Tunnel intelligent monitoring and early warning system integrating multi-source data: Methods, architecture, and engineering practices

IF 7.4 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Tunnelling and Underground Space Technology Pub Date : 2025-09-30 DOI:10.1016/j.tust.2025.107142

Junhong Li , Jiazhi Huang , Xiaohua Bao , Jun Shen , Xiangsheng Chen , Hongzhi Cui

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引用次数: 0

Abstract

Tunnel construction, operation, and maintenance generate vast amounts of data that are difficult to manage and analyze. To address this challenge, we developed an intelligent operation and maintenance platform that is multi-level, multi-dimensional, interconnected, and secure. The platform incorporates an automated monitoring subsystem with sensors, data acquisition, transmission, and analysis modules, enabling real-time collection and transfer. An integrated early warning system combines historical monitoring data with a D-vine copula joint probability model, dynamically quantifying parameter dependencies to establish adaptive risk thresholds. This approach supports detailed risk stratification through joint failure probability analysis, outperforming traditional single-threshold methods. A visualization subsystem builds comprehensive geological and tunnel models from multi-source data, improving spatial transparency for decision-making. Ground-penetrating radar and three-dimensional image reconstruction are further integrated to enable regular defect detection. Applied to the Shizimen Tunnel Project in the Hengqin Free Trade Zone, the platform enhances tunnel safety management by automating data processing and monitoring, strengthening early warning capability, and providing advanced visualization tools. These innovations optimize decision-making and improve the overall safety and efficiency of tunnel operations.

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集成多源数据的隧道智能监测预警系统：方法、体系结构与工程实践

隧道的建设、运营和维护产生了大量难以管理和分析的数据。为应对这一挑战，我们开发了多层次、多维度、互联互通、安全的智能运维平台。该平台集成了一个带有传感器、数据采集、传输和分析模块的自动监控子系统，实现了实时收集和传输。综合预警系统将历史监测数据与D-vine copula联合概率模型相结合，动态量化参数依赖关系，建立自适应风险阈值。该方法通过联合失效概率分析支持详细的风险分层，优于传统的单阈值方法。可视化子系统从多源数据构建综合地质和隧道模型，提高决策的空间透明度。探地雷达和三维图像重建进一步结合，可以定期检测缺陷。该平台应用于横琴保税区石子门隧道工程，通过自动化数据处理和监测，增强预警能力，提供先进的可视化工具，提高隧道安全管理水平。这些创新优化了决策，提高了隧道运营的整体安全性和效率。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Tunnelling and Underground Space Technology 工程技术-工程：土木

CiteScore

11.90

自引率

18.80%

发文量

454

审稿时长

10.8 months

期刊介绍： Tunnelling and Underground Space Technology is an international journal which publishes authoritative articles encompassing the development of innovative uses of underground space and the results of high quality research into improved, more cost-effective techniques for the planning, geo-investigation, design, construction, operation and maintenance of underground and earth-sheltered structures. The journal provides an effective vehicle for the improved worldwide exchange of information on developments in underground technology - and the experience gained from its use - and is strongly committed to publishing papers on the interdisciplinary aspects of creating, planning, and regulating underground space.