Automatic indexing method and device for point cloud tower model and computer equipment

Abstract

The invention relates to the technical field of power transmission line measurement, and discloses an automatic indexing method and device of a point cloud tower model and computer equipment. The method mainly comprises the following steps: acquiring initial point cloud data of a power transmission line, and inputting the initial point cloud data into an initial grid space; according to the initial point cloud data, determining a plurality of tower spaces in the initial grid space; determining the center point of each tower space; reconstructing the initial point cloud data in each tower space to generate a plurality of tower point cloud data; carrying out tower numbering on the tower point cloud data corresponding to each tower space according to the coordinate distribution of the central point of the tower space in the initial grid space; and storing the plurality of pole tower point cloud data according to a pole tower numbering sequence, and generating a pole tower point cloud data table of the power transmission line.

Description

Technical Field

[0001] The invention relates to the field of transmission line measurement, and in particular to an automatic indexing method, device and computer equipment for a point cloud tower model. Background Art

[0002] The longitude and latitude of the transmission line channel and the topography directly affect the risk level of lightning damage to the transmission line towers, thereby affecting the lightning resistance level of the transmission line. Therefore, it is of great significance to accurately obtain information such as the longitude and latitude position parameters of the line towers and objectively evaluate the lightning risk level and lightning resistance level of the transmission line.

[0003] At present, when calculating the shielding failure and back flashover rate of the line and evaluating the lightning damage risk level of the line, the input of various parameters of the tower mainly relies on manual input. The tower engineering documents are used as reference materials, combined with CAD drawings and plane drawings, to find the tower type and its corresponding number, and record the longitude and latitude information of the tower and its corresponding index number in a table. However, this method of obtaining tower parameters is traditional, and the workload of manual filling is large, and it is inevitable that there will be omissions, which will lead to errors in the calculation results of the lightning tripping rate and affect the final evaluation results. If parameter compliance detection and correction are performed, the workload will be further increased, greatly reducing work efficiency. In addition, during the operation and transformation of the line for many years, there will be complex situations such as adding / reducing towers, tower displacement, and changes in the name and tower number of the operating line, which can easily lead to a large-scale mismatch between the actual line tower information and the ledger, resulting in inaccurate lightning protection calculations for the line.

[0004] Therefore, in order to more accurately evaluate the risk level of tower lightning damage, it is necessary to propose a more efficient and accurate method to establish tower indexes in order to address the problems of low efficiency and inaccurate data input. Summary of the invention

[0005] The purpose of the present invention is to provide a method, device and computer equipment for automatically indexing a point cloud tower model, aiming to solve the problems in the prior art.

[0006] A first aspect of the present invention provides an automatic indexing method for a point cloud tower model, comprising: obtaining initial point cloud data of a transmission line, and inputting the initial point cloud data into an initial grid space; confirming a plurality of tower spaces in the initial grid space according to the initial point cloud data; confirming the center point of each tower space according to the initial point cloud data in each tower space; reconstructing the initial point cloud data in the tower space with the center point corresponding to each tower space as the origin to generate a plurality of tower point cloud data, each tower point cloud data corresponding to a tower space; assigning a tower number to the tower point cloud data corresponding to each tower space according to the coordinate distribution of the center point of the tower space in the initial grid space; storing the plurality of tower point cloud data in the order of the tower numbers to generate a tower point cloud data table for the transmission line.

[0007] Optionally, the density grid of the initial grid space is a square.

[0008] Optionally, the density grid side length of the initial grid space is 5 cm.

[0009] Optionally, the confirming a plurality of tower spaces in the initial grid space according to the initial point cloud data comprises:

[0010] A height parameter of the initial point cloud data in the initial grid space is detected along a first horizontal direction, and a plurality of tower spaces are divided according to the height parameter of the initial point cloud data in the initial grid space.

