本文關鍵詞： 系統(tǒng)可靠性 冗余配置優(yōu)化 區(qū)間分析 多元狀態(tài)系統(tǒng) 元件重要度維修性　出處：《中國科學技術大學》2016年博士論文　論文類型：學位論文

【摘要】：系統(tǒng)可靠性作為工業(yè)系統(tǒng)中一個重要的性能評價指標,從上世紀初至今一直倍受國內外專家學者關注。在已有的系統(tǒng)可靠性設計和優(yōu)化以及維修性的研究中,許多工作都是基于特定的假設,即系統(tǒng)或元件的可靠性及失效時間的概率特性或相關參數(shù)是準確可知的。然而,在實際情況中,受限于觀測的難度,資源的限制以及系統(tǒng)復雜性等因素,不確定性問題在工業(yè)系統(tǒng)的建模過程中是不可避免的。對于許多工程系統(tǒng),尤其是在系統(tǒng)設計周期的起始階段,收集足夠多的數(shù)據(jù)不僅難度大而且經濟花費高。另外,隨著科技更新?lián)Q代的節(jié)奏越來越快,無論是工業(yè)領域還是電子科技領域,行業(yè)間的競爭也越來越激烈,導致在新產品的生產設計周期中往往沒有充足的時間來搜集足夠的信息和數(shù)據(jù),因此難以避免出現(xiàn)不確定性的問題。對于一些不確定參數(shù)的概率分布可知的情況,雖然已有相應的研究成果和方法,但是仍有許多情況,我們只能獲知不確定參數(shù)的上下界的相關信息。例如,工業(yè)零部件產品都存在一定范圍內的容錯誤差,這些誤差往往只有上下界的信息而且會被直接帶入組成的系統(tǒng)。隨著系統(tǒng)復雜化程度的增加,這種情況在實際系統(tǒng)中越來越多。因此,在這種情況下如何對系統(tǒng)可靠性問題進行定量分析和建模顯得尤為重要,然而這在以往的研究中卻鮮有涉及。本文以系統(tǒng)可靠性設計與優(yōu)化問題以及系統(tǒng)維修性問題為研究目標,考慮系統(tǒng)及其組成元件的可靠度、失效時間以及性能狀態(tài)的相關參數(shù)存在不確定性的情況,使用區(qū)間分析方法來研究具有區(qū)間值的不確定參數(shù)的問題,構建系統(tǒng)可靠性優(yōu)化問題以及維修性問題的模型,分析系統(tǒng)的可靠性等指標,設計優(yōu)化算法求解系統(tǒng)的最優(yōu)策略。本篇論文主要呈現(xiàn)的具體工作可以分為以下三個部分：第一部分討論了區(qū)間分析方法在系統(tǒng)可靠性優(yōu)化問題中的應用。我們分別考慮了熱備份系統(tǒng)中組成元件的可靠度存在不確定性的情況,冷備份系統(tǒng)中元件失效時間分布函數(shù)的參數(shù)存在不確定性的情況,以及溫備份系統(tǒng)中備份元件在低負荷運轉時工作壽命減速因子存在不確定性的情況,使用了區(qū)間分析方法處理不確定的參數(shù),將這些參數(shù)表示成為具有上下界的區(qū)間值形式,基于區(qū)間分析理論,構建了對應于三種不同冗余配置方式的系統(tǒng)可靠性優(yōu)化問題模型。對于具有區(qū)間值目標函數(shù)的優(yōu)化問題,本文定義了新的基于決策者性格偏好的區(qū)間值排序關系用于比較區(qū)間值之間的優(yōu)劣,設計了相應的遺傳算法來求解系統(tǒng)可靠性優(yōu)化問題的最優(yōu)配置策略。同時,我們通過數(shù)值實例和對比實例的結果驗證了區(qū)間分析方法的正確性和有效性,以及提出的遺傳算法的優(yōu)越性。第二部分針對一些實際系統(tǒng)的性能狀態(tài)具有不確定性或動態(tài)變化特性的情況,提出了一種新的具有區(qū)間狀態(tài)的多元狀態(tài)系統(tǒng)模型,這種系統(tǒng)模型的區(qū)間狀態(tài)表示該系統(tǒng)在當前狀態(tài)下的性能范圍。本文通過一個折疊門系統(tǒng)的示例引入了新的具有區(qū)間狀態(tài)的多元狀態(tài)系統(tǒng)模型,定義了該多元狀態(tài)系統(tǒng)的狀態(tài)空間,分析了該系統(tǒng)中元件狀態(tài)之間的轉移過程,討論了該多元狀態(tài)系統(tǒng)的狀態(tài)分布特性以及可靠性,給出了計算該多元狀態(tài)系統(tǒng)可靠性的迭代算法。此外,本文對一般的多元狀態(tài)系統(tǒng)的元件重要度衡定方法進行了拓展,給出了四種適用于具有區(qū)間狀態(tài)的多元狀態(tài)系統(tǒng)的元件重要度衡定方法,并且通過數(shù)值實例討論了系統(tǒng)的預設性能要求和元件重要度之間的關系。同時,數(shù)值實例的結果也表明了本文提出的四種元件重要度衡定方法得出的結論是一致的。第三部分研究了系統(tǒng)性能退化問題和系統(tǒng)維修性問題。首先,針對冷備份系統(tǒng)的冗余配置優(yōu)化問題,考慮了冷備份元件在待命狀態(tài)下的性能退化,在一般的冷備份系統(tǒng)的可靠性模型中引入了冷備份元件性能退化的情況,采用中心極限定理的方法給出了優(yōu)化問題目標函數(shù)的近似表達,使用了遺傳算法求解優(yōu)化問題,討論了冷備份元件在待命狀態(tài)下的性能退化對系統(tǒng)冗余配置優(yōu)化問題的影響。其次,繼續(xù)深入研究了具有區(qū)間狀態(tài)的多元狀態(tài)系統(tǒng)模型,考慮了系統(tǒng)性能隨工作時間推移而退化的情況以及系統(tǒng)在工作中可能發(fā)生隨機失效的情況,同時也考慮了針對系統(tǒng)性能退化實施非完美修復以及針對系統(tǒng)隨機失效實施最小修復,構建了系統(tǒng)狀態(tài)轉移過程的馬爾可夫模型,通過求解對應的切普曼-柯爾莫哥洛夫方程計算系統(tǒng)的可靠性和可用性。在實例中,本文分析了在不同的修復率下的具有區(qū)間狀態(tài)的多元狀態(tài)系統(tǒng)的可靠性和可用性,實例的結果驗證了本文所提出模型的正確性。
[Abstract]:The reliability of the system as an important index for evaluating the performance of the industrial system, from the beginning of the last century so far has always been the focus of experts and scholars at home and abroad. In the design and optimization of system reliability and maintainability of the existing research, many jobs are based on specific assumptions, the system reliability of system or component failure time and the probability characteristics or the relevant parameters are accurate. However, in reality, due to the difficulty of observing, resource constraints and system complexity and other factors, the uncertainty is unavoidable in the process of modeling in industrial system. For many engineering systems, especially in the initial stage of system design cycle, collect enough the data is not only difficult and high economic costs. In addition, with the development of science and technology upgrading in an increasingly fast pace, whether industry or electronic technology field, inter industry competition Competition has become increasingly fierce, resulting in the production of new product design cycles often do not have enough time to collect enough information and data, so it is difficult to avoid the problem of uncertainty. For some uncertain parameters of the probability distribution of the situation, although the research results and the existing methods of corresponding, but there are still many. We can only learn the related information of uncertain parameters of the upper and lower bounds. For example, industrial parts products are fault tolerance error within a certain range, the error is only the upper and lower bounds on the information and will be directly into the system. As the system complexity increases, this more and more in the actual system. Therefore, in in this case how to system reliability quantitative analysis and modeling is very important, however, that in previous studies in this department are rarely involved. Problems in the design and optimization of system reliability and maintainability problems as the research