摘要
结构安全问题始终贯穿着隧道全寿命周期,是保障交通线路正常通行的关键节点之一。从隧道结构典型病害类型、病害感知、结构安全状态评价与病害整治等方面入手,梳理服役期隧道结构安全控制技术的研究现状。研究结果表明:服役期隧道结构病害主要包括水害、混凝土结构裂损、结构变形超限以及衍生病害;渗漏点的分布与隧道结构的复杂程度有一定关联。隧道病害受周边环境和结构自身共同影响,不同病害之间相互影响、关系密切,在特定情况下互为因果。高清数字图像、激光点云、探地雷达图像均可作为深度学习的训练数据集,病害识别的效果与计算机性能、GPU以及神经网络模型有直接关系,工程中通常借助快速移动平台提高病害的识别效率;依托量子计算的人工智能手段将是隧道病害感知发展的方向。健康监测系统的实施是掌握隧道结构安全状态的重要手段之一,针对其故障率高、成本高、条件要求高的缺点,业内已开展了关于轻量化监测的有关探索。规范中推荐的隧道安全评价方法有单指标评价和综合评价,目前常用的安全评价理论有数十种之多,未来应将相关理论与实际工程应用相结合作为研究的重点。注浆是隧道病害整治的重要手段之一。新技术的应用极大提升了隧道病害整治行业的技术水平,但距离大面积推广尚有一段距离,目前隧道病害整治效果的后评估体系尚未建立。
Structural safety always ran through the whole life cycle of the tunnel,and it is one of the key nodes to ensure the normal passage of the traffic line.Status of tunnel structure safety control technology during service is summarized from the aspects of typical defects types,defects perception,structural safety status evaluation and defects treatment.The research results indicate that tunnel structural defects during service mainly included water damage,concrete structure cracking,structural deformation exceeding limits,and derivative defects.The distribution of leakage points is somewhat related to the complexity of the tunnel structure.Tunnel defects are jointly affected by the surrounding environment and the structure itself,and different defects are interrelated and mutually influenced,and in specific situations,they are mutually causal.High definition digital images,laser point clouds,and ground penetrating radar images can all be used as training datasets for deep learning.The effectiveness of defects recognition is directly related to computer performance,GPU,and neural network models.In engineering,fast moving platforms are often used to improve the efficiency of defects recognition.Artificial intelligence based on quantum computing will be the direction of tunnel defects perception development.The implementation of a health monitoring system is one of the important means to grasp the safety status of tunnel structures.In response to its high failure rate,high cost and high condition requirements,the industry has conducted exploration on lightweight monitoring.The recommended tunnel safety evaluation methods in the specifications include single indicator evaluation and comprehensive evaluation.There are dozens of commonly used safety evaluation theories,and in the future,the focus of research should be on combined relevant theories with practical engineering applications.Grouting is one of the important methods for tunnel defects treatment.The application of new technologies has greatly improved the technical level of tunnel defects e treatment,but there is still a long way to go before it is widely promoted.At present,a post evaluation system for the effectiveness of tunnel defects treatment has not been established.
作者
黄俊
张顶立
梁文灏
董飞
李奥
赵光
杨奎
牛晓凯
HUANG Jun;ZHANG Dingi;LIANG Wenhao;DONG Fei;LI Ao;ZHAO Guang;YANG Kui;NIU Xiaokai(Urban Construction&Railway Design Division,JSTI GROUP,Nanjing 210019,China;Jiangsu Province Engineering Research Center of Underwater Tunnel Green Intelligent Technology,Nanjing 210019,China;Engineering Innovation Center for Urban Underground Space Exploration and Evaluation,Ministry of Natural Resources of the Peoples Republic of China,Nanjing 210016,China;Key Laboratory for Urban Underground Engineering of Ministry of Education,Beijing Jiaotong University,Beijing 100044,China;China Railway Engineering Design and Consulting Group Co.,Ltd.,Beijing 100055,China;China Railway Construction Co.,Ltd.,Beijing 100855,China;Beijing Municipal Road and Bridge Technology Development Co.,Ltd.,Beijing 100037,China)
出处
《铁道标准设计》
北大核心
2024年第4期1-19,共19页
Railway Standard Design
基金
江苏省科技计划项目(BE2020082-2,BE2022820,BE2022156)
国家重点研发计划项目(2022YFE0104300)。
关键词
服役期隧道
结构病害
病害感知
安全评价
病害整治
综述
tunnel in service
structural disease
disease perception
safety evaluation
disease treatment
summarize
