A blasting intelligent auxiliary design system and method based on three-dimensional point cloud data

Abstract

The present application relates to the technical field of point cloud data processing, and discloses a blasting intelligent auxiliary design system and method based on three-dimensional point cloud data, a blasting intelligent auxiliary design system based on three-dimensional point cloud data, comprising: outputting a down-sampled point set; establishing a hierarchical bounding box; calculating a concave curvature scale; calculating a bottleneck scale; generating an offset critical dominant index; generating a modulation distance field; generating an orifice skeleton curve; and generating a hole arrangement scheme.The offset critical dominant index generated by the present application can correct the distance field, effectively eliminating the non-physical trough caused by the bottleneck artifact; the orifice points are sampled along the skeleton curve at equal arc lengths to ensure reasonable distribution, the orifice axis direction is determined by the negative gradient of the modulation distance field to fit the local geometric features, and the hole depth is dynamically solved according to the depth constraint to adapt to the actual site; and the final generated hole arrangement scheme has high fitting with the geometric features of the step free surface, and provides a practical blast hole arrangement basis for site construction.

Description

Technical Field

[0001] This invention relates to the field of point cloud data processing technology, and more specifically, to a blasting intelligent auxiliary design system and method based on three-dimensional point cloud data. Background Technology

[0002] In bench blasting construction in open-pit mines, roadbed excavation and other projects, the rationality of the borehole design directly affects the blasting effect. At present, digital borehole design is mostly carried out by relying on three-dimensional point cloud data. Three-dimensional laser scanning and other technologies can accurately collect point cloud data of the free surface of the bench. However, the original point cloud data is huge and contains a large number of spatial coordinate points. Directly using it for geometric analysis will greatly increase the amount of calculation and reduce the design efficiency. Traditional point cloud downsampling methods are prone to losing key geometric features of the free surface and it is difficult to balance downsampling efficiency and geometric feature preservation.

[0003] Due to the influence of geological conditions and excavation construction, the free surface of the step has uncertain topological morphology, and local bottleneck areas with alternating concave and convex features are easily formed. Such bottleneck artifacts will cause non-physical valleys in the distance field of the free surface. Existing design methods have not analyzed this problem. They have neither quantified the curvature characteristics of the concave bending of the free surface nor detected the spatial proximity characteristics of local bottlenecks. They lack a two-dimensional offset critical judgment mechanism and cannot effectively correct the non-physical valleys in the distance field, which may lead to the selection of blast holes in false low-distance areas.

[0004] Existing designs for bench blasting borehole layouts often rely on manual experience or simple geometric calculations to determine borehole locations, borehole axis directions, and borehole depths. They fail to incorporate the actual geometric characteristics of the bench free surface for dynamic parameter generation. The distribution of borehole points is difficult to adapt to the curve shape of the free surface, and the borehole axis direction cannot match the normal characteristics of the free surface. The borehole depth design relies solely on fixed proportional values ​​without considering the differences in local geometric features. Ultimately, this results in a low degree of fit between the generated borehole layout scheme and the actual geometric characteristics of the bench free surface. During on-site construction, problems such as borehole positioning deviations and inconsistent drilling directions easily occur, affecting the overall effect of blasting operations. Summary of the Invention

[0005] This invention provides an intelligent assisted design system and method for blasting based on three-dimensional point cloud data, which solves the technical problems mentioned in the background.

[0006] This invention provides a blasting intelligent assisted design system based on three-dimensional point cloud data, comprising:

[0007] The point cloud downsampling module downsamples the original 3D point cloud data and outputs a downsampled point set, and calculates the local surface normal of the downsampled point set;

[0008] The hierarchical bounding box construction module uses downsampled point sets and local surface normals to construct triangular meshes and establish hierarchical bounding boxes for the triangular meshes.

[0009] The concave curvature scale calculation module calculates the concave curvature scale based on triangular meshes;

[0010] The bottleneck scale conversion module emits rays bidirectionally along the local surface normal, and obtains the intersection distance between the rays and the triangular mesh in conjunction with the hierarchical bounding box. It then uses the intersection distance to calculate the bottleneck gap on both sides and converts the bottleneck gap into the bottleneck scale.

[0011] The offset critical dominant index generation module selects the minimum value between the concave curvature scale and the bottleneck scale as the reachable scale, and generates the offset critical dominant index by combining the preset design resistance line, reachable scale and concave curvature scale.

[0012] The modulation distance field generation module converts the offset critical dominant index into modulation increments, and superimposes the modulation increments onto the original distances from the spatial points to the triangular mesh to generate the modulation distance field.

[0013] The orifice skeleton curve generation module extracts the isosurface with a value equal to the design resistance line from the modulation distance field to generate the modulation minimum resistance line surface, and calculates the intersection of the modulation minimum resistance line surface and the preset step top platform plane to generate the orifice skeleton curve.

[0014] The hole array scheme generation module samples and outputs the hole opening point along the hole opening skeleton curve, calculates the negative gradient direction of the modulation distance field at the hole opening point as the hole axis direction, advances along the hole axis direction to the point where the depth constraint is satisfied, and outputs the hole depth. The hole opening point, hole axis direction and hole depth are combined to generate the hole array scheme.

[0015] Furthermore, the specific calculation steps of the point cloud downsampling module include:

[0016] A three-dimensional voxel grid is constructed based on the voxel side length, and each point inside the original three-dimensional point cloud data is assigned to the corresponding spatial grid to form a voxel unit point set;

[0017] For non-empty voxel unit point sets, calculate the centroid points and collect all centroid points to generate a downsampled point set;

[0018] For each downsampling point in the downsampling point set, a fixed number of nearest neighbor points with the smallest Euclidean distance are selected within the downsampling point set to form a nearest neighbor set.

[0019] Calculate the mean vector and covariance matrix of the nearest neighbor set; perform eigenvalue decomposition on the covariance matrix to obtain eigenvalues ​​and eigenvectors, and extract the eigenvector corresponding to the smallest eigenvalue as the local surface normal of the downsampled point.

[0020] Furthermore, the specific calculation steps of the hierarchical bounding box building module include:

[0021] Define the tangent plane passing through the downsampling point using the local surface normal;

[0022] Within the set of downsampled points, the nearest neighbor set with the smallest distance to the downsampled point is selected using Euclidean distance as a metric. The nearest downsampled points within the nearest neighbor set are orthogonally projected onto the tangent plane to generate projection points that correspond one-to-one with the nearest downsampled points.

[0023] Triangulation is performed on the projection points within the tangent plane to obtain a two-dimensional triangulation result composed of the triangular connections between the projection points;

[0024] Based on the one-to-one correspondence between the projection points and the nearest neighbor downsampling points, each two-dimensional triangle in the two-dimensional triangulation result is mapped to a three-dimensional triangle composed of three corresponding nearest neighbor downsampling points, generating a triangular mesh.

[0025] Calculate the 3D coordinate extrema of triangles within a triangular mesh and construct an axis-aligned bounding box;

[0026] Recursively partition the set of triangles and construct a hierarchical structure that covers all axis-aligned bounding boxes to generate hierarchical bounding boxes.

[0027] Furthermore, the specific calculation steps of the concave curvature scale calculation module include:

[0028] The vertices of the triangular mesh are used as the points for calculating the curvature scale;

[0029] The tangent plane is determined using the local surface normal; a nearest neighbor set is selected within the downsampled point set; the points within the nearest neighbor set are orthogonally projected onto the tangent plane to obtain the projection points;

[0030] Two mutually orthogonal unit vectors that are orthogonal to the local surface normal are selected in the tangent plane and used as two-dimensional coordinate bases. The local coordinates and height of the projection point in the local coordinate system are calculated.

[0031] The fitting coefficients are obtained by fitting a quadratic surface using local coordinates and height; a quadratic matrix is ​​constructed using the fitting coefficients and the eigenvalues ​​are calculated as principal curvatures; the maximum value between the smaller negative value and the zero value among the principal curvatures is selected as the concave curvature amplitude.

[0032] The concave curvature scale is calculated using the concave curvature amplitude and numerical stability term.

[0033] Furthermore, the specific calculation steps of the bottleneck scale conversion module include:

[0034] Using the downsampling point as the ray origin and the local surface normal as the direction reference, construct a positive ray extending in the positive direction of the local surface normal and a reverse ray extending in the opposite direction of the local surface normal.

[0035] Using hierarchical bounding boxes, perform intersection searches between rays and triangular meshes for both forward and reverse rays;

[0036] In the intersection search, first determine whether the ray intersects with the axis-aligned bounding box corresponding to the hierarchical bounding box node. Prune nodes that do not intersect. For intersecting leaf nodes, determine whether the ray intersects with the triangle contained in the leaf node one by one.

[0037] For results where a ray intersects a triangle and the ray distance parameter is greater than the minimum search distance, record the coordinates of the intersection point and the distance from the ray's starting point to the intersection point as candidate intersection point distances;

[0038] Select the candidate intersection point distance with the smallest distance from all candidate intersection point distances, and obtain the forward intersection point distance and the reverse intersection point distance respectively;

[0039] The bottleneck gap on both sides is calculated by summing the distance between the forward intersection points and the distance between the reverse intersection points; the bottleneck gap is then converted into a bottleneck dimension.

[0040] Furthermore, the specific calculation steps of the offset critical dominant index generation module include:

[0041] For the downsampling points, obtain the concave curvature scale and the bottleneck scale;

[0042] The reachable scale is determined by selecting the minimum values ​​of the concave curvature scale and the bottleneck scale;

[0043] Receive the preset design resistance line; calculate the first ratio of the preset design resistance line to the reachable scale, and calculate the second ratio of the reachable scale to the concave curvature scale;

[0044] The critical deviation index is generated by multiplying the first ratio by one and subtracting the second ratio.

