A mine surveying method and system based on drone remote sensing technology

Abstract

The present invention relates to the technical field of mine surveying and mapping, and particularly to a mine surveying and mapping method and system based on unmanned aerial vehicle (UAV) remote sensing technology. The method includes: obtaining topographic data of a mine; generating a UAV flight trajectory; using the UAV 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 structure model of the mine based on the geological structure data, mineral distribution data, and three-dimensional surface model. By generating the UAV flight trajectory, the present invention ensures that the UAV takes pictures at a reasonable flight altitude and speed in different areas, reduces overlapping coverage, and maximizes the area coverage rate. By generating the three-dimensional structure 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 brought about by on-site surveys.

Description

Technical Field

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

[0002] Mine surveying and mapping can provide information such as the distribution, grade, and reserves of minerals in the mining area, which helps to analyze the evaluation of mineral resources and their potential economic value. By obtaining detailed topographic data and geological structure information of the mine area, the geomorphic features, geological structures, and their evolution history of the mining area can be understood. It is of great significance for judging the shape, distribution, and mining feasibility of ore bodies. Mine surveying and mapping can reveal potential safety hazards, such as risk areas of geological disasters like landslides and collapses, which helps to formulate preventive measures and improve the safety of mine operations. At the same time, through the monitoring of the mining area environment, sudden problems can be detected in a timely manner and corresponding measures can be taken. Through in-depth understanding of the mine topography and geology, it supports reasonable mining design and route planning, optimizes the resource extraction process, reduces costs, and improves efficiency.

[0003] Traditional mine surveying and mapping methods often rely on manual operations, with slow data collection speed and limited coverage. Ground surveys require surveyors to measure point by point on site, which is not only time-consuming and laborious, but also difficult to ensure comprehensive data coverage in large-scale mining areas. On-site exploration often requires personnel to carry out actual measurement work in mines or potentially dangerous areas, increasing the safety risk. Summary of the Invention

[0004] The present invention provides a mine surveying and mapping method and system based on UAV remote sensing technology 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, including:

[0006] S1. Obtain the topographic data of the target mine using a geographic information system.

[0007] S2. Select a UAV equipped with a high-resolution camera and a hyperspectral imager to collect image data and hyperspectral data of the target mine, and generate a UAV flight trajectory according to the collection range of the image data and hyperspectral data.

[0008] S3. According to the UAV flight trajectory, use the UAV to collect image data and hyperspectral data of the target mine.

[0009] S4. According to the image data, construct a three-dimensional surface model of the target mine, including:

[0010] S41. Perform Gaussian filtering denoising on the image data, extract the feature points of the image using the speeded-up robust features (SURF) algorithm, and match adjacent images through a feature matching algorithm.

[0011] S42. Adopt the method based on structure - from - motion to restore the camera pose and scene structure of the image, generate a point cloud using a multi - view stereo algorithm, and perform triangulation and meshing optimization to construct a three - dimensional surface model of the target mine.

[0012] S5. Process and analyze the hyperspectral data to obtain the geological structure data and mineral distribution data of the target mine.

[0013] S6. According to the geological structure data and mineral distribution data, combined with the three - dimensional surface model, obtain the three - dimensional structure model of the target mine.

[0014] According to a mine surveying and mapping method based on UAV 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 undulation, slope, and the distribution of rivers and lakes of the target mine. The surface feature data is used to describe the distribution information of the surface types of the target mine, including vegetation, bare rock, 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 characteristic coordinates of the target mine. The geological background data is used to provide the geological map and mineral resource information of the target mine according to 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.

[0015] 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:

[0016] Obtain the performance parameters of the high - resolution camera and the hyperspectral imager, and set the resolution requirements for the image data.

[0017] According to the performance parameters and resolution requirements of the high - resolution camera, calculate the optimal flight altitude, which is expressed by the formula:

[0018] ;

[0019] In the formula, represents the focal length of the high - resolution camera, represents the resolution requirement for the image data, represents the pixel size of the high - resolution camera.

[0020] Calculate the ground sampling distance, which is expressed by the formula:

[0021] ;

[0022] In the formula, represents the pixel size of the high - resolution camera, and H represents the optimal flight altitude.

