| 石波,王慧超,杨晓磊,李国玉,赵凯,王聪,杨密,林康.基于线阵相机/扫描仪的轨交隧道病害检测系统设计实现[J].电子测量与仪器学报,2024,38(6):181-194 |
| 基于线阵相机/扫描仪的轨交隧道病害检测系统设计实现 |
| Design and implementation of rail crossing tunnel disease detection systemcombined with linear array camera/scanner |
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| DOI： |
| 中文关键词: 隧道病害 隧道病害检测系统 系统集成 病害识别 病害定位 |
| 英文关键词:tunnel disease tunnel disease detection system system integration disease identification disease localization |
| 基金项目:中文基金项目山东省重点研发计划（重大科技创新工程）（2019JZZY010429）、山东科技大学科研创新团队支持计划（2019TDJH103）项目资助 |
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| Author | Institution |
| Shi Bo | College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China |
| Wang Huichao | College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China |
| Yang Xiaolei | Qingdao Xiushan Mobile Measurement Co.,Ltd., Qingdao 266590, China |
| Li Guoyu | Qingdao Xiushan Mobile Measurement Co.,Ltd., Qingdao 266590, China |
| Zhao Kai | College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China |
| Wang Cong | College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China |
| Yang Mi | College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China |
| Lin Kang | College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China |
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| 中文摘要: |
| 隧道维护可以避免隧道病害引发的安全事故,有效的维护依赖于全面和准确的隧道病害检测。传统的隧道病害检测依靠人工巡检,受隧道照明不足、检测时间短等因素的影响,检测效率低下且准确率低。针对这些隧道病害检测中的难题,根据轨交隧道结构均匀、轨道线路固定的特点设计了轨交隧道病害检测系统。系统将激光扫描技术与摄影测量技术相结合,使用激光扫描仪获取隧道三维点云,使用多线阵相机获取隧道影像,借助激光跟踪仪并设计虚拟靶标场对相机和扫描仪进行标定使其坐标基准统一。系统采用分布式的软件架构研发数据采集软件进行传感器交互和数据存储,并采用外触发的方法使传感器采集频率与车速匹配,最后基于Cesium框架研发数据管理平台对隧道数据进行管理。将系统应用于某隧道进行数据精度验证,实验表明轨交隧道病害检测系统能够在实际隧道中检测宽度为0.2 mm的裂缝和错台量0.5 mm的错台,具备轨交隧道病害检测能力。最后,通过将实验采集到的数据应用于隧道裂缝检测、错台检测、变形检测等方面,并对检测出的病害进行定位,证明了轨交隧道病害检测系统的实用性,为轨交隧道病害检测提供了可靠的解决方案。 |
| 英文摘要: |
| Tunnel maintenance is crucial for averting safety incidents triggered by tunnel structural issues. Effective maintenance depends on thorough and accurate detection of tunnel diseases. Traditional methods of tunnel inspection rely on manual detection, which are hindered by factors like inadequate tunnel illumination and limited inspection time, leading to inefficiencies and inaccuracies. To tackle these challenges in tunnel disease detection, a subway tunnel disease monitoring system has been devised, taking into account the uniformity of tunnel structures and the fixed nature of track lines. This system integrates laser scanning technology with photogrammetry, employing laser scanners to capture three dimensional point cloud data of tunnels and multi-line array cameras to obtain tunnel imagery. Laser trackers are utilized for calibrating the spatial coordinates of cameras and scanners to ensure a unified coordinate reference system. Adopting a distributed software architecture, the system develops data acquisition software for sensor communication and data storage. In addition, the system uses an external trigger mechanism to synchronize the sensor data acquisition rate with car speed. Finally, a data management platform, built upon the Cesium framework, is employed for the organization and manage of tunnel data. The system is applied to a tunnel to verify data accuracy. The experiment shows that the rail tunnel disease detection system can detect cracks with a width of 0.2 mm and misalignment with a size of 0.5 mm in the actual tunnel, and has the disease detection ability of subway tunnel. Finally, by applying the data collected in the experiment to tunnel crack detection, misalignment detection, deformation detection, etc., and locating the detected diseases, the practicability of the rail tunnel disease detection system is proved, and a reliable solution is provided for the subway tunnel disease detection. |
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