Method for automatically splicing three-dimensional model of power transmission line iron tower based on design drawing

Abstract

The invention discloses a method for automatically splicing a three-dimensional model of a power transmission line iron tower based on a design drawing, and the method automatically carries out the splicing of the three-dimensional model of the power transmission line iron tower according to the position parameters of the design drawing through the recognition and extraction of drawing data and the copying and translation of point cloud data. According to the method, firstly, a drawing is scanned and analyzed through image processing and text recognition, the position and the relative relation of a local module of each electric tower assembly in an overall three-dimensional model are determined, then displacement operation is carried out under a three-dimensional coordinate axis by utilizing position parameters based on point cloud files of all the assemblies of the iron tower, and the three-dimensional model is obtained. All the assemblies are accurately positioned and adjusted, and a complete three-dimensional model of the power transmission line iron tower is obtained after automatic splicing. According to the method, cost and time waste caused by manual assembly and repeated labor are reduced, a foundation and support are provided for research and development of digital products of the electric power system, and the method has great significance in comprehensively promoting digital transformation of the electric power system.

Description

Technical Field

[0001] The invention relates to the fields of electric power grid, three-dimensional reconstruction, computer vision and artificial intelligence technology, and in particular to a method for automatically splicing a three-dimensional model of a transmission line tower based on a design drawing. Background Art

[0002] Power grids and transmission lines play a vital role in the national economy and people's livelihood. To ensure the stability and reliability of the power grid, digital, intelligent and information-based power grids have become the trend of development and transformation of the power system in today's society. In order to improve the monitoring, control and management capabilities of the power system, many engineering projects have applied digital technology and information and communication technology to modularize, visualize and standardize the various components in the power system, and three-dimensional models have been widely used in them.

[0003] However, the current mainstream transmission line 3D modeling software, such as GIM, Daoheng, etc., has sufficient modular local 3D models of transmission lines, but it is relatively time-consuming to splice the 3D models into a whole. At present, the main 3D model splicing still requires designers to observe drawings, record data, and manually splice the 3D model on specific software. Therefore, the automatic splicing of 3D models based on design drawings is a highly innovative and practical work in the current smart grid construction process. Summary of the invention

[0004] The problem to be solved by the present invention is to provide a method for automatically splicing a three-dimensional model of a transmission line tower based on a design drawing, which can automatically splice the three-dimensional model of a transmission line tower without the need for designers to manually splice it with the help of professional point cloud software.

[0005] The present invention adopts the following technical solution: a method for automatically splicing a three-dimensional model of a transmission line tower based on a design drawing, the specific steps are:

[0006] Step 1: using a digital image processing method, identifying and extracting straight line segments in a design drawing of a transmission line tower at a pixel level, and summarizing to obtain a set of straight line segments;

[0007] Step 2: According to the set of straight line segments extracted in step 1, find the longest vertical line according to the judgment condition, intercept the text side picture based on the longest vertical line to retain the text side content and perform text recognition, and calculate the longitudinal displacement distance of the corresponding cross arm and tower body;

[0008] Step 3: Based on the longest vertical line obtained in step 2, extend to the side of the tower and intercept the side picture of the tower, project the whole side picture of the tower onto the vertical axis, use the probability density projection method to find several density peaks, determine the position of the cross arm, select the recognition frame at the cross arm to perform text recognition on the side picture of the tower, and calculate the lateral displacement distance of the corresponding cross arm;

[0009] Step 4: Convert the pre-input point cloud files of each component of the tower into text files, transform the coordinates of each point cloud by combining the longitudinal displacement distance obtained in step 2 and the lateral displacement distance obtained in step 3, integrate the text files of each point cloud into one text file, and convert and output them into point cloud format files to obtain a complete three-dimensional model of the transmission line tower.

[0010] Preferably, the design drawing used in step 1 is a two-dimensional design drawing of a transmission line tower actually used in a power grid, which is stored in JPG or PNG format and includes an overall steel frame structure diagram, tower assembly instructions, tower detailed height information, and tower detailed width information;

[0011] The digital image processing method is OpenCV and its various functions, including grayscale image conversion, edge detection, Hough line transform, etc., which are used to identify and extract all straight line segments of a certain length in two-dimensional design drawings;

[0012] Grayscale image conversion mainly converts the input image into a grayscale image, and further converts it into a black and white image to simplify processing and facilitate the distinction between text and background;

[0013] The purpose of edge detection is to identify a set of pixels with drastic brightness changes in the input image, so as to facilitate the subsequent positioning and segmentation of straight line segments in the image.

