A method for automatically dividing a multi-metal ore blending unit under complex geological conditions

Abstract

The application discloses a kind of complex geological conditions under multi-metal ore blending unit automatic division method, comprising the following steps;Step 1: collecting rock powder test data;Step 2: the rock powder test data collected is preprocessed;Step 3: based on space geometry, find out blast pile borehole boundary point by means of-shape method, form peripheral boundary polygon, and-shape method is used to approach blast pile boundary;Step 4: the blast pile borehole boundary point is expanded outward;Step 5: by means of Voronoi diagram algorithm, blast hole is divided into tessellation polygon on the level, and the range including influence area is formed;Step 6: fine ore blending unit solution division and evaluation, the inverse ratio of the square of the distance of ore block and each ore blending center is weighted, the attribution proportion of each ore block to different unit is calculated, and ore blending unit division is realized.The application realizes the whole process automation from rock powder test data acquisition processing, boundary extraction, unit division to resource quantity estimation.

Description

Technical Field

[0001] This invention relates to the field of mine geological modeling and intelligent ore blending technology, specifically to an automatic division method for multi-metal ore blending units under complex geological conditions. Background Technology

[0002] In open-pit mining, the division and calculation of ore blending units are crucial for achieving efficient utilization and refined mining of ore resources, directly impacting the scientific validity and feasibility of the blending scheme. Traditional methods, often based on manual experience or simple geometric divisions, suffer from the following problems: 1. Poor adaptability to complex borehole trajectories: Traditional methods are based on the assumption of straight holes and cannot accurately process trajectory data of inclined / curved boreholes, resulting in deviations in the correlation between the spatial position of the borehole and the quality of the ore.

[0003] 2. Inaccurate extraction of bursty heap boundaries: Relying on convex hull algorithms (such as Graham's algorithm) to divide bursty heap boundaries cannot fit the actual concave or irregular shapes, resulting in distortion of the boundary range.

[0004] 3. Insufficient multi-indicator collaborative processing capability: The division of ore blending units does not take into account the coupled effects of multiple indicators such as multi-metal grade, oxidation rate, and harmful elements. Furthermore, the grade division and unit matching rely on manual operation, which is inefficient, highly subjective, and difficult to meet the needs of refined ore blending.

[0005] 4. Weak data quality assurance capability: Traditional methods are insufficient to handle the problems of multi-source heterogeneity, outliers and missing values ​​in rock powder analysis data, which seriously affects the accuracy of ore blending unit index estimation. Summary of the Invention

[0006] To overcome the above technical problems, the purpose of this invention is to provide an automatic division method for polymetallic mineral blending units under complex geological conditions, realizing full automation from rock powder analysis data acquisition and processing, boundary extraction, unit division to resource estimation.

[0007] To achieve the above objectives, the technical solution adopted by the present invention is as follows: An automatic division method for polymetallic ore-blending units under complex geological conditions includes the following steps; Step 1: Collect rock powder test data; Step 2: Preprocess the collected rock powder analysis data; considering the multi-source heterogeneous characteristics of the blast hole data, design a database structure to form a rock powder geological database. Step 3: Based on spatial geometry, using The `-shape` method is used to find the boundary points of the blast hole, forming the outer boundary polygon. - The shape method approximates the burst pile boundary; Step 4: Expand the boundary points of the blast hole; Step 5: Using the Voronoi diagram algorithm, divide the borehole horizontally into Thiessen polygons to form the area of ​​influence. Step 6: Obtain the spatial coordinates, tonnage, grade and other attribute information of the ore blocks, calculate the spatial distance from each ore block to different blending centers, weight the distance between the ore block and each blending center inversely by the square, calculate the proportion of each ore block belonging to different units, and realize the division of blending units.