[0045] Furthermore, the specific calculation steps of the modulation range field generation module include:

[0046] For spatial points, determine the nearest point mapping with the minimum Euclidean distance on a triangular mesh;

[0047] Calculate the original distance using the length between the mapping of a spatial point and its nearest point;

[0048] The modulation increment is calculated by combining the preset design resistance line with the offset critical dominance index corresponding to the nearest point mapping; the original distance and the modulation increment are summed to generate the modulation distance field.

[0049] Furthermore, the specific calculation steps of the orifice skeleton curve generation module include:

[0050] A set of spatial points with values ​​equal to the preset design resistance line is extracted within the modulation distance field to generate the modulation minimum resistance line surface;

[0051] Determine a preset plane for the top platform of the step, including the plane normal and plane constant;

[0052] The orifice skeleton curve is generated by performing an intersection operation between the modulated minimum resistance line surface and the preset step top platform plane.

[0053] Furthermore, the specific calculation steps of the hole array scheme generation module include:

[0054] The orifice skeleton curve is represented as an arc length parameter curve; the sampling ratio coefficient and the design resistance line are received, and the arc length sampling step determined by the product of the sampling ratio coefficient and the design resistance line is calculated.

[0055] The aperture point is obtained by sampling at equal intervals on the arc length parameter curve according to the arc length sampling step size; the voxel side length is received, and the gradient component of the modulation range field at the aperture point is calculated using the central difference scheme containing the voxel side length and then collected to form a gradient.

[0056] The hole axis direction is obtained by taking the negative direction of the gradient and normalizing it.

[0057] The depth scaling factor and the design resistance line are received, and the hole axis parameter point is constructed in the hole axis direction. The hole depth is defined as the minimum advance distance that satisfies the requirement that the value of the modulation distance field at the hole axis parameter point is greater than or equal to the product of the depth scaling factor and the design resistance line.

[0058] The hole array scheme is generated by combining the hole opening point, hole axis direction, and hole depth.

[0059] This invention provides a blasting intelligent assisted design method based on three-dimensional point cloud data, comprising the following steps:

[0060] Step S101: Downsample the original 3D point cloud data to output a downsampled point set, and calculate the local surface normal of the downsampled point set;

[0061] Step S102: Construct a triangular mesh using the downsampling point set and the local surface normal, and establish a hierarchical bounding box for the triangular mesh;

[0062] Step S103: Calculate the concave curvature scale based on the triangular mesh;

[0063] Step S104: Emit rays bidirectionally along the local surface normal, obtain the intersection distance between the rays and the triangular mesh using the hierarchical bounding box, calculate the bottleneck gap on both sides using the intersection distance, and convert the bottleneck gap into the bottleneck scale.

[0064] Step S105: Select the minimum value between the concave curvature scale and the bottleneck scale as the reachable scale, and generate the offset critical dominant index by combining the preset design resistance line, reachable scale and concave curvature scale.

[0065] Step S106: Convert the offset critical dominance index into a modulation increment, and superimpose the modulation increment onto the original distance from the spatial point to the triangular mesh to generate a modulation range field.

[0066] Step S107: Extract the isosurface with a value equal to the design resistance line from the modulation distance field to generate the modulation minimum resistance line surface, and calculate the intersection of the modulation minimum resistance line surface and the preset step top platform plane to generate the orifice skeleton curve.

[0067] Step S108: Sample and output the orifice point along the orifice skeleton curve, calculate the negative gradient direction of the modulation distance field at the orifice point as the orifice axis direction, advance along the orifice axis direction to the point where the depth constraint is satisfied, and output the orifice depth. Combine the orifice point, orifice axis direction and orifice depth to generate the orifice array scheme.

[0068] The beneficial effects of this invention are as follows: This invention achieves efficient downsampling of the original point cloud through voxel meshes, while preserving key geometric features of the free surface, providing a reliable foundation for subsequent geometric analysis. This invention realizes two-dimensional offset critical analysis of the concave curvature and bottleneck features of the free surface. The generated offset critical dominant index can specifically correct the range field, effectively eliminating non-physical troughs caused by bottleneck artifacts, and ensuring that the modulated range field conforms to the actual geometry of the free surface. The borehole layout design parameters can be dynamically generated based on the geometric features of the free surface. Equal arc length sampling of borehole points along the skeleton curve ensures reasonable distribution. The borehole axis direction is determined by the negative gradient of the modulated range field to conform to local geometric features, and the borehole depth is dynamically solved according to depth constraints to adapt to the actual site conditions. The final generated borehole layout scheme has parameters that highly conform to the geometric features of the step free surface and matches the design logic of blasting engineering, providing a practical basis for borehole layout in on-site construction, and improving the geometric adaptability and engineering practicality of the step blasting borehole layout design. Attached Figure Description

[0069] Figure 1 This is a schematic diagram of the calculation process of the present invention;

[0070] Figure 2 This is a schematic diagram of the computational scenario of the present invention. Detailed Implementation

[0071] The subject matter described herein will now be discussed with reference to exemplary embodiments. It should be understood that these embodiments are discussed only to enable those skilled in the art to better understand and implement the subject matter described herein, and changes may be made to the function and arrangement of the elements discussed without departing from the scope of this specification. Various processes or components may be omitted, substituted, or added as needed in the examples. Furthermore, features described in some examples may be combined in other examples.

[0072] It should be noted that, unless otherwise defined, the technical or scientific terms used in one or more embodiments of the present invention should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in one or more embodiments of the present invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" indicate that the element or object preceding the term encompasses the elements or objects listed following the term and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0073] like Figures 1-2 As shown, a blasting intelligent assisted design system based on 3D point cloud data includes:

[0074] The point cloud downsampling module downsamples the original 3D point cloud data and outputs a downsampled point set, and calculates the local surface normal of the downsampled point set;

[0075] The hierarchical bounding box construction module uses downsampled point sets and local surface normals to construct triangular meshes and establish hierarchical bounding boxes for the triangular meshes.

[0076] The concave curvature scale calculation module calculates the concave curvature scale based on triangular meshes;

[0077] The bottleneck scale conversion module emits rays bidirectionally along the local surface normal, and obtains the intersection distance between the rays and the triangular mesh in conjunction with the hierarchical bounding box. It then uses the intersection distance to calculate the bottleneck gap on both sides and converts the bottleneck gap into the bottleneck scale.

[0078] The offset critical dominant index generation module selects the minimum value between the concave curvature scale and the bottleneck scale as the reachable scale, and generates the offset critical dominant index by combining the preset design resistance line, reachable scale and concave curvature scale.

[0079] The modulation distance field generation module converts the offset critical dominant index into modulation increments, and superimposes the modulation increments onto the original distances from the spatial points to the triangular mesh to generate the modulation distance field.

[0080] The orifice skeleton curve generation module extracts the isosurface with a value equal to the design resistance line from the modulation distance field to generate the modulation minimum resistance line surface, and calculates the intersection of the modulation minimum resistance line surface and the preset step top platform plane to generate the orifice skeleton curve.

[0081] The hole array scheme generation module samples and outputs the hole opening point along the hole opening skeleton curve, calculates the negative gradient direction of the modulation distance field at the hole opening point as the hole axis direction, advances along the hole axis direction to the point where the depth constraint is satisfied, and outputs the hole depth. The hole opening point, hole axis direction and hole depth are combined to generate the hole array scheme.

[0082] In one embodiment of the present invention, downsampling the original three-dimensional point cloud data to output a downsampled point set, and calculating the local surface normal of the downsampled point set, includes:

[0083] The original 3D point cloud data is represented as: ;in The original 3D point cloud data, The three-dimensional coordinate vector of the original point;

[0084] Based on voxel side length Construct a three-dimensional voxel mesh to form a voxel unit point set:

[0085] ;in Let the voxel side length be , For the first The set of points within an individual element unit;

[0086] Calculate the centroid point for a non-empty voxel unit point set:

[0087] ;in To reduce sampling points, The number of points inside the voxel unit point set;

[0088] Generate a downsampling point set by combining all centroids:

[0089] ;in For downsampling point set;

[0090] For any downsampling point within the downsampling point set Select points within the downsampling point set that are the same as the downsampling points. Minimum Euclidean distance Each point forms a nearest neighbor set:

[0091] ;in For the number of nearest neighbors, For the nearest neighbor set;

[0092] Calculate the mean vector for the nearest neighbor set: ;in Given the mean vector; calculate the covariance matrix:

[0093] ;in for The covariance matrix;

[0094] Steps for calculating local surface normal: Perform eigenvalue decomposition on the covariance matrix, satisfying:

[0095] ;in For eigenvalues, For the corresponding feature vectors; extract the minimum feature value. The corresponding eigenvectors are used as local surface normals:

[0096] ;in For local surface normals.

