基于网络模型的复杂机电系统关键部件辨识方法

发布时间：2018-06-03 11:42

本文选题：复杂机电系统 + 网络模型　；参考：《北京交通大学》2017年硕士论文

【摘要】：复杂机电系统是融合机、电、液、光等多物理过程于一体并形成特定功能的复杂物理系统,具有结构复杂、高度关联、紧密耦合的特点,并呈现出网络化的趋势。部件间密切关联关系的存在使得系统"牵一发而动全身",一旦系统中某一部件发生故障,可能快速扩展至整个系统,严重时将会使系统陷入瘫痪状态。如何通过描述部件之间复杂的相互作用关系,对部件的重要性进行有效评估并从数量众多且关系繁杂的复杂机电系统中甄别出关键部件显得尤为重要。但是目前对于复杂机电系统的关键部件辨识还局限于传统的单一方法,不能满足其以网络化和相关失效为主要特点的系统关键部件辨识的需求。为此本文深入研究复杂机电系统的结构与功能特点,结合网络理论与方法,提出一种基于网络模型的复杂机电系统部件重要度评估及关键部件辨识方法,主要研究内容如下:首先,分析复杂机电系统的结构特征和功能特征以及体现出的网络化特征,在此基础上,以部件为节点,以部件之间的功能流为连接边,构建可反映系统结构和功能特征的作用关系网络模型,其中将节点的拓扑结构特征参数和可靠性参数作为节点的属性,将部件之间的功能依赖强度作为连接边的权重。其次,分析影响部件重要度的重要因素,以系统作用关系网络模型为载体,从节点在网络结构中所处地位及对系统功能发挥的作用两方面来度量节点重要度,分别用节点结构重要度和节点功能重要度来表示;分析节点的拓扑结构特征参数和节点的功能特征参数,结合节点的k-邻近域和位置信息研究节点的结构重要度评估方法,引入节点的使用可靠度和节点间的功能依赖强度对PageRank算法进行改进,研究节点的功能重要度评估方法;然后综合以上两方面因素,采用贝叶斯信息融合的方法得到节点重要程度的综合量度——节点综合重要度。最后,对复杂机电系统关键部件的概念进行定义,在部件重要度评估的基础上,结合部件故障后可能会引发系统级联失效的情况,对关键部件进行分类并给出其判别依据;基于可变模糊聚类迭代模型将各类关键部件的判别依据作为指标特征值,对复杂机电系统部件集进行聚类分析,结合最优聚类中心确定系统的关键部件集。将上述方法和模型以CRHX型动车组牵引系统为例进行了应用和验证。研究表明,本文提出的基于网络模型的复杂机电系统部件重要度评估与关键部件辨识方法具有良好的系统抽象能力及较高的准确性,为复杂机电系统关键部件的辨识开拓了新思路。
[Abstract]:Complex electromechanical system is a kind of complex physical system which integrates many physical processes, such as machine, electricity, liquid and light, and forms a specific function. It has the characteristics of complex structure, high correlation, tight coupling, and presents the trend of networking. The existence of close relationship between components makes the system "pull one hair and move the whole body". Once one part of the system fails, it may extend to the whole system quickly, and if serious, the system will be paralyzed. How to effectively evaluate the importance of components and identify key components from a large number of complex mechanical and electrical systems is particularly important by describing the complex interaction relationships between components. However, at present, the identification of key components of complex electromechanical systems is still limited to the traditional single method, which can not meet the needs of the identification of key components of complex electromechanical systems which are mainly characterized by network and related failures. In this paper, the structure and function characteristics of complex electromechanical system are studied in depth. Combining with network theory and method, a method for evaluating the importance of components and identifying key components of complex electromechanical system based on network model is proposed. The main research contents are as follows: firstly, the structural and functional characteristics of complex electromechanical systems and their network characteristics are analyzed. On this basis, the components are taken as nodes, and the function flow between components is taken as the connecting edge. The function relation network model which can reflect the system structure and function feature is constructed, in which the topological structure characteristic parameters and reliability parameters of nodes are taken as the attributes of the nodes, and the functional dependence strength among the components is taken as the weight of the connection edge. Secondly, the important factors affecting the importance of components are analyzed, and the importance of nodes is measured from two aspects: the position of nodes in the network structure and the function of the system. It is expressed by node structure importance degree and node function importance degree respectively, the topological structure characteristic parameter of node and the function characteristic parameter of node are analyzed, and the evaluation method of structural importance degree of node is studied by combining the k-adjacent domain and position information of node. This paper introduces the reliability of nodes and the strength of functional dependence between nodes to improve the PageRank algorithm, and studies the evaluation method of the function importance of nodes, and then synthesizes the above two factors. The Bayesian information fusion method is used to obtain the comprehensive measure of node importance-node synthesis importance. Finally, the concept of key components of complex electromechanical system is defined. On the basis of evaluating the importance of components, the key components are classified and judged according to the condition that the failure of components may lead to cascade failure. Based on the variable fuzzy clustering iteration model, the discriminant basis of all kinds of key components is taken as the index eigenvalue, and the component set of complex electromechanical system is analyzed by cluster analysis, and the key component set of the system is determined by combining the optimal clustering center. The above methods and models are applied and verified with the traction system of CRHX EMU as an example. The research results show that the proposed method based on network model has good abstract ability and high accuracy for evaluating the importance of complex electromechanical system components and identifying key components. It opens up a new idea for the identification of the key parts of complex electromechanical system.
【学位授予单位】：北京交通大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TH-39

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