A mine surveying and mapping method and system based on unmanned aerial vehicle remote sensing technology

Abstract

The present invention relates to the field of mine surveying and mapping technology, and in particular to a mine surveying and mapping method and system based on unmanned aerial vehicle remote sensing technology, the method comprising: obtaining terrain data of a mine; generating a flight trajectory of an unmanned aerial vehicle; using an unmanned aerial vehicle to collect image data and hyperspectral data of the mine; constructing a three-dimensional surface model of the mine; obtaining geological structure data and mineral distribution data of the mine; and generating a three-dimensional structural model of the mine based on the geological structure data, mineral distribution data and the three-dimensional surface model. The present invention generates a flight trajectory of an unmanned aerial vehicle to ensure that the unmanned aerial vehicle takes photos at a reasonable flight altitude and speed in different areas, thereby reducing repeated coverage and maximizing regional coverage. By generating a three-dimensional structural model, detailed geological structure and mineral distribution data can be obtained without actually entering the mining area, greatly reducing the safety risks and economic costs that may be caused by on-site surveys.

Description

Technical Field

[0001] The present invention relates to the technical field of mine surveying and mapping, and in particular to a mine surveying and mapping method and system based on unmanned aerial vehicle remote sensing technology. Background Art

[0002] Mine mapping can provide information such as the distribution, grade, and reserves of mineral deposits in the mining area, which is helpful for the evaluation of mineral resources and the analysis of their potential economic value. By obtaining detailed topographic data and geological structure information of the mining area, we can understand the geomorphological characteristics, geological structure, and evolution history of the mining area. It is of great significance to judge the morphology, distribution, and feasibility of mining of the ore body. Mine mapping can reveal potential safety hazards, such as risk areas of geological disasters such as landslides and collapses, which helps to formulate preventive measures and improve the safety of mining operations. At the same time, by monitoring the mining environment, we can promptly discover sudden problems and take countermeasures. Through in-depth understanding of the mine topography and geology, we support reasonable mining design and route planning, optimize resource mining processes, reduce costs, and improve efficiency.

[0003] Traditional mine surveying methods often rely on manual operations, slow data collection speed and limited coverage. Ground surveying requires surveyors to measure point by point on site, which is not only time-consuming and labor-intensive, but also difficult to ensure full data coverage in large mining areas. On-site exploration often requires personnel to conduct actual surveying work in mines or potentially dangerous areas, increasing safety risks. Summary of the invention

[0004] The present invention provides a mine surveying and mapping method and system based on unmanned aerial vehicle remote sensing technology, which are used to solve the defects existing in the prior art.

[0005] On the one hand, the present invention provides a mine surveying and mapping method based on UAV remote sensing technology, comprising: S1. Use geographic information system to obtain the terrain data of the target mine.

[0006] S2. Select a drone equipped with a high-resolution camera and a hyperspectral imager to collect image data and hyperspectral data of the target mine, and generate a flight trajectory of the drone based on the collection range of the image data and hyperspectral data.

[0007] S3. Use the drone to collect image data and hyperspectral data of the target mine according to the drone's flight trajectory.

[0008] S4. Construct a three-dimensional surface model of the target mine based on the image data, including: S41, performing Gaussian filtering to remove noise on the image data, using an accelerated robust feature algorithm to extract feature points of the image, and matching adjacent images through a feature matching algorithm.

[0009] S42. A method based on structured light motion is used to restore the camera pose and scene structure of the image, a multi-view stereo algorithm is used to generate a point cloud, and triangulation and meshing optimization are performed to construct a three-dimensional surface model of the target mine.

[0010] S5. Process and analyze the hyperspectral data to obtain the geological structure data and mineral distribution data of the target mine.

[0011] S6. Based on the geological structure data and mineral distribution data, combined with the three-dimensional surface model, a three-dimensional structural model of the target mine is obtained.

[0012] According to a mine mapping method based on drone remote sensing technology provided by the present invention, in step S1, the terrain data includes terrain elevation data, surface feature data, spatial coordinate data and geological background data. The terrain elevation data is used to describe the terrain undulations, slopes and distribution of rivers and lakes of the target mine. The surface feature data is used to describe the surface type distribution information of the target mine, including vegetation, exposed rocks and soil. The spatial coordinate data is used to determine the coordinate information of the target mine, and the coordinate information includes the boundary coordinates and feature coordinates of the target mine. The geological background data is used to provide the geological map and mineral resource information of the target mine based on historical data. The geological map includes geological structure, rock type and distribution. Mineral resource information includes mineral distribution data and ore body location data.

