隧道结构变形在运营阶段会受到各种环境因素的影响，准确高效的变形检测是保障隧道安全运营的必要手段。目前三维激光扫描技术在隧道断面变形分析方面存在数据量大、噪声干扰多、分析精度不高、缺乏整体分析等问题。鉴于此，围绕三维激光扫描的现场数据采集方法及流程、点云数据处理及变形分析方法开展研究。根据激光扫描仪原理获取隧道衬砌表观点云数据；通过滤波算法对采集点云数据进行预处理，降低了点云噪声；基于投影算法对处理后点云进行三维中轴线提取，根据隧道中轴线采用欧氏聚类分割算法提取断面，降低后续分析的数据量；采用椭圆拟合算法拟合隧道断面参数，并与设计标准圆进行对比得到隧道形变信息。依托工程实际进行方法验证，实验结果证实了该方法的可行性和有效性。

Tunnel structure deformation is influenced by various environmental factors during the operation phase. Accurate and efficient deformation detection is essential for ensuring the safe operation of tunnels. Currently, methods were used for tunnel cross-section deformation analysis with 3D laser scanning technology face challenges such as large data volumes, high noise interference, and low analysis accuracy. In response, the field data collection process using 3D laser scanning, point cloud data processing, and deformation analysis methods were focused. Point cloud data of the tunnel lining surface was obtained based on the principle of laser scanning. A filtering algorithm was applied to preprocess the collected point cloud data, reducing point cloud noise. A projection algorithm was used for the extraction of the 3D centerline from the processed point cloud. Euclidean clustering segmentation was employed to extract the tunnel cross-sections, which reduced the amount of data for subsequent analysis. An elliptical fitting algorithm was applied to fit the tunnel cross-section parameters, which were then compared with the standard circular design to obtain the deformation information of the cross-section. The method was validated with a practical engineering project. Experimental results confirm the feasibility and effectiveness of this approach.