[0097] It should be noted that the voxel edge length is the edge length of the cubic unit used to construct the 3D voxel mesh, reflecting the spatial resolution of the voxel mesh. A preferred value is 0.1 meters to 0.5 meters, as this range is suitable for the density characteristics of the free surface point cloud in a step blasting scenario, allowing for point cloud downsampling while preserving key geometric features of the free surface. The original 3D point cloud data is a set of 3D coordinate points characterizing the spatial geometry of the step free surface. It can be acquired using a 3D laser scanner or photogrammetry system, and the acquisition must cover the entire area of ​​the step free surface. The voxel unit point set is the set of all points in the original 3D point cloud data that fall within the same voxel unit, reflecting the point cloud distribution within a single voxel unit. The centroid point is the geometric center coordinate point calculated from the non-empty voxel unit point set. The downsampled point set reflects the spatial geometry of the step free surface after downsampling. The number of nearest neighbors is a fixed number of nearest neighbors selected for each downsampling point, reflecting the scale of the local neighborhood point cloud. A preferred value is 15 to 30, which ensures sufficient point cloud size to support efficient calculation of the covariance matrix while avoiding the introduction of too many irrelevant points that could affect the accuracy of normal estimation. The covariance matrix is ​​a third-order square matrix calculated as the degree of dispersion of the nearest neighbor set relative to the mean vector, reflecting the discrete distribution characteristics of the nearest neighbor set in three-dimensional space. Eigenvalues ​​are numerical values ​​obtained by eigenvalue decomposition of the covariance matrix, reflecting the degree of dispersion of the nearest neighbor set in the direction of the corresponding eigenvector. The minimum eigenvalue is the eigenvalue with the smallest value after eigenvalue decomposition of the covariance matrix, reflecting the minimum dispersion of the nearest neighbor set in the direction of the corresponding eigenvector. The local surface normal is the eigenvector corresponding to the extracted minimum eigenvalue, reflecting the local spatial normal direction of the free surface of the step at the downsampling point.

[0098] It should be noted that the specific spatial construction rules of the three-dimensional voxel mesh are as follows: the minimum three-dimensional coordinate of the original three-dimensional point cloud data is used as the starting coordinate of the mesh space. The three-dimensional space is divided into three directions along the X-axis, Y-axis and Z-axis at equal intervals according to the voxel side length, forming a continuous and non-overlapping cubic voxel mesh. The three-dimensional coordinate range of each voxel unit can be determined by the starting coordinate and the voxel side length. The specific rule for assigning points from the original 3D point cloud data to the corresponding voxel grid is as follows: For each point in the original point cloud, calculate the difference between its X-axis, Y-axis, and Z-axis coordinates and the starting coordinates in the grid space. Divide each difference by the voxel side length and round to the nearest integer to obtain the voxel cell index corresponding to that point. The point is then assigned to the corresponding voxel cell based on the index. For example, if a point has coordinates of 0.5m, 0.4m, and 0.2m, a starting coordinate of 0m, and a voxel side length of 0.3m, the X-axis difference of 0.5m divided by 0.3m and rounded to 1, the Y-axis difference of 0.4m divided by 0.3m and rounded to 1, and the Z-axis difference of 0.2m divided by 0.3m and rounded to 0, then this point is assigned to the voxel cell with indices 1, 1, and 0. The Jacobi iteration method can be used to perform eigenvalue decomposition on the third-order covariance matrix. This method transforms the covariance matrix into a diagonal matrix through multiple orthogonal transformations. The diagonal elements of the diagonal matrix are the eigenvalues, and the column vectors of the matrix products of the orthogonal transformations are the corresponding eigenvectors. During the decomposition process, it is necessary to ensure that the eigenvalues ​​are arranged in descending order to facilitate the direct extraction of the smallest eigenvalue and its corresponding eigenvector. The Jacobi iteration method is suitable for the eigenvalue decomposition of the third-order square matrix, the calculation process is stable, and the accuracy of the results can meet the requirements for the estimation of the normal of the point cloud of the step free surface.

[0099] It should be noted that the three eigenvalues ​​of the covariance matrix correspond to three orthogonal eigenvector directions. The larger the eigenvalue, the more discrete the distribution of the point cloud in that direction; the smaller the eigenvalue, the more concentrated the distribution. The local region of the free surface of the step is approximately a plane. The point cloud is discretely distributed in two directions within the plane, corresponding to two larger eigenvalues. It is concentrated in the direction perpendicular to the plane, corresponding to the smallest eigenvalue. Therefore, the eigenvector corresponding to the smallest eigenvalue is the surface normal of that local region. This invention addresses the issue of large-scale original 3D point cloud data in stepped blasting scenarios. It achieves point cloud downsampling through voxel meshing, simplifying subsequent geometric calculations. Simultaneously, it accurately estimates local surface normals based on the eigenvalue decomposition of the covariance matrix of local neighborhood point clouds, providing a reliable geometric orientation benchmark for subsequent free surface reconstruction and bottleneck analysis. The invention first constructs a mesh using voxel edge lengths to complete spatial partitioning and downsampling of the point cloud, preserving key geometric features of the free surface. Then, it selects a fixed number of nearest neighbor points to construct a local neighborhood. The covariance matrix reflects the discrete characteristics of the local point cloud, and eigenvalue decomposition extracts the surface normals, thereby achieving efficient downsampling of the original point cloud, reducing resource consumption in subsequent calculations, and ensuring the rationality of local surface normal estimation. This adapts to the geometric analysis requirements of point clouds in stepped blasting free surfaces, providing accurate basic geometric data for subsequent steps.

[0100] In one embodiment of the present invention, a triangular mesh is constructed using a downsampling point set and local surface normals, and a hierarchical bounding box is established for the triangular mesh, including:

[0101] Using local surface normal Define by downsampling points Tangent plane:

[0102] ;in To reduce sampling points, For local surface normal, It is the tangent plane;

[0103] In the set of downsampling points Internal selection and downsampling points Minimum distance Each point forms a nearest neighbor set:

[0104] ;in For the downsampling point set, For the number of nearest neighbors, For the nearest neighbor set;

[0105] Near neighbor set Internal points Orthogonal projection onto the tangent plane Obtain the projection point:

[0106] ;in Let be the projection point. Points are those within the nearest neighbor set;

[0107] It should be noted that the points in the downsampled point set only have three-dimensional coordinate information and have not yet formed connections between triangles. Since the free surface of the step can be approximated as a two-dimensional curved surface in a local region, the tangent plane is first determined using the local surface normal, and the nearest downsampled points are orthogonally projected onto this tangent plane, thereby converting the local three-dimensional neighborhood into a two-dimensional point set suitable for triangulation.

[0108] Projection points are two-dimensional parameterized points obtained by orthogonally projecting nearest-neighbor downsampled points onto the tangent plane. Their function is to determine the two-dimensional triangulation connection relationships within the tangent plane. Each projection point retains the index of its corresponding nearest-neighbor downsampled point before projection; therefore, there is a one-to-one correspondence between projection points and nearest-neighbor downsampled points.

[0109] When triangulating the projection points in the tangent plane, the triangulation result actually determines the triangular connection relationship between the projection points. For any two-dimensional triangle composed of three projection points, the three nearest neighbor downsampling points corresponding to the three projection points are obtained respectively, and the three-dimensional coordinates of the three nearest neighbor downsampling points are used as the three vertices of the three-dimensional triangle, thereby generating a triangular mesh.

[0110] Therefore, the projected points are not output as the 3D vertices of the final triangular mesh, but are only used to determine the topology of triangle connections; each triangle vertex in the final triangular mesh is a point in the downsampled point set.

[0111] For triangles inside the triangular mesh Construct axis-aligned bounding box:

[0112] ;in , , Let be the three-dimensional coordinates of the three vertices of the triangle. For axis-aligned bounding boxes;

[0113] Recursively partition the triangular set and construct a hierarchical tree structure that covers the bounding boxes of each subset to form a hierarchical bounding box:

[0114] ;in It is a hierarchical bounding box.

[0115] It should be noted that the tangent plane is a plane defined using the local surface normal, passing through the downsampled point, reflecting the local approximate planar characteristics of the free surface of the step at the downsampled point. The projection point is the point obtained by orthogonally projecting points within the nearest neighbor set onto the tangent plane, reflecting the geometric position characteristics of the nearest neighbor points within the tangent plane. The triangular mesh is a surface structure formed by triangulating the projection points within the tangent plane and restoring them to three-dimensional coordinates, reflecting the continuous geometric shape of the free surface of the step. The three-dimensional coordinate extrema are the maximum and minimum coordinate values ​​of the three vertices of the triangle on each of the three-dimensional coordinate axes, reflecting the position and extent of the triangle in three-dimensional space. The axis-aligned bounding box is a cube constructed using the three-dimensional coordinate extrema of the triangle, reflecting the bounding range of the triangle in three-dimensional space. The hierarchical bounding box is an axis-aligned bounding box hierarchy constructed after recursively partitioning the triangle set, reflecting the layered bounding geometric characteristics of the triangular mesh.

[0116] It should be noted that the specific calculation method for orthogonally projecting points within the nearest neighbor set onto the tangent plane is as follows: First, determine the plane equation of the tangent plane based on the coordinates of the downsampled points and the local surface normal. Then, substitute the three-dimensional coordinates of the nearest neighbor points and use the general calculation method for orthogonally projecting spatial points onto a plane to obtain the three-dimensional projected coordinates of the points on the tangent plane. The line connecting the projected point and the original nearest neighbor point is strictly perpendicular to the tangent plane, and the coordinates of the projected point satisfy the plane equation of the tangent plane. The specific implementation rule for triangulation of the projected points within the tangent plane is the Delaunay triangulation rule. This rule requires that the circumcircle of any triangle formed by the triangulation does not contain other projected points, and the sides of the triangularly formed triangles are shared only with adjacent triangles, with no intersections or overlaps. For all projected points within the tangent plane, first construct the convex hull of the point set, and then gradually triangulate from the inside of the convex hull until all projected points become vertices of triangles, ultimately forming a complete triangulation result. The vertices of the triangles within the tangent plane are the two-dimensional coordinates of the projection points. These two-dimensional coordinates need to be preserved, and the coordinate values ​​of the downsampled points in the local surface normal direction are assigned to the projection points to restore them to three-dimensional spatial coordinates. The restored three-dimensional coordinate points are the vertices of the triangle mesh, and the three-dimensional coordinates of all vertices fall within the geometric space of the original free surface. The specific partitioning rule for the recursive triangle set is as follows: First, calculate the global axis-aligned bounding box of all triangles. Then, draw the perpendicular bisector along the longest coordinate axis of the bounding box to divide the triangle set into two subsets, making the number of triangles in the two subsets as equal as possible. Repeat the above operation for each subset until the number of triangles in each subset does not exceed a preset threshold, at which point the partitioning process terminates. Furthermore, the specific implementation of constructing a hierarchical structure covering all axis-aligned bounding boxes is to use a binary tree hierarchical structure, where each node of the recursive partition is treated as a node of the binary tree, the top-level node is the overall axis-aligned bounding box that encloses all triangles, each parent node is divided into two child nodes along the partitioning direction, and the child nodes are the axis-aligned bounding boxes of the partitioned subsets. The final subset of the recursive partitioning is the leaf node of the binary tree, and each leaf node corresponds to the axis-aligned bounding box of a single or a small number of triangles; all nodes are connected hierarchically according to parent-child relationships to form a complete hierarchical structure covering all axis-aligned bounding boxes.

