摘要
针对既有铁路防灾监测系统灾害情景预测能力低、主动防控水平差,以及灾害风险发生、发展、演化的路径和应对策略效能评估能力不足等问题,采用数字孪生和基于模型的系统工程(MBSE)技术重新设计铁路防灾监测仿真推演系统架构,采用系统建模语言(SysML)定义系统需求分析、功能架构、逻辑架构和物理架构;研制集铁路环境情景数据采集、孪生监控、情景仿真、情景推演、情景应对、数据资源管理等功能为一体的铁路防灾监测仿真推演系统.结果表明:提出的基于数字孪生和MBSE的铁路防灾监测仿真推演系统可提供新的灾害在线推演预测能力,从根本上改变响应式的灾害防控模式,可为铁路防灾监测系统的数字化转型及预测性主动防控升级提供重要的架构指导和技术支撑.
Abstract
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.
基金项目
中央高校基本科研业务费专项(2023JBZY008)
维普
万方数据