本文關(guān)鍵詞： 狀態(tài)維修 間接狀態(tài)監(jiān)測(cè) 最小平均維修費(fèi)用 設(shè)備殘余壽命 決策標(biāo)準(zhǔn)　出處：《重慶大學(xué)》2011年碩士論文　論文類型：學(xué)位論文

【摘要】：現(xiàn)代制造業(yè)設(shè)備是企業(yè)的核心,為了保證生產(chǎn)能夠順利進(jìn)行,企業(yè)多采用狀態(tài)維修(Condition Based Maintenance)的方式對(duì)設(shè)備進(jìn)行保養(yǎng)。狀態(tài)維修是指在不同時(shí)刻點(diǎn)通過對(duì)設(shè)備運(yùn)行狀態(tài)進(jìn)行跟蹤并對(duì)與其相關(guān)的指標(biāo)值進(jìn)行收集以診斷設(shè)備的老化情況,最終對(duì)其易損件提前置換的一種預(yù)防性維修方法。 在以往的國(guó)內(nèi)外文獻(xiàn)中,許多學(xué)者針對(duì)直接狀態(tài)監(jiān)測(cè)的情況提出了最優(yōu)維修策略,本文旨在針對(duì)間接狀態(tài)監(jiān)測(cè)下劣化狀態(tài)并不能直接診斷的設(shè)備制定費(fèi)用最優(yōu)的設(shè)備預(yù)防性維修策略。其中,設(shè)備的故障率采用威布爾比例故障率模型來表示;設(shè)備的狀態(tài)概率采用貝葉斯公式進(jìn)行計(jì)算;決策標(biāo)準(zhǔn)的制定過程采用部分可觀測(cè)馬爾可夫決策過程和動(dòng)態(tài)規(guī)劃相結(jié)合的方法。 本文為了討論的方便引入了決策標(biāo)準(zhǔn)這一概念。事實(shí)上,設(shè)備預(yù)防性維修的決策標(biāo)準(zhǔn)取決于設(shè)備的已使用年齡、設(shè)備劣化狀態(tài)的概率分布和設(shè)備置換的最小平均維修費(fèi)用。本文假設(shè)設(shè)備的劣化狀態(tài)用馬爾可夫鏈表示,并運(yùn)用貝葉斯規(guī)則和隱馬爾可夫模型建立了指標(biāo)值和老化狀態(tài)之間的隨機(jī)概率關(guān)系。對(duì)于決策標(biāo)準(zhǔn)中最小平均維修費(fèi)用的確定本文引入了遞歸計(jì)算方法,并通過算例驗(yàn)證了該迭代方法的合理性,而且對(duì)比了直接和間接狀態(tài)監(jiān)測(cè)下的設(shè)備長(zhǎng)期平均費(fèi)用,第三章最后還研究了參數(shù)取值不同條件下的設(shè)備長(zhǎng)期平均維修費(fèi)用的變化特性。 鑒于傳統(tǒng)維修決策模型中較少考慮設(shè)備可用度這一問題,本文第四章還給出了在設(shè)備的老化狀態(tài)不能直接測(cè)得但通過狀態(tài)監(jiān)測(cè)可獲得某些有用信息情況下的設(shè)備可靠度函數(shù)及其殘余壽命的建模方法。最后通過具體案例說明了間接狀態(tài)監(jiān)測(cè)下基于最小維修費(fèi)用和殘余壽命相結(jié)合的方法制定最優(yōu)維修策略的實(shí)施步驟,運(yùn)用最小維修成本和殘余壽命相結(jié)合的方法制定設(shè)備狀態(tài)維修決策標(biāo)準(zhǔn)不僅可以節(jié)約維修費(fèi)用還可以有效防止設(shè)備突然停機(jī)。
[Abstract]:Modern manufacturing equipment is the core of the enterprise, in order to ensure the smooth progress of production, Enterprises often use condition condition Based maintenance to maintain equipment. State repair refers to track the running status of equipment at different points and collect the related index value to diagnose the aging of equipment. Finally, it is a preventive maintenance method to replace the damaged parts in advance. In the previous literature at home and abroad, many scholars put forward the optimal maintenance strategy for direct condition monitoring. The purpose of this paper is to establish an optimal preventive maintenance strategy for equipment which can not be directly diagnosed under indirect condition monitoring, in which the failure rate of the equipment is expressed by Weibull proportional failure rate model. The state probability of the equipment is calculated by Bayesian formula, and the decision-making standard is formulated by combining the partially observable Markov decision process with dynamic programming. In this paper, the concept of decision criteria is introduced for the convenience of discussion. In fact, the decision criteria for preventive maintenance of equipment depend on the age at which the equipment is in service. The probability distribution of equipment deterioration state and the minimum average maintenance cost of equipment replacement. The stochastic probability relationship between the index value and the aging state is established by using the Bayesian rules and the hidden Markov model. The recursive calculation method is introduced to determine the minimum average maintenance cost in the decision standard. The rationality of the iterative method is verified by an example, and the long-term average cost of the equipment under direct and indirect condition monitoring is compared. In the third chapter, the variation characteristics of the long-term average maintenance cost of the equipment with different parameters are studied. In view of the fact that equipment availability is less considered in traditional maintenance decision models, In chapter 4th, a modeling method of reliability function and residual life of equipment under the condition that the aging state of equipment can not be directly measured but some useful information can be obtained by state monitoring is also given. Finally, a concrete example is given. The implementation steps of making optimal maintenance strategy based on the combination of minimum maintenance cost and residual life under indirect condition monitoring are explained. The method of combining minimum maintenance cost and residual life can not only save the maintenance cost but also prevent the sudden shutdown of the equipment.
【學(xué)位授予單位】：重慶大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2011
【分類號(hào)】：TH165.3

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