Three-dimensional coal mine area earthwork calculation method and device based on UAV tilt data

Abstract

The present invention provides a method and device for calculating earthwork volume in a three-dimensional coal mine area based on drone tilt data. The method comprises: obtaining an early three-dimensional model of a target mine area before and after excavation and filling, and its corresponding early DOM data, and a late three-dimensional model and its corresponding late DOM data based on the drone tilt data; extracting a target region vector and an interpolation region vector corresponding to the target mine area based on the early DOM data and the late DOM data; performing differentiable block calculation of earthwork volume based on the target region vector and the interpolation region vector, in combination with the early 3D model and the late 3D model, to obtain a set of excavation and fill volumes corresponding to the target mine area; and performing rendering based on the excavation and fill volumes to obtain a rendering result of the excavation and fill volumes corresponding to the target mine area. The present invention can efficiently and accurately calculate earthwork volume in a three-dimensional coal mine area.

Description

Technical Field

[0001] The present invention relates to the technical field of earthwork volume calculation, and in particular to a three-dimensional coal mine area earthwork volume calculation method and device based on drone tilt data. Background Art

[0002] During coal mining operations, accurate calculation of excavation and fill volumes is of vital importance to mining area planning, resource utilization, cost control, and environmental protection.

[0003] Traditional earthwork volume calculation methods, such as grid and contour methods, rely primarily on field surveys. By laying out a grid of a certain size across a portion of the field site, surveyors must establish numerous control points throughout the mine area and perform point-by-point elevation and planimetric measurements using instruments such as levels and total stations. This approach is not only labor-intensive, material-intensive, and time-consuming, but also presents numerous challenges in complex coal mine environments, such as steep pit slopes, large deposits, and frequently changing mining areas. The accuracy and integrity of the measured data are therefore difficult to guarantee. Some research has attempted to calculate cut and fill volumes based on DEMs or three-dimensional models, but DEMs often struggle to maintain temporal resolution, resolution, and accuracy, rely on commercial software, and fail to accurately represent the regional distribution of cut and fill. Calculations based on three-dimensional models often use a single period and a fixed elevation datum, failing to account for the influence of ground interference, such as trees and impacting objects. This leads to significant random errors and makes them useful only as reference quantities. These methods are difficult to meet the requirements of fast coal mining operations and accurate and intuitive calculation results, and also bring technical difficulties to subsequent audit work.

[0004] With the rapid development of drone technology, drone-based oblique photogrammetry has emerged and is gradually gaining widespread application in surveying and mapping. This technology uses multiple sensors mounted on drones to capture ground targets from different angles, rapidly acquiring high-resolution image data over large areas and constructing high-precision 3D models with rich texture information. However, current research on the application of drone-based oblique 3D model data formats to calculate cut and fill volumes in coal mining areas remains insufficient. Existing data processing processes and algorithms often fail to efficiently and accurately extract key information for earthwork calculations and effectively and intuitively display cut and fill results when processing 3D model data from the unique topography and complex operating environments of coal mining areas. Summary of the Invention

[0005] In view of this, the purpose of the present invention is to provide a three-dimensional coal mine area earthwork volume calculation method and device based on drone tilt data, which can realize three-dimensional coal mine area earthwork volume calculation efficiently and accurately.

[0006] In a first aspect, an embodiment of the present invention provides a method for calculating earthwork volume in a three-dimensional coal mine area based on drone tilt data, comprising:

[0007] Based on the UAV tilt data, the target mining area is obtained before and after the filling and excavation of the early three-dimensional model and its corresponding early DOM data, and the late three-dimensional model and its corresponding late DOM data;

[0008] Based on the early DOM data and the late DOM data, the target area vector and the interpolation area vector corresponding to the target mining area are extracted. The target area vector is the area where the excavation and filling volume is to be calculated, and the interpolation area vector is the sub-area with ground interference within the area where the excavation and filling volume is to be calculated.

[0009] Based on the target area vector and the interpolation area vector, combined with the early 3D model and the later 3D model, the earthwork volume is calculated by differentiable blocks to obtain the excavation volume set and the fill volume set corresponding to the target mining area;

[0010] Rendering is performed based on the excavation volume set and the fill volume set to obtain the excavation and fill volume rendering results corresponding to the target mining area.

[0011] In one embodiment, based on the target area vector and the interpolation area vector, combined with the early 3D model and the late 3D model, a differentiable block calculation of earthwork volume is performed to obtain a set of excavation volume and a set of fill volume corresponding to the target mining area, including:

[0012] Determine the virtual camera pose according to the target area vector, and control the virtual camera to adjust its pose according to the virtual camera pose so that the virtual camera faces the early 3D model and the late 3D model;

[0013] Divide the target area vector into a plurality of first differentiable rectangular blocks;

[0014] Perform elevation differentiable interpolation on the interpolation area vector to generate an interpolation triangulation network corresponding to the interpolation area vector;

[0015] Based on the interpolation triangulation corresponding to the first differentiable rectangular block and the interpolation area vector, combined with the early 3D model and the later 3D model within the field of view of the virtual camera, the excavation volume set and the fill volume set corresponding to the target mining area are determined.

[0016] In one embodiment, the virtual camera pose includes camera position coordinates and camera rotation angle; determining the virtual camera pose according to the target area vector includes:

[0017] Determine the minimum bounding rectangle corresponding to the target area vector;

[0018] The center coordinates of the minimum circumscribed rectangle are used as the plane coordinates of the virtual camera; and the height coordinates of the virtual camera are obtained based on the intersection of a perpendicular line passing through the center coordinates and the early 3D model or the late 3D model; the plane coordinates and the height coordinates constitute the camera position coordinates corresponding to the virtual camera;

[0019] The camera rotation angle corresponding to the virtual camera is determined based on the angle between the long side vectors of the minimum circumscribed rectangle in the Cartesian coordinate system.

[0020] In one embodiment, the interpolation region vector carries a label, and the label is used to indicate whether the interpolation region vector belongs to before or after cut and fill. The interpolation region vector is subjected to elevation differentiable interpolation to generate an interpolation triangulation corresponding to the interpolation region vector, including:

[0021] For each boundary point in the boundary point set corresponding to the interpolation region vector, based on the label carried by the interpolation region vector, the intersection point between the vertical line through the boundary point and the previous 3D model or the later 3D model is obtained to generate an interpolation point set. The elevation value of the intersection point in the interpolation point set is consistent with the elevation value of the corresponding boundary point.

[0022] Divide the interpolation region vector into a plurality of second differentiable rectangular blocks, and when the vertices of the second differentiable rectangular blocks fall within the interpolation region vector, add the vertices of the second differentiable rectangular blocks to the interpolation point set, and the elevation values ​​of the vertices in the interpolation point set are 0;

[0023] Using the elevation values ​​of the intersection points in the interpolation point set, the elevation values ​​of the vertices in the interpolation point set are interpolated to obtain the target interpolation point set;

[0024] Generate an interpolation triangulation corresponding to the interpolation area vector based on the target interpolation point set.

