基于Agent與故障樹的故障診斷專家系統(tǒng)的研究
發(fā)布時(shí)間:2018-01-21 03:08
本文關(guān)鍵詞: Agent 故障樹 二叉故障樹 故障診斷 專家系統(tǒng) 出處:《大連交通大學(xué)》2012年碩士論文 論文類型:學(xué)位論文
【摘要】:故障診斷專家系統(tǒng)是故障診斷技術(shù)的一個(gè)發(fā)展方向,其系統(tǒng)的設(shè)計(jì)、采用的技術(shù)及知識(shí)庫、推理機(jī)的設(shè)計(jì)等問題成為故障診斷專家系統(tǒng)中要解決的首要問題。 結(jié)合省自然科學(xué)基金項(xiàng)目“客運(yùn)專線列車故障診斷專家系統(tǒng)關(guān)鍵技術(shù)研究”(項(xiàng)目編號(hào):20102014),針對(duì)電力機(jī)車的電氣系統(tǒng)的故障的特點(diǎn),研究了開發(fā)故障診斷專家系統(tǒng)需要用到的相關(guān)技術(shù),分析了故障診斷專家系統(tǒng)的架構(gòu)設(shè)計(jì)及開發(fā)方法。根據(jù)電力機(jī)車電氣系統(tǒng)的故障特征,以當(dāng)前故障診斷技術(shù)的現(xiàn)狀為背景,以故障診斷專家系統(tǒng)要解決的首要問題為目標(biāo),結(jié)合人工智能技術(shù)、計(jì)算機(jī)技術(shù)、故障診斷技術(shù)等領(lǐng)域的知識(shí),設(shè)計(jì)一個(gè)通用性高、可靠性好的電力機(jī)車電氣系統(tǒng)的故障診斷專家系統(tǒng)。設(shè)計(jì)了作為系統(tǒng)組成單元的各個(gè)Agent的功能及任務(wù);將傳統(tǒng)的專家系統(tǒng)進(jìn)行改造,使其Agent化,并具備Agent的特點(diǎn);重點(diǎn)闡述了在本系統(tǒng)中是如何依據(jù)故障樹模型來進(jìn)行知識(shí)的獲取;將以往常規(guī)的規(guī)則存儲(chǔ)方式改為故障現(xiàn)象、故障原因、診斷結(jié)論分別進(jìn)行存儲(chǔ)的三級(jí)存儲(chǔ)機(jī)制;在故障樹模型的基礎(chǔ)上進(jìn)行改造,結(jié)合數(shù)據(jù)結(jié)構(gòu)的知識(shí),提出二叉故障樹模型,設(shè)計(jì)并實(shí)現(xiàn)了故障診斷專家系統(tǒng)的推理機(jī)制。 將該故障診斷專家系統(tǒng)應(yīng)用于電力機(jī)車的電氣部分中,以電氣系統(tǒng)中某些故障樹為例,詳細(xì)闡述了基于Agent與故障樹的故障專家系統(tǒng)的設(shè)計(jì)細(xì)節(jié)與完整的系統(tǒng)建立過程,并對(duì)系統(tǒng)仿真實(shí)驗(yàn)的結(jié)果進(jìn)行分析,結(jié)果證明將Agent與故障樹應(yīng)用于故障診斷領(lǐng)域能夠有效地提高診斷任務(wù)的工作效率。系統(tǒng)具有良好的擴(kuò)展性,使得系統(tǒng)能夠輕松升級(jí)以適應(yīng)新的需求;系統(tǒng)較高的通用性使得系統(tǒng)無需進(jìn)行太多改動(dòng)就可以應(yīng)用于其他領(lǐng)域及設(shè)備的故障診斷中。
[Abstract]:Fault diagnosis expert system is a developing direction of fault diagnosis technology. The design of fault diagnosis expert system, the adopted technology and knowledge base, and the design of inference machine have become the most important problems to be solved in fault diagnosis expert system. Combined with the project of Provincial Natural Science Foundation, "Research on key Technology of Train Fault diagnosis expert system for passenger dedicated Line" (item No.: 20102014), aiming at the characteristics of electric system fault of electric locomotive. In this paper, the related technologies used in the development of fault diagnosis expert system are studied, and the frame design and development method of the fault diagnosis expert system are analyzed, according to the fault characteristics of electric system of electric locomotive. Based on the current situation of fault diagnosis technology and the primary problem of fault diagnosis expert system, this paper combines the knowledge of artificial intelligence, computer technology, fault diagnosis technology and so on. A fault diagnosis expert system for electric system of electric locomotive with high generality and good reliability is designed, and the functions and tasks of each Agent are designed as a component unit of the system. The traditional expert system is reformed to make it Agent and has the characteristics of Agent. How to acquire knowledge according to fault tree model in this system is expounded emphatically. The conventional rule storage method is changed to the three-level storage mechanism of fault phenomenon, fault reason and diagnosis conclusion respectively. Based on the fault tree model and the knowledge of data structure, the binary fault tree model is proposed, and the reasoning mechanism of fault diagnosis expert system is designed and implemented. The fault diagnosis expert system is applied to the electric part of electric locomotive, and some fault trees in the electric system are taken as an example. The design details of fault expert system based on Agent and fault tree and the complete process of system establishment are described in detail, and the results of system simulation experiment are analyzed. The results show that applying Agent and fault tree to fault diagnosis can effectively improve the work efficiency of the diagnosis task. The system has good expansibility and the system can be easily upgraded to meet the new requirements. Because of its high versatility, the system can be applied to fault diagnosis in other fields and equipments without making too many changes.
【學(xué)位授予單位】:大連交通大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2012
【分類號(hào)】:TH165.3;TP182
【引證文獻(xiàn)】
相關(guān)碩士學(xué)位論文 前1條
1 袁潤紅;多Agent信息融合在列車故障診斷中的應(yīng)用研究[D];大連交通大學(xué);2013年
,本文編號(hào):1450278
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