[0117] It should be noted that this invention, based on the acquired downsampling points and local surface normals, transforms a 3D point cloud into a 2D point set through tangent plane construction and orthogonal projection of spatial points. This set is then reconstructed into a 3D triangular mesh via triangulation, achieving the transformation from discrete point clouds to continuous free-face geometry. Simultaneously, by constructing axis-aligned bounding boxes and a recursively partitioned hierarchical structure, a hierarchical bounding box is generated, providing an accelerated structure for subsequent geometric queries. This invention, through tangent plane projection and triangulation, allows the reconstructed triangular mesh to conform to the actual geometry of the free-face step, achieving a continuous representation of the discrete point cloud. This meets the geometric requirements of blasting design for intersection and distance measurement of free faces. The construction of the hierarchical bounding box enables rapid pruning in subsequent geometric queries, reducing invalid calculations and lowering the system's computational resource consumption, thus adapting to the engineering needs of intelligent assisted blasting design.

[0118] In one embodiment of the present invention, calculating the concave curvature scale based on a triangular mesh includes:

[0119] With triangular mesh The vertex is used as the point for calculating the curvature scale. ; Utilizing local surface normals Define the tangent plane:

[0120] ;in To reduce sampling points, For local surface normal, It is the tangent plane;

[0121] In the set of downsampling points Selection and downsampling points Minimum Euclidean distance Each point forms a nearest neighbor set:

[0122] ;in For the number of nearest neighbors, For the nearest neighbor set;

[0123] For points within a nearest neighbor set The projection point is obtained by orthogonal projection onto the tangent plane. :

[0124] ;in The projection point;

[0125] Select orthogonal unit vectors in the tangent plane , Construct a two-dimensional coordinate basis and calculate the local fitting data:

[0126] ;in and For local coordinates, For height;

[0127] Fit a quadratic surface to the local fitted data:

[0128] ;in The fitting coefficients are used to construct a quadratic form matrix.

[0129] ;

[0130] Calculate the principal curvature: ;in and Principal curvature;

[0131] The maximum value of the negative principal curvature is selected as the concave curvature amplitude:

[0132] ;in The concave curvature amplitude is given; the concave curvature scale is calculated.

[0133] ;

[0134] in For numerically stable terms, It is a concave curvature scale.

[0135] It should be noted that the curvature scale calculation point is the vertex of the triangular mesh. The two-dimensional coordinate basis consists of two mutually orthogonal unit vectors in the tangent plane that are orthogonal to the local surface normal, reflecting the direction reference of the local coordinate system. The local coordinate system is a planar coordinate system with the curvature scale calculation point as the origin and the two-dimensional coordinate basis as the coordinate axes. The quadratic form matrix is ​​a second-order square matrix constructed using fitting coefficients, reflecting the curvature distribution characteristics of the local surface. The principal curvatures are eigenvalues ​​obtained from the eigenvalue decomposition of the quadratic form matrix, reflecting the degree of normal curvature of the local surface in the two orthogonal principal directions. The concave curvature magnitude is the maximum value between the smaller negative value and zero value of the principal curvatures, reflecting the degree to which the local surface only bends in a concave direction. The numerical stability term is a custom parameter set to avoid the division-by-zero problem in numerical calculations, and its preferred value is 10 to the power of -6. The concave curvature scale reflects the curvature radius characteristics of the concave curvature of the local surface. The local region of the free surface of a step can be approximated as a quadratic surface. The mathematical model of a quadratic surface can accurately fit the bending characteristics of the local surface, and the numerical relationship between local coordinates and height can fully reflect this characteristic. The sign of the principal curvature can characterize the bending direction of the surface. A negative value represents bending in the opposite direction to the normal, i.e., concave bending; a positive value represents convex bending; and a zero value represents a plane. By filtering the principal curvature for negative and zero values, we can extract only the concave curvature amplitude that reflects the concave bending characteristic of the surface. The purpose is to eliminate the curvature values ​​of convex bending and plane regions, and only retain the amplitude of concave bending, which fits the engineering characteristics of the concave region of the blasting free surface being prone to offset and folding. In addition, the curvature scale is the reciprocal of the curvature amplitude. The larger the curvature amplitude, the sharper the bending of the surface; the smaller the curvature scale, i.e., the smaller the radius of curvature.

[0136] It should be noted that the specific implementation method for quadratic surface fitting using local coordinates and height is the least squares method. The local coordinates and heights of all projection points are substituted into the mathematical model of the quadratic surface to construct a system of error equations. By solving the least squares solution of the equations, the fitting coefficients that minimize the overall fitting error are obtained. The fitting process must ensure that at least six projection points are involved to guarantee the validity of the fitting results. This invention addresses the engineering characteristic of folding easily occurring in the concave region of a blasted free surface. Using the vertices of a triangular mesh as reference points, a local coordinate system is constructed to transform the three-dimensional surface curvature analysis into two-dimensional numerical calculations. A mathematical model of the local surface is obtained through quadratic surface fitting. Then, the principal curvature is extracted through quadratic form matrix construction and eigenvalue decomposition. Curvature amplitudes reflecting only concave bending are selected, and the concave curvature scale is calculated in conjunction with the numerical stability term, providing critical scale parameters for the curvature dimension for subsequent critical migration analysis. This invention focuses curvature analysis on concave regions of engineering interest, eliminating meaningless curvature values ​​in convex and planar regions, adapting to the actual needs of blasting design. Least squares fitting and matrix eigenvalue decomposition ensure the rationality of curvature calculation, and the obtained concave curvature scale can accurately characterize the degree of bending of the concave region, providing reliable curvature dimension support for the construction of the critical bottleneck dominance index.

[0137] In one embodiment of the present invention, rays are emitted bidirectionally along the local surface normal, and the intersection distance between the rays and the triangular mesh is obtained using a hierarchical bounding box. The bottleneck gap between the two sides is calculated using the intersection distance, and the bottleneck gap is converted into a bottleneck scale, including:

[0138] For downsampling points To reduce sampling points As the starting point of the ray and with the local surface normal... Using the direction as a reference, construct the forward and reverse rays:

[0139] ;

[0140] ;

[0141] in To reduce sampling points, For local surface normal, Forward rays, It is a reverse ray. This is the distance parameter along the ray direction;

[0142] Based on hierarchical bounding boxes Forward and reverse rays in the triangular mesh Perform an intersection search, and set the minimum search distance:

[0143] ;in For numerically stable terms, Minimum search distance;

[0144] Define the distance between the forward intersection points and the distance between the reverse intersection points as:

[0145] ;

[0146] ;

[0147] in It is a triangular grid. It is a layered bounding box. The distance between the positive intersection points. The distance between the opposite intersection points;

[0148] The bottleneck gap between the two opposing sides is calculated by summing the distance between the forward intersection points and the distance between the reverse intersection points:

[0149] ;in For bottleneck gap;

[0150] Convert the bottleneck gap into a bottleneck size:

[0151] ;in This is the bottleneck scale.

[0152] It should be noted that the ray origin is the spatial starting point for ray detection. A forward ray is a ray constructed along the positive direction of the local surface normal, reflecting the spatial detection path along the positive direction of the normal. A reverse ray is a ray constructed along the negative direction of the local surface normal, reflecting the spatial detection path along the negative direction of the normal. The minimum search distance is the initial effective distance for ray detection, reflecting the spatial starting threshold of ray detection. The forward intersection distance is the spatial straight-line distance from the ray origin to the point where the forward ray intersects the triangular mesh, reflecting the proximity to the opposing surface along the positive direction of the normal. The reverse intersection distance is the spatial straight-line distance from the ray origin to the point where the reverse ray intersects the triangular mesh, reflecting the proximity to the opposing surface along the negative direction of the normal. The bottleneck gap is the sum of the forward and reverse intersection distances, reflecting the overall spatial proximity gap between the two opposing surfaces in a local region of the free surface. The bottleneck scale reflects the spatial scale characteristics of the local bottleneck region of the free surface.

[0153] It should be noted that the specific method for constructing positive and negative rays along the local surface normal is as follows: Using the downsampling point as the ray origin, the unit vector of the local surface normal as the direction vector of the positive ray, and the unit vector of the local surface normal as the direction vector of the negative ray, parameterized ray equations are established respectively. The ray parameter represents the distance advanced from the ray origin along the corresponding direction vector, and the point on the ray is the spatial point obtained by extending the ray origin along the corresponding direction vector.

[0154] When searching for intersections between forward and backward rays and the triangular mesh using hierarchical bounding boxes, start from the top-level node of the hierarchical bounding box and determine whether the ray intersects with the axis-aligned bounding box corresponding to the current node. If the ray does not intersect the current axis-aligned bounding box, then discard that node and all its child nodes. If the ray intersects the current axis-aligned bounding box, continue checking the node's child nodes until a leaf node is reached.

