An open-pit blasting warning range intelligent demarcation method based on unmanned aerial vehicle aerial survey

Abstract

The present application relates to a kind of open-air blasting warning range intelligent demarcation method based on unmanned aerial vehicle aerial survey, belong to adaptive data processing technical field, including the following steps: data acquisition and pre-processing: obtain oblique photography image data and RTK image control point coordinate data;Real scene three-dimensional model construction: using SIFT feature extraction and matching, point cloud filtering and Poisson reconstruction algorithm, constructs open-air blasting operation area real scene three-dimensional model;Core influencing factor weight determination: screening core factor, to determine the weight of each factor;Warning range intelligent calculation: obtain actual blasting parameter, combine the weight determined, into multi-factor coupling dynamic calculation model, calculate warning range radius;Warning range visualization and labeling: warning range radius is fused with real scene three-dimensional model, generates and labels circular warning boundary line and warning area;The beneficial effects of the present application: by constructing "data acquisition-preprocessing-modeling-computing-visualization" mode, improve the performance of warning range demarcation.

Description

Technical Field

[0001] This invention belongs to the field of adaptive data processing technology, and specifically relates to a method for intelligently delineating the warning range of open-air blasting based on UAV aerial surveying. Background Technology

[0002] Open-pit blasting is a core process in mining, road construction, and engineering projects. The scientific and precise delineation of its warning range is directly related to the personal safety of workers, the safety of surrounding buildings and property, and the safety of the public environment. It is the core link in the safety management of open-pit blasting operations.

[0003] Currently, the delineation of warning zones for open-pit blasting mainly relies on two methods: traditional manual measurement and experience-based estimation. These methods have several significant drawbacks: First, manual measurement depends on total stations and levels, requiring personnel to set up measuring points and collect data on-site. This is not only inefficient and labor-intensive, but also problematic in open-pit mines with complex terrain and vast operating areas, easily affected by terrain obstruction and severe weather, making it difficult to guarantee measurement accuracy and failing to meet centimeter-level warning and control requirements. Second, experience-based estimation relies entirely on the on-site experience of personnel, exhibiting strong subjective initiative and failing to consider the coupling effects of core influencing factors such as explosive charge quantity, geological lithology, and slope gradient. This leads to significant deviations in the delineation of warning zones, either resulting in excessive expansion of the warning zone, wasting human and material resources, or insufficient warning zones, leaving safety hazards.

[0004] With the rapid development of UAV aerial surveying technology, UAV oblique photography can quickly acquire high-resolution image data of the work area. Combined with RTK positioning technology, it can achieve high-precision coordinate acquisition, providing technical support for the accurate delineation of the warning range for open-pit blasting. However, in existing technologies, the integration of UAV aerial surveying and warning range delineation is not close enough, and an integrated process of "data acquisition—preprocessing—3D modeling—weight calculation—warning range delineation—visual annotation" has not yet been formed: some technologies only realize UAV data acquisition and 3D modeling, without involving intelligent calculation of the warning range; some technologies attempt to calculate the warning range, but do not consider the coupling effect of multiple factors, and do not achieve the fusion and visualization of the warning range and the 3D model, making it impossible for managers to intuitively view the distribution of the warning area and making it difficult to quickly carry out on-site control. In addition, existing technologies lack a scientific method for calculating the weight of core influencing factors, making it impossible to accurately quantify the degree of influence of each factor on the warning range, further reducing the accuracy and adaptability of the warning range delineation. Summary of the Invention

[0005] This invention provides an intelligent method for delineating the warning range of open-air blasting based on UAV aerial surveying, which solves the technical problem of poor warning range delineation performance. It organically combines UAV oblique photography (multi-view acquisition), RTK high-precision positioning, centimeter-level real-scene 3D modeling, analytic hierarchy process (AHP), and multi-factor coupled calculation to construct an integrated technical process of "data acquisition - preprocessing - modeling - calculation - visualization". This realizes full automation from "data acquisition" to "warning range delineation" and improves the performance of warning range delineation.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solution:

[0007] A method for intelligently delineating the warning range for open-pit blasting based on UAV aerial surveying includes the following steps:

[0008] Step S1. Data Acquisition and Preprocessing: Using a drone equipped with oblique photography equipment and RTK positioning equipment, aerial surveys are conducted on the open-pit blasting operation area to acquire oblique photography image data and RTK control point coordinate data. These data are then preprocessed by denoising, geometric correction, stitching, outlier removal, and normalization.

