A tailings pond dry beach overall monitoring method and system based on three-dimensional reconstruction

Abstract

The present invention discloses a method and system for monitoring the dry beach of a tailings pond based on three-dimensional reconstruction. The method comprises: regularly acquiring image data of the tailings pond area, establishing a three-dimensional point cloud model of the dry beach according to the image data; calculating the grid point slope of the dry beach based on the three-dimensional point cloud model of the dry beach, and calculating the length of the dry beach based on the image data and the three-dimensional point cloud model of the dry beach; and performing a safety assessment based on the grid point slope and the length of the dry beach compared with a set safety threshold. The present invention solves the problem that it is difficult for existing monitoring methods to take into account both the diversity and accuracy of acquired parameters.

Description

Technical Field

[0001] The present invention relates to the technical field of dry beach interpretation and monitoring, and in particular to a tailings pond dry beach overall monitoring method and system based on three-dimensional reconstruction. Background Art

[0002] Tailings refer to the "waste residue" (like sand) discharged by mineral processing plants after the concentrate is screened out from metal and non-metallic ores. A large amount of tailings sand is stored in tailings ponds formed by mountain walls. The safe operation of tailings ponds is closely related to the safety of people's lives and property and environmental protection.

[0003] Currently, the online monitoring modules for tailings dams include: dam surface deformation monitoring, dam internal displacement monitoring, infiltration line monitoring, reservoir water level precipitation monitoring, and dry beach length monitoring. Dry beach monitoring includes dry beach length, dry beach slope, and dry beach elevation. Accurately measuring these parameters allows mining companies and safety monitoring departments to effectively prevent tailings dam breaches during the rainy season. Traditional methods for measuring tailings dam dry beach parameters primarily involve deploying physical sensors at selected monitoring points within the tailings dam area to acquire data. Dry beach parameters are then calculated using slope inference, laser angle measurement, and seepage inversion methods. The overall cost of monitoring is high, and it is difficult to balance the diversity and accuracy of the obtained parameters. Traditional methods are also limited in their application to dry beaches over large areas and complex terrain, and typically rely on local monitoring. Summary of the Invention

[0004] (1) Technical issues to be resolved

[0005] Based on the above problems, the present invention provides a tailings pond dry beach overall monitoring method and system based on three-dimensional reconstruction, which solves the problem that existing monitoring methods are difficult to take into account both the diversity and accuracy of acquired parameters.

[0006] (2) Technical solution

[0007] Based on the above technical problems, the present invention provides a tailings pond dry beach overall monitoring method based on three-dimensional reconstruction, comprising the following steps:

[0008] S1. Regularly obtain image data of the tailings pond area and establish a three-dimensional point cloud model of the dry beach based on the image data;

[0009] S2. calculating the grid point slope of the dry beach based on the three-dimensional point cloud model of the dry beach;

[0010] S21. Divide the dry beach three-dimensional point cloud model into multiple point cloud sections along a direction parallel to the central axis of the dam body;

[0011] S22, performing filtering and denoising processing on the divided point cloud profile;

[0012] S23, dividing the denoised point cloud section along a direction perpendicular to the dam axis to form a plurality of grid points;

[0013] S24, calculating the dry beach slope ratio of each grid point based on the point cloud coordinates of the grid point and the beach top coordinates to obtain the grid point slope of the dry beach;

[0014] S3. Simultaneously, calculating the length of the dry beach based on the image data and the three-dimensional point cloud model of the dry beach;

[0015] S31. Identify and extract pixel coordinates of the boundary lines between the water surface and the dry beach, and the boundary lines between the dry beach and the dam body, using the image containing the boundary lines.

[0016] S32, using a transformation matrix to convert the extracted pixel coordinates into spatial coordinates in a three-dimensional point cloud model coordinate system;

[0017] S33. Calculate, based on the converted spatial coordinates, the distance between the three-dimensional point on the boundary line between the water surface and the dry beach and the boundary line between the dry beach and the dam body, projected onto the water surface, to obtain the dry beach length;

[0018] S4. Perform a safety assessment based on the grid point slope and the length of the dry beach and comparing them with a set safety threshold.

[0019] Furthermore, S1 also includes: placing filming equipment on site, with the filming range being able to fully cover the entire dry beach, determining the filming frequency and time according to the monitoring purpose and the change speed of the dry beach, and regularly obtaining image data of the tailings pond area.

[0020] Furthermore, S1 also includes: pre-processing the collected image data.

[0021] Furthermore, in S22, the filtering and denoising processing includes: projecting the three-dimensional point cloud to the XOZ plane, initializing the sliding window, moving the window along the X direction, obtaining the average Z coordinate in the sliding window, setting the filtering conditions, and removing noise points until the sliding window moves to the end point of the point cloud profile.

