A method and system for monitoring annual resource usage of an open pit mine

Abstract

The application discloses a kind of open-pit mining mine annual resource quantity monitoring method and system, it is related to mine resource monitoring technical field, the method includes: obtaining multi-source remote sensing data, and the multi-source remote sensing data is carried out data screening and control point correction preprocessing, obtain the multi-source remote sensing data after preprocessing;Based on the multi-source remote sensing data after preprocessing, DEM extraction, DEM normalization and 3D butt joint ore body processing are carried out, obtain the butt joint three-dimensional ore body model;According to the butt joint three-dimensional ore body model, the earthwork of open-pit mining area is calculated;Based on the earthwork, the annual resource quantity of open-pit mine is calculated;Based on the annual resource quantity of open-pit mine, using vector and raster superposition method, annual resource quantity monitoring result map of open-pit mine is generated.The application can improve the precision and efficiency of mine annual resource quantity monitoring.

Description

Technical Field

[0001] This application relates to the field of mineral resource monitoring technology, and in particular to a method and system for monitoring the annual resource utilization of open-pit mines. Background Technology

[0002] Monitoring the annual resource utilization of open-pit mines is a crucial aspect of mineral resource management, directly impacting the compliance and sustainability of resource development and utilization. Currently, annual resource utilization monitoring in open-pit mines primarily relies on two methods: self-reporting by mining companies and manual sampling. However, data reported by companies is heavily influenced by subjective factors, making it difficult to objectively reflect actual utilization. Manual sampling only covers some technical parameters, failing to achieve comprehensive and all-encompassing monitoring, resulting in insufficient accuracy and low monitoring efficiency.

[0003] Satellite remote sensing technology offers advantages such as objective data, wide coverage, and flexible monitoring cycles, providing a new technological approach for monitoring the annual resource utilization of open-pit mines. However, existing remote sensing monitoring methods suffer from problems such as discontinuous satellite data, inconsistent resolutions across different data sources, and low accuracy in docking ore bodies with 3D models, resulting in monitoring efficiency and detection accuracy that fail to meet practical needs. Therefore, there is an urgent need for a method and device that integrates multi-source remote sensing technologies to achieve unified resolution and precise 3D docking for monitoring the annual resource utilization of open-pit mines, thereby improving the accuracy and efficiency of annual resource utilization monitoring. Summary of the Invention

[0004] The purpose of this application is to provide a method and system for monitoring the annual resource utilization of open-pit mines, which can improve the accuracy and efficiency of monitoring the annual resource utilization of mines.

[0005] To achieve the above objectives, this application provides the following solution.

[0006] In a first aspect, this application provides a method for monitoring the annual resource utilization of open-pit mines, which includes the following steps.

[0007] Multi-source remote sensing data is acquired, and the multi-source remote sensing data is preprocessed by data filtering and control point correction to obtain preprocessed multi-source remote sensing data; the multi-source remote sensing data includes UAV lidar data, UAV oblique photography data, high-resolution satellite remote sensing data, and InSAR data.

[0008] Based on the preprocessed multi-source remote sensing data, DEM extraction, DEM normalization, and 3D docking ore body processing are performed to obtain the docked three-dimensional ore body model.

[0009] Based on the docked three-dimensional ore body model, the earthwork volume of the open-pit mine mining area is calculated.

[0010] Based on the earthwork volume, calculate the annual resource utilization of the open-pit mine.

[0011] Based on the annual resource utilization of the open-pit mine, a monitoring map of the annual resource utilization of the open-pit mine is generated using vector and raster overlay methods.

[0012] Optionally, multi-source remote sensing data is acquired, and the multi-source remote sensing data is preprocessed by data filtering and control point correction to obtain preprocessed multi-source remote sensing data, specifically including the following steps.

[0013] Acquire multi-source remote sensing data.

[0014] The multi-source remote sensing data is filtered, and the priority order of various types of data in the multi-source remote sensing data is determined according to the data accuracy to obtain the filtered multi-source remote sensing data.

[0015] Control point correction is performed on the filtered multi-source remote sensing data to obtain preprocessed multi-source remote sensing data.

[0016] Optionally, the priority order for data filtering is: UAV lidar data > UAV oblique photography data > high-resolution satellite remote sensing data > InSAR data.

[0017] The control point correction includes uniformly distributing horizontal and vertical control points within the monitoring range.

[0018] Optionally, based on the preprocessed multi-source remote sensing data, DEM extraction, DEM normalization, and 3D docking ore body processing are performed to obtain a docked three-dimensional ore body model, specifically including the following steps.

[0019] Based on the preprocessed multi-source remote sensing data, DEM data is extracted.

[0020] Based on the preprocessed multi-source remote sensing data, a coordinate transformation process from camera coordinates to geodetic coordinates is performed to obtain the transformed coordinate information.

[0021] Based on the transformed coordinate information and the DEM data, DEM normalization processing is performed to obtain normalized DEM data.

[0022] Based on the normalized DEM data and the transformed coordinate information, 3D docking ore body processing is performed to obtain the docked three-dimensional ore body model.

[0023] Optionally, the DEM normalization process uses rotation, translation, scaling, and shearing transformations to achieve pixel-level registration of DEM data at different resolutions, so as to minimize the grayscale difference and maximize the grayscale correlation of the registered DEM data.

[0024] Optionally, based on the normalized DEM data and the transformed coordinate information, 3D docking ore body processing is performed to obtain a docked three-dimensional ore body model, specifically including the following steps.

[0025] The pinch-out point of the ore body is determined by interpolation, finite inference, or infinite inference.

[0026] Based on the pinch-out point of the ore body, the normalized DEM data, and the transformed coordinate information, the ore body is modeled in three dimensions using the natural nearest neighbor method, the inverse power distance method, or the Kriging method, respectively constructing an oblique photogrammetry real-scene 3D model and an ore body 3D model.

