• ISSN 0258-2724
  • CN 51-1277/U
  • EI Compendex
  • Scopus
  • Indexed by Core Journals of China, Chinese S&T Journal Citation Reports
  • Chinese S&T Journal Citation Reports
  • Chinese Science Citation Database
Volume 30 Issue 4
Jul.  2017
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Article Contents
PENG Qiyuan, FENG Liping, WEN Chao, ZHANG Xinzhu. Structural Brittleness Analysis of Information Transfer Process of High-speed Railway Train Control[J]. Journal of Southwest Jiaotong University, 2017, 30(4): 796-801,809. doi: 10.3969/j.issn.0258-2724.2017.04.019
Citation: PENG Qiyuan, FENG Liping, WEN Chao, ZHANG Xinzhu. Structural Brittleness Analysis of Information Transfer Process of High-speed Railway Train Control[J]. Journal of Southwest Jiaotong University, 2017, 30(4): 796-801,809. doi: 10.3969/j.issn.0258-2724.2017.04.019

Structural Brittleness Analysis of Information Transfer Process of High-speed Railway Train Control

doi: 10.3969/j.issn.0258-2724.2017.04.019
  • Received Date: 27 Jun 2016
  • Publish Date: 25 Aug 2017
  • The majority of previous studies on train control process safety focused on individual subsystems; this approach lacks wholeness and ignores the risk-sharing problem introduced by information transfer between different subsystems. Here, a three-level system, namely a computer-based interlocking system, train control system, and centralized train control system, was modelled from the perspective of information passing between subsystems, and the structural brittleness of the train control process was analysed. First, the structural brittleness of the high-speed railway train control process was stated according to brittleness sources, the brittleness propagation path, and the system crash standard. Then, a simulation platform was set up for system brittleness analysis based on the I/O file stream in CPN Tools and C# programming language, and a simulation example was designed. The results show that the average correlation between sub-transitions in the movement authority request submodel is 56.72%, and that in the CTCS-3 submodel is 9.56%; these results provide a reference for the differentiated typical safety management strategy.

     

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