本文關(guān)鍵詞：基于貝葉斯網(wǎng)絡(luò)的復(fù)雜系統(tǒng)可靠分析方法研究與應(yīng)用　出處：《天津工業(yè)大學(xué)》2016年博士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 不確定性 可靠性分析 模糊理論 貝葉斯網(wǎng)絡(luò) 故障樹 FMECA

【摘要】：隨著現(xiàn)代工業(yè)技術(shù)的迅速發(fā)展,產(chǎn)品和設(shè)備系統(tǒng)日趨復(fù)雜化。系統(tǒng)的復(fù)雜性,一方面體現(xiàn)為其子系統(tǒng)或部件間相互藕合,另一方面也體現(xiàn)為系統(tǒng)的工作環(huán)境變化等外部影響因素的紛繁眾多。并且,由于受到物質(zhì)、空間和時(shí)間上的限制,很難獲得足夠的數(shù)據(jù)信息對(duì)系統(tǒng)的狀態(tài)、特征和行為做出明確和精準(zhǔn)的判據(jù),這些因素導(dǎo)致系統(tǒng)包含著大量的不確定性。傳統(tǒng)的可靠性分析方法在解決實(shí)際問題中暴露出明顯的不足和局限。本文針對(duì)復(fù)雜系統(tǒng)可靠性分析中的主客觀不確定性的問題,以貝葉斯網(wǎng)絡(luò)理論作為不確定性分析的理論基礎(chǔ),結(jié)合模糊理論和傳統(tǒng)的可靠性分析理論,以電池生產(chǎn)線作為研究對(duì)象,分析了目前可靠性分析理論在復(fù)雜系統(tǒng)可靠性分析中存在的問題和不足,提出了相應(yīng)的解決方法,并建立了分析模型,其主要內(nèi)容如下：(1)分析了傳統(tǒng)故障樹和貝葉斯網(wǎng)絡(luò)的可靠性分析方法的局限性,提出了基于故障樹的模糊貝葉斯網(wǎng)絡(luò)的可靠性分析方法。該方法采用貝葉斯網(wǎng)絡(luò)建模方法進(jìn)行基本建模,用貝葉斯網(wǎng)絡(luò)理論的節(jié)點(diǎn)多態(tài)表達(dá)特性來描述復(fù)雜系統(tǒng)的事件多態(tài)性,用貝葉斯網(wǎng)絡(luò)理論的節(jié)點(diǎn)條件概率表來描述復(fù)雜系統(tǒng)的事件之間的不確定性邏輯關(guān)系。在貝葉斯網(wǎng)絡(luò)模型的框架下,引入模糊集合理論,用模糊數(shù)來描述專家對(duì)事件概率的模糊評(píng)估。在對(duì)不確定權(quán)重的專家評(píng)估信息的集結(jié)過程中,提出了用依賴不確定性有序加權(quán)平均算子綜合不確定權(quán)重的專家們的評(píng)估信息,來實(shí)現(xiàn)專家權(quán)重的客觀定權(quán)。(2)分析了傳統(tǒng)FMECA分析方法的局限性,提出了基于FMECA的模糊貝葉斯網(wǎng)絡(luò)的可靠性分析方法。該方法采用了模糊理論中的模糊數(shù)來表示專家對(duì)RPN屬性參數(shù)的模糊評(píng)級(jí),提出了用帶置信結(jié)構(gòu)的模糊規(guī)則庫替代傳統(tǒng)的模糊規(guī)則庫,并用來描述模糊輸入數(shù)據(jù)不完備的條件下模糊規(guī)則的前提和結(jié)論之間的不確定性；提出了利用貝葉斯網(wǎng)絡(luò)推理技術(shù)合成置信結(jié)構(gòu)的模糊規(guī)則,實(shí)現(xiàn)模糊規(guī)則的推理,并給出了詳細(xì)的建模方法和步驟；提出了利用加權(quán)平均去模糊方法,實(shí)現(xiàn)故障危害等級(jí)的清晰化、明確化。(3)分析了當(dāng)前復(fù)雜系統(tǒng)的可靠性分析中存在的問題,研究了不同可靠性分析方法的結(jié)合應(yīng)用。論文以電池生產(chǎn)線系統(tǒng)的可靠性分析為例,通過對(duì)在多種主客觀不確定信息的條件下電池生產(chǎn)線系統(tǒng)的可靠性分析,來研究可靠性分析方法的結(jié)合應(yīng)用。在電池生產(chǎn)線系統(tǒng)的可靠性分析實(shí)例中,提出了采用基于FMECA的模糊貝葉斯網(wǎng)絡(luò)的可靠性分析方法確定系統(tǒng)的關(guān)鍵重要子系統(tǒng),采用基于故障樹的模糊貝葉斯網(wǎng)絡(luò)的可靠性分析方法確定影響系統(tǒng)的主要部件及其故障模式,定性定量地實(shí)現(xiàn)系統(tǒng)的可靠性分析。
[Abstract]:With the rapid development of modern industrial technology, the product and equipment systems are becoming more and more complicated. The complexity of the system is reflected in the coupling between subsystems or components on the one hand. On the other hand, it is also reflected in the variety of external factors, such as the change of the working environment of the system. Moreover, due to the material, space and time constraints, it is difficult to obtain enough data and information to the state of the system. Characteristics and behaviors provide clear and precise criteria. These factors lead to a large number of uncertainties in the system. The traditional reliability analysis method has exposed obvious shortcomings and limitations in solving practical problems. This paper aims at subjective and objective uncertainty in reliability analysis of complex systems. About sex. Taking Bayesian network theory as the theoretical basis of uncertainty analysis, combined with fuzzy