灰色系统理论在因果图故障诊断中的应用

发布时间：2018-07-25 11:32

【摘要】：故障诊断主要研究如何对系统中出现的故障进行检测、分离和辨识,即判断故障是否发生,定位故障发生的部位和种类以及确定故障发生的时间和故障发生的大小。动态因果图基于一些明显特点(布尔逻辑运算的引入、完全基于概率论等),和有关因果图推理的算法研究的不断优化,使其在系统的故障诊断中应用得越来越广泛。针对现实应用中存在的各种不确定性因素,本论文以因果图理论为基础,结合灰色系统理论的优点,将其应于复杂系统的故障诊断中,提高故障诊断的效率。主要内容包括:(1)按预测、分析、提出预防重点的分析步骤,从整体上对系统进行故障诊断分析。首先用灰色灾变预测模型对事故多发年份进行预测,且模型的预测精度较高。其次对系统的检修可以根据因果图故障分析中的基本事件重要度分析方法得到,选择重要度大的部件进行检修。但是传统的基本事件重要度有3种,本文考虑通过引入灰色关联理论,得到更为直观的基本事件排序,实例表明此方法的引入是合理的。最后提出预防重点,制定合理有效的故障应对方案,以减少此类事故的发生。(2)因果图的一个最小割集代表一种故障模式,基于因果图故障模式的诊断通常是根据其重要度大小来排查故障原因。在本文中,用模糊数来刻画事件发生的概率,根据因果图基本事件的模糊重要度,将灰色关联分析引入,对各种故障模式发生的可能性大小作出判断,据此可以缩小故障诊断空间。同时该方法也解决了由于故障信息缺乏所导致的中间事件和基本事件的概率无法确知,以及基本事件与中间事件的相互关系难以确定的问题。
[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.
【学位授予单位】：重庆师范大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：N941.5

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