[0013] According to a mine surveying and mapping method based on UAV remote sensing technology provided by the present invention, in step S2, the process of generating the UAV flight trajectory includes: Obtain performance parameters for high-resolution cameras and hyperspectral imagers, and set resolution requirements for image data.

[0014] According to the performance parameters and resolution requirements of the high-resolution camera, the optimal flight height is calculated, and the formula is expressed as: ; In the formula, represents the focal length of the high-resolution camera, Indicates the resolution requirement of the image data, Represents the pixel size of a high-resolution camera.

[0015] Calculate the ground sampling distance, the formula is expressed as: ; In the formula, represents the pixel size of the high-resolution camera, and H represents the optimal flying height.

[0016] According to the performance parameters of the high-resolution camera and the hyperspectral imager, combined with the comprehensive actual coverage ground distance, the heading overlap rate and the side overlap rate are calculated. The formula is expressed as follows: ; ; In the formula, represents the heading overlap rate, GSD represents the ground sampling distance, represents the horizontal field of view of the high-resolution camera, represents the horizontal field of view of the hyperspectral imager, Indicates the comprehensive actual coverage ground distance, represents the heading overlap ratio, represents the vertical field of view of the high-resolution camera, Represents the vertical field of view of the hyperspectral imager.

[0017] Calculate the real-time flight speed of the drone, the formula is expressed as: , ; In the formula, Indicates the maximum flight speed of the drone. Indicates the maximum frame rate of a high-resolution camera, represents the exposure time of the high-resolution camera, represents the maximum frame rate of the hyperspectral imager, Represents the exposure time of the hyperspectral imager.

[0018] The maximum length and width of the target mine are obtained according to the terrain data, and the number of rows and columns of the UAV flight trajectory is calculated. The formula is expressed as: ; ; In the formula, The number of rows representing the flight trajectory of the drone, Indicates the maximum width of the target mine, The number of columns representing the flight trajectory of the drone, Indicates the maximum length of the target mine.

[0019] According to a mine mapping method based on UAV remote sensing technology provided by the present invention, in step S41, Gaussian filtering and denoising are performed on the image data, and the formula is expressed as: ; Where x and y represent the pixel coordinates in the image data. and represent the standard deviation in the x and y directions respectively.

[0020] The accelerated robust feature algorithm is used to construct an enhanced Hessian matrix to extract feature points in image data. The enhanced Hessian matrix is ​​expressed as: ; Where, L xx , L xy , L yy Represents the second-order partial derivative of the image data, L xxx , L xxy , L yyy represents the third-order partial derivative of the image, represents a specific scale parameter, Represents the enhancement factor.

[0021] Based on the feature points of the image data, a feature vector of adjacent image data is constructed.

[0022] The feature vectors are matched by a feature matching algorithm based on deep learning to obtain matching feature point pairs. The formula for calculating matching feature point pairs is expressed as: ; In the formula, and represents the feature vector extracted from adjacent image data, Representation vector and The dot product of represents the magnitude of a vector, Represents a very small positive number to prevent the denominator from being zero.

[0023] According to a mine surveying and mapping method based on UAV remote sensing technology provided by the present invention, in step S42, a method based on structured light motion is adopted to restore the camera pose and scene structure of the image, including: By taking images of the calibration plate at different angles, the high-resolution camera intrinsic parameter matrix is ​​solved using the correspondence between the image coordinates and world coordinates of the checkerboard corner points.

[0024] Using the matched feature point pairs, the fundamental matrix is ​​calculated by the normalized eight-point method.

[0025] The intrinsic matrix is ​​calculated by combining the high-resolution camera intrinsic parameter matrix.

[0026] Perform singular value decomposition on the essential matrix to obtain the initial rotation matrix and translation vector of the high-resolution camera.

[0027] The fundamental matrix is ​​optimized using the modified epipolar constraint equation.

[0028] The rotation matrix and translation vector are adjusted by minimizing the reprojection error algorithm.

[0029] According to a mine surveying and mapping method based on UAV remote sensing technology provided by the present invention, in step S42, the process of generating a point cloud using a multi-view stereo algorithm includes: A semi-global matching algorithm is used to calculate the matching feature point pairs between adjacent image data, and the position difference of the same 3D point in adjacent image data is obtained as the disparity.

[0030] The depth value of each pixel in the image data is calculated based on the disparity.

[0031] Convert each pixel in the image data into point coordinates in three-dimensional space.

