Development and application of an intelligent operation and maintenance management platform for the Jiluo Road North Extension Yellow River Tunnel
Ding Ning1, Wang Xiaojian2*, Mao Sheng3, Kong Weixin4, Gong Chenyang5
1. Jinan City Construction Group Co., Ltd., Jinan 250014, Shandong, China; 2. Chengdu Sunrise Information Technology Co., Ltd., Chengdu 610037, Sichuan, China; 3. China Railway Siyuan Survey and Design Group Co., Ltd., Wuhan 430063, Hubei, China; 4. China Railway Jinan Group Co., Ltd., Jinan 250001, Shandong, China; 5. China Railway 14th Bureau Group Electrical Service Engineering Co., Ltd., Jinan 250014, Shandong, China
摘要 针对济泺路穿黄北延隧道运维管理对象复杂、数据来源异构、环境高湿高压封闭、应急响应时效要求高等问题,研发并提出一套集感知、分析、预测、决策、联动与反馈于一体的智能运维管理平台。平台构建了由感知层、数据层、模型层和应用层组成的总体架构,建立统一运维对象标识与信息映射机制,实现结构、设备、环境、交通及运维业务数据的标准化治理与深度融合;结合多源感知、机器学习、规则引擎和BIM(building information modeling)轻量化技术,形成交通态势预测、设备故障诊断、环境风险预警、三维可视化展示及应急联动处置等核心功能。研究表明,该平台可有效提升水下隧道运维效率、预测预警能力与应急处置水平,可为城市水下隧道智能运维提供工程参考。
Abstract: To address the challenges associated with the operation and maintenance of the operation and maintenance of the Jiluo Road North Extension Yellow River Tunnel, including complex maintenance objects, heterogeneous data sources, enclosed high-humidity and high-pressure conditions, and stringent requirements for rapid emergency response, an intelligent operation and maintenance management platform integrating sensing, analysis, prediction, decision-making, coordination, and feedback was developed. An overall architecture comprising a perception layer, a data layer, a model layer, and an application layer was adopted, and a unified identification and information mapping mechanism for operation and maintenance objects was established, thereby enabling standardized governance and deep integration of structural, equipment, environmental, traffic, and maintenance management data. Multi-source sensing, machine learning, rule engines, and lightweight BIM technologies were integrated, and key functions such as traffic state prediction, equipment fault diagnosis, environmental risk early warning, three-dimensional visualization, and coordinated emergency response were supported. The results indicated that operation and maintenance efficiency, predictive warning capability, and emergency response performance in underwater tunnels were effectively improved, and an engineering reference for the intelligent operation and maintenance of urban underwater tunnels was provided.
丁宁,王肖建,毛升,孔维信,龚晨阳. 济泺路穿黄北延隧道智能运维管理平台研发及应用[J]. 隧道与地下工程灾害防治, 2026, 8(3): 135-148.
Ding Ning, Wang Xiaojian, Mao Sheng, Kong Weixin, Gong Chenyang. Development and application of an intelligent operation and maintenance management platform for the Jiluo Road North Extension Yellow River Tunnel. Hazard Control in Tunnelling and Underground Engineering, 2026, 8(3): 135-148.
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2026, Vol. 8 