[0155] Upon reaching a leaf node, each ray is checked to see if it intersects with each triangle within that leaf node. If a ray does not intersect a triangle, that triangle is not considered a candidate intersection point. If a ray intersects a triangle, and the ray distance parameter corresponding to the intersection point is greater than the minimum search distance, the 3D coordinates of the intersection point, the corresponding ray distance parameter, and the distance from the ray's origin to the intersection point are recorded, and this distance is used as the candidate intersection point distance.

[0156] After completing the intersection search for a directional ray, the candidate intersection distance with the smallest value is selected from all candidate intersection distances as the intersection distance for that direction. For a forward ray, the forward intersection distance is obtained; for a reverse ray, the reverse intersection distance is obtained. The forward and reverse intersection distances represent the distances from the ray's origin along the local surface normal in the forward and reverse directions to the nearest valid triangle intersection point, respectively.

[0157] The hierarchical bounding boxes wrap the triangular mesh in layers from coarse to fine. Rays first intersect with the top-level bounding box; if there is no intersection, the corresponding region is directly discarded. If there is an intersection, the search continues in the next lower-level node, thus reducing the computational cost of finding intersections between rays and triangles one by one and improving the efficiency of intersection point search. The sum of the forward intersection distance and the reverse intersection distance represents the bottleneck gap between the two opposing surfaces. The smaller the value, the higher the proximity and the more obvious the bottleneck feature. For example, if the forward intersection distance is 0.8 meters and the reverse intersection distance is 0.6 meters, the bottleneck gap is 1.4 meters, indicating that the proximity gap between the two opposing surfaces at that location is 1.4 meters.

[0158] It should be noted that this invention addresses the engineering problem of bottlenecks caused by topological uncertainty in free surfaces of steps. It constructs bidirectional rays along the local surface normal starting from downsampling points, and uses hierarchical bounding boxes to achieve rapid intersection of the rays and triangular meshes. By setting a minimum search distance, it avoids self-intersection calculation problems, obtains the bidirectional intersection distances, sums them to obtain the bottleneck gap, and then converts it into a bottleneck scale with the same dimensions as the concave curvature scale. This provides critical scale parameters for the bottleneck dimension in subsequent reachability scale calculations. This invention utilizes bidirectional rays to accurately detect the proximity features of opposing surfaces of the free surface. The pruning mechanism of the hierarchical bounding box reduces the amount of intersection calculations and improves geometric query efficiency. The minimum search distance avoids self-intersection anomalies in numerical calculations, ensuring the validity of the intersection distances. The conversion of the bottleneck scale achieves dimensional matching with the concave curvature scale, laying the foundation for the fusion of the two to construct the reachability scale. The quantified bottleneck features accurately reflect the proximity risks brought by free surface topological artifacts, thus adapting to the offset critical analysis requirements of blasting design.

[0159] In one embodiment of the present invention, the minimum value between the concave curvature scale and the bottleneck scale is selected as the reachable scale. A critical deviation dominance index is generated by combining a preset design resistance line, the reachable scale, and the concave curvature scale, including:

[0160] For downsampling points Receive concave curvature scale With bottleneck scale And calculate according to the following formula:

[0161] ;in To reach the scale, To reduce sampling points, For concave curvature scale, The bottleneck scale;

[0162] Receive the preset design resistance line Combined with achievable scale With concave curvature scale The critical dominance index of the offset is calculated according to the following formula:

[0163] ;

[0164] in This is the dominant index for the shift criticality. As a pre-set design resistance line, To reach the scale, It is a concave curvature scale.

[0165] It should be noted that the reachable scale is the minimum value of the concave curvature scale and the bottleneck scale, reflecting the minimum spatial scale of the offset criticality dominated by curvature or bottleneck mechanisms in a local area. The design resistance line is a core parameter of the pre-set blasting design in engineering, reflecting the pre-set distance from the borehole to the free surface in the blasting design. A preferred value is 2 to 8 meters, suitable for the conventional engineering design range of bench blasting. This range covers the mainstream design resistance line values ​​for medium-deep hole bench blasting, conforming to the actual needs of on-site construction. The first ratio is the calculated ratio of the design resistance line to the reachable scale, reflecting the degree to which the design offset distance is close to the local offset critical scale. The second ratio is the calculated ratio of the reachable scale to the concave curvature scale, reflecting the degree of bottleneck dominance in the local offset criticality. The offset criticality dominance index is the product of the first ratio and the difference between the first and second ratios, reflecting the comprehensive characteristics of a local area approaching the offset criticality and dominated by the bottleneck.

[0166] It should be noted that both concave curvature and bottleneck are critical triggers for offset surface folding. Their scale values ​​represent the critical thresholds for offset under their respective mechanisms, with the minimum value representing a more stringent critical condition in the local area, which is the actual critical offset scale. The ratio of the design resistance line to the reachable scale quantifies the degree of proximity of the design offset distance to the local critical offset scale. A larger ratio indicates that the design offset distance is closer to or even exceeds the critical scale, and the risk of offset surface folding is higher. The ratio of the reachable scale to the concave curvature scale characterizes the degree of bottleneck dominance in the local offset criticality. The magnitude of the ratio is determined by the dominance type of the reachable scale. If the reachable scale equals the concave curvature scale, the ratio is 1, representing curvature dominance; if the reachable scale equals the bottleneck scale and is much smaller than the concave curvature scale, the ratio approaches 0, representing bottleneck dominance. Furthermore, multiplying the first ratio by the difference between the first and second ratios can integrate the degree of proximity to the critical offset and the degree of bottleneck dominance to generate a single index characterizing the bottleneck dominance feature of the offset criticality, which will not be elaborated here.

[0167] It should be noted that this invention addresses the problem of two independent critical mechanisms—curvature and bottleneck—in blasting free-face offset. By constructing a unified reachability scale by taking the minimum value of both scales, it integrates the core features of the two critical mechanisms. Combined with the pre-set design resistance line, it quantifies the proximity of the design offset distance to the critical scale and the bottleneck dominance of the local offset criticality. Finally, through multiplication, the quantified features of the two dimensions are fused into a single offset critical dominance index, providing core feature parameters for subsequent range field modulation. The reachability scale achieves scale unification for the two critical mechanisms, allowing for collaborative analysis of critical features from different causes. Ratio calculation provides quantitative characterization of the two dimensions. Index fusion allows a single parameter to simultaneously reflect critical proximity and bottleneck dominance. The introduction of the design resistance line aligns the index with actual engineering design requirements. The continuous numerical characteristics of the index adapt to the continuous modulation of the subsequent range field, providing a concise and engineering-scenario-appropriate comprehensive feature parameter for the offset critical analysis of the entire blasting intelligent assisted design system.

[0168] In one embodiment of the present invention, the offset critical dominance index is converted into a modulation increment, and the modulation increment is superimposed on the original distance from the spatial point to the triangular mesh to generate a modulation range field, including:

[0169] For any point in space In the triangular mesh The mapping of the nearest points that satisfies the minimum Euclidean distance condition is determined above: ;in For spatial points, It is a triangular grid. Mapping to the nearest point;

[0170] Based on nearest point mapping Calculate the original distance:

[0171] ;in This is the original distance;

[0172] Based on the offset critical dominant index and the preset design resistance line Calculate the modulation increment:

[0173] ;in As a pre-set design resistance line, The offset critical dominant index corresponding to the nearest point mapping. For modulation increment;

[0174] The modulation increment is superimposed on the original distance to obtain the modulation range field:

[0175] ;in To modulate the distance field.

[0176] It should be noted that the nearest point mapping is the point with the smallest Euclidean distance between a spatial point and the triangular mesh, reflecting the shortest distance relationship between the spatial point and the free surface. The original distance is the straight-line length between the spatial point and the nearest point mapping, reflecting the original geometric distance from the spatial point to the free surface. The modulation increment is the distance correction value calculated by combining the design resistance line and the offset critical dominant index, reflecting the adjustment magnitude of the original distance. The modulation distance field is a three-dimensional spatial scalar field formed by summing the original distance and the modulation increment, reflecting the effective distance distribution from the spatial point to the free surface after correction. The specific implementation of determining the nearest point mapping with the smallest Euclidean distance between a spatial point and the triangular mesh is to accelerate the search by using hierarchical bounding boxes. First, the positional relationship between the spatial point and the bounding boxes at each level is determined, and non-intersecting mesh regions are eliminated. Then, for the triangles in the remaining regions, the shortest distances from the spatial point to the triangle face, three sides, and three vertices are calculated respectively. The point corresponding to the minimum value among all shortest distances is the nearest point mapping of that spatial point. In addition, the three-dimensional space of the blasting design can be divided into voxel grids according to the voxel side length. The modulation distance value of the centroid point of each voxel grid is calculated to complete the discrete assignment. Then, the trilinear interpolation method is used to interpolate any non-assigned point in the space according to the modulation distance value of the discrete centroid point to obtain its modulation distance value, so as to realize the continuous distribution of the modulation distance field in the entire three-dimensional space.

[0177] It should be noted that this invention addresses the problem of non-physical troughs in the original distance field caused by bottleneck artifacts. It establishes a geometric relationship between spatial points and free surfaces by determining the nearest point mapping on a triangular mesh for any point in 3D space and calculating the original distance. Then, by combining the offset critical dominance index corresponding to the design resistance line and the nearest point mapping, a modulation increment matching the design scale is generated. The original distance and the modulation increment are superimposed to obtain the modulated distance field, achieving targeted correction of the original distance field. The hierarchical bounding box is used to achieve rapid solution of the nearest point mapping, ensuring the efficiency of distance calculation. The exponential operation allows the modulation increment to grow saturatedly, avoiding over-correction. The linear superposition operation preserves the continuous characteristics of the distance field, only specifically lifting the bottleneck-dominant region, eliminating non-physical distance troughs. The modulated distance field balances the original geometric characteristics with the rationality of the correction, providing a reliable spatial distance distribution basis for the subsequent extraction of the modulation minimum resistance line surface, adapting to the geometric analysis requirements of blast hole array design.