[0032] According to a mine surveying and mapping method based on UAV remote sensing technology provided by the present invention, in step S42, the triangulation and grid optimization process includes: The generated point cloud is converted into a triangle mesh using a triangulation algorithm based on topology optimization.

[0033] Minimize the energy function of triangulation to make the triangle mesh regular and smooth.

[0034] The objective function is used to iteratively optimize the triangular mesh and adjust the vertex positions of the triangular mesh until the preset number of iterations is reached to obtain a three-dimensional surface model.

[0035] According to a mine surveying and mapping method based on UAV remote sensing technology provided by the present invention, the process of processing and analyzing hyperspectral data includes: Perform median filtering on the hyperspectral data.

[0036] According to the terrain data, a relationship model between terrain and spectral response is constructed to correct the spectral deviation.

[0037] The non-negative matrix factorization algorithm is used to perform spectral decomposition on the corrected spectral data to obtain the distribution data of minerals in the target mine.

[0038] The spectral absorption characteristic analysis is used to calculate the first-order derivative and second-order derivative of the spectrum at different wavelengths, and the peak and valley values ​​of the first-order derivative and second-order derivative of the spectrum are analyzed to obtain the geological structure data.

[0039] According to a mine surveying and mapping method based on UAV remote sensing technology provided by the present invention, in step S6, the process of obtaining a three-dimensional structure model includes: The geological structure data and the mineral distribution data are standardized to obtain the geological structure standardized data and the mineral distribution standardized data.

[0040] The geological structure data vector is constructed based on the geological structure standardized data. The mineral distribution data vector is constructed based on the mineral distribution standardized data.

[0041] For each vertex in the three-dimensional surface model, the corresponding texture coordinates are set and the fused feature values ​​of each vertex are calculated.

[0042] Using a physically based rendering model, the color is calculated for each vertex.

[0043] On the other hand, the present invention also provides a mine surveying and mapping system based on UAV remote sensing technology, comprising: Geographic information integration module, used to integrate and analyze geographic information data of target mines.

[0044] The flight planning module is used to configure the UAV platform and data acquisition equipment and generate the flight trajectory.

[0045] The data acquisition module is used to enable the UAV to fly according to the flight trajectory and collect image data and hyperspectral data in real time.

[0046] The data processing module is used to construct a three-dimensional surface model of the target mine based on the image data.

[0047] Hyperspectral data analysis module is used to process hyperspectral data and extract geological structure and mineral distribution data.

[0048] The 3D structural model building module is used to combine geological structure data, mineral distribution data and 3D surface model to generate a 3D structural model of the target mine.

[0049] The invention provides a mine mapping method and system based on unmanned aerial vehicle remote sensing technology. By acquiring terrain data, combining unmanned aerial vehicle performance and data acquisition equipment parameters, the flight trajectory of the unmanned aerial vehicle is generated to ensure that the unmanned aerial vehicle is photographed at a reasonable flight height and speed in different areas, thereby maximizing the regional coverage. Reduce repeated coverage during data acquisition and avoid data redundancy caused by multiple shots of the same area. Reduce the computational burden during data processing, improve overall efficiency, and fully present the terrain and characteristics of the mine to the greatest extent. Through precise flight planning, it can be ensured that the target mine is fully covered when collecting images and hyperspectral data. At the same time, a comprehensive and reasonable flight path can capture image data at different angles and under different lighting conditions, laying the foundation for the subsequent generation of high-quality three-dimensional models. High-quality image data and hyperspectral data can be provided by high-resolution cameras and hyperspectral imagers. Compared with traditional methods, higher geometric accuracy is not only guaranteed, but also the geological characteristics inside the mine can be deeply excavated. Image data is processed by advanced technologies such as Gaussian filtering, feature extraction, and multi-view stereo algorithms, which can effectively reduce noise and improve the matching degree of feature points, thereby constructing a high-precision three-dimensional surface model. At the same time, by combining geological structure data, mineral distribution data and 3D surface models, a 3D structural model of the target mine is generated, which can obtain detailed geological structure and mineral distribution data without actually entering the mining area, providing an accurate basis for the mineral distribution, mining plan and resource estimation of the mine. This enables mine managers to have a more comprehensive understanding of the distribution characteristics of ore bodies and ores, greatly reducing the safety risks and economic costs that may be caused by on-site surveys. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the 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 creative work.

[0051] Figure 1 It is a flowchart of a mine surveying and mapping method based on UAV remote sensing technology provided by an embodiment of the present invention; Figure 2 It is a structural schematic diagram of a mine surveying and mapping system based on UAV remote sensing technology provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0053] Combine the following Figure 1-Figure 2 The present invention describes a mine surveying method and system based on unmanned aerial vehicle remote sensing technology.