[0025] In one embodiment, based on the interpolation triangulation corresponding to the first differentiable rectangular block and the interpolation region vector, combined with the early 3D model and the late 3D model within the field of view of the virtual camera, the excavation volume set and the fill volume set corresponding to the target mining area are determined, including:

[0026] For any first differentiable rectangular block, perform the following operations:

[0027] When the center coordinates of the first differentiable rectangular block intersect the interpolation region vector, based on the label carried by the interpolation region vector, the interpolation triangulation corresponding to the intersecting interpolation region vector is used to update the early three-dimensional model or the late three-dimensional model within the field of view of the virtual camera;

[0028] Determine the intersection points of a perpendicular line passing through the center coordinates of the first differentiable rectangular block with the updated early three-dimensional model and the updated late three-dimensional model, respectively, to determine the volume difference corresponding to the first differentiable rectangular block;

[0029] Based on the positive or negative value of the volume difference, the volume difference is saved in the cut volume collection or the fill volume collection.

[0030] In one embodiment, based on the labels carried by the interpolation region vectors, the interpolation triangulation corresponding to the intersecting interpolation region vectors is used to update the early 3D model or the late 3D model within the field of view of the virtual camera, including:

[0031] If the label indicates that the interpolation region vector belongs to the front of the cut-filling process, the interpolation triangulation corresponding to the intersecting interpolation region vector is used to replace the portion corresponding to the interpolation region vector in the previous 3D model within the field of view of the virtual camera;

[0032] If the label indicates that the interpolation region vector belongs to the cut-fill area, the interpolation triangulation corresponding to the intersecting interpolation region vector is used to replace the portion corresponding to the interpolation region vector in the later three-dimensional model within the field of view of the virtual camera.

[0033] In one embodiment, rendering is performed based on the excavation volume set and the fill volume set to obtain the excavation and fill volume rendering result corresponding to the target mining area, including:

[0034] Determine the maximum excavation volume value and the minimum excavation volume value in the excavation volume set, and determine the maximum fill volume value and the minimum fill volume value in the fill volume set;

[0035] Divide the specified color band into a first sub-color band and a second sub-color band;

[0036] Determining a rendering step length for the cut volume based on the maximum cut volume value and the minimum cut volume value, and determining a mapping relationship between the cut volume values ​​in the cut volume set and the color band indexes in the first sub-color band based on the rendering step length for the cut volume; and determining a rendering step length for the fill volume based on the maximum fill volume value and the minimum fill volume value, and determining a mapping relationship between the fill volume values ​​in the fill volume set and the color band indexes in the second sub-color band based on the rendering step length for the fill volume;

[0037] Rendering is performed based on the mapping relationship to obtain the rendering results of the excavation and filling volume corresponding to the target mining area.

[0038] In one embodiment, after obtaining an early three-dimensional model of the target mining area before and after filling and cutting and its corresponding early DOM data, and a late three-dimensional model and its corresponding late DOM data based on the drone tilt data, the method further includes:

[0039] Determine the same reference ground feature point and its corresponding early elevation value and late elevation value from the early 3D model and the late 3D model;

[0040] Determine the offset matrix based on the early elevation value and the late elevation value corresponding to the reference feature point;

[0041] The offset matrix is ​​used to fine-tune the early 3D model and the late 3D model so that the early elevation value and the late elevation value corresponding to the same reference feature point coincide with each other.

[0042] In a second aspect, the present invention further provides a three-dimensional coal mine area earthwork volume calculation device based on drone tilt data, comprising:

[0043] The data acquisition module is used to obtain the early three-dimensional model and its corresponding early DOM data, and the late three-dimensional model and its corresponding late DOM data of the target mining area before and after filling and excavation based on the UAV tilt data;

[0044] The vector extraction module is used to extract the target area vector and interpolation area vector corresponding to the target mining area based on the early DOM data and the late DOM data. The target area vector is the area where the excavation and filling volume is to be calculated, and the interpolation area vector is the sub-area where there are ground interference objects within the area where the excavation and filling volume is to be calculated;

[0045] The earthwork volume calculation module is used to perform differentiable block calculation of earthwork volume based on the target area vector and the interpolation area vector, combined with the early 3D model and the later 3D model, to obtain the excavation volume set and fill volume set corresponding to the target mining area;

[0046] The earthwork volume rendering module is used to render and draw according to the excavation volume set and the fill volume set to obtain the excavation and fill volume rendering results corresponding to the target mining area.

[0047] In a third aspect, the present invention further provides an electronic device comprising a processor and a memory, wherein the memory stores computer-executable instructions that can be executed by the processor, and the processor executes the computer-executable instructions to implement any one of the methods provided in the first aspect.

[0048] The present invention provides a method and device for calculating earthwork volume in a three-dimensional coal mine area based on drone tilt data. First, based on the drone tilt data, an early three-dimensional model of a target mine area before and after excavation and filling and its corresponding early DOM data, and a late three-dimensional model and its corresponding late DOM data are obtained. Then, based on the early DOM data and the late DOM data, a target area vector and an interpolation area vector corresponding to the target mine area are extracted. The target area vector is the area where the excavation and filling volumes are to be calculated, and the interpolation area vector is the sub-area where ground interference objects exist within the area where the excavation and filling volumes are to be calculated. Then, based on the target area vector and the interpolation area vector, in combination with the early three-dimensional model and the late three-dimensional model, differentiable block calculation of earthwork volume is performed to obtain an excavation volume set and a filling volume set corresponding to the target mine area. Finally, rendering is performed based on the excavation volume set and the filling volume set to obtain an excavation and filling volume rendering result corresponding to the target mine area. The above method is based on the tilt modeling scheme of drones, which can quickly and efficiently acquire and process data. Compared with traditional field measurement schemes and other calculation methods, the two-dimensional result display is transferred to the three-dimensional model. The present invention improves the controllability of the calculation scale based on the previous and next three-dimensional models. The interpolation area vector solves the influence of interference objects and realizes the visualization rendering of the calculation results of the excavation and filling volume. It more efficiently and intuitively reflects the scale, process and final result of the calculation, and ultimately effectively improves the planning and management level of coal mine areas, enhances cost control and economic benefit evaluation, provides strong support for the audit work of mining areas, etc., and promotes the innovative application of drone surveying and mapping technology in the coal mining industry.

[0049] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or understood by practicing the present invention. The purposes and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description, claims and drawings.

[0050] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0052] Figure 1 A schematic flow chart of a method for calculating earthwork volume in a three-dimensional coal mine area based on drone tilt data provided by an embodiment of the present invention;

[0053] Figure 2 A schematic diagram of a process for producing three-dimensional data of a mining area in the early and late stages provided by an embodiment of the present invention;

[0054] Figure 3 A schematic diagram of a process for determining a mask vector area provided by an embodiment of the present invention;

[0055] Figure 4 A schematic diagram of a process for differential calculation of excavation and filling volume provided by an embodiment of the present invention;

[0056] Figure 5 A schematic diagram of a three-dimensional rendering and display process provided by an embodiment of the present invention;

[0057] Figure 6 A schematic diagram of the structure of a three-dimensional coal mine area earthwork volume calculation device based on drone tilt data provided by an embodiment of the present invention;

[0058] Figure 7 A schematic structural diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0059] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of them. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0060] At present, when processing three-dimensional model data of coal mine areas with special terrain and complex operating environments, existing data processing processes and algorithms are often unable to efficiently and accurately extract key information for earthwork calculation and efficiently and intuitively display the results of excavation and filling. There is a lack of a unified, efficient and accurate method system for calculating the excavation and filling volume of coal mine areas based on the tilted three-dimensional model data format of drones, which makes it difficult to give full play to the potential advantages of drone tilt photogrammetry technology in the calculation of earthwork volume in coal mine areas, thereby restricting the improvement of the scientific and refined management level of coal mining operations. Based on this, the present invention provides a three-dimensional coal mine area earthwork volume calculation method and device based on drone tilt data, which can efficiently and accurately realize the three-dimensional coal mine area earthwork volume calculation.