[0014] The Hough line transform completes line detection by finding peaks in the parameter space, and obtains a set of straight line segments based on the set minimum straight line length and maximum line segment breakpoints.

[0015] Preferably, in step 2, the judgment condition is to input the longest vertical line within the range of 20%-80% up and down and 20%-80% left and right of the drawing, and a number of longest vertical lines with the same length will be obtained according to the detailed height information of the iron tower provided in the drawing, which respectively correspond to the vertical line of the maximum height of the iron tower, the vertical line of the maximum height of the cross arm from the ground, the vertical line of the maximum height of the tower body from the ground, etc.;

[0016] In step 2, based on the longest vertical line, the text side pictures are intercepted, corresponding to: the text side picture of the entire tower height, the text side picture of the crossarm height, and the text side picture of the tower body height. The range of each text side picture is determined as follows: corresponding to the longest vertical line, extend 50 pixels, 10 pixels, 10 pixels, and 10 pixels to the left, right, top, and bottom, respectively.

[0017] In step 3, based on the vertical line of the maximum height of the tower from the ground, the side image of the tower is captured, with the range being: extending 200 pixels and 1800 pixels to the right side, i.e. the side of the tower, extending 200 pixels to the upper side, and shortening the lower side to the midpoint of the vertical line.

[0018] Preferably, in step 3, a probability density projection method is used to project all pixels of the intercepted tower side image onto the y-axis to obtain a probability density function of the pixel distribution with respect to the y-coordinate, and the observation function is specially made to find a peak value with a density greater than 0.1, and the y-coordinate of the original data is determined, thereby dividing the identification box of the horizontal width of the crossarm.

[0019] Preferably, in step 3, it is necessary to divide several rectangular frames according to certain conditions based on the peak y coordinate and combine them to obtain a recognition frame, that is, every two adjacent peak y coordinates that are no more than 100 pixels long are added to the image width to form a rectangular frame. In particular, the first peak y coordinate is extended upward by 50 pixels to form a rectangular frame plus the image width, and text recognition is performed in the rectangular frame to obtain better recognition effect.

[0020] Preferably, in step 2 and step 3, the image-based text recognition algorithm is tesseract OCR, and the setting parameters are --oem3--psm 6outputbase digits;

[0021] Step 2 further processes the data obtained from text recognition, removes incorrectly recognized text symbols and numbers, separates accidentally conjoined data, and stores each row of recognized data into a parameter matrix. The corresponding row represents the total height, crossarm height, and tower height. The row parameters are accumulated to obtain the height of each group of crossarms and each tower body, which is the longitudinal displacement distance when the whole is spliced.

[0022] Step 3 further processes the data obtained from text recognition, removes incorrectly recognized text symbols and numbers, and only retains the width of each crossarm. All crossarm widths are combined into an array, which is the lateral displacement distance when the crossarms are spliced.

[0023] Preferably, in step 4, the point cloud format is a .pcd file, and the text format is a .txt file. The point cloud file is read using the open3d library, and the data is converted into an array using the numpy library. Each point is then written into the text file in the order of x, y, and z coordinates. In particular, the symmetrical crossarm requires the point cloud file to be converted into two identical text files.

[0024] When converting a text file to a point cloud format file, the PCD header information that needs to be written includes: VERSION, FIELDS, SIZE, TYPE, COUNT, WIDTH, HEIGHT, VIEWPOINT, POINTS, and DATA ascii.

[0025] Preferably, in step 4, the text file converted from the point cloud of each tower component is transformed into coordinates in the x, y, and z directions using the horizontal and vertical displacement distances, and the z coordinate of each point of the point cloud of each tower component is added with the corresponding longitudinal displacement distance, and the x coordinate of each point of each cross arm point cloud is added with the corresponding horizontal displacement distance, and the y coordinate of each component point cloud is kept unchanged, and the x coordinate of each tower body point cloud is kept unchanged;

[0026] The point cloud text files of each component are sequentially combined into a text file, and then converted into a point cloud format file, thus completing the splicing of the three-dimensional model of the overall transmission line tower.

[0027] The technical solution of the present invention also provides: an electronic device, comprising:

[0028] one or more processors;

[0029] a storage device having one or more programs stored thereon;

[0030] When the one or more programs are executed by the one or more processors, the one or more processors implement any of the above-mentioned methods for automatically splicing a three-dimensional model of a transmission line tower based on a design drawing.