[0054] Figure 1 It is a flow chart of a mine surveying and mapping method based on UAV remote sensing technology provided by an embodiment of the present invention.

[0055] like Figure 1 As shown, an embodiment of the present invention provides a mine surveying and mapping method and system based on UAV remote sensing technology, and the execution subject can be a mine surveying and mapping method based on UAV remote sensing technology, including: S1. Use geographic information system to obtain the terrain data of the target mine.

[0056] Terrain data includes terrain elevation data, surface feature data, spatial coordinate data and geological background data. Terrain elevation data is used to describe the terrain undulations, slopes and distribution of rivers and lakes of the target mine. Surface feature data is used to describe the surface type distribution information of the target mine, including vegetation, exposed rocks and soil. Spatial coordinate data is used to determine the coordinate information of the target mine, and the coordinate information includes the boundary coordinates and feature coordinates of the target mine. Geological background data is used to provide geological maps and mineral resource information of the target mine based on historical data. Geological maps include geological structures, rock types and distribution. Mineral resource information includes mineral distribution data and ore body location data.

[0057] S2. Select a drone equipped with a high-resolution camera and a hyperspectral imager to collect image data and hyperspectral data of the target mine, and generate a flight trajectory of the drone based on the collection range of the image data and hyperspectral data.

[0058] The process of generating a drone flight trajectory includes: Obtain performance parameters for high-resolution cameras and hyperspectral imagers, and set resolution requirements for image data.

[0059] According to the performance parameters and resolution requirements of the high-resolution camera, the optimal flight height is calculated, and the formula is expressed as: ; In the formula, represents the focal length of the high-resolution camera, Indicates the resolution requirement of the image data, Represents the pixel size of a high-resolution camera.

[0060] Calculate the ground sampling distance, the formula is expressed as: ; In the formula, represents the pixel size of the high-resolution camera, and H represents the optimal flying height.

[0061] According to the performance parameters of the high-resolution camera and the hyperspectral imager, combined with the comprehensive actual coverage ground distance, the heading overlap rate and the side overlap rate are calculated. The formula is expressed as follows: ; ; In the formula, represents the heading overlap rate, GSD represents the ground sampling distance, represents the horizontal field of view of the high-resolution camera, represents the horizontal field of view of the hyperspectral imager, Indicates the comprehensive actual coverage ground distance, represents the heading overlap ratio, represents the vertical field of view of the high-resolution camera, Represents the vertical field of view of the hyperspectral imager.

[0062] Calculate the real-time flight speed of the drone, the formula is expressed as: , ; In the formula, Indicates the maximum flight speed of the drone. Indicates the maximum frame rate of a high-resolution camera, represents the exposure time of the high-resolution camera, represents the maximum frame rate of the hyperspectral imager, Represents the exposure time of the hyperspectral imager.

[0063] The maximum length and width of the target mine are obtained according to the terrain data, and the number of rows and columns of the UAV flight trajectory is calculated. The formula is expressed as: ; ; In the formula, The number of rows representing the flight trajectory of the drone, Indicates the maximum width of the target mine, The number of columns representing the flight trajectory of the drone, Indicates the maximum length of the target mine.

[0064] S3. Use the drone to collect image data and hyperspectral data of the target mine according to the drone's flight trajectory.

[0065] S4. Construct a three-dimensional surface model of the target mine based on the image data, including: S41, performing Gaussian filtering to remove noise on the image data, using an accelerated robust feature algorithm to extract feature points of the image, and matching adjacent images through a feature matching algorithm.

[0066] Gaussian filtering is used to denoise the image data. The formula is: ; Where x and y represent the pixel coordinates in the image data. and represent the standard deviation in the x and y directions respectively.

[0067] The accelerated robust feature algorithm is used to construct an enhanced Hessian matrix to extract feature points in image data. The enhanced Hessian matrix is ​​expressed as: ; Where, L xx , L xy , L yy Represents the second-order partial derivative of the image data, L xxx , L xxy , L yyy represents the third-order partial derivative of the image, represents a specific scale parameter, Represents the enhancement factor.

[0068] Adjacent image data are matched by a feature matching algorithm based on deep learning to obtain matching feature point pairs, including: constructing feature vectors of adjacent image data according to the feature points of the image data.

[0069] The formula for calculating matching feature point pairs is expressed as: ; In the formula, and represents the feature vector extracted from adjacent image data, Representation vector and The dot product of represents the magnitude of a vector, Represents a very small positive number to prevent the denominator from being zero.

