A method for calculating settlement of tectonic stress-type metal mine subsidence areas based on drone photography

Abstract

The invention discloses a settlement calculation method for a tectonic stress type metal mine subsidence area by drone photography. The method comprises the following steps: firstly, a three-dimensional laser is used to scan the subsidence area, and a topographic map is obtained by post-processing, an aerial picture of the subsidence area is obtained by drone photography, and a calculation boundary is manually marked; then, python is used to identify the picture boundary and main target annotation objects, and a graphic containing the calculation boundary and the target object is exported, and then a CAD zoom command is used to merge the boundary map obtained by the drone with the topographic map obtained by the three-dimensional laser; a DXF2XYZ software processing package is used to export the XYZ coordinates of the three-dimensional laser topographic map, and Surfer software is used to interpolate the coordinates of the topographic map obtained by the three-dimensional laser, where the collapse calculation boundary determined by drone photography needs to be used as the maximum value and minimum value of the XY coordinate; finally, python is used to calculate the settlement value, and the data is imported into Surfer software to obtain the settlement contour line and the three-dimensional settlement cloud map of the subsidence area.

Description

Technical Field

[0001] The present invention belongs to the technical field of ground pit subsidence monitoring in geotechnical engineering, and more specifically, relates to a settlement calculation method for a tectonic stress-type metal mine subsidence area using drone photography. Background Art

[0002] Most mineral resources are located deep underground, and the geological conditions of deep rock masses are complex. Metal mines, in particular, are generally formed by magma intrusion, metamorphism, and are mostly located in mountainous areas with developed tectonic activities. The influence of tectonic stress on underground mining is very significant. When the ore body is mined, the original stress equilibrium state of the surrounding rock in the goaf is destroyed, which will cause the deep surrounding rock to move and deform. At the same time, the destruction of the deep rock mass will gradually be transmitted to the surface, causing surface collapse, forming collapse pits, and also causing deformation and damage to buildings (structures). Moreover, under the influence of tectonic stress, the scope of surface collapse is much larger than that of non-tectonic stress mines. These destructions have seriously affected the production of mines and the personal safety of the people, and restricted the sustainable development of mines. Therefore, understanding the settlement law of the surface collapse area is of great significance for the safety production guidance of underground mining and the governance of surface collapse pits.

[0003] However, the traditional settlement monitoring method is to use a level or GPS, both of which require setting up observation stations on the surface to obtain data. However, the collapse area has large deformation, steep slopes, and widespread surface cracks, and the surface stability is extremely poor, so surveyors cannot enter the area for measurement.

[0004] In recent years, 3D laser scanning and drone photography technologies have been widely used in mine surface monitoring. The working principle of 3D laser scanning is the pulse laser ranging method. It uses non-contact high-speed laser measurement to obtain 3D data of array geometric figures on the surface of the scanned object in the form of point cloud. This type of instrument can effectively perform large-scale scanning deformation monitoring on the surface of mining subsidence areas. Drone photography mainly consists of a handheld platform, a battery pack, a high-definition digital camera, a drone, etc. It is a simple aerial photography method that can shoot dangerous areas and difficult-to-reach areas. Through a large number of image photos, a real three-dimensional record of the space is made.

[0005] However, the topographic map obtained by 3D laser scanning needs to be manually compared in CAD software to obtain the settlement value by comparing the difference between the two measurements. However, the XY coordinates obtained from the two different measurements are inconsistent. In order to calculate the settlement difference, it is necessary to select the points to be calculated for interpolation calculation, and only a few points are calculated, while the large amount of data obtained by 3D laser scanning is seriously wasted. Therefore, the traditional calculation method cannot accurately reflect the settlement law of the collapse area, and the efficiency is low. The aerial pictures taken by drone photography can intuitively see the changes in settlement, but cannot obtain specific settlement values. Summary of the invention

[0006] The purpose of the present invention is to provide a method for calculating the settlement of a surface subsidence area based on three-dimensional laser scanning and drone photography, which uses the powerful data processing and drawing capabilities of Surfer software and the powerful computing capabilities of Python to obtain the settlement values ​​of the subsidence area, and then obtain the settlement law. This method is a practical, fast and efficient method for calculating the settlement of a surface subsidence area. This method gives full play to the advantages of three-dimensional laser scanning and drone photography technology for monitoring pit subsidence, and solves the problem of difficult settlement calculation in subsidence areas.