[0027] The oblique photogrammetry real-scene 3D model and the ore body 3D model are converted to the same coordinate system, and the two are registered by translation, rotation and scale change parameters to obtain the registered model.

[0028] The intersecting, containing, or unrelated relationships of the registered models are determined, and the intersecting parts are cut and modeled. The intersecting parts and unrelated parts after cutting and modeling are used as the three-dimensional ore body model after docking.

[0029] Optionally, the formula for calculating the earthwork volume is as follows.

[0030] .

[0031] .

[0032] .

[0033] in, The earthwork volume of the quota. The distance between every two cross sections. Each pair of cross sections forms a trapezoidal frustum. , These are the cross-sectional areas of D1 and D2, respectively. The distance between the three sides of the upper broken triangle is denoted as . The distance between the three sides of the lower triangular facet is given. This refers to the number of blocks used in calculating the cross-sectional area. The total number of blocks used.

[0034] Optionally, the annual resource utilization of the open-pit mine includes the amount of ore utilized and the amount of metal utilized.

[0035] Based on the earthwork volume, the annual resource utilization of the open-pit mine is calculated, which includes the following steps.

[0036] Using formula Calculate the amount of ore used, and use the formula. Calculate the amount of metal used; wherein, To utilize the amount of ore, To utilize the total number of blocks, For the first The volume of each active block. For the first Density of each active block segment In order to utilize the amount of metal, Let be the grade of the i-th activated block segment.

[0037] Based on the earthwork volume, the volume of the moved blocks, and the preset threshold, the formula is used. Verify the validity of the annual resource utilization volume of the open-pit mine; wherein... The earthwork volume of the quota. This is a preset threshold.

[0038] When satisfied When the annual resource utilization of the open-pit mine is deemed valid, it is determined that the utilization rate is valid.

[0039] Optionally, based on the annual resource utilization of the open-pit mine, a monitoring result map of the annual resource utilization of the open-pit mine is generated using a vector and raster overlay method, specifically including the following steps.

[0040] Based on the annual resource utilization of the open-pit mine, the UAV oblique photography data is processed using RGB color compositing. Vector data and raster data are overlaid in coordinate layers to output a monitoring result map of the annual resource utilization of the open-pit mine in GIS, JPG, or TIF format.

[0041] Secondly, this application provides an annual resource utilization monitoring system for open-pit mines, which is used to implement the annual resource utilization monitoring method for open-pit mines as described in any of the first aspects. The annual resource utilization monitoring system for open-pit mines includes the following modules.

[0042] The multi-source remote sensing data acquisition module is used to acquire multi-source remote sensing data and perform data filtering and control point correction preprocessing on the multi-source remote sensing data to obtain preprocessed multi-source remote sensing data; the multi-source remote sensing data includes UAV lidar data, UAV oblique photography data, high-resolution satellite remote sensing data, and InSAR data.

[0043] The DEM processing and 3D docking module is used to perform DEM extraction, DEM normalization and 3D docking of the ore body based on the preprocessed multi-source remote sensing data, so as to obtain the docked three-dimensional ore body model.

[0044] The earthwork volume calculation module is used to calculate the earthwork volume of the open-pit mine mining area based on the docked three-dimensional ore body model.

[0045] The resource utilization calculation module is used to calculate the annual resource utilization of the open-pit mine based on the earthwork volume.

[0046] The result map output module is used to generate a monitoring result map of the annual resource utilization of the open-pit mine based on the annual resource utilization of the open-pit mine, using vector and raster overlay methods.

[0047] According to the specific embodiments provided in this application, this application has the following technical effects.

[0048] This application provides a method and system for monitoring the annual resource utilization of open-pit mines. It acquires objective data sources through multi-source remote sensing data, including UAV lidar, UAV oblique photography, high-resolution satellite remote sensing, and InSAR. Combined with control point correction, it achieves full-range precision control, ensuring that the monitoring data accurately reflects the annual resource utilization of the mine and guaranteeing the accuracy and reliability of the monitoring results. Addressing past issues of missing UAV oblique photography and discontinuous satellite data, this application allows for flexible selection of single or multiple data sources for monitoring by filtering multi-source remote sensing data. Furthermore, DEM normalization technology unifies the coordinates and elevation benchmarks of data at different resolutions, enabling effective adaptation and collaborative application of multi-source data. 3D orebody docking technology facilitates unified resolution and precise 3D docking. Based on the docked 3D orebody model, the earthwork volume of the open-pit mine area is calculated, and the annual resource utilization of the open-pit mine is further estimated. This effectively improves the accuracy and efficiency of annual resource utilization monitoring, solving the problems of low accuracy and low efficiency inherent in traditional manual monitoring methods. By constructing a complete technical process of "data acquisition - preprocessing - model building - measurement - mapping," the technical methods of each step are clear and seamlessly connected. Compared with traditional manual monitoring methods, it eliminates the need for extensive on-site measurements, significantly shortens the monitoring cycle, simplifies the monitoring process, and improves monitoring efficiency, providing a rapid means for investigating the annual consumption of mineral resources. By employing vector and raster overlay methods to generate monitoring results maps of the annual resource utilization of open-pit mines, the annual utilization scope and resource quantity information of open-pit mines are clearly presented. This aligns with human visual observation habits and provides intuitive and reliable visual support for the investigation, evaluation, and regulatory decision-making of mineral resource utilization. The results are intuitive, easy to understand, and convenient for application and promotion. Attached Figure Description

[0049] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0050] Figure 1 This is an application environment diagram of a method for monitoring the annual resource utilization of open-pit mines, provided as an embodiment of this application.