[0070] S42. A method based on structured light motion is used to restore the camera pose and scene structure of the image, a multi-view stereo algorithm is used to generate a point cloud, and triangulation and meshing optimization are performed to construct a three-dimensional surface model of the target mine.

[0071] The method based on structured light motion is used to restore the camera pose and scene structure of the image. The method includes: by shooting calibration plate images at different angles, using the correspondence between the image coordinates and world coordinates of the checkerboard corner points, solving the high-resolution camera intrinsic parameter matrix, which is expressed as: ; In the formula, and Respectively represent the focal length of the high-resolution camera in the x and y directions, and represents the principal point coordinates, and s represents the distortion coefficient.

[0072] Using the matched feature point pairs, the fundamental matrix is ​​calculated by the normalized eight-point method.

[0073] Combined with the high-resolution camera intrinsic parameter matrix, the essential matrix is ​​calculated and the formula is expressed as: ; Where E represents the essential matrix and F represents the basic matrix.

[0074] Perform singular value decomposition on the essential matrix to obtain the initial rotation matrix and translation vector of the high-resolution camera.

[0075] The improved epipolar constraint equation is used to optimize the fundamental matrix. The formula of the epipolar constraint equation is expressed as: ; In the formula, x and Respectively represent the homogeneous coordinates of corresponding points in two adjacent image data, represents the optimized basic matrix, and c represents the compensation vector.

[0076] The rotation matrix and translation vector are adjusted by minimizing the reprojection error algorithm, which is expressed as: ; Where e represents the reprojection error, represents the coordinates of the feature points in the image data, R represents the initial rotation matrix, t represents the translation vector, Represents the coordinates of a point in a 3D surface model.

[0077] The process of generating a point cloud using a multi-view stereo algorithm includes: using a semi-global matching algorithm to calculate matching feature point pairs between adjacent image data, and obtaining the position difference of the same three-dimensional point in adjacent image data as disparity.

[0078] The depth value of each pixel in the image data is calculated based on the disparity. The formula is expressed as: ; Where B is the baseline length, represents the viewing angle of the high-resolution camera, Indicates parallax.

[0079] Convert each pixel in the image data into point coordinates in three-dimensional space. The formula is: ; Where Z represents the depth value at the pixel point (x, y).

[0080] The triangulation and meshing optimization process includes: using a triangulation algorithm based on topology optimization to convert the generated point cloud into a triangular mesh.

[0081] Minimize the energy function of triangulation to make the triangular mesh regular and smooth. The formula is: ; In the formula, represents the total energy function, represents the set of all triangulations, T represents a single triangle, represents the shape energy of triangle T, represents the smoothing energy of triangle T, and Represents the weight coefficient.

[0082] The objective function is used to iteratively optimize the triangular mesh and adjust the vertex positions of the triangular mesh until the preset number of iterations is reached to obtain a three-dimensional surface model. The objective function formula is expressed as: ; In the formula, represents the vertex positions of the triangle mesh, represents the reference position, Represents the change in vertex position, and Represents the weight coefficient.

[0083] S5. Process and analyze the hyperspectral data to obtain the geological structure data and mineral distribution data of the target mine.

[0084] The process of processing and analyzing hyperspectral data includes: The median filter processing is performed on the hyperspectral data, and the formula is expressed as: ; In the formula, represents the original hyperspectral data, represents the impulse response function of the filter, Represents the filtered hyperspectral data.

[0085] According to the terrain data, the relationship model between terrain and spectral response is constructed to correct the spectral deviation. The formula is expressed as: ; In the formula, represents the corrected spectral reflectance, represents the original spectral reflectance, Represents a correction function based on terrain data.

[0086] The non-negative matrix decomposition algorithm is used to perform spectral decomposition on the corrected spectral data to obtain the distribution data of minerals in the target mine. The formula of the non-negative matrix decomposition algorithm is expressed as: ; Where D represents the hyperspectral data matrix, U represents the endmember matrix, i.e., the pure spectra of different substances, and W represents the abundance matrix, i.e., the relative content of each substance.

[0087] By using the spectral absorption characteristic analysis, the first section derivative and second order derivative of the spectrum at different wavelengths are calculated, and the peak and valley values ​​of the first section derivative and second order derivative of the spectrum are analyzed to obtain the geological structure data. The formula of the first section derivative and second order derivative of the spectrum is expressed as: ; ; In the formula, The wavelength is The first derivative of the spectrum at , The wavelength is The spectral reflectance or absorptivity at The wavelength is The spectral reflectance or absorptivity at represents a small increment of wavelength, The wavelength is The second derivative of the spectrum at .