[0011] Optionally, the determining the center point of each tower space according to the initial point cloud data in each tower space includes:

[0012] The height parameters of the initial point cloud data in the tower space are detected along a second direction, and a maximum elevation point or a center of a line connecting multiple maximum elevation points is selected as a center point, wherein the second direction is perpendicular to the first direction.

[0013] Optionally, the initial point cloud data in the tower space is reconstructed with the center point corresponding to each tower space as the origin to generate a plurality of tower point cloud data, including:

[0014] Detecting the plane distribution of the initial point cloud data in the tower space along the vertical direction, and selecting the plane coordinate axis direction corresponding to each tower space;

[0015] The corresponding center point of each target tower space is used as the origin of the horizontal coordinate axis, and the initial point cloud data in the tower space is reconstructed according to the direction of the plane coordinate axis to generate a plurality of tower point cloud data.

[0016] The second aspect of the present invention provides an automatic indexing device for a point cloud tower model, comprising: an acquisition device, used to acquire initial point cloud data of a transmission line and input the initial point cloud data into an initial grid space; a first confirmation unit, used to confirm multiple tower spaces in the initial grid space according to the initial point cloud data; a second confirmation unit, used to confirm the center point of each tower space according to the initial point cloud data in each tower space; a generation unit, used to reconstruct the initial point cloud data in each tower space with the center point corresponding to the tower space as the origin, and generate multiple tower point cloud data, each of which corresponds to a tower space; a numbering unit, used to number the tower point cloud data corresponding to each tower space according to the coordinate distribution of the center point of the tower space in the initial grid space; a storage unit, used to store the multiple tower point cloud data in the order of the tower numbers, and generate a tower point cloud data table for the transmission line.

[0017] A third aspect of the present invention provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the automatic indexing method of the point cloud tower model of any one of the first aspects when executing the computer program.

[0018] Compared with the prior art, the present invention uses a grid to calculate the coordinates of the center position of the tower to achieve automatic indexing of the point cloud tower model. Compared with the traditional method that relies on manual annotation, the present invention fully realizes the automation of the indexing process. In view of the complexity of the transmission line in many years of operation and transformation, the present invention makes full use of the inherent structural characteristics of the transmission line tower and designs a set of point cloud data processing processes that are specialized and adapted to the transmission line tower. The present invention can automatically confirm the number and position of the towers of the line and establish an index of the tower point cloud model based on the inherent three-dimensional structural characteristics of the transmission line tower, providing data support for subsequent automatic vectorization and automatic measurement of the tower size, improving the application value of point cloud data, getting rid of the dependence on the line operation and transformation ledger, significantly improving the automation and reliability of the transmission line point cloud data processing, and further promoting the digital transformation process of transmission line management. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 A schematic diagram of an embodiment of an automatic indexing method for a point cloud tower model of the present invention;

[0020] Figure 2 A schematic diagram of an embodiment of an automatic indexing method for a point cloud tower model of the present invention;

[0021] Figure 3 A schematic diagram of an embodiment of an automatic indexing method for a point cloud tower model of the present invention;

[0022] Figure 4 A schematic diagram of an embodiment of an automatic indexing method for a point cloud tower model of the present invention;

[0023] Figure 5 A schematic diagram of an embodiment of an automatic indexing method for a point cloud tower model of the present invention;

[0024] Figure 6 A schematic diagram of an embodiment of an automatic indexing device for a point cloud tower model of the present invention;

[0025] Figure 7 A schematic diagram of an embodiment of a computer device of the present invention. DETAILED DESCRIPTION

[0026] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0027] The same or similar numbers in the drawings of this embodiment correspond to the same or similar parts; in the description of the present invention, it should be understood that if the terms "upper", "lower", "left", "right" and the like indicate directions or positional relationships based on the directions or positional relationships shown in the drawings, it is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction. Therefore, the terms describing the positional relationship in the drawings are only used for illustrative purposes and cannot be understood as limitations on this patent. For ordinary technicians in this field, the specific meanings of the above terms can be understood according to specific circumstances.