[0031] The technical solution of the present invention also provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the steps in any of the above-mentioned methods for automatically splicing a three-dimensional model of a transmission line tower based on a design drawing are implemented.

[0032] Compared with the prior art, the present invention adopts the above technical solution and has the following technical effects:

[0033] 1. Compared with the method in which designers read and analyze professional drawings to obtain the position information and relative relationship of each component in the overall model, the method of automatically splicing the three-dimensional model of the transmission line tower of the present invention reduces the manpower demand, and the data extraction is accurate and rapid, and has the potential for expanding applications.

[0034] 2. Compared with the functions of point cloud flipping, copying, and translating of 3D modeling software such as CloudCompare, the method of automatically splicing the 3D model of a transmission line tower in the present invention is suitable for architectural drawings of transmission line towers with numerous components and regular structures. It has fewer requirements for the input of the overall design drawing, does not require a large amount of manual operation, and is more in line with the goals of intelligent and digital design.

[0035] 3. Compared with other traditional methods of splicing three-dimensional models, the method of automatically splicing the three-dimensional model of the transmission line tower of the present invention makes full use of the design structure of the tower and the composition rules of point cloud data for splicing. The algorithm requirements are simple, the operation time is short, and the splicing accuracy is high.

[0036] 4. The method of the present invention can automatically splice the three-dimensional point cloud of the transmission tower based on the design drawings, and can be used for standard point cloud registration, local component position information extraction, three-dimensional model batch transformation and other tasks, and has high engineering application value and academic research value. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 A design flow chart of a method for automatically splicing a three-dimensional model of a transmission line tower according to the present invention;

[0038] Figure 2 It is a general design drawing of a power transmission line tower actually used in an embodiment of the present invention;

[0039] Figure 3 are all straight line segments extracted in the embodiment of the present invention;

[0040] Figure 4 The text side picture captured by the embodiment of the present invention;

[0041] Figure 5 This is a side picture of the tower taken from an embodiment of the present invention;

[0042] Figure 6 is the probability density function of the tower side image projected in the embodiment of the present invention;

[0043] Figure 7 The identification frame divided by the tower body side and the corresponding identification result in the embodiment of the present invention;

[0044] Figure 8 This is a three-dimensional model diagram of an integral transmission line tower automatically spliced ​​according to an embodiment of the present invention. DETAILED DESCRIPTION

[0045] In order to explain the technical content, structural features, achieved purposes and effects of the present invention in detail, the present invention will be described in detail below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiment described in the drawings is only one embodiment of the present invention, not all embodiments. The components of the embodiments of the present invention described and shown in the drawings can be arranged and designed in different quantities and orders. In addition, the image processing algorithm used in the present invention is only a tool for realizing related functions and can be replaced by other algorithmic technologies with the same type of functions. Therefore, based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present invention.

[0046] The present invention provides a method for automatically splicing a three-dimensional model of a transmission line tower based on a design drawing, such as Figure 1 As shown, the steps are as follows:

[0047] Step 1: Using digital image processing technology, identify and extract straight line segments of a certain length in the design drawings of the transmission line tower at the pixel level, and summarize them into a set of multiple straight line segments;

[0048] Step 2: The set of straight line segments extracted in step 1 is subjected to conditional judgment to find the longest vertical line within a certain range, and based on the vertical line, the text side content is retained to capture the text side image, perform text recognition on the image, and calculate the longitudinal displacement distance of the corresponding crossarm and tower body.

[0049] Step 3: Based on the longest vertical line obtained in step 2, extend a certain range to the side of the tower and intercept the picture of the side of the tower, project the whole picture onto the vertical axis, use the probability density projection method to find several density peaks to determine the position of the crossarm, select the recognition box at the crossarm to perform text recognition on the picture, and calculate the lateral displacement distance of the corresponding crossarm.

[0050] Step 4: Convert the pre-input point cloud files of each component of the tower into text files. Based on the lateral displacement distance output in step 3 and the longitudinal displacement distance extracted in step 2, increase or decrease the x-axis and z-axis coordinates of each point cloud accordingly. Finally, integrate the point cloud files into a text file and convert and output them into a point cloud format file to obtain a complete three-dimensional model of the transmission line tower.