[0178] In one embodiment of the present invention, extracting an isosurface with a value equal to the design resistance line from the modulation distance field to generate a modulation minimum resistance line surface, and intersecting the modulation minimum resistance line surface with a preset step top platform plane to generate an orifice skeleton curve, includes:

[0179] Received modulated range field Resistance line of the pre-set design Extract the isosurface that satisfies the following equation as the modulation minimum resistance line surface. :

[0180] ;in For spatial points, To modulate the range field, As a pre-set design resistance line, For scalar values, To modulate the minimum resistance line surface;

[0181] Receive the preset top platform plane of the steps Its expression is:

[0182] ;in For the plane normal of the top platform of the steps, It is a plane constant. This is the pre-defined plane of the platform at the top of the steps;

[0183] Minimum resistance surface to modulation With the pre-set top platform plane of the steps Perform intersection operations to generate the orifice skeleton curve. :

[0184] ;in This is the curve of the orifice skeleton.

[0185] It should be noted that the modulated minimum resistance line surface is the set of spatial points in the modulated distance field whose values ​​are equal to the design resistance line. It reflects the three-dimensional geometric surface that meets the minimum resistance line requirements after modulation in the blasting design. The normal direction of the step top platform plane is a unit vector defining the orientation of the step top platform plane, reflecting the tilt direction of the step top platform in three-dimensional space. It is preferably taken as a unit vector along the vertical direction. Step top platforms are mostly arranged horizontally, and the vertical normal direction is suitable for most engineering scenarios of step blasting. If the platform is tilted, the vector direction can be adjusted according to the actual tilt angle. The plane constant is a scalar value that determines the spatial position of the step top platform plane, reflecting the spatial offset of the step top platform in the normal direction. It is preferably taken as the actual elevation value of the step top platform. This value can directly locate the plane to the actual step top position on site, conforming to the geometric characteristics of construction. The unit is consistent with the length dimension of the coordinate system. The step top platform plane is a three-dimensional spatial plane defined by the step top platform plane normal and the plane constant, reflecting the bearing surface of the borehole opening arrangement in the blasting design. The orifice skeleton curve is the spatial intersection of the modulated minimum resistance line plane and the plane of the top platform of the step, reflecting the geometric trajectory of the orifice candidate position on the top platform of the step that meets the minimum resistance line requirement after modulation.

[0186] It should be noted that the normal to the spatial plane determines the plane's tilt angle, and the plane constant determines the plane's translational position along the normal. The combination of these two can uniquely determine the spatial state of the plane through the plane equation. Therefore, the combination of the normal to the top platform plane and the plane constant can uniquely determine the position and orientation of the top platform plane in three-dimensional space, thereby accurately defining the bearing plane for the orifice arrangement and ensuring that the orifice position conforms to the actual geometric characteristics of the top of the step on site. Points on the intersection line simultaneously satisfy the constraints of two geometric surfaces: they are both within the arrangement range of the top platform and their modulation distance to the free surface equal to the design resistance line. The intersection of the modulation minimum resistance line surface and the top platform plane can filter out candidate orifice positions on the platform plane that meet the design resistance line requirements, excluding areas on the platform that do not meet the resistance line requirements. The specific implementation of extracting the isosurface with a value equal to the design resistance line in the modulation distance field adopts the moving cube method. First, the three-dimensional space of the blasting design is divided into voxel grids according to the voxel side length, and the eight vertices of each voxel are assigned corresponding modulation distance values. It is then determined whether there is a numerical change across the design resistance line within each voxel. If so, the intersection points of the isosurfaces within the voxel are calculated by linear interpolation. The intersection points within all voxels are connected to form triangular facets, and all triangular facets are pieced together to obtain a complete and continuous modulation minimum resistance line surface. In addition, the plane normal is set according to the actual tilt angle of the platform at the top of the step. For the horizontal platform, the vertical direction unit vector is taken, and for the tilted platform, the normal vector is calculated according to the actual tilt angle and normalized. The plane constant is calibrated by the coordinates of the feature points of the platform at the top of the step measured on site. The coordinates of the feature points are substituted into the plane equation to obtain an accurate plane constant value. After calibration, the plane is ensured to fit the actual position of the top of the step on site.

[0187] It should be noted that the three-dimensional coordinates of all intersection points can be extracted according to the spatial connection order of the intersection points to form the original orifice skeleton curve coordinate sequence. A curve smoothing algorithm is used to remove abnormal noise points in the sequence, and cubic spline interpolation is performed on the discrete intersection point coordinates to generate a continuous and smooth orifice skeleton curve, ensuring that the curve has no inflections or discontinuities, and is suitable for subsequent equally spaced orifice sampling. This invention addresses the engineering requirement that the layout of blasting orifices must simultaneously meet the requirements of the minimum modulated resistance line and the constraints of the step top platform layout. The minimum modulated resistance line surface is obtained by extracting an isosurface equal to the design resistance line from the modulation distance field. The step top platform plane is precisely defined through preset plane normals and plane constants. Then, through spatial intersection operations, the three-dimensional geometric surface is transformed into a two-dimensional orifice skeleton curve, and candidate orifice trajectories that meet the design requirements on the platform are selected. Isosurface extraction realizes the transformation from numerical field to geometric surface, making the modulated distance requirement intuitively reflected as three-dimensional geometric features. The preset and calibration of plane normal and constant can make the platform plane fit the actual geometry of the site. Intersection operation accurately selects candidate positions of orifices that meet the dual constraints. Curve optimization makes the skeleton curve continuous and smooth. The extraction and intersection based on the modified modulated distance field avoids false orifice positions caused by bottleneck artifacts. The obtained orifice skeleton curve provides a reliable geometric benchmark that fits the engineering design and the actual site for subsequent orifice discretization.

[0188] In one embodiment of the present invention, the orifice point is sampled and output along the orifice skeleton curve, the negative gradient direction of the modulation distance field at the orifice point is calculated as the orifice axis direction, and the orifice depth is output along the orifice axis direction to the point where the depth constraint is satisfied. The orifice point, orifice axis direction and orifice depth are combined to generate an orifice array scheme, including:

[0189] Orifice skeleton curve Represented as an arc length parameter curve ,in and The total arc length of the curve; the receiving sampling ratio coefficient. Resistance line of design And calculate the arc length sampling step size:

[0190] ;in The sampling step size is the arc length. This is the sampling ratio coefficient. To design the resistance line; sampling step size based on arc length on the arc length parameter curve. Upsampling to obtain orifice point :

[0191] ;in Point of the orifice;

[0192] receiver voxel side length The modulation range field is calculated using central differential. At the orifice gradient components at:

[0193] ;

[0194] ;

[0195] ;

[0196] in Let the voxel side length be , To modulate the range field, The coordinate axes are unit vectors;

[0197] The gradient is composed of gradient components. And calculate the hole axis direction. :

[0198] ;

[0199] in The unit vector along the hole axis;

[0200] Receive depth scaling factor Resistance line of design In the direction of the hole axis Define the hole shaft parameter point :

[0201] ;in To increase the distance;

[0202] Hole depth Defined as the minimum propulsion distance that satisfies the following formula:

[0203] ;in For the depth of the hole, This is the depth scaling factor;

[0204] Collection point of orifice Hole-axis direction With Kong Shen Obtain the hole array scheme :

[0205] ;in For the hole arrangement scheme.

[0206] It should be noted that the arc length parameter curve reflects the correspondence between the geometric shape of the orifice skeleton curve and the actual curve length. The sampling ratio coefficient is a custom coefficient used to determine the orifice sampling interval, reflecting the proportional relationship between the orifice spacing and the design resistance line. A preferred value is 1.0 to 2.0, suitable for the conventional engineering requirement in bench blasting design where the orifice spacing is 1.0 to 2.0 times the design resistance line, and conforms to the construction habits of on-site orifice layout. The arc length sampling step is the product of the sampling ratio coefficient and the design resistance line, reflecting the equal arc length sampling interval of the orifice points on the arc length parameter curve. The orifice point is a spatial point on the arc length parameter curve sampled at equal intervals according to the arc length sampling step, reflecting the actual three-dimensional position of the blasting borehole. The gradient component is the rate of change of the modulated distance field along each coordinate axis at the orifice point, reflecting the trend of the modulated distance field in a single spatial direction. The gradient is a three-dimensional vector formed by the convergence of gradient components along each coordinate axis at the orifice point, reflecting the overall spatial trend of the modulated distance field at the orifice point. The borehole axis direction is a unit vector obtained by normalizing the negative gradient direction, reflecting the three-dimensional spatial orientation of the borehole axis. The depth scaling factor is a custom coefficient used to define the borehole depth constraint, reflecting the proportional relationship between the borehole depth and the design resistance line. A preferred value is 2.0 to 4.0, suitable for mainstream engineering projects where the borehole depth is 2.0 to 4.0 times the design resistance line in bench blasting design, ensuring the effective blasting depth. The borehole axis parameter point is a spatial point constructed along the borehole axis direction with the advance distance as a parameter, reflecting the spatial position corresponding to different extension lengths on the borehole axis. The advance distance is the straight-line distance along the borehole axis direction from the borehole opening to the borehole axis parameter point, reflecting the extension length along the borehole axis. The borehole depth is the minimum advance distance that satisfies the numerical constraint of the modulated distance field, reflecting the effective construction depth of the blasting borehole. The borehole layout scheme is the aggregated result of the borehole opening, borehole axis direction, and borehole depth for all boreholes, reflecting the complete three-dimensional layout parameters of the bench blasting boreholes.