[0022] Furthermore, in S24, the calculation formula of the dry beach slope ratio of each grid point is: Where, (X u , Y u , Z u )、(X d , Y d , Z d ) are the coordinates of the dry beach top and the dry beach grid point, and S is the slope ratio corresponding to each grid point.

[0023] Furthermore, in S31, the method for identifying and extracting pixel coordinates of the boundary line between the water surface and the dry beach, and the boundary line between the dry beach and the dam body includes: converting the image containing the boundary line from the RGB space to the HSV space, segmenting the image in the HSV space using K-means clustering, extracting edge pixels using an edge extraction operator, and removing noise points using DBSCAN to obtain the pixel coordinates of the boundary line.

[0024] Furthermore, in S32, the conversion matrix is: Wherein, point p(u, v) is the point projected from point P(x, y, z) in the world coordinate system to the pixel coordinate system, and f x 、f y are the focal lengths in the x and y directions, c x 、c y is the coordinate of the principal point where the optical axis intersects the image plane. The K matrix composed of it is the internal parameter matrix, [R|t] is the external parameter matrix, which is the rotation matrix and translation matrix between the world coordinate system and the camera coordinate system, r ij is the direction cosine, i=1,2,3; j=1,2,3; t m is the direction vector, m=1,2,3, K and [R|t] matrices are the transformation matrices of the 3D point cloud reconstruction process.

[0025] Furthermore, in S33, the calculation formula of the dry beach length is: Where d is the length of the dry beach, the projection of a three-dimensional point (X, Y, Z) on the boundary line between the water surface and the dry beach onto the horizontal plane (XOY plane) is (x0, y0), and the analytical expression for the projection of the fitting straight line of the boundary line between the dry beach and the dam body onto the horizontal plane is Ax+By+C=0, where A, B, and C are the constant coefficients of the analytical expression.

[0026] The present invention also discloses a tailings pond dry beach overall monitoring system based on three-dimensional reconstruction, comprising:

[0027] at least one processor; and at least one memory communicatively coupled to the processor, wherein:

[0028] The memory stores program instructions that can be executed by the processor, and the processor can execute the method by calling the program instructions.

[0029] The present invention also discloses a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions enable the computer to execute the method.

[0030] (3) Beneficial effects

[0031] The above technical solution of the present invention has the following advantages:

[0032] (1) The present invention calculates the monitoring parameters of the dry beach of the tailings pond based on a three-dimensional point cloud model, including the dry beach length and the grid point slope of the dry beach. The slope ratio of all grid points is calculated based on the point cloud coordinates of the divided grid points and the beach top coordinates to obtain the grid point slope of the entire dry beach. The pixel coordinates of the two dividing lines are obtained based on image recognition. The three-dimensional points on the dividing line between the water surface and the dry beach and the distance between the dividing line between the dry beach and the dam body projected to the horizontal plane are calculated after coordinate conversion to obtain the dry beach length. The calculated dry beach parameters are more comprehensive, and the safety assessment performed thereby is more accurate.

[0033] (2) The present invention divides grid points based on dry beach point cloud data and calculates the slope of grid points, which can cover the entire range of the dry beach and realize the slope ratio calculation of the local area inside the dry beach, thereby evaluating the slope ratio of the local range;

[0034] (3) The present invention can realize the overall monitoring and visual analysis of the dry beach of the tailings pond through the three-dimensional point cloud model. The non-contact monitoring method using photographic equipment is safer and more efficient, with low equipment cost. It can realize comprehensive monitoring of the dry beach and obtain more comprehensive raw data, which is conducive to improving the accuracy of the monitoring results and ensuring the safe operation of the tailings pond. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The features and advantages of the present invention will be more clearly understood by referring to the accompanying drawings, which are schematic and should not be construed as limiting the present invention in any way. In the accompanying drawings:

[0036] Figure 1 Schematic diagram of the process of the overall monitoring method of the tailings pond dry beach based on three-dimensional reconstruction according to an embodiment of the present invention;

[0037] Figure 2 Schematic diagram of a cross-section of a three-dimensional point cloud model according to an embodiment of the present invention;

[0038] Figure 3 A schematic diagram of a three-dimensional point cloud model grid according to an embodiment of the present invention;

[0039] Figure 4 This is a flowchart of point cloud denoising according to an embodiment of the present invention;

[0040] Figure 5 This is a schematic diagram of the point cloud profile denoising effect according to an embodiment of the present invention;

[0041] Figure 6 This is a flow chart of boundary identification according to an embodiment of the present invention;

[0042] Figure 7 A schematic diagram comparing the recognition results of two boundary lines according to an embodiment of the present invention;

[0043] Figure 8A three-dimensional point schematic diagram of the boundary line between the water surface and the dry beach according to an embodiment of the present invention;

[0044] Figure 9 3D point schematic diagram of the boundary line between the dry beach and the dam body according to an embodiment of the present invention. DETAILED DESCRIPTION

[0045] The following embodiments of the present invention are described in further detail with reference to the accompanying drawings and examples. The following examples are used to illustrate the present invention but are not intended to limit the scope of the present invention.