[0009] Step S2. Construction of Real-Scene 3D Model: Based on the preprocessed data, SIFT feature extraction and matching, point cloud filtering and Poisson reconstruction algorithms are used to construct a real-scene 3D model of the open-air blasting operation area with centimeter-level accuracy.

[0010] Step S3. Determining the weights of core influencing factors: Five core factors were selected: explosive charge, geological lithology, slope gradient, distance from surrounding buildings, and personnel activity density. The weights of each factor were determined using the analytic hierarchy process (AHP).

[0011] Step S4. Intelligent calculation of warning range: Obtain the actual blasting parameters, combine them with the weights determined in step S3, and substitute them into the multi-factor coupled dynamic calculation model to calculate the radius of the warning range;

[0012] Step S5. Visualization and labeling of the warning range: The calculated warning range radius is fused with the real-world 3D model to generate and label the circular warning boundary line and warning area.

[0013] Optionally, in step S1, the resolution of the oblique photography image is ≥0.1m, and the positioning accuracy of the RTK positioning device is ≤2cm.

[0014] Optionally, in step S2, the planar error of the real-scene 3D model is ≤5cm, and the elevation error is ≤10cm.

[0015] Optionally, in step S3, after constructing the judgment matrix using the analytic hierarchy process, a consistency test is performed, with a consistency ratio of CR < 0.1 and the sum of the weights of each factor being 1.

[0016] Furthermore, the default weights for the factors are: explosive charge 0.4, distance from surrounding buildings 0.3, slope gradient 0.2, personnel activity density 0.1, and geological lithology 0.1, and manual adjustment is allowed according to the actual operation scenario.

[0017] Optionally, in step S4, the multi-factor coupled dynamic calculation model is: R=k1×Q^(1 / 3)+k2×α+k3×D+k4×P+k5×L, where R is the radius of the warning range, Q is the amount of explosive charge, α is the slope gradient, D is the distance to surrounding buildings, P is the density of personnel activity, L is the geological lithology coefficient, and k1~k5 are the weights of each factor.

[0018] Furthermore, the geological lithology coefficient L is set to 1.0 for hard rocks, 1.2 for medium-hard rocks, and 1.5 for soft rocks.

[0019] Optionally, in step S5, the warning boundary line is a circular boundary line with the blast center point as the center and the radius of the warning range as the center. It is highlighted with thick lines and filled with semi-transparent markings within the warning area to distinguish the warning area from the safe area.

[0020] Optionally, in step S5, editable warning information can be added above the warning boundary line.

[0021] Optionally, the method supports importing data in multiple formats, including image formats such as JPG, PNG, and TIF, and coordinate formats such as TXT, CSV, and XLSX.

[0022] The beneficial effects of this invention are:

[0023] 1. This invention addresses the current disconnect between UAV aerial surveying and warning range delineation by organically combining UAV oblique photography (multi-view acquisition), RTK high-precision positioning, centimeter-level real-scene 3D modeling, analytic hierarchy process (AHP), and multi-factor coupled calculation. It constructs an integrated technical process of "data acquisition - preprocessing - modeling - calculation - visualization," achieving full automation from "data acquisition" to "warning range delineation." This solves the shortcomings of existing technologies that only achieve single aerial surveying modeling or warning calculation and cannot form a closed loop.

[0024] 2. This invention addresses the problem that existing technologies cannot accurately quantify the impact of various factors on the warning range. It innovatively adopts the Analytic Hierarchy Process (AHP) to construct a judgment matrix. Through consistency checks, it determines the weights of five core factors, including explosive charge and geological lithology. Combined with a multi-factor coupled dynamic calculation model, it quantifies and integrates each influencing factor into the warning radius calculation, breaking the subjectivity of traditional experience-based estimation and achieving accurate calculation of the warning range. Compared with existing single-factor calculation and experience-based estimation methods, its scientificity and adaptability are greatly improved, and it can be adapted to open-pit blasting scenarios of different terrains and scales.