[0088] S6. Based on the geological structure data and mineral distribution data, combined with the three-dimensional surface model, a three-dimensional structural model of the target mine is obtained.

[0089] The process includes: The geological structure data and the mineral distribution data are standardized to obtain the geological structure standardized data and the mineral distribution standardized data.

[0090] Constructing geological structure data vector based on geological structure standardized data . Construct mineral distribution data vector based on mineral standard distribution data .in, represents the characteristic value of the i-th geological structure, Represents the content value of the jth mineral.

[0091] For each vertex P (x, y, z) in the three-dimensional surface model, set its corresponding texture coordinates to T (P) = (u, v), and calculate the eigenvalue of each vertex after fusion. The formula is expressed as: ; In the formula, Represents the corresponding value obtained in the geological structure data according to the texture coordinate T(P), represents the corresponding value obtained in the mineral distribution data according to the texture coordinate T(P), Represents the original eigenvalue of vertex P in the three-dimensional surface model. , , Represents the weight coefficient.

[0092] Using the physically based rendering model, the color of vertex P is calculated using the formula: ; In the formula, Represents the ambient light color, represents the diffuse color, Represents the specular color, represents the normal vector of vertex P, represents the light source direction vector, Represents the direction vector of the reflected light, represents the viewing direction vector, Indicates the specular index.

[0093] In summary, this embodiment provides a mine mapping method based on UAV remote sensing technology, which generates a UAV flight trajectory by acquiring terrain data, combining UAV performance and data acquisition equipment parameters, and ensuring that the UAV is photographed at a reasonable flight altitude and speed in different areas, thereby maximizing the regional coverage. Reduce repeated coverage during data acquisition and avoid data redundancy caused by multiple shots of the same area. Reduce the computational burden during data processing, improve overall efficiency, and fully present the terrain and features of the mine to the greatest extent. Through precise flight planning, it can be ensured that the target mine is fully covered when collecting images and hyperspectral data. At the same time, a comprehensive and reasonable flight path can capture image data at different angles and under different lighting conditions, laying the foundation for the subsequent generation of high-quality three-dimensional models. High-resolution cameras and hyperspectral imagers can provide high-quality image data and hyperspectral data, which not only ensures higher geometric accuracy than traditional methods, but also can deeply explore the geological features inside the mine. By processing image data with advanced technologies such as Gaussian filtering, feature extraction, and multi-view stereo algorithms, noise can be effectively reduced and the matching degree of feature points can be improved, thereby constructing a high-precision three-dimensional surface model. At the same time, by combining geological structure data, mineral distribution data and 3D surface models, a 3D structural model of the target mine is generated, which can obtain detailed geological structure and mineral distribution data without actually entering the mining area, providing an accurate basis for the mineral distribution, mining plan and resource estimation of the mine. It enables mine managers to have a more comprehensive understanding of the distribution characteristics of ore bodies and ores, greatly reducing the safety risks and economic costs that may be caused by on-site surveys. It also significantly reduces work costs and human resource investment, and reduces the costs and risks associated with human measurement. Through the generated 3D structural model, efficient and targeted selection can be achieved in actual on-site surveys. Managers can give priority to specific areas for in-depth exploration based on the results of hyperspectral analysis, thereby avoiding extensive and ineffective survey activities throughout the mining area. This not only saves manpower and material costs, but also reduces the impact on the environment.

[0094] Based on the same general inventive concept, the present invention also protects a mine surveying and mapping system based on UAV remote sensing technology. The mine surveying and mapping system based on UAV remote sensing technology provided by the present invention is described below. The mine surveying and mapping system based on UAV remote sensing technology described below and the mine surveying and mapping method based on UAV remote sensing technology described above can be referenced to each other.

[0095] Figure 2 It is a structural schematic diagram of a mine surveying and mapping system based on UAV remote sensing technology provided by an embodiment of the present invention.

[0096] like Figure 2As shown, the mine surveying and mapping system based on UAV remote sensing technology includes geographic information integration module, flight planning module, data acquisition module, data processing module, hyperspectral data analysis module and three-dimensional structure model building module.

[0097] The geographic information integration module is used to integrate and analyze the geographic information data of the target mine; The flight planning module is used to configure the UAV platform and data acquisition equipment and generate the flight trajectory; The data acquisition module is used to enable the UAV to fly according to the flight trajectory and collect image data and hyperspectral data in real time; The data processing module is used to construct a three-dimensional surface model of the target mine based on the image data; The hyperspectral data analysis module is used to process hyperspectral data and extract geological structure and mineral distribution data; The 3D structural model building module is used to combine geological structure data, mineral distribution data and 3D surface model to generate a 3D structural model of the target mine.