[0061] To facilitate understanding of this embodiment, firstly, a three-dimensional coal mine area earthwork volume calculation method based on drone tilt data disclosed in an embodiment of the present invention is described in detail, see Figure 1The flowchart of a method for calculating earthwork volume in a three-dimensional coal mine area based on UAV tilt data is shown. The method mainly includes the following steps S102 to S108:

[0062] Step S102: obtaining an early three-dimensional model and its corresponding early DOM data, and a late three-dimensional model and its corresponding late DOM data of the target mining area before and after filling and excavation based on the UAV tilt data.

[0063] In one example, drones can be controlled to collect tilt data of the target mining area before and after cut-filling. Reconstruction can then be performed based on these tilt data to produce an early 3D model and its corresponding early DOM (Digital Orthophoto Map) data, and a late 3D model and its corresponding late DOM data. Preferably, the same reference feature point can be identified in both the early and late 3D models, and fine-tuned using this reference feature point to eliminate elevation errors between the early and late 3D models.

[0064] Step S104 : extracting a target region vector and an interpolation region vector corresponding to the target mining area based on the early DOM data and the late DOM data.

[0065] The target region vector represents the area for which cut and fill volumes are to be calculated, and the interpolation region vector represents the sub-region within the area for which cut and fill volumes are to be calculated where ground interferences exist. There is at least one interpolation region vector, and ground interferences can be trees, debris, or other objects. The interpolation region vector carries a label that indicates whether the interpolation region vector belongs to the pre-cut or post-cut phase. In one example, the target region vector and multiple interpolation region vectors corresponding to the target mining area can be extracted in relevant engineering software based on pre- and post-cut DOM data, combined with Map World (a public geographic information platform) or other data sources.

[0066] Step S106 , based on the target area vector and the interpolation area vector, combined with the early 3D model and the late 3D model, performs differentiable block calculation of earthwork volume to obtain the excavation volume set and the fill volume set corresponding to the target mining area.

[0067] The excavation volume set includes the excavation volume values ​​corresponding to the differentiable rectangular blocks within the target area vector, and the fill volume set includes the fill volume values ​​corresponding to the differentiable rectangular blocks within the target area vector. In one example, based on the target area vector, the differentiable rectangular blocks contained within the target area vector (referred to as the first differentiable rectangular blocks) are determined by combining the early and late 3D models. Simultaneously, based on the interpolation area vector, the interpolation triangulation corresponding to the interpolation area vector is determined by performing elevation differentiable interpolation in combination with the early and late 3D models. The excavation volume set and fill volume set corresponding to the target mining area are determined by combining the first differentiable rectangular blocks, the interpolation triangulation network, the early and late 3D models.

[0068] Step S108 , performing rendering based on the excavation volume set and the fill volume set to obtain an excavation and fill volume rendering result corresponding to the target mining area.

[0069] The cut and fill volume rendering results are used to depict the cut and fill volume within the target mining area using different colors. In one example, a designated color band can be divided into a first sub-color band and a second sub-color band. Based on the maximum and minimum cut volume values ​​in the cut volume set, a mapping relationship is determined between the cut volume values ​​in the cut volume set and the color band index in the first sub-color band. Based on the maximum and minimum fill volume values ​​in the fill volume set, a mapping relationship is determined between the fill volume values ​​in the fill volume set and the color band index in the second sub-color band. Rendering is then performed based on the mapped restrooms to obtain the corresponding cut and fill volume rendering results.

[0070] The embodiment of the present invention provides a three-dimensional coal mine area earthwork calculation method based on drone tilt data. The drone-based tilt modeling scheme can quickly and efficiently acquire and process data. Compared with traditional field measurement schemes and other calculation methods, the two-dimensional result display is transferred to the three-dimensional model. The present invention improves the controllability of the calculation scale based on the previous and next three-dimensional models, and the interpolation area vector solves the influence of interference objects, realizes the visualization rendering of the excavation and filling earthwork calculation results, and more efficiently and intuitively reflects the scale, process and final result of the calculation, ultimately effectively improving the planning and management level of coal mine areas, enhancing cost control and economic benefit evaluation, providing strong support for the audit work of mining areas, etc., and promoting the innovative application of drone surveying and mapping technology in the coal mining industry.

[0071] For ease of understanding, an embodiment of the present invention provides a specific implementation of a method for calculating earthwork volume in a three-dimensional coal mine area based on drone tilt data.

[0072] (1) Production of 3D data of mining areas before and after the mining period, see Figure 2The schematic diagram of the process for producing 3D data for a mining area in the early and late stages includes: collecting early tilt data for the mining area, reconstructing it through 3D reconstruction to obtain an early 3D model and early DOM data; collecting late tilt data for the mining area, reconstructing it through 3D reconstruction to obtain a late 3D model and late DOM data; and fine-tuning the early and late 3D models. The specific implementation includes the following (1.1) to (1.2):

[0073] (1.1) Based on the UAV tilt data, obtain the early three-dimensional model and its corresponding early DOM data, and the late three-dimensional model and its corresponding late DOM data of the target mining area before and after filling and excavation.

[0074] Use drones to collect tilt data before excavation and filling of the target mining area, and then use professional 3D reconstruction software to reconstruct it, producing the early 3D model Data_pre in the early osgb (Open Scene Graph Binary) format and the corresponding early DOM data Dom_pre; after excavation and filling, the target mining area in the same range is again subjected to tilt data collection and 3D reconstruction, producing the late 3D model Data_last in the late osgb format and the corresponding late DOM data Dom_last.

[0075] (1.2) Determine the same reference feature point and its corresponding early elevation value and late elevation value from the early 3D model and the late 3D model; determine an offset matrix based on the early elevation value and the late elevation value corresponding to the reference feature point; and use the offset matrix to fine-tune the early 3D model and the late 3D model so that the early elevation value and the late elevation value corresponding to the same reference feature point coincide.

[0076] Since it is an uncontrolled 3D reconstruction, there may be a certain elevation error between the early 3D model Data_pre and the later 3D model Data_last, so the 3D model needs to be fine-tuned; find a reference point on the 3D model, such as a construction site point P1, preferably a road or a corner of a house; use the elevation point P1 of the early 3D model Data_pre as the elevation reference point, and set the offset matrix of the later 3D model Data_last to make the same-name point P1 in the early DOM data Dom_pre coincide with the later DOM data Dom_last.

[0077] (2) Determine the mask vector area, see Figure 3 The flowchart shown here shows a process for determining a mask vector area, including: vector collection based on pre- or post-DOM data, Map World, or other data sources to obtain a target area vector and an interpolated area vector. The target area vector and the interpolated area vector constitute the mask vector area.