[0008] Step 1 specifically involves: A rock powder detection database was constructed, and a four-table relational database structure was designed to address the multi-source heterogeneous characteristics of rock powder data from blast holes. Specifically, it includes: (1) Positioning table: Stores the spatial reference information of the borehole. The primary key "Project No." is a unique borehole code, "Blast Pile No." is associated with the blast pile number, the coordinate system adopts East-North-Up (ENU), "Borehole Coordinates E / N / U" records the borehole coordinates (millimeters accurate), "Borehole Depth" is the vertical depth from the borehole opening to the bottom of the borehole, and the "Trajectory Type" field (straight hole / inclined hole / curved hole) breaks through the traditional straight hole assumption limitation and improves the universality of the model; (2) Inclination table: For the modeling requirements of inclined / bent borehole trajectories, the primary key "project number" is associated with the positioning table, "depth" indicates the location of the inclination point, "azimuth" is the clockwise angle between the horizontal projection of the measurement point and the true north direction (0°~360°), and "inclination" is the angle between the extension direction of the measurement point and the horizontal plane (-90°~90°); (3) Lithology table: Record lithology classification codes (such as skarn, wollastonite hornfels, etc.) according to depth range ("starting depth" to "ending depth"); (4) Ore quality table: The primary key is "project number + sampling depth", which stores the test data of multi-metal grade (Mo, tFe, etc.), oxidation rate (accuracy 0.1%) and concentration of harmful elements (ppm level). The field "element type" marks the attribute category (metal / oxidation rate / harmful element).

[0009] Step 2 specifically involves: (1) Outlier handling: The threshold over-limit detection method is adopted to set invalid values ​​that exceed the preset range (such as Mo grade > 5%) to empty; (2) Missing value imputation: Based on the spatial correlation assumption, missing values ​​are calculated using inverse distance weighted interpolation (IDW). Where vk is the test value of the adjacent borehole, dk is the spatial distance, and p is the attenuation coefficient (default value is 2).

[0010] Step 3 specifically involves: (1) Choose Parameters; Select appropriate ones Parameters are used to approximate the burst boundary; (2) Constructing the Delaunay triangulation of the blast hole: For a given blast hole, construct its Delaunay triangulation; (3) -Shape recognition: Traverse the above Delaunay line segments, through... - The shape method determines which line segment lies on the boundary line: passing through the two endpoints of any line segment. and Drawing radius is Given a circle with a given radius, two distinct circles can be drawn through two given points. If neither circle contains any other points, then the points are considered to be... and These are boundary points, and the lines connecting them... - That is, the boundary line segment; the identified The shape edges constitute Shape outline boundary.

[0011] Step 4 specifically involves: shifting and expanding the aforementioned boundary points outwards as a whole; The borehole boundary extension offset is performed using a vector offset method, which moves each edge of the polygon a certain distance along its normal direction to create a new offset polygon; in this process, the movement of the edges is achieved through vectors, which represent the direction and distance. (1) Determine the offset of the borehole boundary: Through field investigation and verification, the offset distance is determined. It can be parameterized with a given default distance and left to the user to customize. (2) Expanding the edges: Traverse each edge of the polygon. For each edge: a. Find the two endpoints A and B of the edge; b. Calculate the normal vector of the edge (the vector perpendicular to the edge). If the edge is from A to B, the normal vector can be (By - Ay, Ax - Bx) or in the opposite direction (expanding or contracting); c. Normalize the normal vector (i.e., divide it by its length) and multiply it by the outer extension distance; d. Add the two endpoints to the calculated vector to obtain two new points; (3) Handling intersections: At each intersection, two or more edges meet. Specific rules are developed through repeated experiments and trials to select the intersection location. (4) Forming a new boundary shape: Combine all the expanded points in sequence to form a new boundary shape.

[0012] Step 5 specifically involves: A Voronoi diagram (also known as a Thiessen polygon or Dirichlet diagram) is a continuous polygon composed of the perpendicular bisectors of lines connecting two adjacent points. The algorithm for generating a Voronoi diagram is as follows: For each blast hole point within the target blast pile, perform the following steps: (1) Calculate the perpendicular bisector (the line dividing the borehole from all other points); (2) Find the half-plane intersection of all the perpendicular bisectors of the borehole point; this intersection is a Voronoi polygon associated with the point; repeat the above until all points are processed and all Voronoi polygons are merged to form a Voronoi diagram.