[0051] In one embodiment of the present invention, the overall design drawings of the transmission line towers actually used in the power grid are adopted, such as Figure 2 The method of the present invention is used to automatically splice the three-dimensional model of the high-voltage tower of the power transmission line, specifically including:

[0052] Step 1. Extract a set of straight line segments of a certain length from the drawing based on image processing technology.

[0053] The digital image processing technology used is OpenCV and the various functions it contains, including: grayscale image conversion, edge detection, Hough line transform, etc.

[0054] Among them, grayscale image conversion: convert the input image into a grayscale image, and further convert it into a black and white image to simplify processing and facilitate the distinction between text and background;

[0055] Edge detection: Identify the set of pixels with drastic brightness changes in the input image, which facilitates the subsequent positioning and segmentation of straight line segments in the image;

[0056] Hough Line Transform: Line detection is performed by finding peaks in parameter space.

[0057] In this embodiment, straight line segments with a minimum length of 500 pixels and a maximum line segment breakpoint of 50 pixels are extracted from the drawing and grouped into one set. The effect is as follows: Figure 3 shown.

[0058] Step 2. Filter out the longest vertical line through conditional judgment, and expand and capture the image based on this to divide the text recognition range.

[0059] In this embodiment, the judgment condition is to input the longest vertical line within the range of 20%-80% above and below and 20%-80% left and right of the drawing. According to the detailed height information of the tower provided in the drawing, several longest vertical lines of the same length will be obtained, which correspond to the maximum height of the tower, the maximum height of the cross arm above the ground, the maximum height of the tower body above the ground, etc.

[0060] According to different subsequent functions, expand to the text side and the tower side to crop the picture, such as Figure 4 As shown, in step 2, the text side images are intercepted based on each vertical line, and the range is: the vertical line extends 50 pixels to the left, that is, the text side, the vertical line extends 10 pixels to the right, and the vertical line extends 10 pixels upward and downward; Figure 5 As shown, the tower side image captured in step 3 is based on the last longest vertical line, that is, the vertical line of the tower's maximum height from the ground. The capture range is that the vertical line extends 200 pixels and 1800 pixels to the right, that is, the tower side, and extends 200 pixels to the upper side, and is shortened to the midpoint of the vertical line on the lower side.

[0061] Then, the probability density projection method is used to project all pixels of the intercepted tower side image to the y-axis, as shown in Figure 6 As shown, the probability density function of the pixel distribution with respect to the y coordinate is obtained.

[0062] Observe the probability density function and find the peak value with density greater than 0.1, determine the y coordinate of the original data, and use it to divide the identification frame of the horizontal width of the crossarm. The identification frame is divided according to certain conditions based on the peak y coordinate, that is, every two adjacent peak y coordinates that do not exceed 100 pixels are long, and the image width is added to form a rectangular frame.

[0063] In particular, in this embodiment, the first peak y coordinate is extended upward by 50 pixels to form a rectangular frame with the image width, such as Figure 7 As shown, text recognition is performed within the rectangular frame to obtain a better recognition effect.

[0064] Step 3. Perform text recognition on the identification boxes in the captured text side image and tower body side image respectively.

[0065] First, the tesseract OCR text recognition algorithm is used to recognize the image, and the parameters are set to --oem3--psm 6outputbase digits.

[0066] At the same time, the identified data needs further processing:

[0067] For the image recognition results on the text side, the incorrectly recognized text symbols and numbers are removed, the accidentally conjoined data are separated, and each row of recognized data is stored in the parameter matrix. The corresponding row represents the total height, crossarm height, and tower body height. The row parameters are added up to obtain the height of each group of crossarms and each tower body, that is, the longitudinal displacement distance when the whole is spliced.

[0068] For the recognition results of the tower side picture, the incorrectly recognized text symbols and numbers are removed, and only the width of each crossarm is retained. All crossarm widths are combined into an array, which is the lateral displacement distance when the crossarms are spliced. In addition, zeros are added to the lateral displacement array until the array length is consistent with the number of spliced ​​parts, which is the lateral displacement distance when the whole is spliced.

[0069] Step 4. Based on the constructed horizontal and vertical displacement distances, convert the point cloud format and perform corresponding coordinate transformation.

[0070] First, import the point cloud format as a .pcd file, and convert it into a .txt file. Use the open3d library to read the point cloud file, and use the numpy library to convert the data into an array. Then write each point into a text file in the order of x, y, and z coordinates. In particular, the symmetrical crossarm requires the point cloud file to be converted into two identical text files.