[0207] It should be noted that the parameter increment of the arc length parameter curve is completely consistent with the actual curve length increment. Equal parameter interval sampling is equivalent to equal arc length interval sampling, which is unaffected by the curvature of the curve. Arc length parameterization of the orifice skeleton curve can achieve uniform sampling of the curve with equal arc length, avoiding uneven density of orifice points at curve bends and ensuring the uniformity of orifice arrangement. The central difference is used to solve for the rate of change by the difference in distance field values ​​at symmetrical positions on both sides of the orifice point. Compared with single-sided difference, the calculation error is smaller and the result is closer to the actual change characteristics of the distance field. The gradient direction is the direction in which the modulated distance field value increases the fastest. Taking the negative value, it points to the direction of decreasing value, i.e., the direction of the free surface. In reality, it points to the area inside the step where the resistance line increases. Normalization can convert it into a standard direction vector, so that the orifice axis direction conforms to the three-dimensional geometric features of the free surface and points to the effective area of ​​blasting.

[0208] It should be noted that the specific implementation of representing the orifice skeleton curve as an arc length parameter curve involves first extracting the three-dimensional coordinates of the discrete intersection points of the orifice skeleton curve, and fitting them into a cubic spline curve according to the spatial connection order; calculating the arc length function of this cubic spline curve to establish the mapping relationship between the original curve parameters and the arc length parameters; replacing the parameters of the original curve with the arc length parameters to obtain the arc length parameter curve, ensuring that the increment of the arc length parameter is consistent with the increment of the actual curve length. Furthermore, each borehole is assigned a unique number according to the sampling order of the orifice points; each borehole number is associated with and stored in relation to the corresponding three-dimensional coordinates of the orifice point, the three components of the borehole axis direction, and the borehole depth value; the storage format adopts a structured numerical list, with the parameters of each borehole on one line, facilitating reading, editing, and construction by engineering software. This invention addresses the engineering requirements for the 3D layout of blasting boreholes. It parameterizes the arc length of the borehole skeleton curve to achieve uniform sampling of borehole points with equal arc lengths. Combining the voxel side lengths, the gradient of the modulated distance field at the borehole point is solved using a central difference scheme. After negation and normalization, the borehole axis direction conforming to geometric features is obtained. The borehole depth constraint is then defined using a depth scaling factor and the design resistance line. The minimum advance distance satisfying the constraint is searched along the borehole axis to determine the borehole depth. Finally, the 3D parameters of all boreholes are collected to generate a borehole layout scheme. Arc length parameterization ensures the uniformity of the borehole point distribution. The sampling step size and borehole depth constraint are both related to the design resistance line, conforming to the parameter design logic of blasting engineering. The central difference scheme makes the gradient solution more accurate. The borehole axis direction conforms to the 3D geometric features of the free surface. The borehole depth solution satisfies both engineering constraints and construction economy. All parameters are determined based on the corrected modulated distance field, avoiding the influence of bottleneck artifacts on the borehole layout. The 3D parameterized borehole layout scheme provides a complete and clear layout basis for blasting construction, realizing the implementation of intelligent assisted design for blasting from geometric analysis to engineering design.

[0209] In one embodiment of the present invention, a blasting intelligent assisted design method based on three-dimensional point cloud data includes the following steps:

[0210] Step S101: Downsample the original 3D point cloud data to output a downsampled point set, and calculate the local surface normal of the downsampled point set;

[0211] Step S102: Construct a triangular mesh using the downsampling point set and the local surface normal, and establish a hierarchical bounding box for the triangular mesh;

[0212] Step S103: Calculate the concave curvature scale based on the triangular mesh;

[0213] Step S104: Emit rays bidirectionally along the local surface normal, obtain the intersection distance between the rays and the triangular mesh using the hierarchical bounding box, calculate the bottleneck gap on both sides using the intersection distance, and convert the bottleneck gap into the bottleneck scale.

[0214] Step S105: Select the minimum value between the concave curvature scale and the bottleneck scale as the reachable scale, and generate the offset critical dominant index by combining the preset design resistance line, reachable scale and concave curvature scale.

[0215] Step S106: Convert the offset critical dominance index into a modulation increment, and superimpose the modulation increment onto the original distance from the spatial point to the triangular mesh to generate a modulation range field.

[0216] Step S107: Extract the isosurface with a value equal to the design resistance line from the modulation distance field to generate the modulation minimum resistance line surface, and calculate the intersection of the modulation minimum resistance line surface and the preset step top platform plane to generate the orifice skeleton curve.

[0217] Step S108: Sample and output the orifice point along the orifice skeleton curve, calculate the negative gradient direction of the modulation distance field at the orifice point as the orifice axis direction, advance along the orifice axis direction to the point where the depth constraint is satisfied, and output the orifice depth. Combine the orifice point, orifice axis direction and orifice depth to generate the orifice array scheme.

[0218] It should be noted that a 3D laser scanner is used to perform a full-area scan of the blasting area at the bench blasting site. Multiple scanning stations are deployed along the top platform and sidewalls of the bench to ensure that the scanned point cloud covers the entire free surface of the bench without obstruction or omissions. After scanning, the point cloud data from each scanning station are registered and stitched together to obtain the original 3D point cloud data of the entire bench. According to this invention, the generated borehole layout plan is transmitted to the on-site construction terminal via data transfer. This can be done via wired transmission to the construction computer or wireless transmission to on-site handheld engineering terminals, total stations, or other construction equipment. Based on the received borehole layout plan, construction personnel locate and drill boreholes on the top platform of the bench. During drilling, the operating posture and drilling depth of the drilling equipment are controlled according to the borehole axis direction and depth parameters in the plan. The parameters output by the system can be directly connected to the CNC system of the drilling equipment to achieve automated drilling, and can also be used for on-site briefings and parameter verification during manual construction.

[0219] It should be noted that, taking open-pit mine bench blasting as a practical application example, the site features a horizontally arranged bench top platform with a measured platform elevation of 380.0 meters. The preset engineering parameters are: voxel side length 0.3 meters, number of nearest neighbor points 20, design resistance line 4.0 meters, sampling scale factor 1.5, and depth scale factor 3.5. Some borehole parameters in the output borehole layout scheme are as follows:

[0220] Hole 1: Hole opening three-dimensional coordinates: 52.3 m, 36.8 m, 380.0 m; unit vector components in the hole axis direction: -0.02, 0.03, -0.99; hole depth: 14.2 m.

[0221] Hole 2: Hole opening point three-dimensional coordinates 58.3 m, 36.9 m, 380.0 m; unit vector components in the hole axis direction -0.01, 0.02, -0.99; hole depth 14.0 m.

[0222] Hole 3: Hole opening three-dimensional coordinates: 64.3 m, 37.1 m, 380.0 m; unit vector components in the hole axis direction: -0.03, 0.01, -0.99; hole depth: 14.3 m.

[0223] Hole 4: Hole opening point three-dimensional coordinates 70.3 m, 37.2 m, 380.0 m; unit vector components in the hole axis direction -0.02, 0.02, -0.99; hole depth 14.1 m.

[0224] In the above-mentioned borehole arrangement, the borehole openings are evenly distributed on the top platform of the step at intervals of 1.5 times the design resistance line. The borehole axis direction is vertically downwards into the step. Due to slight irregularities in the free surface of the step, there are slight deviations in the borehole axis direction component. The borehole depth fluctuates slightly around the value of 3.5 times the design resistance line, all of which conform to the actual geometric characteristics of the site and the engineering design requirements. In addition to the specific parameters of a single borehole, the system also outputs a three-dimensional visualization model containing all boreholes. The spatial arrangement of the boreholes can be viewed in the model. It also outputs two-dimensional construction drawings of the top platform of the step with the coordinates of the borehole openings and the borehole depth marked. Construction personnel can complete the precise positioning and construction of the boreholes on site according to the drawings. In addition, the hole axis direction is determined by taking the negative gradient direction of the modulation distance field at the hole opening point and performing normalization. In engineering output, for the convenience of display and drawing, the direction component is usually truncated to a finite number of decimal places or rounded. Therefore, there may be slight differences in appearance from the strict unit length, but it does not affect the calculation and construction accuracy of the hole axis direction and the spatial position of the hole bottom. That is, if 3 to 4 decimal places are retained when outputting and displaying, it can be verified that the modulus is close to 1. Truncation of two decimal places is a routine operation for displaying engineering data and is not an error in calculation logic or formula application, so it will not be elaborated here.

[0225] It should be noted that the interval and threshold sizes are set for ease of comparison. The size of the threshold depends on the amount of sample data and the base number set by those skilled in the art for each set of sample data, as long as it does not affect the proportional relationship between the parameter and the quantized value. Furthermore, the above formulas are all dimensionless calculations, and the formulas are derived from software simulations using a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0226] The embodiments of this example have been described above. However, this example is not limited to the specific implementation methods described above. The specific implementation methods described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms based on the guidance of this example, and all of them are within the protection scope of this example.

