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| 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
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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 |
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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.
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Published: 12 October 2026
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