[0025] 3. This invention deeply integrates the warning range with a real-world 3D model. Through clear warning boundary lines, semi-transparent warning area markings, and editable prompts, it achieves an intuitive and visual display of the warning range. This solves the problems of unclear warning range markings and the inability of managers to quickly identify warning areas in existing technologies, and improves the convenience and safety of open-pit blasting site management. This visualization method is unique in the field of open-pit blasting warning. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 This is a schematic diagram of the workflow of the present invention;

[0028] Figure 2 This is a schematic diagram of UAV aerial survey data acquisition according to the present invention;

[0029] Figure 3 This is a visualization diagram illustrating the fusion of a real-world 3D model and a warning range according to the present invention;

[0030] Figure 4 This is a pie chart showing the contribution percentage of each core factor of the present invention to the warning range. Detailed Implementation

[0031] The embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0032] like Figure 1 As shown, Figure 1 The invention demonstrates five steps: data acquisition and preprocessing, construction of a realistic 3D model, determination of the weights of core influencing factors, intelligent calculation of the warning range, and visualization and annotation of the warning range. Each step is connected sequentially by arrows, clearly illustrating the complete technical logic and execution order of the method. Specifically, this embodiment provides a method for intelligently delineating the warning range for open-air blasting based on UAV aerial surveying, characterized by the following steps:

[0033] Step S1. As Figure 2As shown, data acquisition and preprocessing: Using a drone equipped with oblique photography equipment and RTK positioning equipment, a comprehensive aerial survey of the open-pit blasting operation area was conducted to acquire multi-view, high-resolution oblique photography image data and RTK control point coordinate data. The oblique photography image data underwent denoising, geometric correction, and multi-image stitching preprocessing to remove image noise and distortion, forming a complete image of the operation area. The RTK control point coordinate data underwent outlier removal and normalization preprocessing to eliminate data errors and obtain standardized coordinate data, providing accurate data support for subsequent 3D modeling.

[0034] Figure 2 It includes an open-air blasting operation area, drones, oblique photography equipment, RTK positioning equipment and RTK image control points. Through multi-view shooting diagrams and aerial survey trajectory lines, it intuitively demonstrates the working status of drones to collect high-precision data from all directions and multiple perspectives in the blasting area.

[0035] Step S2. Figure 3 As shown, the construction of the real-scene 3D model is as follows: Based on the preprocessed data obtained in step S1, the SIFT feature extraction algorithm is used to extract image feature points and match them to construct point cloud data of the open-pit blasting operation area; the point cloud data is filtered and denoised by combining voxel downsampling and statistical filtering to remove redundant and noise points and improve the quality of the point cloud data; the Poisson reconstruction algorithm is used to construct a real-scene 3D model of the open-pit blasting operation area with centimeter-level accuracy, and the planar error and elevation error of the model are calculated to ensure that the model accuracy meets the warning labeling requirements (planar error ≤ 5cm, elevation error ≤ 10cm).

[0036] Figure 3 The three-dimensional terrain model of the open-pit blasting area is displayed from a top-down perspective. A warning boundary line is drawn with the blasting center point as the center to distinguish the warning area from the safe area, and warning text is marked to clearly present the intuitive marking effect of the warning range on the three-dimensional model.

[0037] Step S3. Figure 4 As shown, the weights of the core influencing factors are determined as follows: Five core factors affecting the warning range of open-pit blasting are selected, namely, explosive charge (Q), geological lithology coefficient (L), slope gradient (α), distance from surrounding buildings (D), and personnel activity density (P). The analytic hierarchy process (AHP) is used to construct a judgment matrix, and the rationality of the judgment matrix is ​​verified by a consistency test (consistency ratio CR < 0.1). After the test is completed, the weights of each core factor are determined, and the sum of the weights of all factors is 1. The default weights of each factor are: explosive charge 0.4, distance from surrounding buildings 0.3, slope gradient 0.2, personnel activity density 0.1, and geological lithology 0.1. The weights can be manually adjusted according to the actual operation scenario.

[0038] Figure 4 The pie chart visually represents the weight distribution of five factors: explosive charge, distance to surrounding buildings, slope gradient, personnel activity density, and geological lithology, clearly reflecting the degree of influence of each factor on the calculation of the warning range.