[0078] This step primarily outputs the target area vector V1 and interpolated area vector V2 for calculating cut and fill volumes. The target area vector V1 represents the area for which cut and fill volumes need to be calculated, while the interpolated area vector V2 represents areas containing trees, debris, or other ground obstructions. In this embodiment of the present invention, the target area vector V1 and interpolated area vector V2 can be mapped in GIS software using pre-processing DOM data (Dom_pre) and post-processing DOM data (Dom_last). The interpolated area vector V2 must include an integer field (phase value, also known as a label) to indicate whether the vector area belongs to the pre-processing or post-processing phase. A value of 1 represents the pre-processing phase, 2 represents the post-processing phase, and 3 represents both. Furthermore, the interpolated area vector V2 must ensure that its boundary points fall on the ground, not on obstructions. If the phase difference is not significant, the target area vector V1 and interpolated area vector V2 can be collected using Map World or by using existing target area vectors. However, the coordinates of the target area vector V1 and interpolated area vector V2 must be consistent with the pre-processing 3D model (Data_pre) and post-processing DOM data (Data_last).

[0079] (3) Differentiable calculation of excavation and filling volume, see Figure 4 The schematic diagram of a process for differentially calculating cut and fill volumes is shown, including: calculating the virtual camera pose and differentiable rectangular blocks based on the target area vector and the previous and later 3D models; performing differentiable interpolation based on the interpolation area vector and the previous and later 3D models to obtain an interpolated triangulated network; and performing differentiable block calculation based on the differentiable rectangular blocks and the interpolated triangulated network to obtain cut and fill volumes, including a cut volume set and a fill volume set. The specific implementation includes the following (3.1) to (3.4):

[0080] (3.1) Determine the virtual camera pose based on the target area vector, and control the virtual camera to adjust its pose according to the virtual camera pose so that the virtual camera faces the early 3D model and the late 3D model. In one embodiment, the camera position coordinates Camera_P and the camera rotation angle Rotate_angle of a top-view 3D model area are calculated based on the target area vector V1. The virtual camera is dynamically translated and rotated according to the camera position coordinates Camera_P and the camera rotation angle Rotate_angle so that it faces the 3D model. Specifically:

[0081] (3.11) Determine the minimum bounding rectangle corresponding to the target area vector.

[0082] In the specific implementation, the rotating calipers algorithm is used to calculate the minimum bounding rectangle rect of the target area vector V1. The length of the minimum bounding rectangle rect is W and the width is H.

[0083] (3.12) The center coordinates of the minimum circumscribed rectangle are used as the plane coordinates of the virtual camera; and the height coordinates of the virtual camera are obtained based on the intersection of a perpendicular line through the center coordinates and the early three-dimensional model or the late three-dimensional model; the plane coordinates and the height coordinates constitute the camera position coordinates corresponding to the virtual camera.

[0084] In the specific implementation, the center coordinates coor[x,y] of the minimum circumscribed rectangle rect are used as the plane coordinates of the virtual camera; the default field of view angle fovy of the virtual camera is set, and the long side W of the minimum circumscribed rectangle rect is used as the long side of the transmission transformation of the virtual camera. According to the trigonometric function, tan(fovy / 2)=W / 2 / re_height, so the height of the virtual camera relative to the 3D model surface at this time is re_height = W / (2*tan(fovy / 2)); Make a vertical line segment L1 through the center coordinate coor[x,y] plane coordinates. The starting point of the vertical line segment L1 is L1_P1[coor[x],coor[y],re_height+10000] and the end point is L1_P2[coor[x],coor[y],re_height-10000]; Calculate the spatial intersection of the vertical line segment L1 and the later 3D model Data_last (or the earlier 3D model Data_pre). Since the 3D model is triangulated surface data, there must be an intersection Intersect_P[x,y,z]. Finally, the 3D space coordinates of the virtual camera (that is, the camera position coordinates) are obtained:

[0085] Camera_P[x,y,z] = [coor[x],coor[y],re_height+Intersect_P[z]].

[0086] (3.13) Determine the camera rotation angle corresponding to the virtual camera based on the angle between the long side vectors of the minimum bounding rectangle in the Cartesian coordinate system. In practice, the virtual camera rotation angle Rotate_angle is calculated by calculating the angle α between the long side vectors of the minimum bounding rectangle rect in the first quadrant or β between the long side vectors of the minimum bounding rectangle rect in the second quadrant of the Cartesian coordinate system. Therefore, Rotate_angle = α or Rotate_angle = 90 - β.

[0087] Finally, the virtual camera pose is determined based on the camera position coordinates Camera_P and the camera rotation angle Rotate_angle.

[0088] (3.2) Divide the target region vector into multiple first-differentiable rectangular blocks. In the specific implementation, divide the target vector region V1 into multiple first-differentiable rectangular blocks. With a sufficiently small number of first-differentiable rectangular blocks, the planar area of ​​the target vector region V1 can be approximately fitted. Suppose that the minimum circumscribed matrix rect is differentiated into M rectangles along the long side direction. This value can be dynamically adjusted according to the current area. The smaller the M value, the faster the calculation and the larger the actual error may be. Conversely, the larger the M value, the slower the calculation and the smaller the actual error. Then the side length of each small rectangle is width = W / M, so there are N = int(H / width) + 1 first-differentiable rectangular blocks in the width direction of the minimum circumscribed matrix rect. The total number of first-differentiable rectangular blocks in the entire minimum circumscribed matrix rect is M*N. In actual production, the size of the first-differentiable rectangular blocks is dynamically set according to the target region to control accuracy and efficiency. The larger the M value, the higher the accuracy and the lower the calculation efficiency. Conversely, the lower the accuracy and the higher the efficiency.

[0089] (3.3) Perform elevation differentiable interpolation on the interpolation region vector to generate the interpolation triangulation corresponding to the interpolation region vector. Specifically:

[0090] (3.31) For each boundary point in the boundary point set corresponding to the interpolation region vector, based on the label carried by the interpolation region vector, the intersection point between the vertical line through the boundary point and the early three-dimensional model or the later three-dimensional model is obtained to generate an interpolation point set. The elevation value of the intersection point in the interpolation point set is consistent with the elevation value of its corresponding boundary point.

[0091] In specific implementations, the interpolated 3D data (Data) is determined based on the phase attribute value (also known as the label) of the interpolation region vector V2 feature object. The boundary point set (Interpolation_P_Vec2) of the feature object is read. A vertical line segment is constructed to calculate the 3D intersection between Interpolation_P_Vec2 and Data, generating the interpolation point set (Interpolation_P_Vec3). For example, if the phase attribute value (also known as the label) indicates that the interpolation region vector V2 belongs to the early cut-and-fill phase, the boundary point set (Interpolation_P_Vec2) is intersected with the early 3D model (Data_pre), and the intersection point is added to the interpolation point set (Interpolation_P_Vec3). If the phase attribute value (also known as the label) indicates that the interpolation region vector V2 belongs to the late cut-and-fill phase, the boundary point set (Interpolation_P_Vec2) is intersected with the late 3D model (Data_last), and the intersection point is added to the interpolation point set (Interpolation_P_Vec3).

[0092] (3.32) The interpolation region vector is divided into a plurality of second differentiable rectangular blocks. When the vertices of the second differentiable rectangular blocks fall within the interpolation region vector, the vertices of the second differentiable rectangular blocks are added to the interpolation point set, and the elevation values ​​of the vertices in the interpolation point set are 0.

[0093] In the specific implementation, based on the same minimum circumscribed rectangle differentiation principle as above, the feature object Feature is divided into second differentiable rectangular blocks. If the vertex of the second differentiable rectangular block falls inside the feature object Feature, then the plane coordinates of the point are added to the interpolation point set Interpolation_P_Vec3; at this time, the vertex elevation values ​​of the second differentiable rectangular blocks inside the interpolation point set Interpolation_P_Vec3 are all 0, and the boundary points of the feature object Feature are true values.

