防灾与环境

基于数字孪生的施工隧道智能通风系统研究

  • 吴元金 ,
  • 孙毅 ,
  • 商家旭 ,
  • 王树刚
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  • 1.中铁隧道局集团(上海)特种高新技术有限公司,上海 301206;
    2.大连理工大学 建设工程学部,辽宁 大连 116024
吴元金(1984—),男,江西玉山人,高级工程师,主要从事隧道与地下工程环境控制技术管理与研究工作。E-mail:258334960@qq.com
王树刚(1963—),男,辽宁葫芦岛人,博士,教授,主要从事隧道智能通风技术研究工作。E-mail:sgwang@dlut.edu.cn

收稿日期: 2024-05-28

  网络出版日期: 2025-05-06

基金资助

中国中铁股份有限公司科技研究开发计划(CZ02-专项)

Research on Intelligent Ventilation System for Tunneling Based on Digital Twin

  • Wu Yuanjin ,
  • Sun Yi ,
  • Shang Jiaxu ,
  • Wang Shugang
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  • 1. China Railway Tunnel Bureau Group (Shanghai) Special High-Technology Co.,Ltd, Shanghai 301206, P.R. China;
    2. Dalian University of Technology, Faculty of Infrastructure Engineering, Liaoning, Dalian 116024, P.R. China

Received date: 2024-05-28

  Online published: 2025-05-06

摘要

传感器技术、物联网、大数据以及人工智能技术已广泛应用于隧道建设工程领域,促进了智慧隧道通风系统数字孪生的发展。本研究旨在探索智慧隧道施工通风系统的数字孪生应用,以实现精准通风调控效果,提高施工环境安全管理水平和通风效率。从构建施工隧道通风系统数字孪生的相关研究基础与智能通风的现状分析入手,提出了算测协同的智慧隧道施工通风系统的数字孪生构架,由实体空间、虚拟空间、数据融合、机理模型和应用服务5个模块组成。进一步设计了智能通风数字孪生管理平台架构,针对数字孪生的同步机制,提出了实时数据驱动的多维融合模型,以实现虚拟空间与实体空间状态和动作的精准映射。创建了简捷的施工隧道智能通风系统,并将其融入智能通风数字孪生管理平台且已在某施工隧道通风中获得成功应用。本研究为施工隧道通风管理提供了一种新的思路和方法。

本文引用格式

吴元金 , 孙毅 , 商家旭 , 王树刚 . 基于数字孪生的施工隧道智能通风系统研究[J]. 地下空间与工程学报, 2025 , 21(2) : 720 -729 . DOI: 10.20174/j.JUSE.2025.02.39

Abstract

The development achievements of sensor technology, Internet of Things, big data, and artificial intelligence have been widely applied in the field of tunnel construction engineering, promoting the development of digital twins for smart tunnel ventilation systems. This study aims to explore the application of digital twins in intelligent ventilation systems for tunneling to achieve accurate regulation of ventilation parameters and enhance safety and efficiency in construction environments. This paper took the fundamental related to establishing the digital twin of construction tunnel ventilation systems and the current situation analysis of intelligent ventilation as the point of penetration. The digital twin framework of an intelligent ventilation system for tunneling with computation-measurement complementary was proposed, which consisted of five modules: physical space, virtual space, data fusion, mechanism model and application services. To effectively implement the digital twin, the research designed the architecture of the intelligent ventilation digital twin management platform and introduced a real-time data-driven multidimensional fusion model to achieve accurate mapping of states and behaviors between the virtual and physical spaces. Based on the proposed theories and methodologies, the study conducted practical application and validation in a real tunnel construction ventilation system. By integrating the developed intelligent ventilation twin model into the construction management platform, successful applications were achieved. Consequently, this study provided a new method for ventilation management in construction tunnels by integrating digital twins into daily ventilation management.

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