[0039] Step S4. Intelligent Calculation of Warning Range: Obtain the actual parameters of the open-pit blasting operation, including the amount of explosive charge, geological lithology coefficient (1.0 for hard rock, 1.2 for medium-hard rock, and 1.5 for soft rock), slope gradient, distance to surrounding buildings, and personnel activity density; combine the weights of each factor determined in Step S3, substitute them into the multi-factor coupled dynamic calculation model, and calculate the radius of the warning range; the multi-factor coupled dynamic calculation model is: R=k1×Q^(1 / 3)+k2×α+k3×D+k4×P+k5×L, where k1, k2, k3, k4 and k5 are the weights of explosive charge, slope gradient, distance to surrounding buildings, personnel activity density and geological lithology, respectively, and R is the radius of the warning range.

[0040] Step S5. Visualization and Marking of the Warning Area: The warning area radius calculated in Step S4 is integrated with the real-world 3D model constructed in Step S2. A circular warning boundary line is generated with the blast center point as the center and the warning area radius as the radius. The warning boundary line is visualized and highlighted with thick lines. Semi-transparent markers are filled in the warning area to distinguish it from the safe area. Editable warning information (such as "Blast Warning Area, No Entry") is added above the warning boundary line to achieve clear marking and visualization of the warning area, making it easy for managers to view intuitively.

[0041] Furthermore, by employing UAV aerial surveying and RTK positioning technology, high-precision acquisition of images and coordinate data of the work area is achieved, with RTK positioning accuracy ≤2cm and image resolution ≥0.1m. Combined with centimeter-level real-scene 3D models, the accuracy of the warning range delineation is ensured, with a planar error ≤5cm and an elevation error ≤10cm, thus solving the problem of insufficient accuracy of traditional methods.

[0042] By constructing an integrated process of "data acquisition - preprocessing - 3D modeling - weight calculation - warning delineation - visual annotation", the entire process is highly automated and requires little manual intervention. Compared with traditional manual measurement methods, efficiency is increased by more than 50%, and the labor intensity of operators is greatly reduced.

[0043] The weights of each core influencing factor are determined by the analytic hierarchy process (AHP). Combined with a multi-factor coupled dynamic calculation model, the influence of each factor on the warning range is quantified, avoiding the subjectivity of empirical estimation and making the delineation of the warning range more scientific and adaptable, which can be adapted to open-pit blasting scenarios of different geological conditions and scales.

[0044] With excellent visualization capabilities, it can integrate the warning area with the real-world 3D model for visualization. The warning boundary lines, warning areas, and prompts are clearly identifiable, allowing managers to intuitively view the distribution of the warning area, quickly carry out on-site control, and reduce safety hazards.

[0045] With its simple process and convenient operation, it supports the import and processing of data in multiple formats and can be directly applied to various open-pit mines and open-pit engineering blasting operations without the need for additional complex equipment, making it easy to promote and apply.

[0046] In this embodiment, the technologies upon which the present invention relies are all existing and mature technologies, with no technical barriers, and can be directly implemented based on the existing technology system, as detailed below:

[0047] Firstly, UAV aerial surveying and RTK positioning technologies have been widely used in open-pit mines and engineering construction. The technologies for oblique photogrammetry image acquisition and high-precision coordinate acquisition are mature and can stably acquire data with a resolution of ≥0.1m and a positioning accuracy of ≤2cm, which meets the data acquisition requirements of this invention.

[0048] Secondly, the image preprocessing (Gaussian filtering for noise reduction, perspective transformation for geometric correction, SIFT feature matching and stitching) and 3D modeling (SIFT feature extraction, voxel downsampling filtering, Poisson reconstruction) algorithms are all existing mature algorithms that can be implemented using existing tools such as OpenCV and Open3D. The stability and accuracy of these algorithms have been verified by the industry, ensuring centimeter-level accuracy of the real-world 3D model. Thirdly, the Analytic Hierarchy Process (AHP) coupled with the multi-factor calculation model is logically rigorous and computationally convenient. It can be automated using conventional programming tools, accurately quantifying the impact of each core factor on the warning range, without any technical difficulties.