[0094] (3.33) Using the elevation values ​​of the intersection points in the interpolation point set, the elevation values ​​of the vertices in the interpolation point set are interpolated to obtain the target interpolation point set.

[0095] In the specific implementation, all points in the interpolation point set Interpolation_P_Vec3 are recursively interpolated. Based on the nearest interpolation, for each point with an elevation value of 0, the three closest points on the plane with non-zero elevation values ​​are found and the average elevation is calculated as the elevation value of this point to obtain the target interpolation point set Interpolation_P_Vec3. The target interpolation point set Interpolation_P_Vec3 includes the elevation value corresponding to each point.

[0096] (3.34) Generate an interpolation triangulation corresponding to the interpolation area vector based on the target interpolation point set.

[0097] In the specific implementation, the points in the target interpolation point set Interpolation_P_Vec3 are finally used to generate an interpolation triangulation node based on the triangulation point-by-point interpolation method. This interpolation triangulation node is used to replace the data within the object feature range at this time to participate in the subsequent excavation and fill volume calculation, thereby removing the influence of interference on the elevation value; the interpolation triangulation node is saved to the collection Interpolation_Map according to the id of the object feature.<id,Node> middle.

[0098] (3.4) Based on the interpolation triangulation corresponding to the first differentiable rectangular block and the interpolation region vector, combined with the previous 3D model and the later 3D model within the virtual camera's field of view, determine the set of excavation and fill volumes corresponding to the target mining area. Specifically, for any first differentiable rectangular block, perform the following operations:

[0099] (3.41) When the center coordinates of the first differentiable rectangular block intersect with the interpolation region vector, based on the label carried by the interpolation region vector, the interpolation triangulation corresponding to the intersecting interpolation region vector is used to update the early three-dimensional model or the late three-dimensional model within the field of view of the virtual camera.

[0100] In the specific implementation, the center point coordinates center[x,y] of the M*N first differentiable rectangular blocks are used as plane coordinates to calculate whether they intersect with the object feature Feature in the interpolation area vector V2. If they intersect, the corresponding interpolation triangulation Node is found from the set Interpolation_Map as Target_Data according to the id of the object feature Feature. According to the attribute phase value (that is, the label), it is determined whether Target_Data replaces the early three-dimensional model Data_pre or the later three-dimensional model Data_last to participate in the calculation.

[0101] In one case, if the label indicates that the interpolation region vector belongs to the cut-fill front, the interpolation triangulation corresponding to the intersecting interpolation region vector is used to replace the portion corresponding to the interpolation region vector in the previous 3D model Data_pre within the field of view of the virtual camera.

[0102] In another case, if the label indicates that the interpolation region vector belongs to the cut-fill area, the interpolation triangulation corresponding to the intersecting interpolation region vector is used to replace the portion corresponding to the interpolation region vector in the later 3D model Data_last within the field of view of the virtual camera.

[0103] (3.42) Determine the intersection points of a perpendicular line passing through the center coordinates of the first differentiable rectangular block with the updated early three-dimensional model and the updated late three-dimensional model, respectively, to determine the volume difference corresponding to the first differentiable rectangular block.

[0104] In the specific implementation, the vertical line segment L2 is constructed with the center point coordinate center of the first differentiable rectangular block. The starting point of the vertical line segment L2 is L2_P1[coor[x],coor[y],re_height+10000] and the end point is L2_P2[coor[x],coor[y],re_height-10000]; the intersection calculation is performed to obtain the intersection point Intersect_pre[x,y,z] with the previous three-dimensional model Data_pre and the intersection point Intersect_last[x,y,z] with the later three-dimensional model Data_last; the volume difference v_dis = (Intersect_pre[z]-Intersect_last[z])*width*width between the two three-dimensional models of the first differentiable rectangular block is calculated at this time.

[0105] (3.43) Based on the positive or negative nature of the volume difference, the volume difference is saved in the excavation volume set or the fill volume set.

[0106] In specific implementation, if the volume difference v_dis>0, then the value is saved in the excavation volume set W_vec and accumulated to the total excavation volume value W_sum; if the volume difference v_dis<0, then the value is saved in the fill volume set T_vec and accumulated to the total fill volume value T_sum.

[0107] Finally, output the results to the console or to a csv format file as needed.

[0108] (IV) 3D rendering and display, see Figure 5 The diagram below shows a three-dimensional rendering and display process, which includes operations such as performing range distribution statistics and color band color calculation based on cut and fill volumes to produce cut and fill volume rendering results. Considering that in actual work, simply outputting the total cut and fill volume is not sufficient to effectively determine and analyze key cut and fill volume issues and the overall distribution of actual cut and fill volumes, this step uses the cut and fill volume values ​​calculated by differential calculation to render them in three dimensions. The specific implementation includes the following (4.1) to (4.4):

[0109] (4.1) Determine the maximum and minimum excavation volume values ​​in the excavation volume set, and determine the maximum and minimum fill volume values ​​in the fill volume set.

[0110] In specific implementation, the excavation volume set W_vec and the filling volume set T_vec are circulated to find the maximum and minimum values ​​of the excavation and filling sets respectively, including: the minimum excavation volume value W_min, the maximum excavation volume value W_max, the minimum filling volume value T_min, and the maximum filling volume value T_max.

[0111] (4.2) Divide the specified color band into a first sub-color band and a second sub-color band.

[0112] In the specific implementation, Turbo color band is used for shading rendering. The length of Turbo color band is 256, the colors at both ends are darker, and the color in the middle is lighter. The cut rendering is obtained from the first 128 colors of the color band (that is, the first sub-color band). The larger the cut value, the darker the color and the smaller the color band index value. The fill rendering is obtained from the last 128 colors of the color band (that is, the second sub-color band). The larger the fill value, the darker the color and the larger the color band index value.

[0113] (4.3) Determine the rendering step length of the excavation based on the maximum excavation volume value and the minimum excavation volume value, and determine the mapping relationship between the excavation volume values ​​in the excavation volume set and the color band index in the first sub-color band based on the rendering step length of the excavation; and determine the rendering step length of the fill based on the maximum fill volume value and the minimum fill volume value, and determine the mapping relationship between the fill volume values ​​in the fill volume set and the color band index in the second sub-color band based on the rendering step length of the fill.

[0114] In the specific implementation, the rendering step length W_step of the cut is calculated as (W_max-W_min) / 128, and the rendering step length T_step of the fill is calculated as (T_max-T_min) / 128; the actual rendering color of the cut is obtained by looping the cut volume set W_vec to obtain the current cut value W_Value, calculating the rendering color band index W_color_index = 127-int((W_Value-W_min) / W_step), and then obtaining the cut color W_color = Turbo[W_color_index]; the actual rendering color of the fill is obtained by looping the fill volume set T_vec to obtain the current cut value T_Value, calculating the rendering color band index T_color_index = 128+int((T_Value-T_min) / T_step), and then obtaining the fill color T_color = Turbo[T_color_index].

[0115] (4.4) Rendering is performed based on the mapping relationship to obtain the rendering results of the excavation and filling volume corresponding to the target mining area.

[0116] In the specific implementation, the excavation and filling volume rendering result is created in the three-dimensional space, and the front and rear intersection points, the differential side length width, and the current color W_color or T_color are used to draw a three-dimensional cube to render the overall excavation and filling volume.