theory and traditional reliability analysis theory, the battery production line is taken as the research object. The problems and shortcomings of the reliability analysis theory in complex systems are analyzed, and the corresponding solutions are put forward, and the analysis model is established. The main contents are as follows: (1) the limitations of the traditional fault tree and Bayesian network reliability analysis methods are analyzed. The reliability analysis method of fuzzy Bayesian network based on fault tree is proposed, which is based on Bayesian network modeling method. The characteristics of node polymorphism in Bayesian network theory are used to describe the event polymorphism of complex systems. The uncertain logic relationship between events of complex systems is described by using the nodal conditional probability table of Bayesian network theory. In the framework of Bayesian network model, fuzzy set theory is introduced. Fuzzy numbers are used to describe experts' fuzzy evaluation of event probability. In this paper, the objective weight determination of expert weight is realized by synthesizing the evaluation information of uncertain weights by using the weighted average operator which depends on the uncertainty.) the limitation of traditional FMECA analysis method is analyzed. The reliability analysis method of fuzzy Bayesian network based on FMECA is proposed. The fuzzy number of fuzzy theory is used to express the fuzzy rating of RPN attribute parameters. In this paper, the fuzzy rule base with confidence structure is proposed to replace the traditional fuzzy rule base, and it is used to describe the uncertainty between the premise and conclusion of fuzzy rule under the condition of incomplete fuzzy input data. The fuzzy rules of confidence structure are synthesized by using Bayesian network reasoning technology, and the reasoning of fuzzy rules is realized, and the detailed modeling method and steps are given. In this paper, a weighted average de-fuzzy method is put forward to realize the clarity of fault damage grade, and the problem of reliability analysis of complex system is analyzed. This paper takes the reliability analysis of battery production line system as an example and analyzes the reliability of battery production line system under the condition of various subjective and objective uncertain information. In the example of reliability analysis of battery production line system. A reliability analysis method based on FMECA fuzzy Bayesian network is proposed to determine the key subsystems of the system. The reliability analysis method of fuzzy Bayesian network based on fault tree is used to determine the main components and fault modes of the system, and the reliability analysis of the system is realized qualitatively and quantitatively.
【學(xué)位授予單位】：天津工業(yè)大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2016
【分類號(hào)】：TP18;N945.17

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