[0051] Figure 2 This is a flowchart illustrating a method for monitoring the annual resource utilization of an open-pit mine, as provided in an embodiment of this application.

[0052] Figure 3 This is a schematic diagram illustrating the principle of a method for monitoring the annual resource utilization of an open-pit mine, as provided in an embodiment of this application.

[0053] Figure 4 This is a schematic diagram of calibration points and ranging control points provided in one embodiment of this application.

[0054] Figure 5 This is a schematic diagram of an intersection, unrelated, and inclusion model provided for an embodiment of this application.

[0055] Figure 6 This is a schematic diagram of the structure of an annual resource utilization monitoring system for open-pit mines, provided as an embodiment of this application. Detailed Implementation

[0056] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0057] The purpose of this application is to provide a method and system for monitoring the annual resource utilization of open-pit mines, which can improve the accuracy and efficiency of monitoring the annual resource utilization of mines, solve the problems of poor data objectivity, incomplete coverage and insufficient accuracy of existing monitoring methods, and realize efficient and accurate monitoring of the annual resource utilization of open-pit mines.

[0058] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0059] The method for monitoring annual resource utilization in open-pit mines provided in this application embodiment can be applied to, for example... Figure 1 In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be set up independently, integrated into server 104, or placed in the cloud or on other servers. Terminal 102 can send multi-source remote sensing data to server 104. After receiving the multi-source remote sensing data, server 104 performs data filtering and control point correction preprocessing on the multi-source remote sensing data to obtain preprocessed multi-source remote sensing data. Based on the preprocessed multi-source remote sensing data, DEM (Digital Elevation Model) extraction, DEM normalization, and 3D docking ore body processing are performed to obtain a docked three-dimensional ore body model. Based on the docked three-dimensional ore body model, the earthwork volume of the open-pit mine mining area is calculated. Based on the earthwork volume, the annual resource utilization of the open-pit mine is calculated. Based on the annual resource utilization of the open-pit mine, a vector and raster overlay method is used to generate a monitoring result map of the annual resource utilization of the open-pit mine. Server 104 can feed back the obtained video tags for the video to terminal 102. Furthermore, in some embodiments, the method for monitoring the annual resource utilization of open-pit mines can also be implemented independently by server 104 or terminal 102. For example, terminal 102 can directly perform data processing and resource utilization monitoring on multi-source remote sensing data, or server 104 can obtain multi-source remote sensing data from the data storage system and perform preprocessing, data processing, and computation on the multi-source remote sensing data.

[0060] The terminal 102 can be, but is not limited to, various desktop computers, laptops, smartphones, tablets, and IoT devices. The server 104 can be implemented using a standalone server or a server cluster consisting of multiple servers, or it can be a cloud server.

[0061] In one exemplary embodiment, such as Figure 2 As shown, a method for monitoring the annual resource utilization of open-pit mines is provided. This method is executed by computer equipment, specifically by a terminal or server alone, or by both a terminal and a server. In this embodiment, the method is applied to... Figure 1 Taking server 104 as an example, the explanation includes the following steps S1 to S5.

[0062] S1: Acquire multi-source remote sensing data, and perform data filtering and control point correction preprocessing on the multi-source remote sensing data to obtain preprocessed multi-source remote sensing data. The multi-source remote sensing data includes UAV lidar data, UAV oblique photography data, high-resolution satellite remote sensing data, and InSAR (Interferometric Synthetic Aperture Radar) data.

[0063] S2: Based on the preprocessed multi-source remote sensing data, DEM extraction, DEM normalization, and 3D docking ore body processing are performed to obtain the docked three-dimensional ore body model.

[0064] S3: Calculate the earthwork volume of the open-pit mine mining area based on the docked three-dimensional ore body model.

[0065] S4: Based on the earthwork volume, calculate the annual resource utilization of the open-pit mine.

[0066] S5: Based on the annual resource utilization of the open-pit mine, a monitoring result map of the annual resource utilization of the open-pit mine is generated using vector and raster overlay methods.

[0067] Implementing steps S1 to S5 above can improve the accuracy and efficiency of monitoring the annual resource utilization of mines, solve the problems of poor data objectivity, incomplete coverage and insufficient accuracy of existing monitoring methods, and achieve efficient and accurate monitoring of the annual resource utilization of open-pit mines.

[0068] As an optional implementation, step S1 acquires multi-source remote sensing data and performs data filtering and control point correction preprocessing on the multi-source remote sensing data to obtain preprocessed multi-source remote sensing data, specifically including the following steps.

[0069] S11: Acquire multi-source remote sensing data.

[0070] S12: Perform data filtering on the multi-source remote sensing data, determine the priority order of various types of data in the multi-source remote sensing data according to the data accuracy, and obtain the filtered multi-source remote sensing data.

[0071] S13: Perform control point correction on the screened multi-source remote sensing data to obtain preprocessed multi-source remote sensing data.

[0072] As an optional implementation, in step S12, the priority order for data filtering based on the data accuracy is: UAV lidar data > UAV oblique photography data > high-resolution satellite remote sensing data > InSAR data.

[0073] As an optional implementation, in step S13, the control point correction includes uniformly distributing horizontal control points and vertical control points within the monitoring range.

[0074] As an optional implementation, step S2 involves extracting the DEM, normalizing the DEM, and processing the ore body in 3D docking based on the preprocessed multi-source remote sensing data to obtain the docked three-dimensional ore body model, specifically including the following steps.

[0075] S21: Based on the preprocessed multi-source remote sensing data, DEM data is extracted.

[0076] S22: Based on the preprocessed multi-source remote sensing data, perform coordinate transformation from camera coordinates to geodetic coordinates to obtain the transformed coordinate information.

[0077] S23: Based on the transformed coordinate information and the DEM data, perform DEM normalization processing to obtain normalized DEM data.