[0117] The embodiment of the present invention provides a specific application example of three-dimensional coal mine area earthwork volume calculation based on drone tilt data:

[0118] First, the experimental area, covering approximately 1.6 square kilometers, employed a CW-25E fixed-wing drone equipped with a CA504R full-frame, five-lens oblique aerial camera. Each camera achieved a resolution of 61 megapixels, with a total resolution of 305 million pixels. Without phased array control, the CA504R's ground resolution was as low as 1.5 cm, enabling the generation of high-precision 3D models within 10 cm. After planning the route and setting relevant flight parameters at the ground station, the drone automatically flew, collected data, and monitored its status in real time. The resulting data included photos captured by the five cameras and pose data from the downward-looking camera. This embodiment of the present invention employed domestically produced GodWork software for real-world 3D reconstruction and DOM output. The initial 3D reconstruction took approximately 23 hours, while the subsequent 3D reconstruction took approximately 25 hours. After reconstruction, the resulting 3D data was loaded for height comparison. By fine-tuning the height values ​​of the offset matrix in the 3D data, the roads from the two phases of data were aligned to a consistent height.

[0119] Then, the embodiment of the present invention directly uses DOM data to collect target area vectors and interpolation area vectors, uses ArcMap to create shape vectors and draw vector areas according to needs; since the vector results at this time are two-dimensional, a default uniform height needs to be initialized when loaded into three-dimensional space.

[0120] Next, load the previous and later 3D models, the target area vector, and the interpolation area vector into the 3D space. First, calculate and adjust the viewing angle of the virtual camera to ensure that the overall situation of the current target area vector can be observed. Then, calculate the interpolation area vector to fit the interpolation triangulation network. Finally, calculate the actual cut and fill results based on the differentiable rectangular blocks. The cut volume value is 2219.831050, and the fill volume value is 2205.940127.

[0121] Finally, use the Turbo color band to render evenly based on the cut and fill results. At the same time, turn off the nodes that display the front and back three-dimensional data and vector data. Only the rendering effect of the cut and fill calculation results is displayed, so that the distribution of the cut and fill results can be observed intuitively.

[0122] Based on the above embodiments, the present invention provides a three-dimensional coal mine area earthwork volume calculation device based on drone tilt data, see Figure 6 The following is a schematic diagram of a three-dimensional coal mine area earthwork calculation device based on drone tilt data. The device mainly includes the following parts:

[0123] The data acquisition module 602 is used to acquire the early three-dimensional model and its corresponding early DOM data, and the late three-dimensional model and its corresponding late DOM data of the target mining area before and after filling and cutting based on the UAV tilt data;

[0124] The vector extraction module 604 is used to extract the target area vector and the interpolation area vector corresponding to the target mining area based on the early DOM data and the late DOM data. The target area vector is the area where the cut and fill volume is to be calculated, and the interpolation area vector is the sub-area where the ground interference exists within the area where the cut and fill volume is to be calculated.

[0125] The earthwork volume calculation module 606 is used to perform differentiable block calculation of earthwork volume based on the target area vector and the interpolation area vector, combined with the early 3D model and the late 3D model, to obtain the excavation volume set and the fill volume set corresponding to the target mining area;

[0126] The earthwork volume rendering module 608 is used to render and draw according to the excavation volume set and the fill volume set to obtain the excavation and fill volume rendering results corresponding to the target mining area.

[0127] The embodiment of the present invention provides a three-dimensional coal mine area earthwork calculation device based on drone tilt data. The drone-based tilt modeling scheme can quickly and efficiently acquire and process data. Compared with traditional field measurement schemes and other calculation methods, the two-dimensional result display is transferred to the three-dimensional model. The present invention improves the controllability of the calculation scale based on the previous and next three-dimensional models, and the interpolation area vector solves the influence of interference objects, realizes the visualization rendering of the excavation and filling earthwork calculation results, and more efficiently and intuitively reflects the scale, process and final result of the calculation, ultimately effectively improving the planning and management level of coal mine areas, enhancing cost control and economic benefit evaluation, providing strong support for the audit work of mining areas, etc., and promoting the innovative application of drone surveying and mapping technology in the coal mining industry.

[0128] In one embodiment, the earthwork volume calculation module 606 is specifically configured to:

[0129] Determine the virtual camera pose according to the target area vector, and control the virtual camera to adjust its pose according to the virtual camera pose so that the virtual camera faces the early 3D model and the late 3D model;

[0130] Divide the target area vector into a plurality of first differentiable rectangular blocks;

[0131] Perform elevation differentiable interpolation on the interpolation area vector to generate an interpolation triangulation network corresponding to the interpolation area vector;

[0132] Based on the interpolation triangulation corresponding to the first differentiable rectangular block and the interpolation area vector, combined with the early 3D model and the later 3D model within the field of view of the virtual camera, the excavation volume set and the fill volume set corresponding to the target mining area are determined.

[0133] In one embodiment, the virtual camera pose includes camera position coordinates and camera rotation angle; the earthwork volume calculation module 606 is specifically used to:

[0134] Determine the minimum bounding rectangle corresponding to the target area vector;

[0135] The center coordinates of the minimum circumscribed rectangle are used as the plane coordinates of the virtual camera; and the height coordinates of the virtual camera are obtained based on the intersection of a perpendicular line passing through the center coordinates and the early 3D model or the late 3D model; the plane coordinates and the height coordinates constitute the camera position coordinates corresponding to the virtual camera;

[0136] The camera rotation angle corresponding to the virtual camera is determined based on the angle between the long side vectors of the minimum circumscribed rectangle in the Cartesian coordinate system.

[0137] In one embodiment, the interpolation region vector carries a label, which is used to indicate whether the interpolation region vector belongs to before or after filling and cutting. The earthwork volume calculation module 606 is specifically configured to:

[0138] For each boundary point in the boundary point set corresponding to the interpolation region vector, based on the label carried by the interpolation region vector, the intersection point between the vertical line through the boundary point and the previous 3D model or the later 3D model is obtained to generate an interpolation point set. The elevation value of the intersection point in the interpolation point set is consistent with the elevation value of the corresponding boundary point.

[0139] Divide the interpolation region vector into a plurality of second differentiable rectangular blocks, and when the vertices of the second differentiable rectangular blocks fall within the interpolation region vector, add the vertices of the second differentiable rectangular blocks to the interpolation point set, and the elevation values ​​of the vertices in the interpolation point set are 0;

[0140] Using the elevation values ​​of the intersection points in the interpolation point set, the elevation values ​​of the vertices in the interpolation point set are interpolated to obtain the target interpolation point set;

[0141] Generate an interpolation triangulation corresponding to the interpolation area vector based on the target interpolation point set.

[0142] In one embodiment, the earthwork volume calculation module 606 is specifically configured to:

[0143] For any first differentiable rectangular block, perform the following operations:

[0144] When the center coordinates of the first differentiable rectangular block intersect the interpolation region vector, based on the label carried by the interpolation region vector, the interpolation triangulation corresponding to the intersecting interpolation region vector is used to update the early three-dimensional model or the late three-dimensional model within the field of view of the virtual camera;

[0145] Determine the intersection points of a perpendicular line passing through the center coordinates of the first differentiable rectangular block with the updated early three-dimensional model and the updated late three-dimensional model, respectively, to determine the volume difference corresponding to the first differentiable rectangular block;

[0146] Based on the positive or negative value of the volume difference, the volume difference is saved in the cut volume collection or the fill volume collection.

