表一種故障模式,基于因果圖故障模式的診斷通常是根據(jù)其重要度大小來排查故障原因。在本文中,用模糊數(shù)來刻畫事件發(fā)生的概率,根據(jù)因果圖基本事件的模糊重要度,將灰色關聯(lián)分析引入,對各種故障模式發(fā)生的可能性大小作出判斷,據(jù)此可以縮小故障診斷空間。同時該方法也解決了由于故障信息缺乏所導致的中間事件和基本事件的概率無法確知,以及基本事件與中間事件的相互關系難以確定的問題。
[Abstract]:Fault diagnosis mainly studies how to detect, separate and identify the faults in the system, that is to say, to judge whether the faults occur, to locate the locations and types of the faults, and to determine the time and magnitude of the faults. Dynamic causality diagram is based on some obvious features (Boolean logic operation, probability theory, etc.), and the continuous optimization of reasoning algorithms about causal diagram makes it more and more widely used in system fault diagnosis. Based on causality diagram theory and the advantages of grey system theory, this paper aims at the uncertain factors existing in practical application, and puts it into the fault diagnosis of complex system to improve the efficiency of fault diagnosis. The main contents are as follows: (1) according to the prediction and analysis, the key steps of prevention are put forward, and the fault diagnosis and analysis of the system as a whole is carried out. First, the grey disaster prediction model is used to predict the year of frequent accidents, and the prediction accuracy of the model is high. Secondly, the maintenance of the system can be obtained according to the basic event importance analysis method in the causality diagram fault analysis, and the parts with the high importance can be selected for overhaul. But there are three kinds of traditional basic event importance. This paper considers introducing grey relation theory to get a more intuitionistic sort of basic event. The example shows that this method is reasonable. Finally, the prevention focus is put forward, and a reasonable and effective fault response scheme is made to reduce the occurrence of such accidents. (2) A minimal cut set of causality diagram represents a fault mode. Fault diagnosis based on causality diagram is usually based on its importance to detect the cause of failure. In this paper, fuzzy numbers are used to describe the probability of occurrence of events. According to the fuzzy importance of the basic events in causality diagram, grey relational analysis is introduced to judge the probability of occurrence of various fault modes. Therefore, the fault diagnosis space can be reduced. The method also solves the problem that the probability of intermediate events and basic events can not be ascertained due to the lack of fault information, and the relationship between basic events and intermediate events is difficult to determine.
【學位授予單位】：重慶師范大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：N941.5

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