Pit filling method, system and equipment based on convex hull algorithm and medium

Abstract

The invention provides a pit filling method, system and device based on a convex hull algorithm and a medium. The method comprises the steps of obtaining three-dimensional point cloud data of a pit area, determining a height range of the pit area according to the three-dimensional point cloud data, and segmenting the height range according to a preset vertical interval to obtain a plurality of height layers; filtering the point cloud data in each height layer based on a probability density function of normal distribution, and determining a point set of each height layer; performing boundary analysis on the point set of each height layer based on a convex hull algorithm, determining a convex hull of each height layer, and calculating a convex hull area of each height layer; calculating the volume of the mine pit according to the convex hull area and the vertical spacing of each height layer, and generating a filling construction scheme of the mine pit area based on the volume of the mine pit. The method can replace a traditional manual mine pit volume evaluation method, accurately calculates the mine pit area based on the three-dimensional scanning result, and greatly improves the accuracy of a filling scheme and the filling efficiency.

Description

Technical Field

[0001] The present invention relates to the field of three-dimensional software computing technology, and in particular to a mine filling method, system, equipment and medium based on a convex hull algorithm. Background Art

[0002] Coal mineral resources are one of the world's major fossil energy sources. The coal minerals obtained from mining can play an important role in power generation, industrial production and home heating. However, after the completion of open-pit coal mining, large and small coal mines will be left behind, which seriously affects the sustainable development of resources and the local ecological development. With the improvement of environmental awareness, after open-pit coal mining, open-pit mines need to be filled and reclaimed and greened, so that the mining area after mining becomes fertile land.

[0003] At present, Internet technology has not been widely used in the coal mining industry. It is still in a traditional, closed and backward state, and no scientific means are used for pit backfilling. The current way of backfilling the mine is that after the coal mining is completed, the transportation company is directly entrusted to backfill. The transportation company arranges heavy trucks to transport earth for backfilling. Before backfilling, due to the lack of scientific calculation of the size of the mine, the size of the mine is only estimated by manual experience, and heavy trucks are used to transport earth for backfilling. As the landfill volume increases, the mine is gradually completely filled; but due to the lack of scientific methods to calculate the size of the mine in this process, the manual assessment is relatively backward, and there is often a problem of incorrect assessment of the required backfill volume, resulting in low backfill efficiency. Summary of the invention

[0004] The embodiment of the present invention provides a mine filling method, system, device and medium based on convex hull algorithm to solve the problems existing in the related technology. The technical solution is as follows:

[0005] In a first aspect, an embodiment of the present invention provides a mine filling method based on a convex hull algorithm, comprising:

[0006] Acquire three-dimensional point cloud data of the mine area, determine the height range of the mine area according to the three-dimensional point cloud data, and divide the height range according to a preset vertical spacing to obtain multiple height layers;

[0007] The point cloud data in each altitude layer is filtered based on the probability density function of the normal distribution to determine the point set of each altitude layer;

[0008] Based on the convex hull algorithm, the boundary analysis of the point set of each altitude layer is performed to determine the convex hull of each altitude layer and calculate the convex hull area of ​​each altitude layer;

[0009] The pit volume is calculated according to the convex hull area and vertical spacing of each height layer, and a filling construction plan for the pit area is generated based on the pit volume.

[0010] In one embodiment, it further includes:

[0011] Meshing the mine area based on a preset mesh size to obtain a plurality of mesh units;

[0012] Traverse each grid cell and calculate the variance using the spatial coordinate data within each grid cell;

[0013] The variance is compared with the expected value to obtain a deviation value, and when the deviation value is greater than a threshold, the grid size is optimized to grid the mine area until the deviation value is less than the threshold.

[0014] In one embodiment, filtering the point cloud data in each altitude layer based on a probability density function of a normal distribution includes:

[0015] Traverse each grid unit, calculate the density of the pit depth coordinates of each grid unit based on the probability density function of the normal distribution, and obtain the density value;

[0016] The noise data is determined according to the density value, and the noise data is filtered to obtain the convex hull point cloud data other than the noise data in each grid unit. The convex hull point cloud data of all grid units in the height layer form a point set of the height layer.

