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隧道建设（中英文） ›› 2025, Vol. 45 ›› Issue (12): 2364-2375.DOI: 10.3973/j.issn.2096-4498.2025.12.016

• 施工技术 • 上一篇    下一篇

面向小断面隧洞截割施工的知识图谱及工艺规划方法设计与系统开发

温承永1, 2， 应宗权1, 2, *， 汪海洋1, 2， 王东3， 李博3， 谢骏3   

  1. （1. 中交四航工程研究院有限公司， 广东 广州 510230； 2. 中交集团 交通基础工程环保与安全重点实验室， 广东 广州 510230； 3. 中交四航局第四工程有限公司, 四川 成都 610213）
  • 出版日期:2025-12-20 发布日期:2025-12-20
  • 作者简介:温承永（1989—），男，江西九江人，2014年毕业于长沙理工大学，港口、海岸及近海工程专业，硕士，高级工程师，主要从事数字化施工技术研究工作。E-mail: wenchengyong@ccccltd.cn。 *通信作者： 应宗权， E-mail:yingzongquan@ccccltd.cn。

Design and System Development of Knowledge Graph and Process Planning Methods for Excavating Tunnels With Small Cross-Sections

WEN Chengyong1, 2, YING Zongquan1, 2, *, WANG Haiyang1, 2, WANG Dong3, LI Bo3, XIE Jun3   

  1. (1. CCCC Fourth Harbor Engineering Institute Co., Ltd., Guangzhou 510230, Guangdong, China; 2. Key Laboratory of Environment and Safety Technology of Transportation Infrastructure Engineering, CCCC, Guangzhou 510230, Guangdong, China; 3. The Fourth Engineering Company of CCCC Fourth Harbor Engineering Co., Ltd., Chengdu 610213, Sichuan, China)
  • Online:2025-12-20 Published:2025-12-20

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摘要： 为实现小断面隧洞施工工艺参数的智能化生成与动态优化，提升施工安全性和效率，针对小断面隧洞悬臂式掘进施工中工艺参数配置存在的共性化与差异化管控难题，提出一种基于知识图谱与图模型推演的智能掘进工艺规划方法。首先，围绕掘进机构件、施工环境与质量控制要素，构建结构化掘进知识图谱，并引入图卷积网络实现异构知识的语义融合与实体对齐；其次，设计结合约束规则与相似度计算的方案推演机制，利用历史数据库与边界条件建立参数自适应的工艺规划方法；再次，在虚幻引擎平台上开发掘进施工推演与数字孪生系统，集成DeepSeek-R1语义推理模型，实现施工条件的结构化识别、方案问答与动态优化；最后，将该系统应用在四川亭子口灌区小断面输水隧洞施工项目中进行验证，毛洞拱顶沉降可控制在5 mm内，截割超欠挖量可控制在5 cm内。相较传统经验法，该方法在小断面隧洞施工工艺智能规划和参数自适应优化方面提升效果显著，为小断面隧洞智能化截割施工提供了新的思路及可行的技术路径。

关键词: 小断面隧洞, 悬臂式掘进施工, 知识图谱, 工艺规划, 智能问答, 方案推演

Abstract: To achieve intelligent generation and dynamic optimization of the process parameters in the construction of tunnels with small cross-sections, aiming to enhance construction safety and efficiency, an intelligent excavation process planning method based on knowledge graphs and graph model inference is proposed. This method addresses the challenges of generalized and differentiated management in configuring the process parameters for cantilever excavator in the construction of tunnels with small cross-sections. Firstly, a structured excavation knowledge graph is designed considering the excavator components, construction environment, and quality control elements. Graph convolutional networks are introduced to achieve semantic fusion and entity alignment of heterogeneous knowledge. Secondly, a scheme deduction mechanism based on rule constraints and similarity computation is proposed. By integrating historical databases and construction boundary conditions, a parameter-adaptive process planning method is established. Subsequently, the excavation process is simulated and a digital twin system employing unreal engine is developed. By integrating the DeepSeek-R1 semantic reasoning model, the system enables structured recognition of construction conditions, process-scheme Q&A, and dynamic optimization. The proposed system was applied and validated in the construction of a water-conveyance tunnel with a small cross-section in the Tingzikou irrigation construction project in Sichuan, China, yielding a tunnel crown settlement within 5 mm and an overbreak/underbreak within 5 cm. Compared to traditional empirical methods, the proposed approach demonstrates remarkable improvements in the intelligent construction-process planning and adaptive optimization of parameters for the excavation of tunnels with small cross-sections, providing novel insights and a feasible technical pathway for the intelligent excavation of such tunnels.

Key words: small cross-section tunnel, cantilever excavation and construction, knowledge graph, process planning, intelligent Q&, A, scenario simulation

主办单位：中铁隧道勘察设计研究院有限公司    主管单位：中铁隧道局集团有限公司

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