# Automated Tunnel Point Cloud Segmentation and Extraction Method
## 3 Engineering Application
### Analysis of Tunnel Convergence Deformation and Misalignment Deformation  
Traditional methods for analyzing tunnel convergence deformation often use the designed axis normal vector plane to extract tunnel cross-sections of a specific thickness. However, the ring-based plane extraction technique proposed in this study can directly extract cross-sections based on the point cloud data of each tunnel ring, enabling precise extraction of tunnel segments and thickness. This method is also applicable to curved tunnels. The specific results are shown in Figure 18.  
Under the processing of the TMatch algorithm, the single-ring point cloud data of the tunnel are accurately extracted, while non-tunnel structural point clouds are removed, preserving the structural features of the single-ring tunnel. Subsequently, SVD fitting technology is applied to fit each ring, enabling central plane fitting based on the single-ring tunnel lining. By calculating the distance from each point in the point cloud to the fitted plane, we can extract the tunnel center cross-section point cloud for each ring, as shown in Figure 19. The extracted point cloud data are precisely positioned at the center of each ring, and through plane adjustments, the relative position of the cross-section extraction within a single ring is optimized. This process enhances the accuracy of tunnel intelligent management, meeting the requirements for high-precision detection and monitoring. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Algorithm** & **F1 Score** & **IoU** \\ \hline TMatch & 0.9527 & 0.9055 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Performance evaluation of the TMatch algorithm in tunnel segmentation. Figure 17: Schematic diagram of tunnel lining boundary features. Figure 18: Cross-section extraction. (**a**) Centerline extraction technology. (**b**) Ring plane fitting technology. Based on the extracted point cloud data, the structural deformation and misalignment of the tunnel ring segments were analyzed. For horizontal convergence deformation of the tunnel, least squares ellipse fitting was applied to compare the horizontal tunnel lining with the horizontal standard values provided by the detection system. The specific results are shown in Table 2.  
As shown in the table, the tunnel cross-sections extracted using the method presented in this paper, after being fitted with the above-mentioned fitting technology, have a maximum error of 1.4 mm, a minimum error of 0.2 mm, and an average error far less than 1 mm when compared to the standard data provided by the detection system. This demonstrates millimeter-level accuracy, validating the efficiency and reliability of the method in cross-section extraction. The standard data used in this paper were obtained through field measurements, using the Leica TM60 total station, Leica, Wetzlar, Germany (angular accuracy of 0.5 arcseconds, distance accuracy of 0.6 mm + 1 ppm) and the associated tunnel cross-section measurement software (SimpleSection_362871_V8.1). The post-processing of the data was conducted using Leica TunnelMonitor software ([[https://leica-camera.com/en-int](https://leica-camera.com/en-int)]([https://leica-camera.com/en-int](https://leica-camera.com/en-int))). The measurement method employed the \"proximal point search method\" for standard data detection. Specifically, field measurements were taken at the center of each tunnel ring segment to avoid obstructions such as bolt holes and pipe supports. The measurement