[0017] In one embodiment, it further includes:

[0018] After filtering the noise data, the ratio between the amount of point cloud data after filtering and the amount of point cloud data before filtering is calculated. When the ratio is greater than or equal to the preset expected value, the boundary analysis of the point set of the height layer is performed based on the convex hull algorithm to determine the convex hull of the point set of the height layer. When the ratio is less than the preset expected value, the grid size is adjusted to re-grid the mine area.

[0019] In one embodiment, performing boundary analysis on the point set of each altitude layer based on a convex hull algorithm to determine the convex hull of the point set of each altitude layer includes:

[0020] All data points in the height layer are sorted in ascending order according to the coordinates of the convex hull point cloud data in the point set on the X-axis, and the leftmost data point and the rightmost data point after sorting are determined;

[0021] The boundary of the point set at the altitude layer is determined based on the leftmost data point and the rightmost data point, and the convex hull corresponding to the altitude layer is obtained.

[0022] In one embodiment, determining the boundary of the point set at the altitude layer based on the leftmost data point and the rightmost data point includes:

[0023] Taking the leftmost data point as the starting point, traverse each data point in the point set in a counterclockwise direction to determine the first target point that meets the monotonically increasing condition, and connect all the first target points to determine the lower convex hull;

[0024] Taking the rightmost data point as the starting point, traverse each data point in the point set in a clockwise direction to determine the second target point that meets the monotonically decreasing condition, and connect all the second target points to determine the upper convex hull;

[0025] Merge the lower convex hull and the upper convex hull, remove the duplicate points of the lower convex hull and the upper convex hull to get the boundary of the convex hull.

[0026] In one implementation, calculating the convex hull area of ​​each height layer includes:

[0027] Traverse all vertices of the convex hull, connect each vertex with the same origin to form multiple extension lines, and the multiple extension lines and the boundary of the convex hull form multiple triangles;

[0028] Calculate the area of ​​each triangle and calculate the convex hull area based on the areas of all triangles.

[0029] In a second aspect, an embodiment of the present invention provides a mine filling system based on a convex hull algorithm, which executes the mine filling method based on a convex hull algorithm as described above.

[0030] In a third aspect, an embodiment of the present invention provides an electronic device, the device comprising: a memory and a processor. The memory and the processor communicate with each other through an internal connection path, the memory is used to store instructions, the processor is used to execute the instructions stored in the memory, and when the processor executes the instructions stored in the memory, the processor executes the method in any one of the above-mentioned embodiments.

[0031] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, which stores a computer program. When the computer program runs on a computer, the method in any one of the above-mentioned embodiments is executed.

[0032] The advantages or beneficial effects of the above technical solution include at least:

[0033] The present invention determines the pit area by three-dimensional scanning, and divides the pit area into multiple height layers with a preset vertical gap. The convex hull boundary is determined by analyzing the point cloud data on each height layer based on the convex hull algorithm, and the convex hull area of ​​each height layer is calculated. The pit volume can be calculated according to the convex hull area and the vertical gap, so as to determine the filling scheme according to the pit volume. The present invention can replace the traditional method of manually evaluating the pit volume, accurately calculate the pit area based on the three-dimensional scanning results, and greatly improve the accuracy and efficiency of the filling scheme.

[0034] The above summary is for illustrative purposes only and is not intended to be limiting in any way. In addition to the illustrative aspects, embodiments and features described above, further aspects, embodiments and features of the present invention will be readily apparent by reference to the accompanying drawings and the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In the accompanying drawings, unless otherwise specified, the same reference numerals throughout the multiple drawings represent the same or similar parts or elements. These drawings are not necessarily drawn to scale. It should be understood that these drawings only depict some embodiments disclosed in the present invention and should not be regarded as limiting the scope of the present invention.

[0036] Figure 1 It is a schematic diagram of the process of the mine filling method based on the convex hull algorithm of the present invention;

[0037] Figure 2 It is a schematic diagram of the mine volume calculation process of the present invention;

[0038] Figure 3 A two-dimensional plane map is mapped to the three-dimensional point cloud of the present invention;

[0039] Figure 4 This is a trend diagram of mesh size deviation of the present invention;

[0040] Figure 5 It is a two-dimensional point cloud segmentation diagram of the present invention;

[0041] Figure 6 It is the convex hull point cloud data graph of the present invention;

[0042] Figure 7 It is a schematic diagram of the convex hull of the present invention;

[0043] Figure 8 It is a schematic diagram of calculating the area of ​​any polygon in the present invention;

[0044] Fig. 9 The structure block diagram of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0045] In the following, only some exemplary embodiments are briefly described. As those skilled in the art will appreciate, the described embodiments may be modified in various ways without departing from the spirit or scope of the present invention. Therefore, the drawings and descriptions are considered to be exemplary and non-restrictive in nature.

