Design of Railway Disaster Prevention Monitoring Simulation System Based on Digital Twin and MBSE

被引：0
|
作者：
Ma X. [1 ,2 ]
Wang X. [1 ,2 ]
Jia L. [1 ,2 ]
Li S. [1 ,2 ]
机构：
[1] State Key Laboratory of Advanced Rail Autonomous Operation, Beijing Jiaotong University, Beijing
[2] School of Traffic and Transportation, Beijing Jiaotong University, Beijing
来源：
Zhongguo Tiedao Kexue/China Railway Science | 2024年 / 45卷 / 03期
关键词：
Digital twins; MBSE; Railway disaster prevention; SysML; System architecture;
D O I：
10.3969/j.issn.1001-4632.2024.03.16
中图分类号：
学科分类号：
摘要：
Regarding the issues of the existing railway disaster prevention monitoring system, such as low disaster scenario prediction capability, poor active prevention and control level, and insufficient ability to evaluate the effectiveness of disaster risk occurrence, development, evolution paths and response strategies, the digital twin and model-based systems engineering (MBSE) technologies are adopted to redesign the architecture of the railway disaster prevention monitoring and simulation deduction system. The System Modeling Language (SysML) is used to define the system requirements analysis, functional architecture, logical architecture, and physical architecture. Furthermore, the railway disaster prevention monitoring and simulation deduction system is developed, integrating railway environment scenario data collection, twin monitoring, scenario simulation, scenario deduction, scenario response, and data resource management functions. Research shows that the railway disaster prevention monitoring and simulation deducion system based on digital twins and MBSE proposed in this paper can provide new online deduction and prediction capabilities for disasters, fundamentally changing the responsive disaster prevention and control mode, which can provide important architecture guidance and technical support for the digital transformation of railway disaster prevention and monitoring systems and the upgrade of predictive and active prevention and control. © 2024 Chinese Academy of Railway Sciences. All rights reserved.
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页码：168 / 181
页数：13
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