Claims

1. A blasting intelligent auxiliary design system based on three-dimensional point cloud data, characterized in that, include: The point cloud downsampling module downsamples the original 3D point cloud data and outputs a downsampled point set, and calculates the local surface normal of the downsampled point set; The hierarchical bounding box construction module uses downsampled point sets and local surface normals to construct triangular meshes and establish hierarchical bounding boxes for the triangular meshes. The concave curvature scale calculation module calculates the concave curvature scale based on triangular meshes; The bottleneck scale conversion module emits rays bidirectionally along the local surface normal, and obtains the intersection distance between the rays and the triangular mesh in conjunction with the hierarchical bounding box. It then uses the intersection distance to calculate the bottleneck gap on both sides and converts the bottleneck gap into the bottleneck scale. The offset critical dominant index generation module selects the minimum value between the concave curvature scale and the bottleneck scale as the reachable scale, and generates the offset critical dominant index by combining the preset design resistance line, reachable scale and concave curvature scale. The modulation distance field generation module converts the offset critical dominant index into modulation increments, and superimposes the modulation increments onto the original distances from the spatial points to the triangular mesh to generate the modulation distance field. The orifice skeleton curve generation module extracts the isosurface with a value equal to the design resistance line from the modulation distance field to generate the modulation minimum resistance line surface, and calculates the intersection of the modulation minimum resistance line surface and the preset step top platform plane to generate the orifice skeleton curve. The hole array scheme generation module samples and outputs the hole opening point along the hole opening skeleton curve, calculates the negative gradient direction of the modulation distance field at the hole opening point as the hole axis direction, advances along the hole axis direction to the point where the depth constraint is satisfied, and outputs the hole depth. The hole opening point, hole axis direction and hole depth are combined to generate the hole array scheme.

2. The intelligent assisted design system for blasting based on three-dimensional point cloud data according to claim 1, characterized in that, The specific calculation steps of the point cloud downsampling module include: A three-dimensional voxel grid is constructed based on the voxel side length, and each point inside the original three-dimensional point cloud data is assigned to the corresponding spatial grid to form a voxel unit point set; For non-empty voxel unit point sets, calculate the centroid points and collect all centroid points to generate a downsampled point set; For each downsampling point in the downsampling point set, a fixed number of nearest neighbor points with the smallest Euclidean distance are selected within the downsampling point set to form a nearest neighbor set. Calculate the mean vector and covariance matrix of the nearest neighbor set; perform eigenvalue decomposition on the covariance matrix to obtain eigenvalues ​​and eigenvectors, and extract the eigenvector corresponding to the smallest eigenvalue as the local surface normal of the downsampled point.

3. The intelligent assisted design system for blasting based on three-dimensional point cloud data according to claim 1, characterized in that, The specific calculation steps for the hierarchical bounding box building module include: Define the tangent plane passing through the downsampling point using the local surface normal; Within the set of downsampled points, the nearest neighbor set with the smallest distance to the downsampled point is selected using Euclidean distance as a metric. The nearest downsampled points within the nearest neighbor set are orthogonally projected onto the tangent plane to generate projection points that correspond one-to-one with the nearest downsampled points. Triangulation is performed on the projection points within the tangent plane to obtain a two-dimensional triangulation result composed of the triangular connections between the projection points; Based on the one-to-one correspondence between the projection points and the nearest neighbor downsampling points, each two-dimensional triangle in the two-dimensional triangulation result is mapped to a three-dimensional triangle composed of three corresponding nearest neighbor downsampling points, generating a triangular mesh. Calculate the 3D coordinate extrema of triangles within a triangular mesh and construct an axis-aligned bounding box; Recursively partition the set of triangles and construct a hierarchical structure that covers all axis-aligned bounding boxes to generate hierarchical bounding boxes.

4. The intelligent assisted design system for blasting based on three-dimensional point cloud data according to claim 1, characterized in that, The specific calculation steps of the concave curvature scale calculation module include: The vertices of the triangular mesh are used as the points for calculating the curvature scale; The tangent plane is determined using the local surface normal; a nearest neighbor set is selected within the downsampled point set; the points within the nearest neighbor set are orthogonally projected onto the tangent plane to obtain the projection points; Two mutually orthogonal unit vectors that are orthogonal to the local surface normal are selected in the tangent plane and used as two-dimensional coordinate bases. The local coordinates and height of the projection point in the local coordinate system are calculated. The fitting coefficients are obtained by fitting a quadratic surface using local coordinates and height; a quadratic matrix is ​​constructed using the fitting coefficients and the eigenvalues ​​are calculated as principal curvatures; the maximum value between the smaller negative value and the zero value among the principal curvatures is selected as the concave curvature amplitude. The concave curvature scale is calculated using the concave curvature amplitude and numerical stability term.

5. The intelligent assisted design system for blasting based on three-dimensional point cloud data according to claim 1, characterized in that, The specific calculation steps of the bottleneck scale conversion module include: Using the downsampling point as the ray origin and the local surface normal as the direction reference, construct a positive ray extending in the positive direction of the local surface normal and a reverse ray extending in the opposite direction of the local surface normal. Using hierarchical bounding boxes, perform intersection searches between rays and triangular meshes for both forward and reverse rays; In the intersection search, first determine whether the ray intersects with the axis-aligned bounding box corresponding to the hierarchical bounding box node. Prune nodes that do not intersect. For intersecting leaf nodes, determine whether the ray intersects with the triangle contained in the leaf node one by one. For results where a ray intersects a triangle and the ray distance parameter is greater than the minimum search distance, record the coordinates of the intersection point and the distance from the ray's starting point to the intersection point as candidate intersection point distances; Select the candidate intersection point distance with the smallest distance from all candidate intersection point distances, and obtain the forward intersection point distance and the reverse intersection point distance respectively; The bottleneck gap on both sides is calculated by summing the distance between the forward intersection points and the distance between the reverse intersection points; the bottleneck gap is then converted into a bottleneck dimension.

6. The intelligent assisted design system for blasting based on three-dimensional point cloud data according to claim 1, characterized in that, The specific calculation steps of the offset critical dominance index generation module include: For the downsampling points, obtain the concave curvature scale and the bottleneck scale; The reachable scale is determined by selecting the minimum values ​​of the concave curvature scale and the bottleneck scale; Receive the preset design resistance line; calculate the first ratio of the preset design resistance line to the reachable scale, and calculate the second ratio of the reachable scale to the concave curvature scale; The critical deviation index is generated by multiplying the first ratio by one and subtracting the second ratio.

7. The intelligent assisted design system for blasting based on three-dimensional point cloud data according to claim 1, characterized in that, The specific calculation steps of the modulation distance field generation module include: For spatial points, determine the nearest point mapping with the minimum Euclidean distance on a triangular mesh; Calculate the original distance using the length between the mapping of a spatial point and its nearest point; The modulation increment is calculated by combining the preset design resistance line with the offset critical dominance index corresponding to the nearest point mapping; the original distance and the modulation increment are summed to generate the modulation distance field.

8. The intelligent assisted design system for blasting based on three-dimensional point cloud data according to claim 1, characterized in that, The specific calculation steps for the orifice skeleton curve generation module include: A set of spatial points with values ​​equal to the preset design resistance line is extracted within the modulation distance field to generate the modulation minimum resistance line surface; Determine a preset plane for the top platform of the step, including the plane normal and plane constant; The orifice skeleton curve is generated by performing an intersection operation between the modulated minimum resistance line surface and the preset step top platform plane.

9. The intelligent assisted design system for blasting based on three-dimensional point cloud data according to claim 1, characterized in that, The specific calculation steps of the hole array scheme generation module include: The orifice skeleton curve is represented as an arc length parameter curve; the sampling ratio coefficient and the design resistance line are received, and the arc length sampling step determined by the product of the sampling ratio coefficient and the design resistance line is calculated. The aperture point is obtained by sampling at equal intervals on the arc length parameter curve according to the arc length sampling step size; the voxel side length is received, and the gradient component of the modulation range field at the aperture point is calculated using the central difference scheme containing the voxel side length and then collected to form a gradient. The hole axis direction is obtained by taking the negative direction of the gradient and normalizing it. The depth scaling factor and the design resistance line are received, and the hole axis parameter point is constructed in the hole axis direction. The hole depth is defined as the minimum advance distance that satisfies the requirement that the value of the modulation distance field at the hole axis parameter point is greater than or equal to the product of the depth scaling factor and the design resistance line. The hole array scheme is generated by combining the hole opening point, hole axis direction, and hole depth.

10. A blasting intelligent-assisted design method based on three-dimensional point cloud data, characterized in that, The blasting intelligent assisted design system based on three-dimensional point cloud data as described in any one of claims 1 to 9 includes the following steps: Step S101: Downsample the original 3D point cloud data to output a downsampled point set, and calculate the local surface normal of the downsampled point set; Step S102: Construct a triangular mesh using the downsampling point set and the local surface normal, and establish a hierarchical bounding box for the triangular mesh; Step S103: Calculate the concave curvature scale based on the triangular mesh; Step S104: Emit rays bidirectionally along the local surface normal, obtain the intersection distance between the rays and the triangular mesh using the hierarchical bounding box, calculate the bottleneck gap on both sides using the intersection distance, and convert the bottleneck gap into the bottleneck scale. Step S105: Select the minimum value between the concave curvature scale and the bottleneck scale as the reachable scale, and generate the offset critical dominant index by combining the preset design resistance line, reachable scale and concave curvature scale. Step S106: Convert the offset critical dominance index into a modulation increment, and superimpose the modulation increment onto the original distance from the spatial point to the triangular mesh to generate a modulation range field. Step S107: Extract the isosurface with a value equal to the design resistance line from the modulation distance field to generate the modulation minimum resistance line surface, and calculate the intersection of the modulation minimum resistance line surface and the preset step top platform plane to generate the orifice skeleton curve. Step S108: Sample and output the orifice point along the orifice skeleton curve, calculate the negative gradient direction of the modulation distance field at the orifice point as the orifice axis direction, advance along the orifice axis direction to the point where the depth constraint is satisfied, and output the orifice depth. Combine the orifice point, orifice axis direction and orifice depth to generate the orifice array scheme.

Images