[0046] At present, Internet technology has not been widely used in the coal mining industry. It is still in a traditional, closed and backward state, and no scientific means are used for pit backfilling. The current way of backfilling the mine is that after the coal mining is completed, the transportation company is directly entrusted to backfill. The transportation company arranges heavy trucks to transport earth for backfilling. Before backfilling, due to the lack of scientific calculation of the size of the mine, the size of the mine is only estimated by manual experience, and heavy trucks are used to transport earth for backfilling. As the landfill volume increases, the mine is gradually completely filled; but due to the lack of scientific methods to calculate the size of the mine in this process, the manual assessment is relatively backward, and there is often a problem of incorrect assessment of the required backfill volume, resulting in low backfill efficiency.

[0047] In order to solve the above problems, this embodiment provides a mine filling method based on a convex hull algorithm, which can accurately determine the volume of the mine, thereby generating a suitable filling method and improving the filling efficiency.

[0048] refer to Figure 1 , Figure 2 As shown in FIG. 1 , the pit filling method based on the convex hull algorithm specifically includes the following steps:

[0049] Step S1: Acquire three-dimensional point cloud data of the mine area, determine the height range of the mine area according to the three-dimensional point cloud data, divide the height range according to a preset vertical spacing, and obtain multiple height layers.

[0050] The acquisition of 3D point cloud data can be done by using a drone equipped with 3D scanning equipment to photograph an open pit mine, and by setting up an electronic fence to limit the area of ​​the mine pit, thereby acquiring the 3D point cloud data of the mine pit. Based on the 3D point cloud data, the boundary of the mine pit can be determined, and then the mine points within the boundary of the mine pit can be detected and identified to obtain the 3D point cloud data inside the boundary of the mine pit.

[0051] The 3D point cloud data inside the mine is stored in PCD format. 3D point cloud data usually refers to a set of vectors in a 3D coordinate system. Vectors are usually expressed in the form of X, Y, and Z coordinates, i.e. L(x, y, z), where X represents the horizontal coordinate, Y represents the vertical coordinate, and Z represents the height (depth). 3D point cloud data generally mainly represents the outer surface geometry of an object. In addition, 3D point cloud data can also be accompanied by RGB information, i.e. the color information of each coordinate point, and can also contain other information such as reflection intensity information and echo number information.

[0052] like Figure 3 , Figure 5As shown, the three-dimensional point cloud data is mapped to a two-dimensional plane, and the pit area is grid cut in the two-dimensional plane based on a preset grid size, that is, the height coordinates in the three-dimensional point cloud data are temporarily ignored, and the point cloud is cut according to the pit length coordinates and the pit width coordinates, and the two-dimensional plane is divided into multiple regular grids, thereby obtaining multiple grid units.

[0053] Each grid cell is traversed, and the variance is calculated using the spatial coordinate data of the three-dimensional point cloud in each grid cell. The variance is compared with the expected value to obtain the deviation value. When the deviation value is greater than the threshold, the grid size is optimized to mesh the mine area until the deviation value is less than the threshold.

[0054] It should be clear that the variance is used to reflect the spatial distribution of the point cloud. The variance can be used to measure whether the grid unit obtained by dividing according to the preset grid size is appropriate. The variance formula can be expressed as:

[0055]

[0056] Where M is x1, x2, x3, ... x n The average of x1, x2, x3...x n represents the horizontal coordinate of each 3D point cloud in the grid unit, and n is the number of 3D point cloud data in the grid unit.

[0057] The variance reflects the degree of discreteness of the horizontal coordinate of the point cloud data in the grid unit. If the variance is large, it means that the point cloud data is unevenly distributed in the horizontal coordinate direction, and there may be large errors; if the variance is small, it means that the point cloud data is relatively evenly distributed in the horizontal coordinate direction, and the error is small.