[0049] The core technologies upon which this invention and its method rely are all existing mature technologies, with no technical barriers, and can be directly implemented based on existing technology systems. Specifically: First, UAV aerial surveying and RTK positioning technologies have been widely used in open-pit mines, engineering construction, and other fields. Oblique photogrammetry image acquisition and high-precision coordinate acquisition technologies are mature and can stably acquire data with a resolution ≥0.1m and a positioning accuracy ≤2cm, meeting the data acquisition requirements of this invention. Second, the algorithms for image preprocessing (Gaussian filtering for noise reduction, perspective transformation for geometric correction, SIFT feature matching and stitching) and 3D modeling (SIFT feature extraction, voxel downsampling filtering, Poisson reconstruction) are all existing mature algorithms and can be implemented using existing tools such as OpenCV and Open3D. The stability and accuracy of these algorithms have been verified by the industry, ensuring centimeter-level accuracy requirements for real-world 3D models. Third, the Analytic Hierarchy Process (AHP) coupled with a multi-factor calculation model is logically rigorous and computationally convenient. It can be automated through conventional programming tools, accurately quantifying the influence of each core factor on the warning range, without any technical difficulties.

[0050] The feasibility of the equipment in this invention is that all required equipment are mature devices that can be directly purchased from the market, requiring no custom development. The equipment cost is controllable and the operation is convenient. Specifically, the equipment includes: drones (such as DJI M300 and M350 models), oblique photography cameras (multi-lens, supporting 0°, 45° and 90° multi-view shooting), and RTK positioning modules. The above equipment has achieved mass production, is technologically mature and highly stable, and is widely used in aerial surveying, mapping and other fields. Operators can operate it proficiently after simple training. In addition, the computer equipment required for data processing, model building and warning calculation can be met by ordinary industrial computers, without the need for high-performance special equipment, which further reduces the implementation threshold of the method of this invention.

[0051] This invention is feasible to apply, with a simple process and convenient operation, adaptable to various open-pit blasting operation scenarios (open-pit mines, open-pit engineering, etc.), without requiring significant adjustments to existing blasting operation procedures, and can be quickly integrated into the existing safety management system. Furthermore, the method supports importing data in multiple formats (image formats JPG, PNG, TIF; coordinate formats TXT, CSV, XLSX), adaptable to different types of UAV aerial survey data, and highly versatile. In addition, the method is highly automated, requiring minimal manual intervention, significantly reducing the labor intensity of operators, improving warning and control efficiency, meeting the safety, efficiency, and precision management requirements of open-pit blasting operations, and has broad application prospects.

[0052] In summary, the above analysis shows that this invention relies on existing mature technologies and algorithms, eliminating technical barriers. It utilizes readily available commercially available equipment, ensuring cost control and ease of operation. Furthermore, it is adaptable to various open-pit blasting scenarios and can be quickly integrated into existing management systems, demonstrating strong feasibility. This invention effectively addresses the shortcomings of existing technologies in determining the warning range for open-pit blasting, including low accuracy, low efficiency, and high subjectivity. It achieves intelligent, precise, and efficient delineation of the warning range, fulfilling the intended purpose of the invention and possessing significant application value and promising prospects for wider adoption. All required equipment is readily available and commercially viable, requiring no custom development. The equipment is cost-effective and easy to operate. Specifically, it includes: drones (such as DJI M300 and M350 models), oblique photography cameras (multi-lens, supporting 0°, 45°, and 90° multi-view shooting), and RTK positioning modules. All of these devices are already in mass production, technologically mature, highly stable, and widely used in aerial surveying, mapping, and other fields. Operators can become proficient after simple training. Furthermore, the computer equipment required for data processing, model building, and alert calculations can be met by ordinary industrial computers, eliminating the need for high-performance specialized equipment and further lowering the implementation threshold of this invention.

[0053] This invention is feasible for application, featuring a simple process, convenient operation, and adaptability to various open-pit blasting operation scenarios (open-pit mines, open-pit engineering, etc.). It requires no significant adjustments to existing blasting operation procedures and can be quickly integrated into existing safety management systems. Furthermore, the method supports importing data in multiple formats (image formats JPG, PNG, TIF; coordinate formats TXT, CSV, XLSX), making it compatible with different types of UAV aerial survey data and highly versatile. In addition, the method is highly automated, requiring minimal manual intervention, significantly reducing the labor intensity of operators, improving warning and control efficiency, and meeting the safety, efficiency, and precision management requirements of open-pit blasting operations, thus demonstrating broad application prospects.

