The protection and monitoring of subway tunnels have always been an important guarantee for the safe operation of urban rail transit. The current monitoring of tunnel deformation and convergence relies on traditional technology methods such as convergence meters and electronic total stations. Although the 3D laser scanning method of stationary station setup and station-to-station splicing of monitoring station is gradually becoming mature, the error accumulation and slow operation efficiency brought by station-to-station splicing are still the bottleneck of subway tunnel protection and monitoring. Based on the analysis of the principles and advantages of mobile 3D laser scanning technology, this paper deeply studies the mobile 3D laser scanning technology for rapid collection of point cloud data in subway tunnels, proposes an improved RANSAC algorithm based on the tunnel ellipse parameter model, and extracts metro tunnel deformation information through denoising and fitting of the tunnel cross section point cloud data, achieving convergence analysis of metro tunnel section. The results show that this method can quickly and accurately obtain tunnel section data, which provides a new and efficient technical approach for subway tunnel protection monitoring.

地铁隧道的保护与监控一直是城市轨道交通安全运营的重要保障。目前隧道变形和收敛监测依赖于收敛计、电子全站仪等传统技术手段。虽然固定站架设和监测站站到站拼接的3D激光扫描方式逐渐成熟，但站到站拼接带来的误差积累和运行效率慢仍然是地铁隧道保护监测的瓶颈。 . 本文在分析移动3D激光扫描技术的原理和优势的基础上，深入研究了移动3D激光扫描技术在地铁隧道快速采集点云数据，提出了一种基于隧道椭圆参数模型的改进RANSAC算法，通过对隧道断面点云数据进行去噪拟合提取地铁隧道变形信息，实现地铁隧道断面的收敛性分析。结果表明，该方法能够快速、准确地获取隧道断面数据，为地铁隧道保护监测提供了一种新的、高效的技术途径。