[0058] It should be noted that the variance can also be calculated for the horizontal coordinate (X), vertical coordinate (Y), and vertical coordinate (Z) separately to evaluate the distribution of the point cloud data in different directions. If you need to evaluate the variance of the entire point cloud dataset, you can perform a similar calculation for the coordinates of all points.

[0059] After the variance is calculated, the variance is compared with the preset expected value to obtain the deviation value; assuming that the deviation value is greater than the threshold, it means that the difference between the calculated variance and the theoretical expectation is relatively large. At this time, the grid size needs to be optimized, and the mine area is re-gridded according to the optimized grid size. The variance of the point cloud data of the re-gridged grid unit is calculated until the deviation between the variance and the expected value is less than the threshold, and then the convex hull construction is performed on the point set in the grid unit.

[0060] According to the irregular shape of the mine pit and the experience accumulated in actual application, the grid unit can be divided into 0.5m*0.5 cubes, and the deviation value must be controlled within ±2%. The data obtained in actual application is analyzed using the variance formula and expressed in a line graph, such as Figure 4 As shown, Figure 4 The horizontal axis is the grid side length, and the vertical axis is the deviation value ratio. It can be seen that when the grid side length of the grid unit is 0.5m, the deviation value ratio can be maintained at about ±2%.

[0061] Before constructing the convex hull, the height range of the pit area is determined according to the pit depth coordinates in the three-dimensional point cloud data, and the height direction is divided into multiple uniform vertical segments according to the preset vertical spacing, thereby obtaining multiple height layers. This is equivalent to cutting the pit in a direction parallel to the bottom surface according to the preset vertical spacing to obtain the cross-section of the pit at different heights. The point cloud data existing on each cross-section can be determined according to the spatial coordinate data in the three-dimensional point cloud data, so as to perform convex hull calculation on the point cloud data on each cross-section.

[0062] Step S2: Filter the point cloud data in each altitude layer based on the probability density function of the normal distribution to determine the point set of each altitude layer.

[0063] In order to further improve the accuracy of the point cloud data at each altitude layer, the point cloud data in the grid unit at each altitude layer is cleaned and denoised. The specific methods are as follows:

[0064] According to objective facts, the point cloud data set in the grid unit satisfies the normal distribution law. Each grid unit is traversed, and the density of the pit depth coordinates of each grid unit is calculated based on the probability density function of the normal distribution to obtain the density value.

[0065] The density value is calculated as:

[0066] Calculate the average value of the pit depth coordinates of the point cloud data in the grid unit to obtain its average value μ;

[0067] The standard deviation is set according to actual experience, and the standard deviation can be set to σ = 0.1m;

[0068] The density value of each data point is calculated by the probability density function. The probability density function calculation formula is as follows:

[0069]

[0070] Here, x is a random variable, μ is the mean, and σ is the standard deviation.

[0071] Determine the noise data according to the density value, filter the noise data, and obtain the convex hull point cloud data other than the noise data in each grid cell (such as Figure 6As shown in the figure), the convex hull point cloud data of all grid cells in the altitude layer form a point set of the altitude layer.

[0072] Among them, the density value (N is the total amount of unit grid data), the data point can be determined to be noise data, and the noise data is filtered; and the unfiltered point cloud data can be called convex hull point cloud data, and the convex hull point cloud data is retained for constructing the convex hull.

[0073] After filtering the noise data, error verification can be performed again to calculate the ratio between the amount of point cloud data after filtering and the amount of point cloud data before filtering. When the ratio is greater than or equal to the preset expected value, it means that a large number of original data points are retained in the denoising process, indicating that the error of this grid division is relatively small. In this case, the boundary analysis of the point set of the height layer can be performed based on the convex hull algorithm to determine the convex hull of the point set of the height layer. When the ratio is less than the preset expected value, it means that the error of this grid division is relatively large. In this case, it is necessary to adjust the grid size and re-grid the mine area until the ratio is greater than or equal to the preset expected value.

[0074] According to the probability density function of the normal distribution, the point cloud data in all grid cells at each altitude layer are cleaned and denoised to ensure that the z difference in the point cloud data of the grid cells is within the expected reasonable range, and the convex hull point cloud data of the grid cells is obtained. The convex hull point cloud data of the grid cells forms a new point set for constructing the convex hull.