[0078] S24: Based on the normalized DEM data and the transformed coordinate information, perform 3D docking ore body processing to obtain the docked three-dimensional ore body model.

[0079] As an optional implementation, in step S23, the DEM normalization process achieves pixel-level registration of DEM data at different resolutions through rotation, translation, scaling and shearing transformations, so as to minimize the grayscale difference and maximize the grayscale correlation of the registered DEM data.

[0080] As an optional implementation, step S24 performs 3D docking ore body processing based on the normalized DEM data and the transformed coordinate information to obtain a docked three-dimensional ore body model, specifically including the following steps.

[0081] S241: Use interpolation, finite inference, or infinite inference to determine the pinch-out point of the ore body.

[0082] S242: Based on the pinch-out point of the ore body, the normalized DEM data, and the transformed coordinate information, the ore body is modeled in three dimensions using the natural nearest neighbor method, the inverse power distance method, or the Kriging method, and an oblique photogrammetry real-scene three-dimensional model and an ore body three-dimensional model are constructed respectively.

[0083] S243: Transform the oblique photogrammetry real-scene 3D model and the ore body 3D model to the same coordinate system, and register the two through translation, rotation and scale change parameters to obtain the registered model.

[0084] S244: Determine the intersection, inclusion, or unrelated relationships of the registered models, and cut and model the intersection parts, using the cut and modeled intersection parts and unrelated parts as the docked three-dimensional ore body model.

[0085] As an optional implementation, in step S4, the annual resource utilization of the open-pit mine includes the utilization of ore and the utilization of metal.

[0086] Step S4 calculates the annual resource utilization of the open-pit mine based on the earthwork volume, specifically including the following steps.

[0087] S41: Use formula Calculate the amount of ore used, and use the formula. Calculate the amount of metal used; wherein, To utilize the amount of ore, To utilize the total number of blocks, For the first The volume of each active block. For the first Density of each active block segment In order to utilize the amount of metal, For the first Each segment uses a quality grade.

[0088] S42: Based on the earthwork volume, the volume of the moved blocks, and the preset threshold, the formula is used. Verify the validity of the annual resource utilization volume of the open-pit mine; wherein... The earthwork volume of the quota. A preset threshold is used. The validity of the annual resource utilization of the open-pit mine is verified, including the following two scenarios.

[0089] (1) When satisfied When the annual resource utilization of the open-pit mine is deemed valid, it is determined that the utilization rate is valid.

[0090] (2) When satisfied If the annual resource utilization of the open-pit mine is deemed invalid, the process returns to the registration process in step S243, and the registration and calculation are repeated until the above conditions are met, i.e., the annual resource utilization of the open-pit mine is valid.

[0091] As an optional implementation, step S5 generates a monitoring result map of the annual resource utilization of the open-pit mine based on the annual resource utilization of the open-pit mine using a vector and raster overlay method, specifically including the following steps.

[0092] Based on the annual resource utilization of the open-pit mine, the UAV oblique photography data is processed using RGB color compositing. Vector data and raster data are overlaid in coordinate layers to output a monitoring result map of the annual resource utilization of the open-pit mine in GIS, JPG, or TIF format.

[0093] To make the technical solution of this application clearer, the specific implementation process of the technical solution of this application will be explained in detail below with examples.

[0094] This application employs satellite InSAR, UAV oblique photography, high-resolution satellite stereo image pairs, and lidar technologies to investigate the annual resource utilization of open-pit mines. This addresses the issues of insufficient and discontinuous satellite data, stemming from the lack of UAV oblique photography in previous years. One method is chosen for DEM calculation: UAV lidar and UAV oblique photography are prioritized for DEM extraction; high-resolution satellite remote sensing is used to extract DEM from annual open-pit mine images; and finally, InSAR technology is used. For data with varying resolutions, modeling techniques are used to standardize the resolution and calculate mine resource utilization. Then, the annual earthwork volume of open-pit mines is compared, and the resource utilization is calculated using a block method. The core technologies are resolution standardization and three-dimensional alignment of the ore body. This application provides a new method for investigating the annual resource utilization of open-pit mines, primarily solving the problem of real-time investigation. It offers a rapid new method for assessing annual mineral resource consumption and is of great significance for the investigation and evaluation of mineral resource utilization. This application mainly utilizes multi-source remote sensing technology to investigate the annual resource utilization of open-pit mines; the specific methods and steps are as follows.

[0095] The methodology in this application includes multiple aspects such as data source acquisition and selection, high-precision geometric positioning, DEM extraction and normalization, 3D docking of ore bodies, earthwork quota calculation, resource utilization estimation, and final mapping. Figure 3 As shown, it mainly includes the following contents.

[0096] (1) Data preprocessing, including the following.

[0097] 1) Data acquisition.

[0098] Data acquisition methods include high-resolution satellite data, InSAR data, lidar data, and UAV oblique photography, each with its own quality requirements. High-resolution satellite data requires acquiring optical remote sensing stereo image pairs with no clouds, snow, or sparse vegetation. InSAR data requires acquiring short-term master-slave image pairs. UAV oblique photography typically involves defining the area, planning flight paths, and setting up calibration and ranging control points to acquire image data from five cameras. LiDAR directly acquires ground elevation data.

[0099] 2) Data selection.

[0100] Based on accuracy, the preferred data is generally UAV lidar data, followed by UAV oblique photography data, then high-resolution satellite remote sensing data, and finally InSAR data. Alternatively, two or more types of data can be selected for cross-validation.

[0101] 3) Control point calibration.

[0102] All data requires control point calibration. Generally, control points are selected evenly distributed within a given range. For elevation control points, some distance-measuring (horizontal and vertical) control points can also be established, such as... Figure 4 As shown, it provides comprehensive control precision.

