Affiliations: [a] State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, China
| [b] School of Traffic and Transportation, Beijing Jiaotong University, Beijing, China
| [c] Beijing Research Center of Urban Traffic Information Sensing and Service Technology, Beijing Jiaotong University, Beijing, China
Abstract: Due to the mechanical, electrical and information tripling coupling relationships among the components of mechatronics system, it is not reasonable enough to evaluate the criticality of components only in the view of physical structure or function. Our work makes two contributions. Firstly, the concept of the key components of mechatronics system is defined, and three identification measures of components have been proposed from system structure, function and the impact of single fault components on the whole system respectively. The structural importance is calculated based on the improved importance evaluation matrix; the functional importance is calculated using IPR algorithm; and the failure relevance importance is calculated based on cascading failure process. Secondly, a fuzzy clustering method for key component identification of mechatronics system is proposed, which calculates the comprehensive importance according to the characteristic of clustering center and the membership degree of the component. Taking a component network of China Railway CRHX EMU vehicle bogie system as an example, a list of ordered comprehensive importance of components is given by combining attribute characteristics of clustering centers with the degree of membership of each component, and the results show that the accuracy of the identification is 83.3%.
Keywords: Comprehensive importance of components, key components identification, fuzzy clustering method, mechatronics system
