基于数字孪生的客站安全态势推演技术研究
Research on situation deduction for railway passenger station safety based on digital twin
王小书 1史天运 2白伟 3彭凯贝 3吕晓军3
作者信息
- 1. 中国铁道科学研究院 研究生部,北京 100081
- 2. 中国铁道科学研究院集团有限公司 科技和信息化部,北京 100081
- 3. 中国铁道科学研究院集团有限公司 电子计算技术研究所,北京 100081
- 折叠
摘要
为实现铁路客站实时掌握安全变化趋势,将数字孪生技术引入客站安全管理领域.通过设计客站安全态势推演框架,构建客站安全觉察、理解、预测的安全态势感知模型和安全结果的推演4 层体系;设计基于数字孪生的客站安全态势推演框架;根据旅客乘车流程为主线,抽取日常与突发事件时,客站人员-设备-列车-作业联动行为变化,形成客站数字孪生协作动行为模型,镜像反映客站安全态势推演过程;并以客站水灾事件为典型案例,细化态势推演协作动行为具体内容.研究结果表明:从外观保真性、数据采集准确性、过程模拟忠诚度3 个孪生指标,验证清河站数字孪生技术在客站安全态势推演中的有效性.研究结果可为客站安全管理提供强有力的技术支撑.
Abstract
In order to grasp the safety change trend of railway passenger station in real time,the digital twin technology was introduced into the field of passenger station safety management.Through designing the framework for situation deduction of passenger station safety,a four-layer deduction system including the safety situation awareness model of passenger station safe-ty awareness,understanding and prediction and the safety results was established,and a framework for situation deduction of passenger station safety based on digital twin was designed.According to the boarding process of passenger as the main line,the change in the coordinated actions among station personnel,equipment,trains,and operations during both routine and emergency scenarios was extracted,then a digital twin collaborative action behavior model of the station was formed,and the mirror image reflected the deduction process of passenger station safety situation.Taking the flood event of a passenger station as a typical case,the specific content of the cooperative behavior of the situation deduction was refined.The results show that the effectiveness of digital twin technology in safety situation deduction of Qinghe station is verified from three twin indexes:appearance fidelity,data acquisition accuracy and process simulation loyalty.The research results can provide strong technical support for the safety management of passenger stations.
关键词
智能车站/态势感知/态势推演/数字孪生/客站安全Key words
intelligent railway passenger station/situation awareness/situation deduction/digital twin/railway passenger station safety引用本文复制引用
基金项目
国家自然科学基金委员会-中国国家铁路集团有限公司铁路基础研究联合基金项目(U2268217)
中国铁道科学研究院集团有限公司科研开发基金项目(2023YJ125)
出版年
2024
NETL
NSTL
万方数据