object, considering the reliability of the system and its components, the uncertainty of the relative parameters of failure time and performance status, to study with uncertain parameters of the problem of interval analysis method using interval, construction of system reliability and maintainability optimization problem model reliability index analysis, system design, optimal strategy optimization algorithm for solving the system. This paper mainly presents the specific work can be divided into the following three parts: the first part discusses the interval analysis method in the optimization of the reliability of the system. We consider the reliability of the components in the hot backup system does not exist the deterministic case, the uncertainty of the parameters of component failure time distribution function of cold backup system, and Backup temperature backup system in low load operation life of deceleration parameter uncertainty and parameters using interval analysis method to deal with uncertainty, these parameters will be expressed as interval with the upper and lower bounds of the value form of interval analysis based on the theory of system reliability optimization model is constructed corresponding to three different redundant configuration way. With interval valued objective function optimization problems, this paper introduces a new definition of interval decision character based on the preference value ordering relation for comparison between interval value quality, genetic algorithm is designed corresponding to the optimal allocation strategy of reliability optimization problem solving system. At the same time, we verify the correctness and validity of the interval analysis method through numerical examples and comparison results, and the superiority of the proposed genetic algorithm. In the second part, according to some actual The performance of state system has the characteristics of uncertainty or dynamic situation, put forward a new multi state system model with interval state, this state interval system model in the current state of the performance range of the system. In this paper, through a folding door system example introduced multiple state system model with interval the new definition of the state space, the multi state system, analyzes the transfer process between the state of the element in the system, discussed the distribution characteristics of the multi state system reliability calculation and the state, the multi state system reliability iteration algorithm is given. In addition, the multi state component importance scale system in general the method is extended to component importance weights are four applied to multi state systems with interval state setting method, and through the number The value of example discusses the relationship between the importance of preset performance requirements and system component. At the same time, numerical results also show that is consistent with four kinds of component importance weights is proposed in this paper will draw the conclusion. The third part studies the system performance degradation and system maintenance problems. Firstly, aiming at the cold backup the optimization problem of redundant configuration, considering the degradation performance of cold backup element in the standby state of the degradation of the performance of the cold backup components introduced in the reliability model of cold backup system in general, by the central limit theorem gives the approximate expression of the objective function of the optimization problem, using genetic algorithm to solve the optimization problem. The performance of cold backup components in the standby state under the effects of degradation on the optimization problem of system redundancy allocation. Secondly, further research with multi state interval State system model, considering the system performance with the working time and the degradation of the system at work may occur in random failure, but also consider the performance degradation for the system implementation and non perfect repair system for the random failure with minimal repair, construction of the Markov model process of system state transition, by solving the corresponding Karl Chapman - kolmogoroff equation to calculate the system reliability and availability. In the example, this paper analyzes the state of the multi state system with interval in different repair rates of reliability and availability, example results verify the correctness of the proposed model.

【學位授予單位】：中國科學技術大學
【學位級別】：博士
【學位授予年份】：2016
【分類號】：TB114.3
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本文編號：1463717