城市轨道交通数字孪生技术架构及其应用
辛佐先1,2裴芳琼1,2王柳2
Urban Rail Transit Digital Twin Technology Architecture and Application
XIN ZuoxianPEI FangqiongWANG Liu
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作者信息:1.上海市隧道工程轨道交通设计研究院， 200235， 上海
2.上海申电云数字科技有限公司， 200063， 上海
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Affiliation:Shanghai Tunnel Engineering & Rail Transit Design and Research Institute, 200235, Shanghai, China
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关键词:
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Key words:
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DOI:10.16037/j.1007-869x.2023.08.041
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中图分类号/CLCN:U29.39
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栏目/Col:应用技术
摘要:
目的：研究数字孪生技术在城市轨道交通行业的应用，提出适用于城市轨道交通应用场景的数字孪生技术架构，并在典型应用场景进行实践应用。方法：以城市轨道交通运维管理业务需求为导向，从数据感知、融合处理、功能实现三个层次分析数字孪生技术架构，重点对数字孪生体进行分析，利用数据中台对静态数据和动态数据进行融合治理，研究基于机理模型和基于数据驱动的仿真方法，建设仿真模型库提供统一的仿真服务，选取城市轨道交通车站运维管理和列车运维管理作为典型业务应用场景进行实践应用。结果及结论：提出的城市轨道交通数字孪生技术架构以运维管理业务需求为导向，以静态数据、动态数据以及仿真模型组成的数字孪生体为核心，可满足城市轨道交通车站运维管理和列车运维管理场景的应用需求，实现了设备实时告警、设备剩余寿命预测、智能排故、应急处置建议、人员管理等运维应用，可及时评估设备健康情况，降低事故发生概率，提升处置效率。
Abstracts:
Objective: It is aimed to explore the application of DTT (digital twin technology) in URT (urban rail transit) industry, and to propose a DTT architecture suitable for URT application scenarios with practical implementation in the typical scenarios. Method: Guided by URT OM (operationmaintenance) management business requirements, the DTT architecture is analyzed from 3 levels: data perception, fusion processing, and functionality realization. Special emphasis is placed on the analysis of digital twin entity, utilizing a data middle office to amalgamate and govern static and dynamic data. Methods based on mechanistic models and datadriven simulation are studied, and standardized simulation service is provided by simulation model library. station OM management and train OM management in URT are selected as typical application scenarios for practical implementation. Result & Conclusion: The proposed DTT architecture for URT is oriented towards OM management business requirements, centered on a digital twin entity composed of static data, dynamic data, and simulation models. This architecture can effectively meet the application needs of URT station OM management and train OM management scenarios, enabling equipment realtime alarms, equipment remaining life prediction, intelligent troubleshooting, emergency response recommendations, personnel management, and other OM applications. Timely assessment of equipment health can be provided to reduce accident occurrence probability and improve disposal efficiency.
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