[0071] It should be noted that, in this embodiment, during the process of converting a text file into a point cloud format file, the PCD header information written includes:

[0072] (a) “VERSION 07\n”

[0073] (b) “FIELDS xyz\n”

[0074] (c) “SIZE 4 4 4\n”

[0075] (d) "TYPE FFF\n"

[0076] (e) “COUNT 1 1 1\n”

[0077] (f)"WIDTH{}\n".format(len(points))

[0078] (g)“HEIGHT 1\n”

[0079] (h) "VIEWPOINT 0 0 0 1 0 0 0\n"

[0080] (i)"POINTS{}\n".format(len(points))

[0081] (j) "DATA ascii\n"

[0082] Next, the text files converted from the point clouds of each tower component are transformed in the x, y, and z directions using the horizontal and vertical displacement distances. That is, the z coordinate of each point in the point cloud of each tower component is added with the corresponding longitudinal displacement distance, and the x coordinate of each point in the point cloud of each crossarm is added with the corresponding horizontal displacement distance. In addition, the y coordinate of each component point cloud is kept unchanged, and the x coordinate of each tower body point cloud is kept unchanged.

[0083] Finally, all the text files of each component are read and written into a text file in sequence, and then converted into a point cloud format file, so as to obtain the three-dimensional model diagram of the overall transmission line tower. Figure 8 shown.

[0084] In an embodiment of the present invention, an electronic device is also provided, including: one or more processors; a storage device on which one or more programs are stored; when the one or more programs are executed by the one or more processors, the one or more processors implement the method described in the embodiment for automatically splicing a three-dimensional model of a transmission line tower based on a design drawing.

[0085] In an embodiment of the present invention, a computer-readable storage medium is further provided, on which a computer program is stored. When the program is executed by a processor, the steps in the method for automatically splicing a three-dimensional model of a transmission line tower based on a design drawing described in the embodiment are implemented.

[0086] It should be noted that the image processing method provided by the present invention may have a variety of variations and improvements. Without creative work, those skilled in the art may adopt different drawing data, different parameter ranges, different algorithm variations, etc. in the above manner, which are all included in the patent protection scope of the present invention.

[0087] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for automatically splicing a three-dimensional model of a transmission line tower based on a design drawing, characterized in that: The steps include: Step 1: using a digital image processing method, identifying and extracting straight line segments in a design drawing of a transmission line tower at a pixel level, and summarizing to obtain a set of straight line segments; Step 2: According to the set of straight line segments extracted in step 1, find the longest vertical line according to the judgment condition, intercept the text side picture based on the longest vertical line to retain the text side content and perform text recognition, and calculate the longitudinal displacement distance of the corresponding cross arm and tower body; Step 3: Based on the longest vertical line obtained in step 2, extend to the side of the tower and intercept the side picture of the tower, project the whole side picture of the tower onto the vertical axis, use the probability density projection method to find several density peaks, determine the position of the cross arm, select the recognition frame at the cross arm to perform text recognition on the side picture of the tower, and calculate the lateral displacement distance of the corresponding cross arm; Step 4: Convert the pre-input point cloud files of each component of the tower into text files, transform the coordinates of each point cloud by combining the longitudinal displacement distance obtained in step 2 and the lateral displacement distance obtained in step 3, integrate the text files of each point cloud into one text file, and convert and output them into point cloud format files to obtain a complete three-dimensional model of the transmission line tower.

2. The method for automatically splicing a three-dimensional model of a transmission line tower according to claim 1, characterized in that: In step 1, the design drawing is a two-dimensional design drawing of a transmission line tower actually used in a power grid, which is stored in the form of JPG or PNG and includes an overall steel frame structure diagram, tower assembly instructions, tower detailed height information, and tower detailed width information; The digital image processing method is based on OpenCV and the functions included therein, and includes: grayscale image conversion, edge detection, and Hough line transformation, which are used to identify and extract straight line segments within a preset length range in the two-dimensional design master drawing, and obtain a straight line segment set according to the set minimum straight line length and maximum line segment breakpoint; The grayscale image conversion converts the input image into a grayscale image and a black-and-white image in sequence, so as to distinguish text from background; The edge detection identifies pixels in the input image whose brightness changes exceed a threshold value and forms a set for locating and segmenting straight line segments in the image; The Hough line transform performs line detection by finding the peak value in the parameter space.