[0103] Figure 4 The calibration points in the image are ground-based measured points with accurate spatial information (including longitude, latitude, and elevation). Line segments are distance measurement points, representing the distance from one point to another, including both length and orientation. The main function is to control the accurate spatial position of each point on the image, and the distance and orientation between two points within the image.

[0104] (2) Data processing, including the following.

[0105] 1) The following methods can be used to extract the DEM from the data.

[0106] ① The DEM is extracted using UAV oblique photography, mainly by extracting the DEM camera center point through collinearity equations. Like a dot and target point The three are collinear, and through a rotation matrix Translation vector Establish the proportional relationship as follows.

[0107] .

[0108] in, For camera focal length, This is the scaling factor.

[0109] By rotation matrix Then we have the following formula.

[0110] .

[0111] .

[0112] Ground elevation points can be calculated using collinearity equations. .

[0113] ② Calculate the DEM using lidar.

[0114] LiDAR primarily calculates elevation using the triangulation method. It can be calculated using the time method, phase difference method, or triangular reflection method. The calculation formula for the time method is as follows.

[0115] .

[0116] in, At the speed of light, This is the time difference between laser emission and reception.

[0117] The formula for calculating the phase difference method is as follows.

[0118] .

[0119] in, At the speed of light, The phase difference between the transmitted wave and the echo. For modulation frequency, This embodiment uses pi (π) as the mathematical constant. The value is 3.14.

[0120] The formula for calculating the triangular reflection method is as follows.

[0121] .

[0122] in, The location of the light spot. The distance between the laser and the sensor. For camera focal length, The angle of incidence is denoted as .

[0123] ③ Satellite stereo relative calculation of DEM.

[0124] Calculate the 3D coordinates using the camera model, including the pixel coordinates of the two cameras. x 1, y 1) and ( x 2, y 2) Camera distance parallax Camera focal length Target point coordinates The coordinates of the target point can then be calculated using the following formula.

[0125] .

[0126] .

[0127] .

[0128] ④ Calculate DEM from InSAR image pairs.

[0129] Master-slave image phase difference Elevation can be calculated based on phase difference and radar wavelength, as shown in the following formula.

[0130] .

[0131] in, For elevation, For radar wavelength, From a radar perspective, The master-slave image phase difference, and , and These are the phases of the master and slave images, respectively.

[0132] 2) Coordinate transformation and precision control, including the following:

[0133] ① Coordinate transformation is mainly the process of transforming image coordinates to geodetic coordinates, primarily through the transformation from camera coordinates to geodetic coordinates.

[0134] According to the camera focal length Principal point coordinates ( , ),Location and attitude angle Assuming the image coordinates are The distance from the camera to the target point is So, camera coordinates The formula for calculating is as follows.

[0135] .

[0136] .

[0137] .

[0138] The formula for converting camera coordinates to geodetic coordinates is as follows.

[0139] .

[0140] in, Let be a geodetic coordinate point, and its coordinates are... , For rotation matrix, T It is a translation vector.

[0141] (3) Normalized DEM.

[0142] Because images from different data sources have varying resolutions, normalization is necessary for further processing. This is particularly important in 3D imagery. That is, coordinates and elevation, with a resolution of [missing information]. The elevation resolution is Common transformations include translation, rotation, and scaling, with the source image coordinates... , , Target image , , If the rotation matrix is The translation vector is T Scaling factor is Shearing factor Then we have the following formula.

[0143] .

[0144] .

[0145] for dot pixel and dot pixel The corresponding gray levels are respectively , , Scaling factor Shearing factor , , As a translation vector factor, pixel-level registration can be achieved using the evaluation mean square error, and the maximum grayscale can be achieved through the two pixels. and variance The minimum value is calculated using the following formula.

[0146] .

[0147] .

[0148] in, This represents the number of relevant known points.

[0149] (4) 3D docking of ore bodies.

[0150] In this embodiment, estimating the amount of ore body resources to be utilized first requires 3D docking of the ore body with the oblique photogrammetry 3D model. After the calculation and modeling, the obtained result is a 3D spatial coordinate in a coordinate system. Most mines use cross-sectional descriptions for their ore bodies, which require the creation of a 3D model. The oblique photogrammetry real-scene 3D model and the ore body 3D model are visually surface features. After docking, there are various relationships such as intersection, overlap, and inclusion. These relationships need to be interpreted before remodeling.

[0151] 1) Ore body modeling: First, use interpolation, finite inference or infinite inference to determine the pinch-out point of the ore body.

[0152] The interpolation method mainly obtains the boundary reference points through interpolation, and the specific formula is as follows.

[0153] .

[0154] in, This is the distance from the borehole where the ore was found to the boundary of the ore body. Grade at the boundary of the ore body , Drilling for industrial mineral deposits Non-industrial mineral drilling The grade of the ore body, This represents the distance between two boreholes. If the ore body thickness in a borehole that has not encountered ore is less than the minimum minable thickness but the grade meets the requirements, then the following formula applies.

[0155] .

[0156] in, , Drilling holes to find mineral deposits Non-industrial mineral drilling The thickness of the ore body This is the minimum mineable thickness.

[0157] 2) Common interpolation methods for 3D modeling of ore bodies include the natural critical point method, the inverse power distance method, and the Kriging method.

[0158] The natural nearest neighbor method uses the dual graph of the triangular network to interpolate arbitrary points, and the formula is as follows.

[0159] 。

[0160] in, Information values ​​for known points; The distance between the point to be interpolated and its naturally nearest known points; The critical influence distance. This represents the number of relevant known points; For the first The value of the interpolation point obtained from each known point individually.

[0161] For the inverse power law of distance, it is assumed that the known point and interpolation points The closer the distance, the greater the correlation. The main calculation formula is as follows.

[0162] .

