基于T-S重要度和贝叶斯网络的多态液压系统可靠性分析

发布时间：2018-03-25 16:03

本文选题：T-S模糊　切入点：故障树分析　出处：《燕山大学》2011年硕士论文

【摘要】：广泛应用于各类设备、处于控制和动力传输重要核心地位的液压系统,其可靠性问题一直是工业技术亟待完善的关键所在,因此研究液压系统的可靠性分析方法具有重要的理论和实际意义。现有液压系统可靠性分析方法仍局限于常规的二态分析方法,由此建立的可靠性分析模型与实际情况存在较大差异。为此,本文致力于研究多态液压系统的可靠性分析方法,提出了T-S重要度算法以及T-S模糊故障树与贝叶斯网络相结合算法,以促进可靠性方法的发展及其在液压工程中的应用。在T-S模糊故障树分析方法基础上,针对系统处于不同的已知条件,提出了三种T-S重要度分析算法,包括T-S状态重要度、T-S规则重要度和T-S模糊重要度。通过与现有的传统故障树和模糊故障树的重要度算法进行对比,并结合液压机动力源系统应用实例,验证了所提T-S重要度算法的可行性。这三种重要度分别从不同角度反映了部件对系统的贡献,为不同条件下的可靠性工程应用提供了依据。在研究基于T-S模糊故障树、贝叶斯网络与Barlow方法的二态和多态系统可靠性分析方法的基础上,提出了由贝叶斯网络来处理T-S模糊故障树的方法。针对贝叶斯网络建造问题,提出由T-S模糊故障树向贝叶斯网络的转化方法,完成了贝叶斯网络与T-S模糊故障树,以及贝叶斯条件概率和几种常见T-S重要度的算法比较,验证了所提方法的可行性。结合T-S模糊故障树重要度算法和贝叶斯网络对某提梁机卷扬系统进行分析,提高了卷扬系统的可靠性。
[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.
【学位授予单位】：燕山大学
【学位级别】：硕士
【学位授予年份】：2011
【分类号】：TH137

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