[0013] Step 6 specifically involves: By weighting the distance between the ore block and each ore blending center inversely proportionally, the proportion of each ore block belonging to different units is automatically calculated, thus achieving a smooth, continuous, and interpretable division of ore blending units. Two criteria for dividing ore blending units are used. First, lithology is given priority. Lithological boundaries are the primary principle for dividing ore blending units, and ore blending units cannot be divided across lithological boundaries. Secondly, under normal circumstances, the minimum ore quantity of a blending unit is ≥ 3 days of loading (approximately 12,000 tons). If the grade of a blast pile of ore is evenly distributed, it can be directly used as a blending unit (single lithology). The inverse square method treats the influence of each ore block (or sampling point) on the center of each ore blending unit as inversely proportional to the square of the distance: weighting = After normalization, the allocation ratio can be obtained (soft allocation); alternatively, the maximum weight can be taken for hard partitioning. The "square" power of the weight makes the influence of nearby objects stronger and the decay of distant objects faster, which is suitable for mineral allocation based on the nearest neighbor in space.

[0014] The beneficial effects of this invention are: This invention systematically solves the key technical problems of solving polymetallic ore-blending units under complex geological conditions through a standardized process of "rock powder analysis data acquisition and processing—data preprocessing—precise boundary extraction—boundary expansion—Thysen polygon division—refined unit calculation and estimation." Specifically, it addresses the following: First, by coordinating rock powder analysis data acquisition in step 1 and data preprocessing in step 2, it specifically solves the problem of traditional methods' weak ability to handle multi-source heterogeneity, outliers, and missing values ​​in rock powder analysis data, providing high-quality data support for subsequent calculations. Second, it relies on the boundary point identification and boundary approximation of blast boreholes based on the -shape method in step 3. Furthermore, the boundary expansion process in step 4 overcomes the limitations of traditional convex hull algorithms, accurately fitting the actual concave or irregular shape of the blast pile and solving the problem of boundary range distortion. In step 5, the Voronoi diagram algorithm horizontally divides the blast holes into Thiessen polygons to determine the influence area. Combined with step 6, which calculates the attribution ratio based on the inverse square weighted distance between the ore block and the blending center, automated and precise division and valuation of blending units are achieved. This solves the problems of poor adaptability to complex blast hole trajectories and deviations in the correlation between blast hole spatial location and ore quality in traditional methods, and also avoids the predicament of relying on manual operation for multi-indicator collaborative processing, significantly improving the efficiency and objectivity of division. This method features high accuracy, high efficiency, and strong adaptability, and can be widely applied to blending operations in polymetallic mines, providing reliable technical support for the efficient utilization of mineral resources. Attached Figure Description

[0015] Figure 1 This is a database design diagram of the method of the present invention.

[0016] Figure 2 This is a schematic diagram of the boundary points of the blast hole in the method of the present invention.

[0017] Figure 3 This is a schematic diagram of the explosion boundary extraction process of the method of the present invention.

[0018] Figure 4 This is a schematic diagram of the expansion of the explosion boundary point in the method of the present invention.

[0019] Figure 5 This is a schematic diagram of the burst-heap Thiessen polygon of the method of the present invention.

[0020] Figure 6 This is a schematic diagram illustrating an example of the calculation and division of the ore blending unit in the method of this invention. Detailed Implementation

[0021] The present invention will now be described in further detail with reference to the accompanying drawings.