[0023] According to the performance parameters of the high-resolution camera and the hyperspectral imager, combined with the comprehensive actual ground coverage distance, calculate the forward overlap rate and the side overlap rate, which are expressed by the formulas as follows:

[0024] ;

[0025] ;

[0026] In the formulas, represents the forward overlap rate, GSD represents the ground sampling distance, represents the horizontal field of view angle of the high-resolution camera, represents the horizontal field of view angle of the hyperspectral imager, represents the comprehensive actual ground coverage distance, represents the forward overlap rate, represents the vertical field of view angle of the high-resolution camera, represents the vertical field of view angle of the hyperspectral imager.

[0027] Calculate the real-time flight speed of the UAV, which is expressed by the formula as follows:

[0028] , ;

[0029] In the formula, represents the maximum flight speed of the UAV, represents the maximum frame rate of the 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.

[0030] Obtain the maximum length and maximum width of the target mine according to the terrain data, and calculate the number of rows and columns of the UAV flight trajectory, which are expressed by the formulas as follows:

[0031] ;

[0032] ;

[0033] In the formulas, represents the number of rows of the UAV flight trajectory, represents the maximum width of the target mine, represents the number of columns of the UAV flight trajectory, represents the maximum length of the target mine.

[0034] A mine mapping method based on UAV remote sensing technology provided by the present invention, in step S41, Gaussian filtering is performed on the image data, and the formula is expressed as:

[0035] ;

[0036] In the formula, x and y represent the pixel coordinates in the image data, and respectively represent the standard deviations in the x and y directions.

[0037] The accelerated robust feature algorithm is used to construct an enhanced Hessian matrix to extract feature points in the image data, and the enhanced Hessian matrix is expressed as:

[0038] ;

[0039] In the formula, L xx , L xy , L yy represent the second-order partial derivatives of the image data, L xxx , L xxy , L yyy represent the third-order partial derivatives of the image, represents a specific scale parameter, represents an enhancement coefficient.

[0040] According to the feature points of the image data, a feature vector of adjacent image data is constructed.

[0041] The feature vectors are matched by a feature matching algorithm based on deep learning to obtain matching feature point pairs, and the formula for calculating the matching feature point pairs is expressed as:

[0042] ;

[0043] In the formula, and represent the feature vectors extracted from adjacent image data, represents the dot product of the vectors and , represents the modulus of the vector, represents a very small positive number to prevent the denominator from being zero.

[0044] A mine mapping method based on UAV remote sensing technology provided by the present invention, in step S42, a method based on structure from motion is used to restore the camera pose and scene structure of the image, including:

[0045] By taking calibration board images at different angles, and using the correspondence between the image coordinates and world coordinates of the checkerboard corners, the high-resolution camera internal parameter matrix is solved.

[0046] Using the matching feature point pairs, calculate the fundamental matrix by the normalized eight-point method.

[0047] Combine with the high-resolution camera internal parameter matrix to calculate the essential matrix.

[0048] Perform singular value decomposition on the essential matrix to obtain the initial rotation matrix and translation vector of the high-resolution camera.

[0049] Use the improved epipolar constraint equation to optimize the fundamental matrix.

[0050] Adjust the rotation matrix and translation vector through the least squares reprojection error algorithm.

[0051] According to a mine mapping method based on UAV remote sensing technology provided by the present invention, in step S42, the process of generating point cloud by using the multi-view stereo algorithm includes:

[0052] Use the semi-global matching algorithm to calculate the matching feature point pairs between adjacent image data, and obtain the position difference of the same three-dimensional point in adjacent image data as the disparity.

[0053] Calculate the depth value of each pixel point in the image data according to the disparity.

[0054] Convert each pixel point in the image data into the point coordinates in the three-dimensional space.

[0055] According to a mine mapping method based on UAV remote sensing technology provided by the present invention, in step S42, the process of triangulation and grid optimization includes:

[0056] Use the triangulation algorithm based on topological optimization to convert the generated point cloud into a triangular mesh.

[0057] Minimize the energy function of the triangulation to make the triangular mesh regular and smooth.

[0058] Use the objective function to perform iterative optimization on the triangular mesh, adjust the vertex positions of the triangular mesh until the preset number of iterations is reached, and obtain the three-dimensional surface model.

[0059] According to a mine mapping method based on UAV remote sensing technology provided by the present invention, the process of processing and analyzing the hyperspectral data includes:

[0060] Perform median filtering on the hyperspectral data.

[0061] According to the terrain data, construct a relationship model between the terrain and the spectral response to correct the spectral deviation.