[0075] Step S3: Based on the convex hull algorithm, boundary analysis is performed on the point set of each altitude layer, the convex hull of each altitude layer is determined, and the convex hull area of ​​each altitude layer is calculated.

[0076] The measurement of irregularly shaped mine pits can be converted into the measurement of the shape implicitly defined by the point set on the same plane. Since the collected raw data are all discrete and unordered point sets, it is necessary to find out which points are at the boundary of the shape and in what order they are connected. Only after this arrangement can various subsequent calculations be performed. Therefore, the convex hull algorithm must be used to find the convex hull of the point set. Specifically:

[0077] Traverse the point set in the grid unit in each altitude layer, sort all the data points in the altitude layer in ascending order according to the X coordinate of the convex hull point cloud data in the point set, determine the data point located on the leftmost and the data point located on the rightmost after sorting, call the data point located on the leftmost data point, and call the data point located on the backmost side the rightmost data point. These two points must be on the convex hull. Therefore, based on the leftmost and rightmost data points, determine the boundary of the point set on the altitude layer, and obtain the convex hull corresponding to the altitude layer.

[0078] Specifically, the method for constructing the lower convex hull is: taking the leftmost data point as the starting point, traversing each convex hull point cloud data in the point set in a counterclockwise direction, and determining all first target points that meet the monotonically increasing condition, that is, starting from the leftmost data point, traversing the point set in a counterclockwise direction, and when the current data point moves to the next data point, the turning angle increases counterclockwise.

[0079] It should be noted that the counterclockwise increasing steering angle means that after determining the broken line formed by the current data point and the last two data points on the chain, if the broken line forms a larger counterclockwise angle than the previous broken line segment formed by the last two data points on the chain, then the current point can be added to the chain. Before adding a new data point, it is necessary to check whether the last three data points on the chain still form a monotonically increasing chain. If the addition of a new data point destroys this monotonicity (i.e., monotonically increasing counterclockwise), the last data point needs to be deleted from the chain until the monotonically increasing condition is met after the addition of the new data point.

[0080] The data table that meets the above monotonically increasing condition is marked as the first target point, and all the first target points are arranged in order to gradually construct the boundary of a convex polygon, which is the lower convex hull.

[0081] Similarly, a similar method is used to construct the upper convex hull, that is, taking the rightmost data point as the starting point, traversing each data point in the point set in a clockwise direction, determining the second target point that satisfies the monotonically decreasing condition, connecting all the second target points, maintaining a monotonically decreasing chain, and thus determining the upper convex hull.

[0082] Merge the data points of the lower convex hull and the data points of the upper convex hull, and remove the duplicate data points between the lower convex hull and the upper convex hull to obtain the boundary of the entire convex hull (such as Figure 7 shown).

[0083] The convex hull of each height layer is calculated according to the above method, and the area and perimeter of the convex hull of each height layer are calculated to accurately determine the scope of the mine pit that needs to be filled.

[0084] In order to calculate the perimeter of the convex hull, it is necessary to calculate the distances between adjacent points in the order of the data points (for example, in the order generated by the convex hull algorithm) and add up the distances. Since the generated convex hull is a list of points in order, the problem of perimeter calculation is simplified to the problem of summing the distances between adjacent points. In a two-dimensional Euclidean space, for two given points P1 (Xa, Ya) and P2 (Xb, Yb), the distance d between the two points can be calculated using the Euclidean distance formula:

[0085]

[0086] The calculation method of the convex hull area is based on the concept of vector cross multiplication. The calculation of the polygon area is converted into the idea of ​​dividing the polygon into multiple triangles, and the area of ​​the triangle is calculated.

[0087] That is, given an arbitrary polygon consisting of n vertices, the area of ​​the polygon is equal to the sum of the directed areas of the triangles formed by every two adjacent vertices on the polygon and the coordinate origin, where the directed area means that if the three vertices of the triangle are arranged in counterclockwise order, the area is positive, otherwise it is negative.

[0088] Back to the present embodiment, all vertices of the convex hull are traversed, and each vertex is connected to the same origin to form multiple extension lines, and the multiple extension lines and the boundary of the convex hull form multiple triangles; the area of ​​each triangle is calculated, and the area of ​​the convex hull is calculated based on the areas of all triangles.