[0022] This invention discloses an automatic division method for polymetallic ore blending units under complex geological conditions, comprising the following steps; I. Data Acquisition and Processing of Rock Powder Analysis 1. Construction of a rock powder detection database: Addressing the multi-source heterogeneous characteristics of rock powder data from blast boreholes, a database design was developed as follows: Figure 1 The four-table relational database structure shown is as follows: (1) Positioning table: stores the spatial reference information of the boreholes. The primary key "Project No." is a unique borehole code, "Blast Pile No." is associated with the blast pile number, the coordinate system adopts East-North-Up (ENU), "Borehole Coordinates E / N / U" records the borehole coordinates (millimeters accurate), "Borehole Depth" is the vertical depth from the borehole opening to the bottom of the borehole, and the "Trajectory Type" field (straight hole / inclined hole / curved hole) breaks through the traditional straight hole assumption limitation and improves the universality of the model; (2) Inclination table: for the modeling requirements of inclined / curved borehole trajectories, the foreign key "Project No." is associated with the positioning table, "Depth" identifies the location of the inclination point, and "Azimuth" is the clockwise angle between the horizontal projection of the measurement point and the true north direction (0°~360°). "Inclination" is the angle between the direction of the measuring point extension and the horizontal plane (-90°~90°); (3) Lithology table: record lithology classification codes (such as skarn, wollastonite hornfels, etc.) according to the depth range ("starting depth" to "ending depth"); (4) Ore quality table: the primary key is "project number + sampling depth", storing the test data of multi-metal grade (Mo, tFe, etc.), oxidation rate (accuracy 0.1%) and harmful element concentration (ppm level), and the field "element type" marks the attribute category (metal / oxidation rate / harmful element); 2. Data preprocessing: (1) Outlier handling: The threshold out-of-bounds detection method is used to set invalid values ​​that exceed the preset range (e.g., Mo grade > 5%) to null; (2) Missing value imputation: Based on the spatial correlation assumption, missing values ​​are calculated by inverse distance weighted interpolation (IDW): Where vk is the test value of the adjacent borehole, dk is the spatial distance, and p is the attenuation coefficient (default value is 2).

[0023] II. Ore blending unit division and calculation Step 1: Based on spatial geometry, using... The `-shape` method identifies the boundary points of the blast hole and forms the outer boundary polygon, such as... Figure 2 As shown.

[0024] Bursting pile boundaries exhibit concave properties, and traditional Graham and other convex hull algorithms cannot satisfy the requirement for realistic bursting pile shapes. This idea proposes to adopt... The shape method approximates the boundary of a bursty heap, and its basic idea is: ① Choose parameter. Parameters determine - The density of the shape. Larger. A value of 1 will result in a generated shape that is closer to the convex hull, while a smaller value will result in a shape that is closer to the convex hull. The value will make the shape fit the burst more tightly. Choosing the appropriate value... The value is crucial and usually needs to be determined based on the characteristics of the point cloud and the required level of detail in the boundary. This approach aims to repeatedly test and verify the value to select a suitable one. Parameters are used to approximate the burst boundary; ② Construct the Delaunay triangulation of the borehole point. For a given blast pile borehole point, construct its Delaunay triangulation, such as... Figure 3 As shown.

[0025] ③ -shape recognition. Traverse the above Delaunay segments, through... - The shape method determines which line segment lies on the boundary line: passing through the two endpoints of any line segment. and Drawing radius is Given a circle with a given radius, two distinct circles can be drawn through two given points. If neither circle contains any other points, then the points are considered to be... and These are boundary points, and the lines connecting them... - That is, the boundary line segment; the identified The shape edges constitute Shape contour boundaries, these boundary points closely fit the borehole data and can describe concave and irregular shapes. It is important to note that... -shape algorithm for parameters The choice of α is very sensitive. Smaller α values ​​result in finer boundaries but may include too much detail and noise, while larger α values... A higher value will make the boundaries smoother, but may lose some important geometric features. Therefore, in practical applications, it is necessary to choose the appropriate value based on specific needs and data characteristics. value.

