3D laser scanning equipment is an important equipment for reverse engineering. It is used as an information sensing device for the Industrial IoT. After analyzing and processing the measured data, it can issue construction instructions to equipment such as TBMs and shotcrete manipulator. It can be used to solve the problems of initial support contour detection, flatness detection, monitoring measurement, and so on in tunnel engineering. This paper considers that 3D laser scanning point cloud is a scattered point cloud and cannot be used directly. In order to extract the point cloud information as much as possible, it is necessary to fit the point cloud obtained by scanning first. This paper uses the triangulation method, the Poisson reconstruction method, and the Lagrange method, etc. to fit the scattered point cloud, analyzes the advantages and disadvantages of several fitting methods, and analyzes the accuracy of the surfaces generated by several fitting methods. This creates conditions for the subsequent utilization of the tunnel 3D laser scanning point cloud.

中文翻译：

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基于3D激光扫描的散射点云拟合算法研究

3D激光扫描设备是逆向工程的重要设备。它被用作工业物联网的信息传感设备。对实测数据进行分析处理后，可向TBM、喷射混凝土机械手等设备下达施工指令。可用于解决隧道工程中的初始支护轮廓检测、平整度检测、监测测量等问题。本文认为3D激光扫描点云是一种分散的点云，不能直接使用。为了尽可能地提取点云信息，需要先对扫描得到的点云进行拟合。本文采用三角剖分法、泊松重构法、拉格朗日法等方法对散点云进行拟合，分析了几种拟合方法的优缺点，分析了几种拟合方法生成的曲面的精度。这为隧道3D激光扫描点云的后续利用创造了条件。