[0007] The present invention provides a method for calculating the settlement of a tectonic stress type metal mine subsidence area by drone photography, comprising the following steps:

[0008] Step 1: Scan the collapse area of ​​the known topographic map at different times by using a 3D laser scanner, and process the data to obtain a surface topographic map whose 3D coordinates can be viewed through CAD. The known topographic map is a 3D coordinate topographic map containing the target object, and uses the same coordinate system as the surface topographic map;

[0009] Step 2: Obtain an aerial picture of the subsidence area through drone photography, manually mark the calculated boundary of the subsidence area in the picture, and select the target object;

[0010] Step 3: Use Python to identify the calculated boundaries and target objects in the aerial images, and export the aerial graphics files containing the calculated boundaries and target objects. The aerial graphics files are in the same format as the surface topographic map. Then, through the CAD scaling command, the target objects in the aerial graphics files are made the same size as the target objects in the known topographic map. First, the target objects in the known topographic map are imported into the surface topographic maps of different periods through the CAD base point copy command. Then, the corner points of the target objects are used as insertion points to import the aerial graphics files into the surface topographic maps of different periods, so that the edges of the target objects in the two files overlap.

[0011] Step 4: Determine the calculation boundary coordinates of the calculation boundary of the aerial photography graphics file in the surface topographic map at different periods, export the XYZ coordinates within the calculation boundary coordinate range in the surface topographic map at different periods, and use Surfer software to draw the settlement cloud map at different periods according to the exported XYZ coordinates;

[0012] Step 5: Based on the settlement cloud maps of different periods, make a difference to obtain the three-dimensional settlement cloud map and the settlement contour lines of the collapse area.

[0013] Furthermore, the step 1 comprises:

[0014] Step 11: Use a 3D laser scanner to scan the subsidence area of ​​the known topographic map at different times, use GPS to locate the foresight point and the backsight point of the scan, and use MaptekⅠ-Site Studio 4.0 software to splice, filter, and denoise the acquired point cloud data of the subsidence area to obtain the ground scan topography of the entire mining subsidence area, and output the surface scan topographic map in dxf format;

[0015] Step 12, import the dxf file obtained in step 11 into the DXF2XYZ software processing package to obtain the three-dimensional data coordinates in xyz format, then open the xyz format file with Notepad and save it as a csv format file;

[0016] Furthermore, in step 2, when the drone is photographing, the lens is perpendicular to the ground, and the direction of photography is adjusted according to the built-in compass so that the top, bottom, left, right, and right of the photographed plane image correspond to north, south, west, and east respectively; the calculated boundary is a closed area drawn by mutually perpendicular line segments;

[0017] Furthermore, in step 3, the calculation of boundaries and target objects in the aerial image by Python includes:

[0018] In Python, call the third-party library CV2 assembly to convert the jpg format image into a dxf format file. During the conversion, subtract the Y coordinate value of the corresponding point in the upper left corner of the jpg image from the image height of the jpg image, so that the point obtained in the dxf file is consistent with the position of the point in the jpg image.

[0019] Call the ezdxf assembly to delete the redundant lines in the dxf format file, leaving only the boundary lines and target object lines.

[0020] Furthermore, step 5 includes: using the pandas.read_csv() command to read the settlement cloud maps of different periods drawn by the Surfer software, using the numpy.array() command to convert the settlement cloud map data of different periods into arrays, using slices to extract X-axis data, Y-axis data and Z-axis data, and using a for loop to perform settlement calculations, specifically: dZ=Z1[i]-Z[i], Z1[i] is a settlement cloud map measured recently, Z[i] is a settlement cloud map measured in the long term, i is the number of loops, the number of loops depends on the length of a single column, the length of a single column indexes the number of data in the group, and is calculated by the len() command; filtering the obtained dZ, and when dZ≤0, using the pandas.DataFrame() command to store the XY coordinates of the recently measured settlement cloud map and the dZ data in a list; using c.to_csv() (c= pandas.DataFrame()) to save the data as a csv format file; and then importing the file into Surfer to obtain the settlement cloud map and settlement contour map of the collapse area.

[0021] The beneficial effects of the present invention are: giving full play to the advantages of three-dimensional laser scanning and drone photography technology for pit collapse subsidence monitoring, solving the difficult problem of difficult settlement calculation in the collapse area, and having been successfully applied to a metal mine in Hubei Province. It is of great significance to the safety production guidance of underground mining in domestic metal mines and the control of surface pit collapse. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 It is the original topographic map;

[0023] Figure 2 It is a 2016 topographic map based on 3D laser scanning;

[0024] Figure 3 The 2020 topographic map is based on 3D laser scanning;

[0025] Figure 4 Aerial images based on drone photography (manually annotated);

[0026] Figure 5 This is a schematic diagram of the conversion between jpg format image coordinates and dxf format coordinates;