[0098] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0099] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A mine surveying and mapping method based on UAV remote sensing technology, characterized in that: include: S1. Use geographic information system to obtain topographic data of the target mine; S2, selecting a drone equipped with a high-resolution camera and a hyperspectral imager to collect image data and hyperspectral data of the target mine, and generating a flight trajectory of the drone according to the collection range of the image data and the hyperspectral data; S3. Collecting image data and hyperspectral data of the target mine using the drone according to the flight trajectory of the drone; S4. Constructing a three-dimensional surface model of the target mine according to the image data, including: S41, performing Gaussian filtering to remove noise on the image data, extracting feature points of the image using an accelerated robust feature algorithm, and matching adjacent images using a feature matching algorithm; S42, using a method based on structured light motion to restore the camera pose and scene structure of the image, using a multi-view stereo algorithm to generate a point cloud, and performing triangulation and meshing optimization to construct a three-dimensional surface model of the target mine; S5. Processing and analyzing the hyperspectral data to obtain geological structure data and mineral distribution data of the target mine; S6. Obtain a three-dimensional structural model of the target mine based on the geological structure data and the mineral distribution data in combination with the three-dimensional surface model.

2. A mine surveying and mapping method based on UAV remote sensing technology according to claim 1, characterized in that: In step S1, the terrain data includes terrain elevation data, surface feature data, spatial coordinate data and geological background data; the terrain elevation data is used to describe the terrain undulation, slope and distribution of rivers and lakes of the target mine; the surface feature data is used to describe the surface type distribution information of the target mine, including vegetation, exposed rocks and soil; the spatial coordinate data is used to determine the coordinate information of the target mine, and the coordinate information includes the boundary coordinates and feature coordinates of the target mine; the geological background data is used to provide the geological map and mineral resource information of the target mine based on historical data; the geological map includes geological structure, rock type and distribution; the mineral resource information includes mineral distribution data and ore body location data.

3. The mine surveying and mapping method based on UAV remote sensing technology according to claim 2 is characterized in that: In step S2, the process of generating the UAV flight trajectory includes: Obtaining performance parameters of the high-resolution camera and the hyperspectral imager, and setting resolution requirements for the image data; According to the performance parameters of the high-resolution camera and the resolution requirement, the optimal flying height is calculated, and the formula is expressed as: ； In the formula, represents the focal length of the high-resolution camera, Indicates the resolution requirement of the image data, Represents the pixel size of a high-resolution camera; Calculate the ground sampling distance, the formula is expressed as: ； In the formula, represents the pixel size of the high-resolution camera, and H represents the optimal flying altitude; According to the performance parameters of the high-resolution camera and the hyperspectral imager, combined with the comprehensive actual coverage ground distance, the heading overlap rate and the side overlap rate are calculated. The formula is expressed as follows: ； ； In the formula, represents the heading overlap rate, GSD represents the ground sampling distance, represents the horizontal field of view of the high-resolution camera, represents the horizontal field of view of the hyperspectral imager, Indicates the comprehensive actual coverage ground distance, represents the heading overlap ratio, represents the vertical field of view of the high-resolution camera, represents the vertical field of view of the hyperspectral imager; Calculate the real-time flight speed of the drone, the formula is expressed as: ， ； In the formula, Indicates the maximum flight speed of the drone. Indicates the maximum frame rate of a high-resolution camera, represents the exposure time of the high-resolution camera, represents the maximum frame rate of the hyperspectral imager, represents the exposure time of the hyperspectral imager; The maximum length and maximum width of the target mine are obtained according to the terrain data, and the number of rows and columns of the UAV flight trajectory is calculated. The formula is expressed as: ； ； In the formula, The number of rows representing the flight trajectory of the drone, Indicates the maximum width of the target mine, The number of columns representing the flight trajectory of the drone, Indicates the maximum length of the target mine.