[0163] in, The distance from the interpolation point to the known point. It is a power exponent.

[0164] For the Kriging method, based on the covariance, the interpolation points are minimized through linear regression, as shown in the following formula.

[0165] 。

[0166] in, Given the point value, The weights can be solved using a combination of functions.

[0167] .

[0168] in, for The values ​​of the two-point distance model variable graph.

[0169] 3) Registration of the ore body with the 3D image model.

[0170] First, the ore body and the image need to be transformed to the same coordinate system, two projected coordinate systems. Switch to The origin of both O 1 and O 2. They are different; the coordinate axes are not parallel. During transformation, in addition to the translation parameters... Euler angle is still needed , , Corresponding rotation parameters α , β , γ Additionally, scale variation parameters need to be set. There are a total of 7 transformation parameters, and the transformed coordinates are consistent with the coordinates of the 3D model.

[0171] .

[0172] .

[0173] .

[0174] .

[0175] .

[0176] in, , 、 This is the transformation matrix.

[0177] 4) Processing for docking orebody 3D models with open-pit mine image 3D models: This mainly includes docking based on intersection, inclusion, and irrelevance, such as... Figure 5 As shown, the activity monitoring data for open-pit mines are either intersecting or uncorrelated. If the ore body is not fully mined, the activity data is intersecting; if the ore body is fully mined, the activity data is uncorrelated.

[0178] In this embodiment, when determining intersection, a triangular mesh based on image modeling is used. T 1. Triangular mesh of the ore body model T 2. Calculate the intersection line M Intersection M With triangular mesh T 1 and T The intersection of 2 A , B , C , D Forming intervals [ A , B ]and[ C , D If they overlap, they intersect; otherwise, they do not intersect.

[0179] For ore bodies that are not related to the 3D model of the open-pit mine image A ,common n The first block segment, according to the first... Volume of each block ,density ,grade Ore quantity and metal content The total resource volume of the entire ore body is directly included in the utilization volume, expressed as the following formula.

[0180] .

[0181] For intersecting ore bodies, the intersecting portion needs to be cut out before calculation. The intersection includes the line of intersection between the ore body and the ground of the 3D image model. The surface within the intersection line is used as the top surface of the ore body for modeling. The intersection line and the triangular mesh form a closed polygon; triangular meshes are constructed for the vertices of the polygon. The resulting polygon vertices […]. V 1, V 2, V 3, ..., Vn Take three points in sequence and determine if they are collinear. If they are collinear, delete the intermediate point and repeat the above process until finished. Determine the concavity and convexity of the vertices using normal vector calculation. These triangular meshes are constructed into surfaces using a TIN (Triangulated Irregular Network) to serve as the top surface of the docked 3D ore body model.

[0182] (5) Calculation of earthwork quota.

[0183] Open-pit mining involves not only extracting the ore body but also the surrounding rock. Therefore, the earthwork quota refers to the earthwork volume of the ore body, and thus mainly calculates the earthwork volume of the mined portion of the ore body. T Assume the top surface constructed in the first year is... S 1. The top surface constructed in the second year is S 2. How to use the top surface of the second year as the bottom surface, the top surface of the first year as the top surface, and the side surface of the ore body as the side surface to form a volume? This volume is the earthwork quota calculation quantity.

[0184] This embodiment will S 1 and S 2. The earthwork and rock excavation formed by the side of the ore body are divided along a certain direction. n Each segment has two cross-sections. and The cross-sectional area is divided into sections by calculating the cross-sectional area using a DTM network. m The area of ​​a small triangular mesh. The cross-sectional area is , The cross-sectional area is Then we have the following formula.

[0185] .

[0186] .

[0187] in, , They are respectively Cross-sectional area Cross-sectional area, The distance between the three sides of the upper broken triangle is denoted as . The distance between the three sides of the lower triangular facet is given. This refers to the number of blocks used when calculating the cross-sectional area.

[0188] Each pair of cross sections forms a trapezoidal frustum. , The distance between the three sides of the upper broken triangle is denoted as . Given the distances between the three sides of the lower triangular face, the earthwork volume is calculated using the following formula.

[0189] .

[0190] in, The earthwork volume of the quota. The distance between every two cross sections. Each pair of cross sections forms a trapezoidal frustum. To utilize the total number of blocks, i.e., the top surface constructed in the first year. S 1. The top surface constructed in the second yearS 2. The number of working blocks formed by the earthwork and rock excavation along a certain direction, consisting of the side of the ore body.

[0191] (6) Estimate of the amount of resources to be used, including the following.

[0192] 1) Resource estimation: The estimation parameters, methods, and block divisions for all types of resources should be consistent with the exploration report. The industrial indicators for the deposit should be consistent with current industrial indicators; any inconsistencies between the industrial indicators in the report and current industrial indicators should be corrected to the current indicators.

[0193] In this embodiment, the basic parameters for resource estimation include the area, average thickness, dip angle, grade, and average weight of the ore body within the utilization range. Sometimes, ore moisture content and ore-bearing coefficient are also included. The data should be based on the most recent exploration report. The location of the profile lines is selected based on factors such as the geological body occurrence, faults, and exploration projects. The vertical profile method is used to create the boundary lines of each profile line, which are then projected onto the reserve estimation map. The boundary points of each profile line are connected to delineate the utilization range.

[0194] Based on the scope of resource utilization, the amount of overburden is calculated using geometric methods (arithmetic mean method, geological block method, mining block method, cross-section method, contour line method, linear reserve method, trigonometric method, nearest area method, polygonal method), statistical analysis methods (distance-weighted method, kriging method), and the SD (inverse power-proportional-moving average) method. The geological block method and the cross-section method are commonly used. Overburden is a core component of the utilized resource volume, and the two are essentially the same in the open-pit mine monitoring scenario (i.e., the actual amount of resources consumed during mining). Calculating overburden is a crucial step in mineral resource management. Its purpose is to accurately calculate the actual annual mineral resource consumption of open-pit mines, ensure that resource development complies with planning targets, and provide data support for the collection of mineral resource compensation fees and the review of mining compliance.

