城区高铁大直径盾构隧道施工智能控制理论与关键技术

The high density of structures and population brings high risk of construction for high-speed large-diameter shield tunnel in urban areas.The intelligent control of shield tunnel construction is of great significance for the fine construction of high-speed railway tunnel. However, in the process of large-diameter shield tunneling, shield equipment, active and passive parameters and formation information generate massive multi-source heterogeneous data, which leads to serious difficulties in the realization of intelligent control of high-speed shield tunnel construction. This project is aimed at key problems such as tool wear, attitude control and stability of the excavation face faced by high-speed railway large-diameter shield tunnel construction. Specific content includes, based on fracture mechanics theory and tool collision test, the mechanism and configuration method of shield cutter collision damage are studied. The shield tool wear big data prediction model and the tool wear intelligent warning platform based on shield tunneling dynamic information are established. The large-diameter shield attitude control method is studied through the shield tunneling test, and the high-precision and high-intelligence attitude control system is established based on the robust learning model. The stability model and determination method of excavation face are investigated by centrifugal model and triaxial fracturing test. The multi-source information fusion technology is used to establish the stability control system for shield construction excavation surface stability. Finally, combined with the actual project, the key theory and technology of intelligent construction of high-speed large-diameter shield tunnel are established through the large data analysis of shield tunneling.

城市地区建（构）筑物密集、人群密度大，高铁大直径盾构隧道进入城区施工风险高，盾构隧道施工智能控制对于高铁隧道精细化建设具有重要意义。然而大直径盾构掘进过程中盾构设备、主被动参数以及地层信息等产生海量的多源异构数据，导致高铁盾构隧道施工智能控制的实现面临严重困难。本项目针对高铁大直径盾构隧道施工面临的刀具磨损、姿态控制以及开挖面稳定等关键性问题，具体内容包括：基于断裂力学理论和刀具碰撞试验，研究盾构刀具碰撞损伤机理及配置方法，建立盾构掘进刀具磨损信息动态识别方法；通过盾构模拟掘进试验，研究大直径盾构约束荷载计算模型，基于鲁棒学习方法建立盾构姿态智能控制理论与方法；通过离心模型和三轴劈裂试验研究开挖面稳定机理及判定方法，基于深度学习理论建立盾构施工开挖面及地层稳定智能控制方法。最后结合高铁盾构隧道实际工程，通过盾构掘进大数据分析和多源数据融合技术，建立高铁大直径盾构隧道智能施工关键理论与技术。

城市地区建（构）筑物密集、人群密度大，高铁大直径盾构隧道进入城区施工风险高，盾构隧道智能施工对于高铁隧道安全、精细化建设具有重要意义。然而大直径盾构掘进过程中盾构设备、主被动参数以及地层信息等产生海量的多源异构数据，导致高铁盾构隧道施工智能控制的实现面临严重困难。本项目针对高铁大直径盾构隧道施工面临的刀具磨损、姿态控制以及开挖面稳定等关键性问题，具体工作包括：基于断裂力学理论和刀具碰撞试验，研究了盾构刀具碰撞损伤机理及配置方法，建立了基于盾构掘进动态信息盾构刀具磨损智能预测模型预警方法；开展了盾构掘进模型试验，构建了盾构掘进负载模型和动力学模型，提出了基于模型预测控制算法的盾构掘进轨迹自动跟踪控制方法；通过离心模型和三轴劈裂试验研究盾构开挖面失稳机理，提出了合理支护压力设定方法，基于随机森林和粒子群优化算法建立了盾构施工开挖面稳定智能控制方法。结合实际工程，构建了城区高铁盾构掘进智能控制理论与方法，成果可为高铁大直径盾构隧道的安全高效施工提供理论和技术支撑。