[0062] Adopt the non-negative matrix factorization algorithm to perform spectral decomposition on the corrected spectral data to obtain the distribution data of minerals in the target mine.

[0063] Using spectral absorption feature analysis, calculate the first-order derivative and second-order derivative of the spectrum at different wavelengths, and analyze the peaks and valleys of the first-order derivative and second-order derivative of the spectrum to obtain geological structure data.

[0064] 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 the three-dimensional structure model includes:

[0065] Perform standardization processing on the geological structure data and mineral distribution data to obtain standardized geological structure data and standardized mineral distribution data.

[0066] Construct a geological structure data vector based on the standardized geological structure data. Construct a mineral distribution data vector based on the standardized mineral distribution data.

[0067] For each vertex in the three-dimensional surface model, set its corresponding texture coordinates and calculate the fused eigenvalue of each vertex.

[0068] Use a physically based rendering model to calculate the color of each vertex.

[0069] On the other hand, the present invention also provides a mine surveying and mapping system based on UAV remote sensing technology, including:

[0070] A geographic information integration module for integrating and analyzing geographic information data of the target mine.

[0071] A flight planning module for configuring the UAV platform and data acquisition equipment and generating a flight trajectory.

[0072] A data acquisition module for enabling the UAV to fly according to the flight trajectory and real-time collecting image data and hyperspectral data.

[0073] A data processing module for constructing a three-dimensional surface model of the target mine based on the image data.

[0074] A hyperspectral data analysis module for processing the hyperspectral data and extracting geological structure and mineral distribution data.

[0075] A three-dimensional structure model construction module for combining the geological structure data, mineral distribution data and three-dimensional surface model to generate a three-dimensional structure model of the target mine.

[0076] A mine mapping method and system based on UAV remote sensing technology provided by the present invention generates a UAV flight trajectory by acquiring terrain data and combining UAV performance and data acquisition device parameters, ensuring that the UAV takes pictures at a reasonable flight altitude and speed in different regions, thereby maximizing the regional coverage rate. It reduces the repeated coverage during data acquisition and avoids data redundancy caused by multiple shootings of the same area. It reduces the computational burden during data processing, improves the overall efficiency, and presents the terrain and features of the mine in the most complete manner. Through precise flight planning, it can ensure full coverage when collecting images and hyperspectral data of the target mine. At the same time, a comprehensive and reasonable flight path can capture image data under different angles and lighting conditions, laying a foundation for generating high-quality three-dimensional models in the future. High-resolution cameras and hyperspectral imagers can provide high-quality image data and hyperspectral data. Compared with traditional methods, it not only ensures higher geometric accuracy but also can deeply explore the geological features inside the mine. By processing image data through advanced technologies such as Gaussian filtering, feature extraction, and multi-view stereo algorithms, it 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 three-dimensional surface models, a three-dimensional structure model of the target mine is generated, enabling detailed geological structure and mineral distribution data to be obtained without actually entering the mining area, providing an accurate basis for mineral distribution, mining plans, and resource estimation in the mine. It enables mine managers to have a more comprehensive understanding of the distribution characteristics of ore bodies and ores, and greatly reduces the safety risks and economic costs that may be brought by on-site surveys. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0078] Figure 1 It is a schematic flowchart of a mine mapping method based on UAV remote sensing technology provided by an embodiment of the present invention;

[0079] Figure 2 It is a schematic structural diagram of a mine mapping system based on UAV remote sensing technology provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0080] To make the objectives, technical solutions and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below with reference to the accompanying drawings in the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present invention without making creative efforts shall fall within the protection scope of the present invention.

[0081] The following combines Figure 1 - Figure 2 to describe a mine surveying and mapping method and system based on UAV remote sensing technology of the present invention.

[0082] Figure 1 is a schematic flowchart of a mine surveying and mapping method based on UAV remote sensing technology provided by an embodiment of the present invention.

[0083] As Figure 1 shown, a mine surveying and mapping method and system based on UAV remote sensing technology provided by an embodiment of the present invention, the execution subject may be a mine surveying and mapping method based on UAV remote sensing technology, including:

[0084] S1. Obtain the terrain data of the target mine using a geographic information system.

[0085] The terrain data includes terrain elevation data, surface feature data, spatial coordinate data, and geological background data. The terrain elevation data is used to represent the undulation of the terrain, slope, and distribution of rivers and lakes of the target mine. The surface feature data is used to represent the distribution information of the surface types 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 according to historical data. The geological map includes geological structures, rock types, and their distributions. The mineral resource information includes mineral distribution data and ore body location data.

