基于T-S重要度和貝葉斯網(wǎng)絡(luò)的多態(tài)液壓系統(tǒng)可靠性分析
本文選題:T-S模糊 切入點:故障樹分析 出處:《燕山大學(xué)》2011年碩士論文
【摘要】:廣泛應(yīng)用于各類設(shè)備、處于控制和動力傳輸重要核心地位的液壓系統(tǒng),其可靠性問題一直是工業(yè)技術(shù)亟待完善的關(guān)鍵所在,因此研究液壓系統(tǒng)的可靠性分析方法具有重要的理論和實際意義,F(xiàn)有液壓系統(tǒng)可靠性分析方法仍局限于常規(guī)的二態(tài)分析方法,由此建立的可靠性分析模型與實際情況存在較大差異。為此,本文致力于研究多態(tài)液壓系統(tǒng)的可靠性分析方法,提出了T-S重要度算法以及T-S模糊故障樹與貝葉斯網(wǎng)絡(luò)相結(jié)合算法,以促進可靠性方法的發(fā)展及其在液壓工程中的應(yīng)用。 在T-S模糊故障樹分析方法基礎(chǔ)上,針對系統(tǒng)處于不同的已知條件,提出了三種T-S重要度分析算法,包括T-S狀態(tài)重要度、T-S規(guī)則重要度和T-S模糊重要度。通過與現(xiàn)有的傳統(tǒng)故障樹和模糊故障樹的重要度算法進行對比,并結(jié)合液壓機動力源系統(tǒng)應(yīng)用實例,驗證了所提T-S重要度算法的可行性。這三種重要度分別從不同角度反映了部件對系統(tǒng)的貢獻,為不同條件下的可靠性工程應(yīng)用提供了依據(jù)。 在研究基于T-S模糊故障樹、貝葉斯網(wǎng)絡(luò)與Barlow方法的二態(tài)和多態(tài)系統(tǒng)可靠性分析方法的基礎(chǔ)上,提出了由貝葉斯網(wǎng)絡(luò)來處理T-S模糊故障樹的方法。針對貝葉斯網(wǎng)絡(luò)建造問題,提出由T-S模糊故障樹向貝葉斯網(wǎng)絡(luò)的轉(zhuǎn)化方法,完成了貝葉斯網(wǎng)絡(luò)與T-S模糊故障樹,以及貝葉斯條件概率和幾種常見T-S重要度的算法比較,驗證了所提方法的可行性。 結(jié)合T-S模糊故障樹重要度算法和貝葉斯網(wǎng)絡(luò)對某提梁機卷揚系統(tǒng)進行分析,提高了卷揚系統(tǒng)的可靠性。
[Abstract]:Hydraulic system, which is widely used in all kinds of equipment and is in the important core position of control and power transmission, its reliability problem is always the key to be improved urgently in industrial technology. Therefore, it is of great theoretical and practical significance to study the reliability analysis method of hydraulic system. The existing reliability analysis method of hydraulic system is still limited to the conventional two-state analysis method. There is a great difference between the established reliability analysis model and the actual situation. Therefore, this paper is devoted to study the reliability analysis method of the polymorphic hydraulic system. T-S importance algorithm and T-S fuzzy fault tree combined with Bayesian network are proposed to promote the development of reliability method and its application in hydraulic engineering. Based on T-S fuzzy fault tree analysis method, three T-S importance analysis algorithms are proposed for the system under different known conditions. It includes T-S state importance, T-S rule importance and T-S fuzzy importance. Compared with the traditional fault tree and fuzzy fault tree, and combined with the application example of hydraulic press power source system, The feasibility of the proposed T-S importance algorithm is verified, which reflects the contribution of the components to the system from different angles, and provides the basis for the reliability engineering application under different conditions. Based on T-S fuzzy fault tree, Bayesian network and Barlow method, the reliability analysis method of two-state and polymorphic system is studied, and the method of dealing with T-S fuzzy fault tree by Bayesian network is proposed. The transformation method from T-S fuzzy fault tree to Bayesian network is proposed. The Bayesian network is compared with T-S fuzzy fault tree, and the Bayesian conditional probability and several common algorithms of T-S importance are compared. The feasibility of the proposed method is verified. Combined with T-S fuzzy fault tree importance algorithm and Bayesian network, the hoisting system of a beam hoist is analyzed, and the reliability of the hoisting system is improved.
【學(xué)位授予單位】:燕山大學(xué)
【學(xué)位級別】:碩士
【學(xué)位授予年份】:2011
【分類號】:TH137
【參考文獻】
相關(guān)期刊論文 前10條
1 鄭恒;吳祈宗;汪佩蘭;史愛芬;;貝葉斯網(wǎng)絡(luò)在火工系統(tǒng)安全評價中的應(yīng)用[J];兵工學(xué)報;2006年06期
2 姚成玉;趙靜一;;兩棲車液壓系統(tǒng)及其故障診斷搜索策略研究[J];兵工學(xué)報;2006年04期
3 霍利民,朱永利,范高鋒,劉軍,蘇海鋒;一種基于貝葉斯網(wǎng)絡(luò)的電力系統(tǒng)可靠性評估新方法[J];電力系統(tǒng)自動化;2003年05期
4 王永傳,郁文賢,莊釗文;基于模糊數(shù)的故障樹分析方法研究[J];電子產(chǎn)品可靠性與環(huán)境試驗;2000年01期
5 霍利民,朱永利,張在玲,陳麗;貝葉斯網(wǎng)絡(luò)在配電系統(tǒng)可靠性評估中的應(yīng)用[J];電工技術(shù)學(xué)報;2004年08期
6 周汝勝;焦宗夏;王少萍;;液壓系統(tǒng)故障診斷技術(shù)的研究現(xiàn)狀與發(fā)展趨勢[J];機械工程學(xué)報;2006年09期
7 戴智華,易建鋼,陳新元;模糊故障樹理論在液壓系統(tǒng)故障診斷中的應(yīng)用[J];機床與液壓;2002年05期
8 李青,陸廷金;模糊重要度分析方法的研究[J];模糊系統(tǒng)與數(shù)學(xué);2000年01期
9 何淑靜,周偉國,嚴(yán)銘卿;上海城市燃氣輸配管網(wǎng)失效模糊故障樹分析法[J];同濟大學(xué)學(xué)報(自然科學(xué)版);2005年04期
10 李儉川,胡蔦慶,秦國軍,溫熙森;貝葉斯網(wǎng)絡(luò)理論及其在設(shè)備故障診斷中的應(yīng)用[J];中國機械工程;2003年10期
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