[0046] The present invention discloses a tailings pond dry beach overall monitoring method based on three-dimensional reconstruction, such as Figure 1 As shown, the following steps are included:

[0047] S1. Point cloud data acquisition: regularly acquiring image data of the tailings pond area and establishing a three-dimensional point cloud model of the dry beach based on the image data;

[0048] Filming equipment is placed on site so that its shooting range can fully cover the entire dry beach. The shooting frequency and time are determined according to the monitoring purpose and the change speed of the dry beach, and high-resolution image data of the tailings pond area is regularly obtained; the collected image data is pre-processed, and then computer vision technology and 3D reconstruction algorithms are used to convert the image data into a 3D point cloud model.

[0049] S2. Dry beach grid point slope interpretation: Calculating the dry beach grid point slope based on the dry beach three-dimensional point cloud model;

[0050] S21, dividing the dry beach three-dimensional point cloud model into a plurality of point cloud sections along a direction parallel to the central axis of the dam body;

[0051] In this embodiment, the dry beach three-dimensional point cloud model is evenly divided into multiple point cloud sections along the direction parallel to the central axis of the dam body, such as Figure 2 shown.

[0052] S22, performing filtering and denoising processing on the divided point cloud profile;

[0053] Ideally, the 3D reconstructed point cloud section should be a plane without thickness. However, there are noisy point clouds around the actual divided point cloud section. If denoising is not performed, the error of the calculation result will be relatively large. Therefore, denoising is required before dividing the point cloud section into grids.

[0054] According to the point cloud features, a sliding window filtering algorithm is proposed. First, the 3D point cloud is projected to the XOZ plane. After initializing the sliding window, the window is moved along the X direction to obtain the average Z coordinate in the sliding window. Based on the characteristics of the Z coordinate, filtering is performed and filtering conditions are set to remove noise points until the sliding window reaches the end point of the point cloud profile. The specific process is as follows: Figure 4As shown; the point cloud profile filtering effect is as follows Figure 5 shown.

[0055] S23, dividing the denoised point cloud section along a direction perpendicular to the dam axis to form a plurality of grid points;

[0056] In this embodiment, the multiple point cloud sections after denoising are evenly divided along the direction perpendicular to the axis of the dam body to form multiple grid points, such as Figure 3 shown.

[0057] S24, calculating the dry beach slope ratio of each grid point, i.e., the grid point slope of the dry beach, based on the coordinates of the grid points and the beach top coordinates;

[0058] Using the point cloud data and beach top coordinates around the grid points, the formula for calculating the dry beach slope ratio of each grid point is as follows: Where, (X u , Y u , Z u )、(X d , Y d , Z d ) are the coordinates of the dry beach top and the dry beach grid point, and S is the slope ratio corresponding to each grid point.

[0059] The slope of each grid point is Figure 3 As shown in FIG, when the slope ratio of each grid point on the three-dimensional point cloud model of the dry beach is calculated, the slope ratio data of the entire dry beach can be obtained, and the obtained slope ratio parameters are more comprehensive.

[0060] S3, dry beach length interpretation: At the same time, the dry beach length is calculated based on the image data and the dry beach 3D point cloud model;

[0061] S31. Identify and extract pixel coordinates of the boundary lines between the water surface and the dry beach, and the boundary lines between the dry beach and the dam body, using the image containing the boundary lines.

[0062] First, it is necessary to identify the boundary between the water surface and the dry beach, and the boundary between the dry beach and the dam body, and extract pixel coordinates. The basic process of boundary line identification is as follows: Figure 6 As shown in the figure, the image containing the boundary line is converted from RGB space to HSV space, and the image in HSV space is segmented using K-means clustering. The edge extraction operator is then used to extract edge pixels. For some extracted noise points, DBSCAN (Density-Based Spatial Clustering of Applications with Noise) is used to remove them to obtain the pixel coordinates of the boundary line, as shown in the figure. Figure 7 As shown, Figure 7 Figure (a) is a photo of the boundary between the water surface and the dry beach. Figure 7Figure (b) is a photo of the boundary between the dry beach and the dam body. Figure 7 Figure (c) shows the recognition result of the boundary between the water surface and the dry beach. Figure 7 Figure (d) shows the identification result of the boundary line between the dry beach and the dam body. Figure 8 is the three-dimensional point of the boundary between the water surface and the dry beach, Figure 9 It is the three-dimensional point of the boundary between the dry beach and the dam body.

