本文選題：故障診斷　切入點(diǎn)：專家系統(tǒng)　出處：《中國科學(xué)院研究生院（光電技術(shù)研究所）》2015年碩士論文　論文類型：學(xué)位論文

【摘要】：光電跟蹤設(shè)備是集光機(jī)電于一體的大型光電設(shè)備,其層次結(jié)構(gòu)復(fù)雜,單元部件多,采用傳統(tǒng)的建模方法和信號(hào)處理方法均不能從系統(tǒng)層面上實(shí)現(xiàn)故障診斷的要求,而人工智能領(lǐng)域中的專家系統(tǒng)可依據(jù)領(lǐng)域經(jīng)驗(yàn)知識(shí)與理論知識(shí)實(shí)現(xiàn)故障診斷。近年來專家系統(tǒng)在航空航天領(lǐng)域大型設(shè)備故障診斷方面取得了突破進(jìn)展,為光電跟蹤設(shè)備故障診斷系統(tǒng)的研究奠定了技術(shù)基礎(chǔ)。本文分析了光電跟蹤設(shè)備的組成和工作流程,對(duì)設(shè)備故障進(jìn)行了分類并總結(jié)了各類故障的底層故障原因,然后分別以妨礙設(shè)備運(yùn)行的主要故障事件為頂事件建立了光電跟蹤設(shè)備故障樹。故障樹是一顆由故障現(xiàn)象到故障原因的倒置樹,具有逆因果性,可以顯示故障知識(shí)相關(guān)信息以及故障間的聯(lián)系。根據(jù)設(shè)備故障特點(diǎn),采用了產(chǎn)生式規(guī)則和框架表示法相結(jié)合的知識(shí)表示方式將故障樹表示的設(shè)備故障知識(shí)轉(zhuǎn)化為電腦中可存儲(chǔ)的知識(shí),建立專家系統(tǒng)知識(shí)庫。采用正向推理方式與高置信度優(yōu)先的控制策略設(shè)計(jì)推理機(jī),其中置信度是由故障發(fā)生概率與排查難易程度共同決定的,并設(shè)計(jì)了專家規(guī)則來解決知識(shí)間的相斥情況。本文采用擅長編寫謂詞邏輯、語義分析類程序的專家系統(tǒng)編程語言CLIPS設(shè)計(jì)專家系統(tǒng)核心部分:知識(shí)庫和推理機(jī),實(shí)現(xiàn)故障診斷;采用VC的應(yīng)用程序框架MFC設(shè)計(jì)專家系統(tǒng)界面,實(shí)現(xiàn)友好的人機(jī)交互;在數(shù)據(jù)庫SQLSEVER中設(shè)計(jì)了故障知識(shí)表、維修建議表和診斷案例表存儲(chǔ)設(shè)備故障相關(guān)知識(shí),以便更好地維護(hù)和管理知識(shí)。本文采用直接嵌入法和ADO對(duì)象技術(shù)將CLIPS與SQLSEVER嵌入MFC,同時(shí)利用代碼自動(dòng)生成技術(shù)實(shí)現(xiàn)數(shù)據(jù)庫與CLIPS知識(shí)庫的同步更新,協(xié)調(diào)這三個(gè)部分共同運(yùn)行,完成光電跟蹤設(shè)備故障診斷專家系統(tǒng)的設(shè)計(jì)。本文最后對(duì)專家系統(tǒng)主要功能做了介紹并通過具體故障實(shí)例對(duì)系統(tǒng)進(jìn)行了測試,測試結(jié)果表明該故障診斷專家系統(tǒng)能準(zhǔn)確診斷設(shè)備故障并對(duì)故障知識(shí)進(jìn)行有效管理。
[Abstract]:Photoelectric tracking equipment is a large optoelectronic device, which has complex hierarchical structure and many unit parts. The traditional modeling method and signal processing method can not realize fault diagnosis from the system level. The expert system in the field of artificial intelligence can realize fault diagnosis according to the field experience and theory knowledge. In recent years, the expert system has made a breakthrough progress in the field of large-scale equipment fault diagnosis in the field of aeronautics and astronautics. It lays a technical foundation for the research of the fault diagnosis system of photoelectric tracking equipment. This paper analyzes the composition and work flow of the photoelectric tracking equipment, classifies the faults of the equipment and summarizes the underlying fault causes of all kinds of faults. Then the fault tree of photoelectric tracking equipment is established based on the main failure events which hinder the operation of the equipment. The fault tree is an inverted tree from the fault phenomenon to the cause of the fault, which has the inverse causality. Can display fault knowledge related information and the relationship between the fault. According to the characteristics of the equipment failure, In this paper, the fault knowledge of equipment represented by the fault tree is transformed into the knowledge that can be stored in the computer by the way of knowledge representation which combines the production rule and the frame representation. The knowledge base of expert system is established. The inference engine is designed by using forward reasoning and high confidence priority control strategy, in which the confidence is determined by the probability of fault occurrence and the degree of difficulty in checking. In this paper, the expert system programming language CLIPS, which is good at writing predicate logic and semantic analysis program, is used to design the core parts of expert system: knowledge base and inference engine, to realize fault diagnosis. The expert system interface is designed by using VC application program framework MFC to realize friendly man-machine interaction, and fault knowledge table, maintenance suggestion table and diagnosis case table are designed in database SQLSEVER. In order to better maintain and manage knowledge, this paper adopts direct embedding method and ADO object technology to embed CLIPS and SQLSEVER in MFC. at the same time, we use code automatic generation technology to realize synchronous updating of database and CLIPS knowledge base, and coordinate these three parts to run together. Finally, the main functions of the expert system are introduced and the system is tested by a specific fault example. The test results show that the fault diagnosis expert system can accurately diagnose equipment faults and manage fault knowledge effectively.
【學(xué)位授予單位】：中國科學(xué)院研究生院（光電技術(shù)研究所）
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：TN29

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本文編號(hào)：1579735