摘要
本研究将以城市轨道交通隧道维护工作为研究对象,重点围绕机器视觉系统的应用展开研究,拟结合智能化检测显著提高隧道故障诊断准确性及维护效率。在简要阐述机器视觉系统理论基础后,详细阐述基于机器视觉方法的隧道检测系统架构设计,涵盖硬件选择配置、图像处理、软件系统设计等。在此基础上结合具体案例分析,有效验证了机器视觉在实际应用中的准确性。研究结果显示,机器视觉技术的引入可切实提升隧道维护工作整体效率质量,以此保障轨道交通安全运营。
This study will focus on the maintenance work of urban rail transit tunnels,with a particular emphasis on the application of machine vision systems.It aims to significantly improve the accuracy of tunnel fault diagnosis and maintenance efficiencyby combining intelligent detection.After briefly explaining the theoretical basis of machine vision systems,elaborate on the architecture design of tunnel detection systems based on machine vision methods,covering hardware selection and configuration,image processing,software system design,etc.Based on this,combined with specific case analysis,the accuracy of machine vision in practical applications has been effectively verified.The research results show that the introduction of machine vision technology can effectively improve the overall efficiency and quality of tunnel maintenance work,thereby ensuring the safe operation of rail transit.
作者
蒋翔
Jiang Xiang(Beijing Urban Construction Survey and Design InstituteCo.,Ltd.Nanning Branch,Nanning 530000,China)
出处
《绿色建造与智能建筑》
2025年第3期161-164,共4页
Green Construction and Intelligent Building
关键词
城市轨道交通
隧道维护
机器视觉技术
智能检测系统
病害识别率
urban rail transit
tunnel maintenance
machine vision technology
intelligent detection system
disease recognition rate
作者简介
蒋翔,大学本科,工程技术人员,工程师,主要研究方向:城市轨道交通建设期间地质勘察和基坑第三方监测、城市轨道交通隧道运营期间监测及运营期间涉铁项目安全评估。