3. The method for automatically splicing a three-dimensional model of a transmission line tower according to claim 1, characterized in that: In step 2, the judgment condition is: input the longest vertical line within the range of 20%-80% up and down and 20%-80% left and right of the design drawing, and obtain a number of longest vertical lines of the same length according to the tower height information provided by the design drawing, which correspond to the vertical line of the maximum height of the tower, the vertical line of the maximum height of the cross arm from the ground, and the vertical line of the maximum height of the tower body from the ground; Based on the longest vertical line, the text side pictures are cut off, corresponding to: the text side picture of the entire tower height, the text side picture of the crossarm height, and the text side picture of the tower body height. The range of each text side picture is determined as follows: corresponding to the longest vertical line, extend 50 pixels, 10 pixels, 10 pixels, and 10 pixels to the left, right, top, and bottom respectively.

4. The method for automatically splicing a three-dimensional model of a transmission line tower according to claim 3, characterized in that: In step 3, the side image of the tower is captured in the following range: based on the vertical line of the maximum ground height of the tower, the image is extended 200 pixels and 1800 pixels to the side of the tower, 200 pixels to the upper side, and the lower side is shortened to the midpoint of the vertical line; The probability density projection method projects all pixels of the intercepted tower side image to the y-axis, obtains the probability density function of the pixel distribution about the y-coordinate, finds the peak value with density greater than 0.1, determines the y-coordinate of the original data, and divides it to obtain the identification frame of the horizontal width of the crossarm.

5. The method for automatically splicing a three-dimensional model of a transmission line tower according to claim 4, characterized in that: In step 3, a recognition frame is selected at the cross arm to perform text recognition on the tower side picture, and a number of rectangular frames are divided according to the peak y coordinate to form a text recognition frame; The width of the rectangular frame is the width of the image, the length of the first rectangular frame is 50 pixels upward from the first peak y coordinate, and the length of other rectangular frames is the peak y coordinates of each two adjacent frames that are no more than 100 pixels long.

6. The method for automatically splicing a three-dimensional model of a transmission line tower according to claim 4, characterized in that: In step 2 and step 3, the image-based text recognition method is tesseract OCR, and the parameters are set to oem 3, psm 6, and outputbase digits; Step 2: After performing text recognition on the text side image, remove the incorrectly recognized text symbols and numbers, separate the accidentally conjoined data, store each row of recognized data into the parameter matrix, and the corresponding row represents the total height, crossarm height, and tower height. The row parameters are accumulated to obtain the height of each group of crossarms and each tower body as the longitudinal displacement distance when the whole is spliced; Step 3: After performing text recognition on the tower side image, remove the incorrectly recognized text symbols and numbers, retain only the width of each crossarm, and combine all the crossarm widths into an array as the lateral displacement distance when the crossarms are spliced.

7. The method for automatically splicing a three-dimensional model of a transmission line tower according to claim 4, characterized in that: In step 4, the point cloud file is in .pcd format, and the text file is in .txt format. The point cloud file is read through the open3d library, and the point cloud data is converted into an array using the numpy library. Each point is written into the text file in the order of x, y, and z coordinates. For the symmetrical crossarm, the point cloud file is converted into two identical text files. Integrate the text files of each point cloud into one text file, write the header information of the pcd file, and convert and output it into a point cloud format file; The header information includes: VERSION, FIELDS, SIZE, TYPE, COUNT, WIDTH, HEIGHT, VIEWPOINT, POINTS, DATA ascii.

8. The method for automatically splicing a three-dimensional model of a transmission line tower according to claim 7, characterized in that: In step 4, the coordinates of each point cloud are transformed, and the text files converted from the point clouds of each component of the tower are transformed in the x, y, and z directions using the horizontal and vertical displacement distances. The z coordinate of each point in the point cloud of each component of the tower is added with the corresponding longitudinal displacement distance, and the x coordinate of each point in the crossarm point cloud is added with the corresponding horizontal displacement distance. The y coordinate of the point cloud of each component remains unchanged, and the x coordinate of the point cloud of each tower body remains unchanged.

9. An electronic device, characterized in that: include: one or more processors; a storage device having one or more programs stored thereon; When the one or more programs are executed by the one or more processors, the one or more processors implement the method for automatically splicing a three-dimensional model of a transmission line tower based on a design drawing as described in any one of claims 1-8.

10. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the program is executed by a processor, the steps in the method for automatically splicing a three-dimensional model of a transmission line tower based on a design drawing as described in any one of claims 1 to 8 are implemented.

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