[0089] like Figure 8 As shown, the convex hull ABCDE can be regarded as the sum of the areas of the three positive triangles OBC, OCD, ODE and the two negative triangles OAB and OEA; after calculating the area of ​​each triangle, the three positive triangles OBC, OCD, ODE are added to get the total area, and the areas of the negative triangles OAB and OEA are subtracted from the total area to get the area of ​​the convex hull ABCDE.

[0090] Step S4: Calculate the pit volume according to the convex hull area and vertical spacing of each height layer, and generate a filling construction plan for the pit area based on the pit volume.

[0091] After determining the convex hull area of ​​each height layer, multiply the convex hull area by the vertical spacing to get the volume of a single height layer, and add the volumes of each height layer to get the volume of the entire pit. Therefore, the calculation formula for the approximate value of the volume of any irregular pit is as follows:

[0092]

[0093] After determining the volume of the mine pit, the amount of earth and stone materials needed to fill the mine pit can be determined. The construction plan can be determined based on the amount of earth and stone materials used, so that the construction party can transport the required amount of earth and stone materials to the mine site to fill the mine pit, so that the ground after filling reaches the stability, uniformity and bearing capacity requirements.

[0094] This embodiment adopts the idea of ​​the differential element method for volume estimation of irregular-shaped mine point clouds, that is, the total height of the mine point cloud is divided into many small parts with a very small distance as the vertical spacing, and the convex hull area of ​​the point set of the cross section is calculated at each height, and then the approximate value of the volume is obtained by multiplying the area by the spacing and accumulating them. This can improve the accuracy of mine volume measurement, reduce the possibility of repeated transportation of filling materials by on-site personnel due to insufficient single transportation, and reduce the waste of materials due to excessive transportation of filling materials, thereby improving filling efficiency.

[0095] In another embodiment, a mine filling system based on a convex hull algorithm is provided. The system executes the mine filling method based on a convex hull algorithm as described above.

[0096] The functions of the various modules of the system of the embodiment of the present invention can be found in the corresponding description of the above method, which will not be repeated here.

[0097] In another embodiment, an electronic device is provided. Fig. 9 FIG. 2 shows a structural block diagram of an electronic device according to an embodiment of the present invention. Fig. 9 As shown, the electronic device includes: a memory 100 and a processor 200. The memory 100 stores a computer program that can be run on the processor 200. When the processor 200 executes the computer program, the mine filling method based on the convex hull algorithm in the above embodiment is implemented. The number of the memory 100 and the processor 200 can be one or more.

[0098] The electronic device also includes:

[0099] The communication interface 300 is used to communicate with external devices and perform data exchange transmission.

[0100] If the memory 100, the processor 200 and the communication interface 300 are implemented independently, the memory 100, the processor 200 and the communication interface 300 can be connected to each other through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Fig. 9 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0101] Optionally, in a specific implementation, if the memory 100, the processor 200 and the communication interface 300 are integrated on a chip, the memory 100, the processor 200 and the communication interface 300 can communicate with each other through an internal interface.

[0102] An embodiment of the present invention provides a computer-readable storage medium storing a computer program, which implements the method provided in the embodiment of the present invention when executed by a processor.

[0103] An embodiment of the present invention further provides a chip, which includes a processor for calling and executing instructions stored in the memory from the memory, so that a communication device equipped with the chip executes the method provided by the embodiment of the present invention.

[0104] An embodiment of the present invention also provides a chip, including: an input interface, an output interface, a processor and a memory, wherein the input interface, the output interface, the processor and the memory are connected via an internal connection path, and the processor is used to execute the code in the memory. When the code is executed, the processor is used to execute the method provided by the embodiment of the invention.

[0105] It should be understood that the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. It is worth noting that the processor may be a processor supporting the advanced RISC machines (ARM) architecture.

[0106] Further, optionally, the above-mentioned memory may include a read-only memory and a random access memory, and may also include a non-volatile random access memory. The memory may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may include a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may include a random access memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of RAM are available. For example, static RAM (SRAM), dynamic random access memory (DRAM), synchronous DRAM (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM) and direct rambus RAM (DR RAM).

[0107] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function according to the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium.

[0108] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine different embodiments or examples described in this specification and the features of different embodiments or examples, unless they are contradictory.