[0195] This embodiment uses the geological block method to calculate the amount of ore and metal mobilized in the resource utilization, respectively. The calculation formula is as follows.

[0196] The formula for calculating the amount of ore used is as follows.

[0197] .

[0198] in, To utilize the amount of ore, To utilize the total number of blocks, For the first The volume of each active block. For the first Individual block density.

[0199] The formula for calculating the amount of metal used is as follows.

[0200] .

[0201] in, In order to utilize the amount of metal, For the first Each segment uses a quality grade.

[0202] 2) Verification of resource utilization: Verify the estimated volume of ore utilized (volume of all utilized blocks). (sum of) and earthwork volume If the absolute value of the difference between the two is less than or equal to a preset threshold ε, the resource utilization calculation is considered valid; otherwise, the resource utilization is recalculated starting from the registration of the ore body and the 3D image model. In this embodiment, the preset threshold ε can be set as the earthwork volume. 0.05~0.1 (ie 5%~10%).

[0203] .

[0204] (7) The final image can be generated using either of the following two methods.

[0205] 1) Vector and raster overlay method. The optimized annual mobilization range vector is input, along with the bands R (red): 669.43nm, G (green): 538.96nm, B (blue): 479.25nm from oblique photography, serving as input for the RGB (red, green, blue) color composite image. The composite color image uses points, lines, and surfaces with the same projection to represent the vectors. The raster and vector are then overlaid using coordinate layering.

[0206] For vectors ,in, For the corresponding coordinates, For eigenvalues, Vector values, raster , and For the corresponding coordinates, Let be the raster grayscale value. Thus achieving a grid Grayscale values ​​and vectors The process involves overlaying raster and vector data using corresponding coordinates to output a GIS vector and raster overlay image. This creates an image that is visually appealing to the human eye.

[0207] 2) Input the UAV oblique photography image and the annual usage range, and output a GIS format overlay image suitable for human observation. The final image can be output as a JPG or TIF format through software.

[0208] Based on the same inventive concept, this application also provides an open-pit mine annual resource utilization monitoring system for implementing the above-mentioned open-pit mine annual resource utilization monitoring method. The solution provided by this open-pit mine annual resource utilization monitoring system is similar to the solution described in the above-described method. Therefore, the specific limitations in the following embodiments of the open-pit mine annual resource utilization monitoring system can be found in the limitations of the open-pit mine annual resource utilization monitoring method described above, and will not be repeated here.

[0209] In one exemplary embodiment, such as Figure 6 As shown, an annual resource utilization monitoring system for open-pit mines is provided, which includes the following modules.

[0210] The multi-source remote sensing data acquisition module is used to acquire multi-source remote sensing data and perform data filtering and control point correction preprocessing on the multi-source remote sensing data to obtain preprocessed multi-source remote sensing data; the multi-source remote sensing data includes UAV lidar data, UAV oblique photography data, high-resolution satellite remote sensing data, and InSAR data.

[0211] The DEM processing and 3D docking module is used to perform DEM extraction, DEM normalization and 3D docking of the ore body based on the preprocessed multi-source remote sensing data, so as to obtain the docked three-dimensional ore body model.

[0212] The earthwork volume calculation module is used to calculate the earthwork volume of the open-pit mine mining area based on the docked three-dimensional ore body model.

[0213] The resource utilization calculation module is used to calculate the annual resource utilization of the open-pit mine based on the earthwork volume.

[0214] The result map output module is used to generate a monitoring result map of the annual resource utilization of the open-pit mine based on the annual resource utilization of the open-pit mine using vector and raster overlay methods.

[0215] This application integrates multi-source remote sensing data, adopts a precision-first screening principle, and combines control point correction technology to ensure the objectivity and reliability of monitoring data, solving the accuracy problems caused by the reliance on manual reporting and sampling in traditional methods. DEM normalization processing achieves resolution uniformity across different data sources, and 3D docking technology enables precise matching between the ore body and the 3D model, effectively solving technical challenges such as discontinuous satellite data and low model docking accuracy, thus improving monitoring accuracy. Automated earthwork calculation and resource estimation processes, coupled with visualized mapping of results, significantly improve monitoring efficiency, providing a fast and efficient technical means for annual mineral resource consumption surveys, and are of great significance for the evaluation of mineral resource development and utilization.

[0216] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0217] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for monitoring the annual resource utilization of open-pit mines, characterized in that, The method for monitoring the annual resource utilization of open-pit mines includes: Acquire multi-source remote sensing data, and perform data filtering and control point correction preprocessing on the multi-source remote sensing data to obtain preprocessed multi-source remote sensing data; the multi-source remote sensing data includes UAV lidar data, UAV oblique photography data, high-resolution satellite remote sensing data, and InSAR data; Based on the preprocessed multi-source remote sensing data, DEM extraction, DEM normalization and 3D docking ore body processing are performed to obtain the docked three-dimensional ore body model. Based on the docked three-dimensional ore body model, calculate the earthwork volume of the open-pit mining area; Based on the earthwork volume, calculate the annual resource utilization of the open-pit mine; Based on the annual resource utilization of the open-pit mine, a monitoring map of the annual resource utilization of the open-pit mine is generated using vector and raster overlay methods.

