Affiliations: [a] State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China
| [b] School of traffic and transportation, Beijing Jiaotong University, Beijing, China
| [c] Volgenau School of Engineering, George Mason University, Fairfax, VA, US
| [d]
Beijing Research Center of Urban Traffic Information Sensing and Service Technologies, Beijing Jiaotong University, Beijing, China
Correspondence:
[*]
Corresponding author. Limin Jia, State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China. E-mail: [email protected].
Abstract: The aim of this study is to introduce a novel weakness measure based on Interval-Valued Intuitionistic Hesitant Fuzzy Choquet Integral (IVIHFCI), and to illustrate the applicability of the proposed weakness measure to the identification problem for weak component of complex electromechanical systems. First, the definition of weak component, which has a great impact on system performance, especially on system reliability during actual operation, is proposed along with the comparison of critical component. Then, the properties of components, such as reliability measures, centrality measures and failure consequence, are pre-chosen in terms of the holistic topological network and historical fault data. However, complete records of failure data, such as a component for a same car of a same high-speed train, are in shortage due to special structural designs of the holistic electromechanical system and complex operating environments. The proposed Interval-Valued Intuitionistic Hesitant Fuzzy Number (IVIHFN) is used to solve the problem of insufficient data of single component when the properties of components are calculated. Subsequently, IVIHFCI-based weakness measure, which takes into account the various attributes of components, is proposed to integrate IVIHFNs of all nodes’ properties and then, identify weak components. Finally, an illustrative example is provided for illustration-of-method purposes and to demonstrate difference between the proposed weakness measure used for weak component and the existing measures which are used to identify critical components.