[0109] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0110] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of various changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A mine filling method based on convex hull algorithm, characterized in that: include: Acquire three-dimensional point cloud data of a mine area, determine a height range of the mine area according to the three-dimensional point cloud data, and divide the height range according to a preset vertical spacing to obtain a plurality of height layers; Filtering the point cloud data in each altitude layer based on a probability density function of a normal distribution to determine a point set in each altitude layer; Performing boundary analysis on the point set of each altitude layer based on a convex hull algorithm, determining the convex hull of each altitude layer, and calculating the convex hull area of ​​each altitude layer; The volume of the mine pit is calculated according to the convex hull area of ​​each height layer and the vertical spacing, and a filling construction plan for the mine pit area is generated based on the mine pit volume.

2. The mine filling method based on convex hull algorithm according to claim 1, characterized in that: Also includes: Dividing the mine area into grids based on a preset grid size to obtain a plurality of grid units; Traversing each of the grid cells, and calculating the variance using the spatial coordinate data in each of the grid cells; The variance is compared with an expected value to obtain a deviation value, and when the deviation value is greater than a threshold, the grid size is optimized to grid the mine area until the deviation value is less than the threshold.

3. The mine filling method based on convex hull algorithm according to claim 2, characterized in that: The probability density function based on normal distribution filters the point cloud data in each altitude layer, including: Traversing each of the grid cells, and performing density calculation on the pit depth coordinates of each of the grid cells based on a probability density function of a normal distribution to obtain a density value; Noise data is determined according to the density value, and the noise data is filtered to obtain convex hull point cloud data other than the noise data in each grid unit, and the convex hull point cloud data of all the grid units in the height layer form the point set of the height layer.

4. The mine filling method based on convex hull algorithm according to claim 3 is characterized in that: Also includes: After filtering the noise data, the ratio between the amount of data after filtering and the amount of data before filtering is calculated; when the ratio is greater than or equal to a preset expected value, a boundary analysis is performed on the point set of the height layer based on a convex hull algorithm to determine the convex hull of the point set of the height layer; when the ratio is less than the preset expected value, the grid size is adjusted to re-grid the mine area.

5. The mine filling method based on convex hull algorithm according to claim 3, characterized in that: The step of performing boundary analysis on the point set of each of the height layers based on a convex hull algorithm to determine the convex hull of the point set of each of the height layers comprises: Sorting all data points in the height layer in ascending order according to the coordinates of the convex hull point cloud data in the point set on the X-axis, and determining the leftmost data point and the rightmost data point after sorting; The boundary of the point set at the altitude layer is determined based on the leftmost data point and the rightmost data point, and the convex hull corresponding to the altitude layer is obtained.

6. The mine filling method based on convex hull algorithm according to claim 5, characterized in that: The step of determining a boundary of the point set at the altitude layer based on the leftmost data point and the rightmost data point comprises: Taking the leftmost data point as the starting point, traverse each data point in the point set in a counterclockwise direction to determine a first target point that satisfies a monotonically increasing condition, and connect all the first target points to determine a lower convex hull; Taking the rightmost data point as the starting point, traverse each data point in the point set in a clockwise direction to determine a second target point that satisfies a monotonically decreasing condition, and connect all the second target points to determine an upper convex hull; The lower convex hull and the upper convex hull are merged, and duplicate points of the lower convex hull and the upper convex hull are removed to obtain the boundary of the convex hull.

7. The mine filling method based on convex hull algorithm according to claim 1, characterized in that: The calculating of the convex hull area of ​​each height layer comprises: Traversing all vertices of the convex hull, connecting each vertex with the same origin to form a plurality of extension lines, and the plurality of extension lines and the boundary of the convex hull to form a plurality of triangles; The area of ​​each triangle is calculated, and the convex hull area is calculated based on the areas of all triangles.

8. A mine filling system based on convex hull algorithm, characterized in that: Execute the mine filling method based on convex hull algorithm as described in any one of claims 1 to 7.

9. An electronic device, characterized in that: include: A processor and a memory, wherein the memory stores instructions, and the instructions are loaded and executed by the processor to implement the mine filling method based on the convex hull algorithm as claimed in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the mine filling method based on the convex hull algorithm according to any one of claims 1 to 7 is implemented.

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