[0147] In one embodiment, the earthwork volume calculation module 606 is specifically configured to:

[0148] If the label indicates that the interpolation region vector belongs to the front of the cut-filling process, the interpolation triangulation corresponding to the intersecting interpolation region vector is used to replace the portion corresponding to the interpolation region vector in the previous 3D model within the field of view of the virtual camera;

[0149] If the label indicates that the interpolation region vector belongs to the cut-fill area, the interpolation triangulation corresponding to the intersecting interpolation region vector is used to replace the portion corresponding to the interpolation region vector in the later three-dimensional model within the field of view of the virtual camera.

[0150] In one embodiment, the earthwork volume rendering module 608 is specifically configured to:

[0151] Determine the maximum excavation volume value and the minimum excavation volume value in the excavation volume set, and determine the maximum fill volume value and the minimum fill volume value in the fill volume set;

[0152] Divide the specified color band into a first sub-color band and a second sub-color band;

[0153] Determining a rendering step length for the cut volume based on the maximum cut volume value and the minimum cut volume value, and determining a mapping relationship between the cut volume values ​​in the cut volume set and the color band indexes in the first sub-color band based on the rendering step length for the cut volume; and determining a rendering step length for the fill volume based on the maximum fill volume value and the minimum fill volume value, and determining a mapping relationship between the fill volume values ​​in the fill volume set and the color band indexes in the second sub-color band based on the rendering step length for the fill volume;

[0154] Rendering is performed based on the mapping relationship to obtain the rendering results of the excavation and filling volume corresponding to the target mining area.

[0155] In one embodiment, the data acquisition module 602 is specifically configured to:

[0156] Determine the same reference ground feature point and its corresponding early elevation value and late elevation value from the early 3D model and the late 3D model;

[0157] Determine the offset matrix based on the early elevation value and the late elevation value corresponding to the reference feature point;

[0158] The offset matrix is ​​used to fine-tune the early 3D model and the late 3D model so that the early elevation value and the late elevation value corresponding to the same reference feature point coincide with each other.

[0159] The device provided in the embodiment of the present invention has the same implementation principle and technical effects as those in the aforementioned method embodiment. For the sake of brief description, for matters not mentioned in the device embodiment, reference can be made to the corresponding content in the aforementioned method embodiment.

[0160] An embodiment of the present invention provides an electronic device. Specifically, the electronic device includes a processor and a memory. The memory stores a computer program, and when the computer program is executed by the processor, it executes the method described in any one of the above-mentioned embodiments.

[0161] Figure 7 A structural diagram of an electronic device provided in an embodiment of the present invention, the electronic device 100 includes: a processor 70, a memory 71, a bus 72 and a communication interface 73, wherein the processor 70, the communication interface 73 and the memory 71 are connected via the bus 72; the processor 70 is used to execute an executable module stored in the memory 71, such as a computer program.

[0162] Memory 71 may include high-speed random access memory (RAM) and may also include non-volatile memory, such as at least one disk storage. Communication between the system network element and at least one other network element is achieved through at least one communication interface 73 (which may be wired or wireless), and may utilize the Internet, a wide area network, a local area network, a metropolitan area network, or the like.

[0163] The bus 72 may be an ISA bus, a PCI bus, or an EISA bus. The bus may be divided into an address bus, a data bus, a control bus, and the like. For ease of representation, Figure 7 Only one bidirectional arrow is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0164] Among them, the memory 71 is used to store programs, and the processor 70 executes the program after receiving the execution instruction. The method executed by the device for flow process definition disclosed in any embodiment of the above-mentioned embodiment of the present invention can be applied to the processor 70 or implemented by the processor 70.

[0165] The processor 70 may be an integrated circuit chip with signal processing capabilities. During implementation, the steps of the above-described method may be performed by hardware integrated logic circuits or software instructions within the processor 70. The processor 70 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It may implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of the present invention. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in conjunction with the embodiments of the present invention may be directly implemented and executed by a hardware decoding processor, or by a combination of hardware and software modules within the decoding processor. The software modules may be located in storage media well-known in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or the like. The storage medium is located in the memory 71 , and the processor 70 reads the information in the memory 71 and completes the steps of the above method in combination with its hardware.

[0166] The computer program product of the readable storage medium provided in the embodiment of the present invention includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the method described in the previous method embodiment. The specific implementation can be referred to the previous method embodiment and will not be repeated here.

[0167] If the functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage media include various media capable of storing program code, such as USB flash drives, mobile hard drives, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.

[0168] Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the above-described embodiments, those skilled in the art should understand that any person skilled in the art can modify or easily conceive of changes to the technical solutions described in the above-described embodiments within the technical scope disclosed by the present invention, or replace some of the technical features therein with equivalents. Such modifications, changes, or replacements do not deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be subject to the scope of protection of the claims.

Claims

1. A three-dimensional coal mine area earthwork calculation method based on drone tilt data, characterized in that: include: Based on the UAV tilt data, the target mining area is obtained before and after the filling and excavation of the early three-dimensional model and its corresponding early DOM data, and the late three-dimensional model and its corresponding late DOM data; Extracting a target region vector and an interpolation region vector corresponding to the target mining area based on the early DOM data and the late DOM data, wherein the target region vector is a region for which the cut and fill volume is to be calculated, and the interpolation region vector is a subregion within the region for which the cut and fill volume is to be calculated where ground interferences exist; Based on the target area vector and the interpolation area vector, in combination with the early three-dimensional model and the late three-dimensional model, a differentiable block calculation of earthwork volume is performed to obtain a set of excavation volumes and a set of fill volumes corresponding to the target mining area; Rendering is performed according to the excavation volume set and the fill volume set to obtain an excavation and fill volume rendering result corresponding to the target mining area; Based on the target area vector and the interpolation area vector, in combination with the early three-dimensional model and the late three-dimensional model, a differentiable block calculation of the earthwork volume is performed to obtain a set of excavation volume and a set of filling volume corresponding to the target mining area, including: determining a virtual camera pose according to the target area vector, controlling the virtual camera to adjust its pose according to the virtual camera pose so that the virtual camera faces the early three-dimensional model and the late three-dimensional model; dividing the target area vector into a plurality of first differentiable rectangular blocks; performing elevation differentiable interpolation on the interpolation area vector to generate an interpolation triangulation network corresponding to the interpolation area vector; based on the first differentiable rectangular blocks and the interpolation triangulation network corresponding to the interpolation area vector, in combination with the early three-dimensional model and the late three-dimensional model within the field of view of the virtual camera, determining a set of excavation volume and a set of filling volume corresponding to the target mining area; The virtual camera pose includes camera position coordinates and camera rotation angle; determining the virtual camera pose according to the target area vector includes: determining the minimum circumscribed rectangle corresponding to the target area vector; using the center coordinates of the minimum circumscribed rectangle as the plane coordinates of the virtual camera; and obtaining the height coordinates of the virtual camera based on the intersection of the perpendicular line through the center coordinates and the early three-dimensional model or the late three-dimensional model; the plane coordinates and the height coordinates constitute the camera position coordinates corresponding to the virtual camera; determining the camera rotation angle corresponding to the virtual camera based on the angle between the long side vector of the minimum circumscribed rectangle and the Cartesian coordinate system.