[0026] Step Two: Expanding the Boundary Points of the Blast Holes. To ensure the boundary line encompasses all blast hole points, the aforementioned boundary points need to be shifted and expanded outwards as a whole, such as... Figure 4 As shown.

[0027] This paper proposes to use a vector offset method for borehole boundary extension offset. The basic idea of ​​this method is to move each edge of a polygon a certain distance along its normal direction to create a new offset polygon. In this process, the movement of the edges is achieved through vectors, which represent both direction and distance.

[0028] ① Determine the outward offset of the borehole boundary. Through field investigation and verification, determine the offset distance, which can be parameterized given a default distance and then customized by the user. ② Expand the edges. Traverse each edge of the polygon. For each edge: a. Find the two endpoints A and B of the edge; b. Calculate the normal vector of the edge (the vector perpendicular to the edge). If the edge is from A to B, the normal vector can be (By - Ay, Ax - Bx) or in the opposite direction (expanding or contracting); c. Normalize the normal vector (i.e., divide it by its length) and multiply it by the outer extension distance; d. Add the two endpoints to the calculated vector to obtain two new points.

[0029] ③ Handling intersections. At each intersection, two or more edges meet. This idea aims to repeatedly experiment and test to develop specific rules for selecting the intersection location; ④ Forming a new boundary shape. Combining all the expanded points sequentially forms a new boundary shape, such as... Figure 4 As shown.

[0030] Step 3: Using the Voronoi diagram algorithm, divide the borehole horizontally into Thiessen polygons, forming a region including the area of ​​influence, such as... Figure 5 As shown.

[0031] A Voronoi diagram (also known as a Thiessen polygon or Dirichlet diagram) is a continuous polygon composed of perpendicular bisectors of lines connecting adjacent points. The basic idea behind this algorithm for generating Voronoi diagrams is as follows: For each blast hole point within the target blast pile, perform the following steps: ① Calculate the perpendicular bisector (the line dividing the point from all other points); ② Find the half-plane intersection of all perpendicular bisectors of the point. This intersection is a Voronoi polygon associated with the point. Repeat the above until all points have been processed. Merge all Voronoi polygons to form the Voronoi diagram.

[0032] Step 4: Calculation, division, and valuation of refined ore blending units.

[0033] This invention employs an automatic settlement method for ore blending units based on the "inverse square weighting method" principle proposed by the applicant and their team. By weighting the distances between ore blocks and each blending center inversely by the square, it automatically calculates the proportion of each ore block belonging to different units, achieving smooth, continuous, and interpretable ore blending unit division. We adhere to two criteria for ore blending unit division: first, lithology is given priority; lithological boundaries are the primary principle for ore blending unit division, and ore blending units cannot be divided across lithological boundaries. Second, under normal circumstances, the minimum ore quantity for a blending unit is ≥3 days' loading volume (approximately 12,000 tons). If the ore grade distribution of a blast pile is uniform, it can be directly considered as a ore blending unit (single lithology). The inverse square weighting method treats the influence of each ore block (or sampling point) on the center of each ore blending unit as inversely proportional to the square of the distance: weighting... = After renormalization, the allocation ratio can be obtained (soft allocation); alternatively, the maximum weight can be used for hard partitioning. The square power of the weight makes the influence of nearby objects stronger and the decay of distant objects faster, which is suitable for ore allocation based on proximity in space.

[0034] This method includes the following steps: ① Data acquisition and modeling: Obtain the spatial coordinates, tonnage, grade and other attribute information of the ore block (or mining grid point), as well as the preset center point location of the ore blending unit.

[0035] ② Distance Calculation: For any ore block i and the center j of the ore mixing unit, calculate their Euclidean distance: ③ Inverse Square Weight Calculation: The attribution weight is calculated based on the inverse square principle. in, To prevent small constants from being divided by zero.

[0036] Weight This represents the degree of affiliation of mineral block i to unit j, and satisfies... ; ④ Ore blending unit calculation: Based on the weights, the ore block attributes are proportionally allocated to each ore blending unit: in, In terms of ore block tonnage. For the grade of the ore block, and These represent the calculated tonnage and average grade of unit j, respectively.