2. The method for monitoring annual resource utilization in open-pit mines according to claim 1, characterized in that, Acquire multi-source remote sensing data, and perform data filtering and control point correction preprocessing on the multi-source remote sensing data to obtain preprocessed multi-source remote sensing data, specifically including: Acquire multi-source remote sensing data; The multi-source remote sensing data is filtered, and the priority order of various types of data in the multi-source remote sensing data is determined according to the data accuracy to obtain the filtered multi-source remote sensing data. Control point correction is performed on the filtered multi-source remote sensing data to obtain preprocessed multi-source remote sensing data.

3. The method for monitoring annual resource utilization in open-pit mines according to claim 2, characterized in that, The priority order for data filtering is: UAV lidar data > UAV oblique photography data > high-resolution satellite remote sensing data > InSAR data; The control point correction includes uniformly distributing horizontal and vertical control points within the monitoring range.

4. The method for monitoring annual resource utilization in open-pit mines according to claim 1, characterized in that, Based on the preprocessed multi-source remote sensing data, DEM extraction, DEM normalization, and 3D docking ore body processing are performed to obtain the docked 3D ore body model, specifically including: Based on the preprocessed multi-source remote sensing data, DEM data is extracted; Based on the preprocessed multi-source remote sensing data, a coordinate transformation from camera coordinates to geodetic coordinates is performed to obtain the transformed coordinate information; Based on the transformed coordinate information and the DEM data, DEM normalization processing is performed to obtain normalized DEM data; Based on the normalized DEM data and the transformed coordinate information, 3D docking ore body processing is performed to obtain the docked three-dimensional ore body model.

5. The method for monitoring annual resource utilization in open-pit mines according to claim 4, characterized in that, The DEM normalization process uses rotation, translation, scaling, and shearing transformations to achieve pixel-level registration of DEM data at different resolutions, so as to minimize the grayscale differences and maximize the grayscale correlation of the registered DEM data.

6. The method for monitoring annual resource utilization in open-pit mines according to claim 4, characterized in that, Based on the normalized DEM data and the transformed coordinate information, 3D docking ore body processing is performed to obtain the docked three-dimensional ore body model, specifically including: The pinch-out point of the ore body can be determined using interpolation, finite inference, or infinite inference methods. Based on the pinch-out point of the ore body, the normalized DEM data, and the transformed coordinate information, the natural nearest neighbor method, the inverse power distance method, or the Kriging method are used to perform 3D modeling of the ore body, and respectively construct oblique photogrammetry real-scene 3D model and ore body 3D model. The oblique photogrammetry real-scene 3D model and the ore body 3D model are transformed to the same coordinate system, and the two are registered by translation, rotation and scale change parameters to obtain the registered model. The intersecting, containing, or unrelated relationships of the registered models are determined, and the intersecting parts are cut and modeled. The intersecting parts and unrelated parts after cutting and modeling are used as the three-dimensional ore body model after docking.

7. The method for monitoring annual resource utilization in open-pit mines according to claim 1, characterized in that, The formula for calculating the volume of earth and rock is: ； ； ； in, The earthwork volume of the quota. The distance between every two cross sections. Each pair of cross sections forms a trapezoidal frustum. , These are the cross-sectional areas of D1 and D2, respectively. The distance between the three sides of the upper broken triangle is denoted as . The distance between the three sides of the lower triangular facet is given. This refers to the number of blocks used in calculating the cross-sectional area. The total number of blocks used.

8. The method for monitoring annual resource utilization in open-pit mines according to claim 1, characterized in that, The annual resource utilization of the open-pit mine includes the amount of ore utilized and the amount of metal utilized; Based on the aforementioned earthwork volume, the annual resource utilization of the open-pit mine is calculated, specifically including: Using formula Calculate the amount of ore used, and use the formula. Calculate the amount of metal used; wherein, To utilize the amount of ore, To utilize the total number of blocks, For the first The volume of each active block. For the first Density of each active block segment In order to utilize the amount of metal, The grade of the i-th activated block segment; Based on the earthwork volume, the volume of the moved blocks, and the preset threshold, the formula is used. Verify the validity of the annual resource utilization volume of the open-pit mine; wherein... The earthwork volume of the quota. The preset threshold; When satisfied When the annual resource utilization of the open-pit mine is deemed valid, it is determined that the utilization rate is valid.

9. The method for monitoring annual resource utilization in open-pit mines according to claim 1, characterized in that, Based on the annual resource utilization of the open-pit mine, a monitoring map of the annual resource utilization of the open-pit mine is generated using vector and raster overlay methods, specifically including: Based on the annual resource utilization of the open-pit mine, the UAV oblique photography data is processed using RGB color compositing. Vector data and raster data are overlaid in coordinate layers to output a monitoring result map of the annual resource utilization of the open-pit mine in GIS, JPG, or TIF format.

10. A monitoring system for annual resource utilization in open-pit mines, characterized in that, The open-pit mine annual resource utilization monitoring system is used to implement the open-pit mine annual resource utilization monitoring method according to any one of claims 1-9, and the open-pit mine annual resource utilization monitoring system includes: The multi-source remote sensing data acquisition module is used to acquire multi-source remote sensing data and perform data filtering and control point correction preprocessing on the multi-source remote sensing data to obtain preprocessed multi-source remote sensing data; the multi-source remote sensing data includes UAV lidar data, UAV oblique photography data, high-resolution satellite remote sensing data and InSAR data; The DEM processing and 3D docking module is used to perform DEM extraction, DEM normalization and 3D docking of the ore body based on the preprocessed multi-source remote sensing data to obtain the docked three-dimensional ore body model. The earthwork volume calculation module is used to calculate the earthwork volume of the open-pit mine mining area based on the docked three-dimensional ore body model. The resource utilization calculation module is used to calculate the annual resource utilization of the open-pit mine based on the earthwork volume; The result map output module is used to generate a monitoring result map of the annual resource utilization of the open-pit mine based on the annual resource utilization of the open-pit mine, using vector and raster overlay methods.

Images