Identifying Critical Component Set of High-Speed Train System Based on Topological Integrated Importance Analysis

The aim of this study is to introduce a critical component set identification method based on topological integrated importance and to illustrate the application of the proposed measure to high-speed train system. Firstly, a multi-layer-multi-granularity network model is proposed including virtual and actual nodes in view of equipment and other closely related factors, such as the environment, human and management. In addition, for convenience of calculation, the fusion rules of the links of different layers are designed, which merge different connections of the same node. Then, a topological integrated importance ranking algorithm by combining complex networks with actual function and risk characteristics is presented to identify critical components. Finally, a typical high-speed train system is provided for illustration of method purposes, and the critical component set is obtained.