[0037] ⑤ Results Output and Visualization. Outputs the boundaries, average grade, tonnage, and spatial distribution of each unit. The results can be directly used as input for the ore blending and scheduling system to achieve automated zoning. Detailed implementation method: ① Data Input. The coordinates and attributes of the centers of the three ore blocks and two ore mixing units are shown in Table 1: Coordinates of the center of the ore blending unit: c1: (0,1) c1: (3,0) ② Calculate the distance matrix.

[0039] The calculation yielded: =1, =3, =2, =1, =2, =3.6 d i The straight-line spatial distance from the target ore block to the i-th ore blending center (unit: m). ③ Inverse square weighting calculation. Calculate the weight for each mineral block: The results are shown in Table 2.

[0040] ④ Calculation of ore blending unit.

[0041] Tonnage and average grade of each unit: =100×0.9+150×0.2+120×0.8=222, =100×0.1+150×0.8+120×0.2=148, =(100×0.9×1.2+150×0.2×0.8+120×0.8×1.0) / 222≈1.04, =(100×0.1×1.2+150×0.8×0.8+120×0.2×1.0) / 148≈0.89 It is evident that the division results naturally reflect spatial continuity and maintain an overall balance of quality.

[0042] ⑤ Visualize the results.

[0043] Drawing the boundaries of ore blending units can be used for dividing ore blending units. For example... Figure 6 Schematic diagram of settlement division example for ore blending unit.

[0044] Table 1 is a table of ore block attributes for the method of this invention. Table 2 is the ore block weight table of the method of the present invention. Table 3 shows examples of rock powder quality test data obtained using the method of this invention.

Claims

1. A method for automatically dividing polymetallic ore-blending units under complex geological conditions, characterized in that, Includes the following steps; Step 1: Collect rock powder test data; Step 2: Preprocess the collected rock powder analysis data; design a database structure to form a rock powder geological database, taking into account the multi-source heterogeneous characteristics of the blast hole data; Step 3: Based on spatial geometry, using The `-shape` method is used to find the boundary points of the blast hole, forming the outer boundary polygon. - The shape method approximates the burst pile boundary; Step 4: Expand the boundary points of the blast hole; Step 5: Using the Voronoi diagram algorithm, divide the borehole horizontally into Thiessen polygons to form the area of ​​influence. Step 6: Obtain the spatial coordinates, tonnage, and grade of the ore blocks, calculate the spatial distance from each ore block to different blending centers, weight the distances between the ore blocks and each blending center inversely by the square, calculate the proportion of each ore block belonging to different units, and realize the division of blending units.

2. The method for automatically dividing polymetallic ore-blending units under complex geological conditions according to claim 1, characterized in that, Step 1 specifically involves: A rock powder detection database was constructed, and a four-table relational database structure was designed to address the multi-source heterogeneous characteristics of rock powder data from blast holes. The four tables specifically include: (1) Positioning table: Stores the spatial reference information of the blast hole. The primary key "Project No." is a unique blast hole code, "Blast Pile No." is associated with the blast pile number, the coordinate system adopts East-North-Up (ENU), "Opening Coordinates E / N / U" records the hole opening coordinates, "Blast Hole Depth" is the vertical depth from the hole opening to the bottom of the hole, and the "Trajectory Type" field breaks through the traditional straight hole assumption limitation; (2) Inclination table: For the modeling requirements of inclined / bent borehole trajectories, the primary key "project number" is associated with the positioning table, "depth" indicates the location of the inclination point, "azimuth" is the clockwise angle between the horizontal projection of the measurement point and the true north direction (0°~360°), and "inclination" is the angle between the extension direction of the measurement point and the horizontal plane (-90°~90°). (3) Lithology table: records lithology classification codes according to depth range; (4) Ore quality table: The primary key is "project number + sampling depth", which stores the test data of multi-metal grade, oxidation rate and concentration of harmful elements. The "element type" field marks the attribute category.