[0027] Figure 6 It is a drone aerial image .dxf format exported based on Python;

[0028] Figure 7 2016 topographic map based on 3D laser scanning with calculated boundaries and object annotations;

[0029] Figure 82020 topographic map based on 3D laser scanning with calculated boundaries and object annotations;

[0030] Fig. 9 2016 surface subsidence cloud map interpolated for Surfer software;

[0031] Fig.10 2020 surface subsidence cloud map interpolated for Surfer software;

[0032] Fig.11 A cloud map of the difference in ground subsidence between two 3D laser scanning measurements interpolated by Surfer software;

[0033] Fig.12 Contour map of settlement differences between two 3D laser scan measurements interpolated by Surfer software. DETAILED DESCRIPTION

[0034] In order to make the purpose, technical solution and advantages of the embodiments of the present disclosure clearer, the technical solution of the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings of the embodiments of the present disclosure. Obviously, the described embodiments are part of the embodiments of the present disclosure, not all of the embodiments. Based on the described embodiments of the present disclosure, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present disclosure.

[0035] Example 1

[0036] S01, such as Figure 1 As shown, a topographic map with known three-dimensional coordinates is required. The topographic map must contain the target objects manually marked by the drone, so as to facilitate the subsequent calibration of the specific location of the objects in the drone photography. In the safe area next to the subsidence area, the Leica HDS8800 3D laser scanner is used for scanning, and GPS is used to locate the foresight and backsight points of the scan, so as to facilitate the subsequent comparison with the topographic map with known coordinates. The acquired point cloud data of the subsidence area is processed by Maptek Ⅰ-Site Studio 4.0 post-processing software, and the surface scanned topographic map of the entire subsidence area is obtained. The surface scanned topographic map shows the topographic contour lines (dxf format). The surface scanned topographic map contains XYZ three-dimensional coordinates and is consistent with the Figure 1 The coordinate system in the surface scan topographic map is consistent. The coordinates in the surface scan topographic map can be viewed through the PROPERTIES command in CAD. Here we take the surface scan topographic map results of 2016 and 2020 as an example. Figure 2 and Figure 3 shown.

[0037] In this step, the foresight point is usually a reference point in front of the scanner's current position, and the backsight point is a reference point behind the scanner's current position. Maptek I-Site Studio 4.0 is a professional 3D point cloud processing and modeling software used to create accurate 3D surface models from point cloud data.

[0038] S02. Convert the format of the surface scanned topographic map:

[0039] Import the surface scanned topographic map obtained by S01 into the DXF2XYZ software processing package, set the data output format to the XYZ three-dimensional coordinate format, and obtain the three-dimensional data coordinates in the xyz format; then open the xyz format file with Notepad and save it as a csv format file to prepare for the subsequent convenient import into the Surfer software. DXF2XYZ is a software specifically used to convert DXF files into coordinate data. Surfer is a terrain mapping and three-dimensional surface mapping software.

[0040] S03. Use a drone to photograph the subsidence area, and make the drone rise to a height where the entire subsidence area can be clearly seen. During the specific operation, the camera lens should be perpendicular to the ground, and the direction should be adjusted according to the built-in compass so that the captured plane image meets the "north at the top, south at the bottom, west at the left, and east at the right" rule, which is convenient for merging and comparing with subsequent topographic maps. Then annotate the aerial images, select the image processing tool that comes with Windows, and draw the boundary of the subsidence area for settlement calculation according to the location of the collapse (the boundary is a rectangle here). When annotating, select the straight line tool, and try to ensure that the lines intersect vertically. Then select a target object of known size. As an example target object, select an abandoned building in the mining area, and this building is in Figure 1 Distances can be measured using the DIST command in CAD.

[0041] Convert the pictures obtained by drone photography into dxf format graphics based on python:

[0042] like Figure 4 The picture shown is the completed annotation picture. Then use python and the third-party library CV2 package and ezdxf package to convert the jpg format picture into a dxf format file.

[0043] The CV2 package is part of the OpenCV (Open Source Computer Vision Librar) project, an open source library designed for computer vision and machine learning. OpenCV is widely used for real-time image processing and computer vision tasks. ezdxf is a python library designed for processing DXF files. DXF is a file format developed by Autodesk for data interoperability between AutoCAD and other software applications. ezdxf allows creating, modifying, and reading DXF files programmatically using Python.