[0086] S2. Select a UAV equipped with a high-resolution camera and a hyperspectral imager to collect the image data and hyperspectral data of the target mine, and generate a UAV flight trajectory according to the collection ranges of the image data and hyperspectral data.

[0087] The process of generating the UAV flight trajectory includes:

[0088] Obtain the performance parameters of the high-resolution camera and the hyperspectral imager, and set the resolution requirements for the image data.

[0089] According to the performance parameters of the high-resolution camera and the resolution requirements, calculate the optimal flight altitude, and the formula is expressed as:

[0090] ;

[0091] In the formula, represents the focal length of the high-resolution camera, represents the resolution requirement of the image data, represents the pixel size of the high-resolution camera.

[0092] Calculate the ground sampling distance, and the formula is expressed as:

[0093] ;

[0094] In the formula, represents the pixel size of the high-resolution camera, and H represents the optimal flight altitude.

[0095] According to the performance parameters of the high-resolution camera and the hyperspectral imager, combined with the comprehensive actual ground coverage distance, calculate the forward overlap rate and the side overlap rate. The formula is expressed as:

[0096] ;

[0097] ;

[0098] In the formula, represents the forward overlap rate, GSD represents the ground sampling distance, represents the horizontal field of view angle of the high-resolution camera, represents the horizontal field of view angle of the hyperspectral imager, represents the comprehensive actual ground coverage distance, represents the forward overlap rate, represents the vertical field of view angle of the high-resolution camera, represents the vertical field of view angle of the hyperspectral imager.

[0099] Calculate the real-time flight speed of the UAV, and the formula is expressed as:

[0100] , ;

[0101] In the formula, represents the maximum flight speed of the UAV, represents the maximum frame rate of the 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.

[0102] Obtain the maximum length and maximum width of the target mine according to the terrain data, and calculate the number of rows and columns of the UAV flight trajectory. The formula is expressed as:

[0103] ;

[0104] ;

[0105] In the formula, represents the number of rows of the UAV flight trajectory, represents the maximum width of the target mine, represents the number of columns of the UAV flight trajectory, represents the maximum length of the target mine.

[0106] S3. According to the UAV flight trajectory, use the UAV to collect the image data and hyperspectral data of the target mine.

[0107] S4. According to the image data, construct a three-dimensional surface model of the target mine, including:

[0108] S41. Perform Gaussian filtering denoising on the image data, extract the feature points of the image using the Speeded Up Robust Features (SURF) algorithm, and match adjacent images through the feature matching algorithm.

[0109] Perform Gaussian filtering denoising on the image data, and the formula is expressed as:

[0110] ;

[0111] In the formula, x and y represent the pixel coordinates in the image data, and respectively represent the standard deviations in the x and y directions.

[0112] Construct an enhanced Hessian matrix using the SURF algorithm to extract the feature points in the image data, and the enhanced Hessian matrix is expressed as:

[0113] ;

[0114] In the formula, L xx , L xy , L yy represent the second-order partial derivatives of the image data, L xxx , L xxy , L yyy represent the third-order partial derivatives of the image, represents a specific scale parameter, represents an enhancement coefficient.

[0115] Match adjacent image data through a feature matching algorithm based on deep learning to obtain matching feature point pairs, including: construct the feature vectors of adjacent image data according to the feature points of the image data.

[0116] The formula for calculating the matching feature point pairs is expressed as:

[0117] ;

[0118] Wherein, and represent the feature vectors extracted from adjacent image data, represents the vector and is the dot product of, represents the norm of the vector, represents a very small positive number to prevent the denominator from being zero.

[0119] S42. Adopt the method based on structure from motion to restore the camera pose and scene structure of the image, generate point cloud using the multi-view stereo algorithm, and perform triangulation and meshing optimization to construct the three-dimensional surface model of the target mine.

[0120] Adopting the method based on structure from motion to restore the camera pose and scene structure of the image includes: by taking calibration board images at different angles, using the correspondence between the image coordinates and world coordinates of the checkerboard corner points, solving the high-resolution camera internal parameter matrix, and the formula is expressed as:

[0121] ;

[0122] Wherein, and respectively represent the focal lengths of the high-resolution camera in the x and y directions, and represent the principal point coordinates, and s represents the distortion coefficient.

