## 5 Field Experimental Studies
### Analysis of HalfHole Point Cloud Data  
After obtaining the filtered and denoised 3D point cloud data, the halfhole point cloud data can be analyzed, and the curvature value is selected as the eigenvalue of the halfhole point cloud for analysis and processing. The principle of the processing is as follows: the normal vector difference of the point cloud is used as the point cloud expression signal. If the curvature of the point cloud at a certain place of the 3D model is larger than the set threshold, the point cloud expresses a changing signal, and if the curvature of the point cloud at a certain place is smaller than the set threshold, the point cloud expresses an unchanging signal [61; 62]. The halfhole point cloud coordinates data with curvature values as eigenvalues are visualized and colored according to curvature magnitude. In Figure 17, the colors range from orange to blue, where orange, yellow, and green represent higher curvature values, and blue represents lower curvature values. Thank you for your comment. In Figure 17, the different colors represent the curvature magnitude at various points of the model. The color gradient ranges from orange (indicating higher curvature) to blue (indicating lower curvature). We have added this explanation to the text for clarity. Please let us know if any further clarification is needed. Figure 16: Contrast before and after filtering. As shown in the figure above, in the actual construction process of the project, the retention of the blast holes after blasting is often not very good, and only through the visualization of the point cloud data can we get the desired results, so it is necessary to carry out a more in-depth analysis of the point cloud model. After the 3D point cloud model is cut again, the point cloud model of a single gun hole is extracted for analysis (Figure 18). Similar to Figure 17, the colors in Figure 18 represent the curvature magnitude, with orange indicating higher curvature values and blue indicating lower curvature values, providing further insights into the detailed geometry of the blast hole. The 3D point cloud coordinates of individual boreholes were projected onto a plane perpendicular to the borehole axis, with the colors representing the curvature magnitude. In Figure 19, orange indicates areas of higher curvature, while blue represents areas of lower curvature (Figure 19). In a large amount of noise data, according to the chance of occurrence of the correct data on the sampling data for random selection, according to the law of large numbers, stochastic simulation can be approximated by the correct results obtained so as to halfhole point cloud projection data fitted to the target circle can be obtained halfhole aperture diameter as well as the location of the center of the circle. The colors in Figure 20 represent the curvature magnitude, and the small circle in the middle indicates the location of the center of the circle based on curvature fitting. The effect of the fit is shown in Figure 20.  
The straight line through which the center of the fitted circle passes is the halfhole axis. The 3D point cloud processing software was used to fit the cylinder using the halfhole axis as the center axis and the radius of the fitted circle as the bottom radius, intersecting the halfhole point cloud model. The point clouds located inside the cylinder were labeled as compliant halfhole point cloud data. With a spacing of d = 3 cm on the fitted cylinder along the direction of the central axis of the slice cut, and each cutting plane again using the RANSAC algorithm for fitting, calculated the arc length C of the fitted circular arc, set the threshold C0 = \(\pi\)\(\pi\) (65 mm), when the arc length C is greater than the threshold value of C0, the halfhole segments are considered to be noncompliant with the requirements, need to be removed; when the arc length C is less than the threshold value of C0, it is believed that the halfhole segment is compliant with the requirements.