[0044] Specific operations:

[0045] Use cv2.imread() command to import the image, and then use cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) command to convert the image to a grayscale image (where image is the path of the imported image, and cv2.COLOR_BGR2GRAY is to convert color to gray). The relationship between blue, green, and red and gray is: Gray=0.299×R+0.587×G+0.114×B;

[0046] Among them, B: blue; G: green; R: red;

[0047] Use cv2.GaussianBlur() command to perform blur processing to reduce the noise in the image and make edge detection more accurate. Then use cv2.Canny command to find the boundary of the image. Then use cv2.findContours() to search for the image contour. Use for loop to traverse the points in the contour and create polylines in the DXF file. It should be noted that the Y coordinate representation in the coordinate system of the jpg format image and the dxf format file is inconsistent (such as Figure 5As shown), the 0 point of the jpg format image is in the upper left corner, Y is vertically downward, and the 0 point of the dxf file coordinates is in the lower left corner, and Y is vertically upward. This requires the Y coordinate to be transformed. Just subtract the Y coordinate value of the corresponding point in the upper left corner of the jpg image from the image height of the jpg image, so that the point obtained by the dxf file is consistent with the position of the point in the jpg image. The image height refers to the number of pixels from the top to the bottom of the image. Use the ezdxf.new() command to create a new DXF document and assign it to variable a. Use the a.modelspace() (a= ezdxf.new()) command to establish a model space based on variable a and assign it to variable b. Use the b. add_lwpolyline() (b=a.modelspace()) command to draw the contour points traversed from variable b as polylines, and then use the a.saves() (a=ezdxf.new()) command to export the dxf file of the polyline (as shown in Figure 6 Delete the redundant lines and keep only the boundary lines and target object lines.

[0048] S04. Import the dxf format graphic boundary obtained by drone photography into the topographic map obtained by S01 3D laser to determine the calculation boundary of the collapse area:

[0049] Before copying, the graphics obtained in S03 need to be scaled proportionally according to the length of the sides of the target objects in the two graphics, so that they can overlap with the surface scan topographic maps processed in two different periods in step S01. Therefore, the DIST command in CAD is used to select the long side of the target object for measurement, and the long side of the target object in the graphics obtained in S03 is X times the long side of the building in the surface scan topographic map obtained in S01. Then the Scale command in CAD is used to scale the graphics obtained in S03 to 1\X times. Figure 1 ) is imported into the surface scanned topographic maps of two different periods processed by step S01 (such as Figure 7 and Figure 8The 2016 and 2020 surface scan topographic maps of the target building are imported respectively). The dxf file of the graphics obtained in S03 is imported into the dxf files of the surface scan topographic maps of two different periods processed by step S01 using the copy command, and the building corner point is used as the insertion point to make the building side lengths of the two files completely overlap. In the surface scan topographic maps of two different periods processed in step S01, different color line types are used to redraw the calculation boundary (the calculation boundary is the boundary of the collapse area manually marked by the drone aerial photography, which is a rectangular boundary). The PROPERTIES command in CAD is used to view the calculation boundary coordinates, which are (578447.1276, 3334811.4044) and (578896.4671, 3334811.4044), and (578447.1276, 3335148.3103) and (578896.4671, 3335148.3103).

[0050] S05. Calculation of settlement in the subsidence area and drawing of settlement contour lines and cloud maps:

[0051] According to the XY coordinates of the calculated boundary determined in step S04, select the coordinates of the two corner points of the calculated boundary of the rectangle (578447.1276, 3334811.4044) and (578896.4671, 3335148.3103). Use Surfer software to import the maximum and minimum coordinates in the X and Y directions, and set the scale interpolation interval in the X and Y directions to 1m. Figure 3 The XYZ coordinates in the specified area are obtained by importing the XYZ coordinates into Surfer, and then the GRD file is obtained after Surfer interpolation (here Kriging interpolation method is selected) and then saved as a DAT file. Figure 7 and Figure 8 The XY coordinates of the different 3D laser scanning results are consistent, only the Z coordinate is inconsistent due to surface subsidence. The settlement cloud map of the two results is drawn by Surfer software (such as Fig. 9 and Fig.10 as shown).

[0052] S06. Import the data file in S05 into the python software and use the numpy and pandas libraries to calculate the settlement value dZ obtained from the two measurements.

[0053] Specific steps:

[0054] Use the pandas.read_csv() command to read the subsidence cloud maps drawn by the Surfer software in 2016 and 2020, use the numpy.array() command to convert different subsidence cloud map data into arrays, and use slicing to extract X-axis data, Y-axis data, and Z-axis data. Use a for loop to calculate the subsidence, specifically: dZ=Z1[i] - Z[i], where Z1[i] is the subsidence value (i.e., Z coordinate) of the topographic map measured in 2020, Z[i] is the topographic map data measured in 2016, and i is the number of loops. The number of loops depends on the length of a single column. The length of a single column refers to the number of data in the group data, which can be calculated by the len() command. Filter the obtained dZ. When dZ≤0, use the pandas.DataFrame() command to store the XY coordinates and dZ data of 2020 in a list. Use c.to_csv() (c= pandas.DataFrame()) to save the data as a csv file. Then import the file into Surfer to obtain the settlement cloud map and settlement contour map of the collapse area, such as Fig.11 and Fig.12 .