[0123] Using the matched feature point pairs, calculate the fundamental matrix by the normalized eight-point method.

[0124] Combined with the high-resolution camera internal parameter matrix, calculate the essential matrix, and the formula is expressed as:

[0125] ;

[0126] Wherein, E represents the essential matrix and F represents the fundamental matrix.

[0127] Perform singular value decomposition on the essential matrix to obtain the initial rotation matrix and translation vector of the high-resolution camera.

[0128] Use the improved epipolar constraint equation to optimize the fundamental matrix, and the formula of the epipolar constraint equation is expressed as:

[0129] ;

[0130] Wherein, x and respectively represent the homogeneous coordinates of the corresponding points in two adjacent image data, Let \(\hat{F}\) represent the optimized fundamental matrix and \(c\) represent the compensation vector.

[0131] The rotation matrix and translation vector are adjusted by minimizing the reprojection error algorithm, which is expressed by the formula:

[0132] ;

[0133] In the formula, \(e\) represents the reprojection error, \((u, v)\) represents the coordinates of the feature points in the image data, \(R\) represents the initial rotation matrix, \(t\) represents the translation vector, \((X, Y, Z)\) represents the coordinates of the points in the 3D surface model.

[0134] The process of generating the point cloud using the multi-view stereo algorithm includes: calculating the matching feature point pairs between adjacent image data using the semi-global matching algorithm to obtain the position difference of the same 3D point in adjacent image data, which is used as the disparity.

[0135] The depth value of each pixel point in the image data is calculated according to the disparity, and the formula is expressed as:

[0136] ;

[0137] In the formula, \(B\) represents the baseline length, \(\theta\) represents the viewing angle of the high-resolution camera, \(d\) represents the disparity.

[0138] Each pixel point in the image data is converted into the point coordinates in the 3D space, and the formula is expressed as:

[0139] ;

[0140] In the formula, \(Z\) represents the depth value at the pixel point \((x, y)\).

[0141] The process of triangulation and meshing optimization includes: using the triangulation algorithm based on topological optimization to convert the generated point cloud into a triangular mesh.

[0142] Minimize the energy function of the triangulation to make the triangular mesh regular and smooth, and the formula is expressed as:

[0143] ;

[0144] In the formula, \(E\) represents the total energy function, \(\mathcal{T}\) represents the set of all triangulations, \(T\) represents a single triangle, \(E_s(T)\) represents the shape energy of triangle \(T\), \(E_c(T)\) represents the smooth energy of triangle \(T\), and \(\alpha\) and \(\beta\) represent the weight coefficients.

[0145] Iteratively optimize the triangular mesh using the objective function to adjust the vertex positions of the triangular mesh until the preset number of iterations is reached, obtaining a three-dimensional surface model. The formula of the objective function is expressed as:

[0146] ;

[0147] In the formula, represents the vertex position of the triangular mesh, represents the reference position, represents the change in vertex position, and represent the weight coefficients.

[0148] S5. Process and analyze the hyperspectral data to obtain the geological structure data and mineral distribution data of the target mine.

[0149] The process of processing and analyzing the hyperspectral data includes:

[0150] Perform median filtering on the hyperspectral data. The formula is expressed as:

[0151] ;

[0152] In the formula, represents the original hyperspectral data, represents the impulse response function of the filter, represents the filtered hyperspectral data.

[0153] Construct a relationship model between the terrain and spectral response based on the terrain data to correct the spectral deviation. The formula is expressed as:

[0154] ;

[0155] In the formula, represents the corrected spectral reflectance, represents the original spectral reflectance, represents the correction function based on the terrain data.

[0156] Use the non-negative matrix factorization algorithm to perform spectral decomposition on the corrected spectral data to obtain the mineral distribution data in the target mine. The formula of the non-negative matrix factorization algorithm is expressed as:

[0157] ;

[0158] In the formula, 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.

[0159] Using spectral absorption feature analysis, calculate the first derivative and second derivative of the spectrum at different wavelengths, and analyze the peaks and valleys of the first derivative and second derivative of the spectrum to obtain geological structure data. The formulas for the first derivative and second derivative of the spectrum are as follows:

[0160] ;

[0161] ;

[0162] In the formula, represents the first derivative of the spectrum at the wavelength of , represents the spectral reflectance or absorptance at the wavelength of , represents the spectral reflectance or absorptance at the wavelength of , represents a small increment of the wavelength, represents the second derivative of the spectrum at the wavelength of .