4. The mine surveying and mapping method based on UAV remote sensing technology according to claim 1 is characterized in that: In step S41, Gaussian filtering is performed on the image data to remove noise, and the formula is expressed as: ； Where x and y represent the pixel coordinates in the image data. and Represent the standard deviation in the x and y directions respectively; An accelerated robust feature algorithm is used to construct an enhanced Hessian matrix to extract feature points in the image data. The enhanced Hessian matrix is ​​expressed as: ； Where, L xx , L xy , L yy Represents the second-order partial derivative of the image data, L xxx , L xxy , L yyy represents the third-order partial derivative of the image, represents a specific scale parameter, represents the enhancement coefficient; According to the feature points of the image data, a feature vector of adjacent image data is constructed; The feature vectors are matched by a feature matching algorithm based on deep learning to obtain matching feature point pairs. The formula for calculating matching feature point pairs is expressed as: ； In the formula, and represents the feature vector extracted from adjacent image data, Representation vector and The dot product of represents the magnitude of a vector, Represents a very small positive number to prevent the denominator from being zero.

5. The mine surveying and mapping method based on UAV remote sensing technology according to claim 4 is characterized in that: In step S42, the camera pose and scene structure of the image are restored by using a method based on structured light motion, including: By taking images of the calibration plate at different angles, the high-resolution camera intrinsic parameter matrix is ​​solved using the correspondence between the image coordinates and world coordinates of the checkerboard corner points. Using the matching feature point pairs, a basic matrix is ​​calculated by a normalized eight-point method; Calculating an intrinsic matrix in combination with the high-resolution camera intrinsic parameter matrix; Performing singular value decomposition on the essential matrix to obtain an initial rotation matrix and translation vector of the high-resolution camera; optimizing the fundamental matrix using a modified epipolar constraint equation; The rotation matrix and the translation vector are adjusted by minimizing the reprojection error algorithm.

6. The mine surveying and mapping method based on UAV remote sensing technology according to claim 5 is characterized in that: In step S42, the process of generating a point cloud using a multi-view stereo algorithm includes: A semi-global matching algorithm is used to calculate the matching feature point pairs between adjacent image data, and the position difference of the same 3D point in adjacent image data is obtained as the disparity; Calculate the depth value of each pixel in the image data according to the disparity; Convert each pixel in the image data into point coordinates in three-dimensional space.

7. The mine surveying and mapping method based on UAV remote sensing technology according to claim 1 is characterized in that: In step S42, the triangulation and meshing optimization process includes: The generated point cloud is converted into a triangular mesh using a triangulation algorithm based on topology optimization; Minimize the energy function of triangulation to make the triangular mesh regular and smooth; The triangular mesh is iteratively optimized using an objective function, and the vertex positions of the triangular mesh are adjusted until a preset number of iterations is reached to obtain a three-dimensional surface model.

8. The mine surveying and mapping method based on UAV remote sensing technology according to claim 1 is characterized in that: The process of processing and analyzing the hyperspectral data includes: Performing median filtering on the hyperspectral data; According to the terrain data, a relationship model between terrain and spectral response is constructed to correct spectral deviation; The non-negative matrix decomposition algorithm is used to perform spectral decomposition on the corrected spectral data to obtain the distribution data of minerals in the target mine; The spectral absorption characteristic analysis is used to calculate the first section derivative and the second order derivative of the spectrum at different wavelengths, and the peak values ​​and valley values ​​of the first section derivative and the second order derivative of the spectrum are analyzed to obtain the geological structure data.

9. The mine surveying and mapping method based on UAV remote sensing technology according to claim 1, characterized in that: In step S6, the process of obtaining the three-dimensional structure model includes: Performing standardization processing on the geological structure data and the mineral distribution data to obtain geological structure standardized data and mineral distribution standardized data; Constructing a geological structure data vector according to the geological structure standardized data; constructing a mineral distribution data vector according to the mineral distribution standardized data; For each vertex in the three-dimensional surface model, set its corresponding texture coordinates and calculate the fused feature value of each vertex; Using a physically based rendering model, the color of each of the vertices is calculated.

10. A mine surveying and mapping system based on UAV remote sensing technology, wherein the mine surveying and mapping system based on UAV remote sensing technology adopts the mine surveying and mapping method based on UAV remote sensing technology as claimed in any one of claims 1 to 9, characterized in that: The mine surveying and mapping system based on UAV remote sensing technology includes: Geographic information integration module, used to integrate and analyze geographic information data of target mines; The flight planning module is used to configure the UAV platform and data acquisition equipment and generate the flight trajectory; Data acquisition module, used to enable the UAV to fly according to the flight trajectory and collect image data and hyperspectral data in real time; A data processing module, used to construct a three-dimensional surface model of the target mine based on the image data; Hyperspectral data analysis module, used to process hyperspectral data and extract geological structure and mineral distribution data; The 3D structural model building module is used to combine geological structure data, mineral distribution data and 3D surface model to generate a 3D structural model of the target mine.

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