[0054] Therefore, this invention relies on existing mature technologies and algorithms, eliminating technical barriers; it utilizes readily available commercially available mature equipment, ensuring cost control and ease of operation; and it is adaptable to various open-pit blasting scenarios, allowing for rapid integration into existing management systems, demonstrating strong feasibility. This invention effectively addresses the shortcomings of existing technologies in determining the warning range for open-pit blasting, including low accuracy, low efficiency, and strong subjectivity, achieving intelligent, precise, and efficient delineation of the warning range, thus fulfilling the intended purpose of the invention and possessing significant application value and promising prospects for wider application.

[0055] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope described in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for intelligently delineating the warning range for open-pit blasting based on UAV aerial surveying, characterized in that, Includes the following steps: Step S1. Data Acquisition and Preprocessing: Using a drone equipped with oblique photography equipment and RTK positioning equipment, aerial surveys are conducted on the open-pit blasting operation area to acquire oblique photography image data and RTK control point coordinate data. These data are then preprocessed by denoising, geometric correction, stitching, outlier removal, and normalization. Step S2. Construction of Real-Scene 3D Model: Based on the preprocessed data, SIFT feature extraction and matching, point cloud filtering and Poisson reconstruction algorithms are used to construct a real-scene 3D model of the open-air blasting operation area with centimeter-level accuracy. Step S3. Determining the weights of core influencing factors: Five core factors were selected: explosive charge, geological lithology, slope gradient, distance from surrounding buildings, and personnel activity density. The weights of each factor were determined using the analytic hierarchy process (AHP). Step S4. Intelligent calculation of warning range: Obtain the actual blasting parameters, combine them with the weights determined in step S3, and substitute them into the multi-factor coupled dynamic calculation model to calculate the radius of the warning range; Step S5. Visualization and labeling of the warning range: The calculated warning range radius is fused with the real-world 3D model to generate and label the circular warning boundary line and warning area.

2. The method for intelligent delineation of open-pit blasting warning range based on UAV aerial surveying according to claim 1, characterized in that, In step S1, the resolution of the oblique photographic image is ≥0.1m, and the positioning accuracy of the RTK positioning device is ≤2cm.

3. The method for intelligent delineation of open-pit blasting warning range based on UAV aerial surveying as described in claim 1, characterized in that, In step S2, the planar error of the real-scene 3D model is ≤5cm, and the elevation error is ≤10cm.

4. The method for intelligent delineation of open-pit blasting warning range based on UAV aerial surveying according to claim 1, characterized in that, In step S3, after constructing the judgment matrix using the analytic hierarchy process, a consistency test is performed, with a consistency ratio of CR < 0.1 and the sum of the weights of each factor being 1.

5. The method for intelligent delineation of open-pit blasting warning range based on UAV aerial surveying according to claim 4, characterized in that, The default weights for the factors are: explosive charge 0.4, distance from surrounding buildings 0.3, slope gradient 0.2, personnel activity density 0.1, and geological lithology 0.1, and manual adjustment is allowed according to the actual operation scenario.

6. The method for intelligent delineation of open-pit blasting warning range based on UAV aerial surveying according to claim 1, characterized in that, In step S4, the multi-factor coupled dynamic calculation model is: R=k1×Q^(1 / 3)+k2×α+k3×D+k4×P+k5×L, where R is the radius of the warning range, Q is the amount of explosive charge, α is the slope gradient, D is the distance to surrounding buildings, P is the density of personnel activity, L is the geological lithology coefficient, and k1~k5 are the weights of each factor.

7. The method for intelligent delineation of open-pit blasting warning range based on UAV aerial surveying according to claim 6, characterized in that, The geological lithology coefficient L is set to 1.0 for hard rocks, 1.2 for medium-hard rocks, and 1.5 for soft rocks.

8. The method for intelligent delineation of open-pit blasting warning range based on UAV aerial surveying according to claim 1, characterized in that, In step S5, the warning boundary line is a circular boundary line with the blast center point as the center and the radius of the warning range as the center. It is highlighted with thick lines and filled with semi-transparent markings within the warning area to distinguish the warning area from the safe area.

9. The method for intelligent delineation of open-pit blasting warning range based on UAV aerial surveying according to claim 1, characterized in that, In step S5, editable warning messages can be added above the warning boundary line.

10. The method for intelligent delineation of open-pit blasting warning range based on UAV aerial surveying according to claim 1, characterized in that, The method supports importing data in multiple formats, including image formats such as JPG, PNG, and TIF, and coordinate formats such as TXT, CSV, and XLSX.

Images