[0063] S32. Convert the extracted pixel coordinates into spatial coordinates in a three-dimensional point cloud model coordinate system using a conversion matrix; the conversion formula is as follows: Wherein, point p(u, v) is the point projected from point P(x, y, z) in the world coordinate system to the pixel coordinate system, and f x 、f y are the focal lengths in the x and y directions, c x 、c y is the coordinate of the principal point where the optical axis intersects the image plane. The K matrix composed of it is the internal parameter matrix, [R|t] is the external parameter matrix, which is the rotation matrix and translation matrix between the world coordinate system and the camera coordinate system, r ij is the direction cosine, i=1,2,3; j=1,2,3; t m is the direction vector, m=1,2,3, K and [R|t] matrices are the transformation matrices of the 3D point cloud reconstruction process.

[0064] S33. Calculate, based on the converted spatial coordinates, the distance between the three-dimensional point on the boundary line between the water surface and the dry beach and the boundary line between the dry beach and the dam body, projected onto the water surface, to obtain the dry beach length;

[0065] The distance between the three-dimensional point on the boundary line between the water surface and the dry beach and the boundary line between the dry beach and the dam body projected onto the water surface is the dry beach length, such as Figure 3 As shown in FIG, the calculation formula of the dry beach length is: Where d is the length of the dry beach, the projection of a three-dimensional point (X, Y, Z) on the boundary line between the water surface and the dry beach onto the horizontal plane (XOY plane) is (x0, y0), and the analytical expression for the projection of the fitting straight line of the boundary line between the dry beach and the dam body onto the horizontal plane is Ax+By+C=0, where A, B, and C are the constant coefficients of the analytical expression.

[0066] S4. Safety assessment: Conduct a safety assessment based on the grid point slope and dry beach length of the dry beach and compare them with the set safety threshold;

[0067] The calculated dry beach length and the dry beach slope ratio of each grid point are analyzed and compared with the set safety threshold to conduct a safety assessment: if the calculated dry beach length is greater than the corresponding set length threshold and the dry beach slope ratio of the grid point does not exceed the corresponding set slope ratio threshold, it is safe; otherwise, it is unsafe.

[0068] Finally, it should be noted that the above method can be converted into software program instructions, which can be implemented by running a system including a processor and a memory, or by computer instructions stored in a non-transitory computer-readable storage medium. The above-mentioned integrated unit implemented in the form of a software functional unit can be stored in a computer-readable storage medium. The above-mentioned software functional unit is stored in a storage medium, including a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to perform some steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0069] In summary, the above-mentioned tailings pond dry beach overall monitoring method and system based on three-dimensional reconstruction has the following beneficial effects:

[0070] (1) The present invention calculates the monitoring parameters of the dry beach of the tailings pond based on a three-dimensional point cloud model, including the dry beach length and the grid point slope of the dry beach. The slope ratio of all grid points is calculated based on the point cloud coordinates of the divided grid points and the beach top coordinates to obtain the grid point slope of the entire dry beach. The pixel coordinates of the two dividing lines are obtained based on image recognition. The three-dimensional points on the dividing line between the water surface and the dry beach and the distance between the dividing line between the dry beach and the dam body projected to the horizontal plane are calculated after coordinate conversion to obtain the dry beach length. The calculated dry beach parameters are more comprehensive, and the safety assessment performed thereby is more accurate.

[0071] (2) The present invention divides grid points based on dry beach point cloud data and calculates the slope of grid points, which can cover the entire range of the dry beach and realize the slope ratio calculation of the local area inside the dry beach, thereby evaluating the slope ratio of the local range;

[0072] (3) The present invention can realize the overall monitoring and visual analysis of the dry beach of the tailings pond through the three-dimensional point cloud model. The non-contact monitoring method using photographic equipment is safer and more efficient, with low equipment cost. It can realize comprehensive monitoring of the dry beach and obtain more comprehensive raw data, which is conducive to improving the accuracy of the monitoring results and ensuring the safe operation of the tailings pond.

[0073] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations shall fall within the scope defined by the appended claims.