3. The method for automatically dividing polymetallic ore-blending units under complex geological conditions according to claim 1, characterized in that, Step 2 specifically involves: (1) Outlier handling: The threshold out-of-bounds detection method is used to set invalid values ​​that exceed the preset range to empty; (2) Missing value imputation: Based on the spatial correlation assumption, missing values ​​are calculated using inverse distance weighted interpolation. Where v k d represents the test value of a nearby borehole. k Where is the spatial distance and p is the attenuation coefficient.

4. The method for automatically dividing polymetallic ore-blending units under complex geological conditions according to claim 1, characterized in that, Step 3 specifically involves: (1) Select appropriate Parameters are used to approximate the burst boundary; (2) For a given blast hole point, construct its Delaunay triangulation; (3) Traverse the above Delaunay segments, through - The shape method determines which line segment lies on the boundary line: It passes through the two endpoints of any line segment. and Drawing radius is Given a circle with a given radius, two distinct circles can be drawn through two given points. If neither circle contains any other points, then the points are considered to be... and These are boundary points, and the lines connecting them... - That is, the boundary line segment; the identified The shape edges constitute Shape outline boundary.

5. The method for automatically dividing polymetallic ore-blending units under complex geological conditions according to claim 1, characterized in that, Step 4 specifically involves: shifting and expanding the aforementioned boundary points outwards as a whole; The borehole boundary extension offset is performed using a vector offset method, which moves each edge of the polygon a certain distance along its normal direction to create a new offset polygon; in this process, the movement of the edges is achieved through vectors, which represent the direction and distance. (1) Determine the offset distance through on-site investigation and verification, parameterize it under the given default distance, and let the user customize it; (2) Traverse each edge of the polygon. For each edge: a. Find the two endpoints A and B of the edge; b. Calculate the normal vector of the edge; if the edge is from A to B, then the normal vector is (By - Ay, Ax - Bx) or in the opposite direction; c. Normalize the normal vector and multiply it by the outward extension distance; d. Add the two endpoints to the calculated vector to obtain two new points; (3) At each intersection point, two or more edges intersect. Specific rules are developed to select the intersection point location through repeated experiments and trials. (4) Combine all the expanded points in sequence to form a new boundary shape.

6. The method for automatically dividing polymetallic ore-blending units under complex geological conditions according to claim 1, characterized in that, The algorithm for generating the Voronoi diagram in step 5 is as follows: For each blast hole point within the target blast pile, perform the following steps: (1) Calculate the perpendicular bisector between the borehole point and all other points; (2) Find the half-plane intersection of all the perpendicular bisectors of the borehole point; this intersection is a Voronoi polygon associated with the point; repeat the above until all points are processed and all Voronoi polygons are merged to form the Voronoi diagram.

7. The method for automatically dividing polymetallic ore-blending units under complex geological conditions according to claim 1, characterized in that, Step 6 specifically involves: By weighting the distance between the ore block and each ore blending center inversely proportionally, the proportion of each ore block belonging to different units is automatically calculated, thus achieving a smooth, continuous, and interpretable division of ore blending units. Two criteria for dividing ore blending units are used. First, lithology is given priority. Lithological boundaries are the primary principle for dividing ore blending units, and ore blending units cannot be divided across lithological boundaries. Second, under normal circumstances, the minimum ore quantity of the blending unit is ≥ 3 days of loading. If the grade of the ore in a blast pile is evenly distributed, it can be directly used as a blending unit. The inverse square method treats the influence of each ore block on the center of each ore distribution unit as inversely proportional to the square of the distance: weighting = After normalization, the allocation ratio is obtained; or the maximum weight is taken for hard partitioning. The "square" power of the weight makes the influence of nearby objects stronger and the decay of distant objects faster, which is suitable for mineral allocation based on nearby objects in space.

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