[0055] The invention has been successfully applied in a metal mine in Hubei Province, and has important significance for the safety production guidance of underground mining and the treatment of surface pit collapse in domestic metal mines.

[0056] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for calculating the settlement of a tectonic stress type metal mine subsidence area using drone photography, characterized in that: The steps include: Step 1: Scan the collapse area of ​​the known topographic map at different times by using a 3D laser scanner, and process the data to obtain a surface topographic map whose 3D coordinates can be viewed through CAD. The known topographic map is a 3D coordinate topographic map containing the target object, and uses the same coordinate system as the surface topographic map; Step 2: Obtain an aerial picture of the subsidence area through drone photography, manually mark the calculated boundary of the subsidence area in the picture, and select the target object; Step 3: Use Python to identify the calculated boundaries and target objects in the aerial images, and export the aerial graphics files containing the calculated boundaries and target objects. The aerial graphics files are in the same format as the surface topographic map. Then, through the CAD scaling command, the target objects in the aerial graphics files are made the same size as the target objects in the known topographic map. First, the target objects in the known topographic map are imported into the surface topographic maps of different periods through the CAD base point copy command. Then, the corner points of the target objects are used as insertion points to import the aerial graphics files into the surface topographic maps of different periods, so that the edges of the target objects in the two files overlap. Step 4: Determine the calculation boundary coordinates of the calculation boundary of the aerial photography graphics file in the surface topographic map at different periods, export the XYZ coordinates within the calculation boundary coordinate range in the surface topographic map at different periods, and use Surfer software to draw the settlement cloud map at different periods according to the exported XYZ coordinates; Step 5: Based on the settlement cloud maps of different periods, make a difference to obtain the three-dimensional settlement cloud map and the settlement contour lines of the collapse area.

2. The method according to claim 1, characterized in that: The step 1 comprises: Step 11: Use a 3D laser scanner to scan the subsidence area of ​​the known topographic map at different times, use GPS to locate the foresight point and the backsight point of the scan, and use MaptekⅠ-Site Studio 4.0 software to splice, filter, and denoise the acquired point cloud data of the subsidence area to obtain the ground scan topography of the entire mining subsidence area, and output the surface scan topographic map in dxf format; Step 12: Import the dxf file obtained in step 11 into the DXF2XYZ software processing package to obtain the three-dimensional data coordinates in the xyz format, then open the xyz format file with Notepad and save it as a csv format file.

3. The method according to claim 1, characterized in that In step 2, when the drone is photographing, the lens is perpendicular to the ground, and the direction of photography is adjusted according to the built-in compass so that the top, bottom, left, right and right of the photographed plane image correspond to the north, south, west and east respectively; the calculated boundary is a closed area drawn by mutually perpendicular line segments.

4. The method according to claim 1, characterized in that In step 3, Python recognizes the calculation boundary and target object in the aerial image, including: In Python, call the third-party library CV2 assembly to convert the jpg format image into a dxf format file. During the conversion, subtract the Y coordinate value of the corresponding point in the upper left corner of the jpg image from the image height of the jpg image, so that the point obtained in the dxf file is consistent with the position of the point in the jpg image. Call the ezdxf assembly to delete the redundant lines in the dxf format file, leaving only the boundary lines and target object lines.

5. The method according to claim 1, characterized in that The step 5 comprises: Use the pandas.read_csv() command to read the settlement cloud maps of different periods drawn by the Surfer software, use the numpy.array() command to convert the settlement cloud map data of different periods into arrays, use slicing to extract the X-axis data, Y-axis data and Z-axis data, and use the for loop to calculate the settlement: dZ=Z1[i] - Z[i], Z1[i] is the settlement cloud map measured recently, Z[i] is the settlement cloud map measured in the long term, i is the number of loops, the number of loops depends on the length of a single column, and the length of a single column refers to the number of data in the group, which is calculated by the len() command; filter the obtained dZ, and when dZ≤0, use the pandas.DataFrame() command to store the XY coordinates of the recently measured settlement cloud map and the dZ data in a list; use c.to_csv() (c= pandas.DataFrame()) to save the data as a csv format file; then import the file into Surfer to obtain the settlement cloud map and settlement contour map of the collapse area.

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