Claims

1. A tailings pond dry beach overall monitoring method based on three-dimensional reconstruction, characterized in that: The following steps are involved: S1. Regularly obtain image data of the tailings pond area, and establish a three-dimensional point cloud model of the dry beach based on the image data; S2, calculating the grid point slope of the dry beach based on the three-dimensional point cloud model of the dry beach; S21, dividing a plurality of point cloud sections along a direction parallel to the central axis of the dam body on the dry beach three-dimensional point cloud model; S22, performing filtering and denoising processing on the divided point cloud profile; S23, dividing the denoised point cloud section along a direction perpendicular to the axis of the dam body to form a plurality of grid points; S24, calculating the dry beach slope ratio of each grid point according to the point cloud coordinates of the grid point and the beach top coordinates, and obtaining the grid point slope of the dry beach; In the formula, (X u , Y u , Z u )、(X d , Y d , Z d ) are the coordinates of the top of the dry beach and the grid points of the dry beach, respectively, and S is the slope ratio corresponding to each grid point; S3. At the same time, calculating the length of the dry beach based on the image data and the three-dimensional point cloud model of the dry beach; S31, identifying and extracting pixel coordinates of the boundary line between the water surface and the dry beach, and the boundary line between the dry beach and the dam body through the picture containing the boundary line; S32, using a transformation matrix to transform the extracted pixel coordinates into spatial coordinates in a three-dimensional point cloud model coordinate system; S33, calculating the distance between the three-dimensional point on the boundary line between the water surface and the dry beach and the boundary line between the dry beach and the dam body projected onto the water surface according to the converted spatial coordinates, to obtain the length of the dry beach; In the formula, d is the length of the dry beach, the projection of a three-dimensional point (X, Y, Z) on the boundary line between the water surface and the dry beach to the point on the horizontal plane is (x0, y0), the analytical expression of the projection of the fitting straight line of the boundary line between the dry beach and the dam body to the horizontal plane is Ax+By+C=0, and A, B, C are the constant coefficients of the analytical expression; S4. Perform a safety assessment based on the grid point slope and the length of the dry beach and the set safety threshold.

2. The tailings pond dry beach overall monitoring method based on three-dimensional reconstruction according to claim 1 is characterized in that: S1 also includes: placing shooting equipment on site, with the shooting range being able to fully cover the entire dry beach, determining the shooting frequency and time according to the monitoring purpose and the change speed of the dry beach, and regularly acquiring image data of the tailings pond area.

3. The tailings pond dry beach overall monitoring method based on three-dimensional reconstruction according to claim 1 is characterized in that: S1 also includes: pre-processing the collected image data.

4. The tailings pond dry beach overall monitoring method based on three-dimensional reconstruction according to claim 1 is characterized in that: In S22, the filtering and denoising process includes: projecting the three-dimensional point cloud to the XOZ plane, initializing the sliding window, moving the window along the X direction, obtaining the average Z coordinate in the sliding window, setting filtering conditions, and removing noise points until the sliding window moves to the end point of the point cloud profile.

5. The tailings pond dry beach overall monitoring method based on three-dimensional reconstruction according to claim 1 is characterized in that: In S31, the method for identifying the boundary line between the water surface and the dry beach, and the boundary line between the dry beach and the dam body, and extracting pixel coordinates includes: converting the image containing the boundary line from the RGB space to the HSV space, segmenting the image in the HSV space using K-means clustering, extracting edge pixels using an edge extraction operator, and removing noise points using DBSCAN to obtain the pixel coordinates of the boundary line.

6. The tailings pond dry beach overall monitoring method based on three-dimensional reconstruction according to claim 1 is characterized in that: In S32, the conversion matrix is: Where point p(u, v) is the point projected from point P(x, y, z) in the world coordinate system to the pixel coordinate system, and f x 、f y are the focal lengths in the x and y directions, c x 、c y is the coordinate of the principal point where the optical axis intersects the image plane. The K matrix composed of it is the internal parameter matrix, [R|t] is the external parameter matrix, which is the rotation matrix and translation matrix between the world coordinate system and the camera coordinate system, r ij is the direction cosine, i=1,2,3; j=1,2,3; t m is the direction vector, m=1,2,3, K and [R|t] matrices are the transformation matrices of the 3D point cloud reconstruction process.

7. A tailings pond dry beach overall monitoring system based on three-dimensional reconstruction, characterized in that: include: at least one processor; and at least one memory in communication with the processor, wherein: The memory stores program instructions executable by the processor, and the processor can execute the method according to any one of claims 1 to 6 by calling the program instructions.

8. A non-transitory computer-readable storage medium, characterized in that: The non-transitory computer-readable storage medium stores computer instructions, which cause the computer to execute the method according to any one of claims 1 to 6.

Images