2. The three-dimensional coal mine area earthwork volume calculation method based on drone tilt data according to claim 1 is characterized in that: The interpolation region vector carries a label, and the label is used to indicate whether the interpolation region vector belongs to before cut-fill or after cut-fill. The interpolation region vector is subjected to elevation differentiable interpolation to generate an interpolation triangulation network corresponding to the interpolation region vector, including: For each boundary point in the boundary point set corresponding to the interpolation region vector, based on the label carried by the interpolation region vector, obtain an intersection point between a perpendicular line through the boundary point and the early 3D model or the late 3D model to generate an interpolation point set, wherein the elevation value of the intersection point in the interpolation point set is consistent with the elevation value of the corresponding boundary point; Divide the interpolation region vector into a plurality of second differentiable rectangular blocks, and when vertices of the second differentiable rectangular blocks fall within the interpolation region vector, add the vertices of the second differentiable rectangular blocks to the interpolation point set, and the elevation values ​​of the vertices in the interpolation point set are 0; Using the elevation values ​​of the intersection points in the interpolation point set, interpolate the elevation values ​​of the vertices in the interpolation point set to obtain a target interpolation point set; An interpolation triangulation corresponding to the interpolation region vector is generated based on the target interpolation point set.

3. The three-dimensional coal mine area earthwork volume calculation method based on drone tilt data according to claim 2 is characterized in that: Determining a set of excavation volumes and a set of fill volumes corresponding to the target mining area based on the interpolation triangulation corresponding to the first differentiable rectangular block and the interpolation region vector and combining the early three-dimensional model and the late three-dimensional model within the field of view of the virtual camera, including: For any of the first differentiable rectangular blocks, perform the following operations: When the center coordinates of the first differentiable rectangular block intersect the interpolation region vector, based on the label carried by the interpolation region vector, the interpolation triangulation corresponding to the intersecting interpolation region vector is used to update the early three-dimensional model or the late three-dimensional model within the field of view of the virtual camera; Determine the intersection points of a perpendicular line passing through the center coordinates of the first differentiable rectangular block with the updated early three-dimensional model and the updated late three-dimensional model, respectively, to determine the volume difference corresponding to the first differentiable rectangular block; Based on the positive or negative nature of the volume difference, the volume difference is saved in an excavation volume set or a fill volume set.

4. The three-dimensional coal mine area earthwork volume calculation method based on drone tilt data according to claim 3 is characterized in that: Based on the label carried by the interpolation region vector, the interpolation triangulation corresponding to the intersecting interpolation region vector is used to update the early three-dimensional model or the late three-dimensional model within the field of view of the virtual camera, including: If the label indicates that the interpolation region vector belongs to the front of the cut-filling process, the interpolation triangulation corresponding to the interpolation region vector is used to replace the portion of the previous three-dimensional model within the field of view of the virtual camera corresponding to the interpolation region vector; If the label indicates that the interpolation region vector belongs to cut-fill, the interpolation triangulation corresponding to the intersecting interpolation region vector is used to replace the portion corresponding to the interpolation region vector in the later three-dimensional model within the field of view of the virtual camera.

5. The three-dimensional coal mine area earthwork volume calculation method based on drone tilt data according to claim 3 is characterized in that: Rendering is performed according to the excavation volume set and the fill volume set to obtain an excavation and fill volume rendering result corresponding to the target mining area, including: Determine the maximum excavation volume value and the minimum excavation volume value in the excavation volume set, and determine the maximum fill volume value and the minimum fill volume value in the fill volume set; Divide the specified color band into a first sub-color band and a second sub-color band; Determining a rendering step length for the cut volume based on the maximum cut volume value and the minimum cut volume value, and determining a mapping relationship between cut volume values ​​in the cut volume set and color band indexes in the first sub-color band based on the rendering step length for the cut volume; and determining a rendering step length for the fill volume based on the maximum fill volume value and the minimum fill volume value, and determining a mapping relationship between fill volume values ​​in the fill volume set and color band indexes in the second sub-color band based on the rendering step length for the fill volume; Rendering is performed based on the mapping relationship to obtain a rendering result of the excavation and filling volume corresponding to the target mining area.

6. The three-dimensional coal mine area earthwork volume calculation method based on drone tilt data according to claim 1 is characterized in that: After obtaining the early three-dimensional model and corresponding early DOM data, and the late three-dimensional model and corresponding late DOM data of the target mining area before and after filling and cutting based on the UAV tilt data, the method further includes: Determining the same reference feature point and its corresponding early elevation value and late elevation value from the early three-dimensional model and the late three-dimensional model; Determining an offset matrix based on the early elevation value and the late elevation value corresponding to the reference feature point; The early three-dimensional model and the late three-dimensional model are fine-tuned using the offset matrix so that the early elevation value and the late elevation value corresponding to the same reference feature point coincide with each other.

7. A three-dimensional coal mine area earthwork calculation device based on drone tilt data, characterized in that: include: The data acquisition module is used to obtain the early three-dimensional model and its corresponding early DOM data, and the late three-dimensional model and its corresponding late DOM data of the target mining area before and after filling and excavation based on the UAV tilt data; A vector extraction module is configured to extract a target area vector and an interpolation area vector corresponding to the target mining area based on the early DOM data and the late DOM data, wherein the target area vector is the area for which the cut and fill volume is to be calculated, and the interpolation area vector is the sub-area within the area for which the cut and fill volume is to be calculated where ground interferences exist; an earthwork volume calculation module, configured to perform differentiable block calculation of earthwork volume based on the target area vector and the interpolation area vector, in combination with the early three-dimensional model and the late three-dimensional model, to obtain a set of excavation volumes and a set of fill volumes corresponding to the target mining area; an earthwork volume rendering module, configured to render and draw according to the excavation volume set and the fill volume set, and obtain an excavation and fill volume rendering result corresponding to the target mining area; The earthwork volume calculation module is specifically configured to: determine a virtual camera pose according to the target area vector, and control the virtual camera to adjust its pose according to the virtual camera pose so that the virtual camera faces the early three-dimensional model and the late three-dimensional model; divide the target area vector into a plurality of first differentiable rectangular blocks; perform elevation differentiable interpolation on the interpolation area vector to generate an interpolation triangulation network corresponding to the interpolation area vector; determine an excavation volume set and a fill volume set corresponding to the target mining area based on the first differentiable rectangular blocks and the interpolation triangulation network corresponding to the interpolation area vector, in combination with the early three-dimensional model and the late three-dimensional model within the field of view of the virtual camera; The virtual camera pose includes camera position coordinates and camera rotation angle; the earthwork volume calculation module is specifically used to: determine the minimum circumscribed rectangle corresponding to the target area vector; use the center coordinates of the minimum circumscribed rectangle as the plane coordinates of the virtual camera; and obtain the height coordinates of the virtual camera based on the intersection of the perpendicular line through the center coordinates and the early three-dimensional model or the late three-dimensional model; the plane coordinates and the height coordinates constitute the camera position coordinates corresponding to the virtual camera; based on the angle between the long side vector of the minimum circumscribed rectangle and the Cartesian coordinate system, determine the camera rotation angle corresponding to the virtual camera.

8. An electronic device, characterized in that: The method comprises a processor and a memory, wherein the memory stores computer-executable instructions that can be executed by the processor, and the processor executes the computer-executable instructions to implement the method according to any one of claims 1 to 6.

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