[0163] S6. According to the geological structure data and the mineral distribution data, combined with the three-dimensional surface model, obtain the three-dimensional structure model of the target mine.

[0164] The process includes:

[0165] Perform standardization processing on the geological structure data and the mineral distribution data to obtain the standardized geological structure data and the standardized mineral distribution data.

[0166] Construct a geological structure data vector according to the standardized geological structure data. Construct a mineral distribution data vector according to the standardized mineral distribution data. Among them, represents the eigenvalue of the i-th geological structure, represents the content value of the j-th mineral.

[0167] For each vertex P(x, y, z) in the three-dimensional surface model, set its corresponding texture coordinate as T(P) = (u, v), and calculate the fused eigenvalue of each vertex. The formula is as follows:

[0168] ;

[0169] In the formula, represents the corresponding value obtained from the geological structure data according to the texture coordinate T(P), represents the corresponding value obtained from the mineral distribution data according to the texture coordinate T(P), represents the original eigenvalue of the vertex P in the three-dimensional surface model. 、 , represents the weight coefficient.

[0170] Using a physically based rendering model, the color of vertex P is calculated, and the formula is expressed as:

[0171] ;

[0172] In the formula, represents the ambient light color, represents the diffuse reflection color, represents the specular reflection color, represents the normal vector of vertex P, represents the light source direction vector, represents the reflected light direction vector, represents the viewing direction vector, represents the specular exponent.

[0173] In summary, this embodiment provides a mine mapping method based on UAV remote sensing technology. By acquiring terrain data and combining UAV performance and data acquisition device parameters, a UAV flight trajectory is generated to ensure that the UAV takes pictures at a reasonable flight altitude and speed in different regions, thereby maximizing the regional coverage rate. It reduces the repeated coverage during data acquisition and avoids data redundancy caused by multiple shootings of the same area. It reduces the computational burden during data processing, improves the overall efficiency, and presents the terrain and features of the mine as completely as possible to the greatest extent. Through precise flight planning, it can ensure full coverage of the target mine when collecting image and hyperspectral data. At the same time, a comprehensive and reasonable flight path can capture image data under different angles and lighting conditions, laying a foundation for generating high-quality three-dimensional models in the future. Through high-resolution cameras and hyperspectral imagers, high-quality image data and hyperspectral data can be provided. Compared with traditional methods, it not only ensures higher geometric accuracy but also can deeply explore the geological features inside the mine. By processing image data through 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 three-dimensional surface models, a three-dimensional structure 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 brought by on-site surveys. It also significantly reduces the working cost and human resource input, reducing the costs and risks related to manual measurement. Through the generated three-dimensional structure model, efficient targeted selection can be achieved in actual on-site surveys. Managers can, according to the hyperspectral analysis results, preferentially select specific areas for in-depth exploration, 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.

[0174] Based on the same general inventive concept, the present invention also protects a mine mapping system based on UAV remote sensing technology. The following describes a mine mapping system based on UAV remote sensing technology provided by the present invention. The mine mapping system based on UAV remote sensing technology described below can be mutually corresponded and referred to with the mine mapping method based on UAV remote sensing technology described above.

[0175] Figure 2 It is a schematic structural diagram of a mine mapping system based on UAV remote sensing technology provided by an embodiment of the present invention.

[0176] As Figure 2As shown in the figure, the mine mapping system based on UAV remote sensing technology includes a geographic information integration module, a flight planning module, a data acquisition module, a data processing module, a hyperspectral data analysis module, and a three-dimensional structure model construction module.

[0177] The geographic information integration module is used to integrate and analyze the geographic information data of the target mine;

[0178] The flight planning module is used to configure the UAV platform and data acquisition equipment and generate a flight trajectory;

[0179] 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;

[0180] The data processing module is used to construct a three-dimensional surface model of the target mine based on the image data;

[0181] The hyperspectral data analysis module is used to process the hyperspectral data and extract geological structure and mineral distribution data;

[0182] The three-dimensional structure model construction module is used to combine the geological structure data, mineral distribution data, and three-dimensional surface model to generate a three-dimensional structure model of the target mine.

[0183] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the essence of the above technical solution, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions for causing 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.

[0184] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of each embodiment 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 and denoising 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: ， ； 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; 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; 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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