[0028] The present invention mainly proposes an automatic segmented indexing method for a point cloud tower model, which uses a grid with a specific step size to surround the point cloud model, and judges the overall shape of the point cloud through the inclusion relationship between the small squares inside the grid and the point cloud. The tower position and its coordinate values ​​are gradually determined through combined rendering from multiple angles such as side view, front view, and top view, and then the coordinates of the center position of the tower are calculated through the grid to achieve automatic indexing of the model. Compared with the traditional method of extracting and indexing tower position information mainly through manual annotation or AI intelligent calculations such as machine learning, this method is more accurate and efficient, provides guidance for lightning protection calculations and engineering design of lines, and provides data support for subsequent work such as automatic measurement of tower dimensions. The implementation of the present invention is described in detail below in conjunction with specific embodiments.

[0029] Reference Figure 1 As shown, a preferred first embodiment of the automatic indexing method of the point cloud tower model of the present invention is provided. The embodiment includes the following steps:

[0030] 101. Acquire initial point cloud data of the transmission line, and input the initial point cloud data into an initial grid space;

[0031] The initial point cloud data of the transmission line is usually collected by LiDAR, which includes the point cloud data of the tower of the entire transmission line. In addition, it may also include other point cloud data collected by LiDAR, such as cables, ground, surrounding buildings, etc. The initial point cloud data can be provided directly by LiDAR, or it can be filtered or other pre-processed point cloud data, but the point cloud data of the tower should be distinguished separately.

[0032] An initial grid space that basically matches the size of the initial point cloud data is established. The initial grid space is composed of a density grid of a preset size. The size of the density grid can be adjusted. A better choice is to set the density grid to a square with a side length of 5 cm.

[0033] 102. According to the initial point cloud data, confirm multiple tower spaces in the initial grid space;

[0034] Select a direction to perform a side section on the entire data segment to generate Figure 1 As shown in the cross section. Since the point cloud of the tower must be the maximum elevation in the nearby grid, the maximum elevation point of the model in the grid bounding box is the tower position. Figure 3 That is, it is the corresponding point cloud collection of a pole tower. According to one or more features of these point clouds, it can be confirmed that the point cloud collection is the highest point within 10 meters nearby. There is a pole tower here, so a pole tower space is established around this place.

[0035] 103. According to the initial point cloud data in each tower space, the center point of each tower space is respectively confirmed;

[0036] According to the distribution of the initial point cloud data in each tower space, a spatial position is selected in each tower space as the center point of the tower space. It is understandable that the center point is not necessarily the geometric center of the initial point cloud data in the tower space or the center of the tower space, and it only needs to be located in the tower space.

[0037] 104. Taking the center point corresponding to each of the tower spaces as the origin, reconstruct the initial point cloud data in the tower space to generate a plurality of tower point cloud data;

[0038] Each tower space corresponds to a tower. The center point of the tower grid is used as the origin to reconstruct the initial point cloud data falling into the tower space to form a tower point cloud data. Each tower point cloud data corresponds to a tower space. The tower point cloud model generated after reconstruction uses the center point of the tower space as the origin, which is convenient for analyzing the tower point cloud model separately. At this time, when analyzing a single tower, it is no longer necessary to use the points on the transmission line as a reference, which greatly facilitates the data retrieval and use of construction and maintenance personnel.

[0039] 105. According to the coordinate distribution of the center of the tower space in the initial grid space, number the towers for the tower point cloud data corresponding to each tower space;

[0040] In the present invention, the pole tower center point, the pole tower space and the pole tower grid model correspond one to one. Each pole tower will have a center point, a pole tower space and a pole tower grid model. Therefore, in order to facilitate construction and maintenance personnel to quickly find the pole tower point cloud data corresponding to each pole tower, each pole tower and its corresponding pole tower point cloud data or pole tower space are numbered according to the position of the center point, usually from top to bottom or horizontally according to the map direction. It is understandable that the numbering method of the pole tower can be in any form, but it is ensured that each pole tower space has a unique number so that the pole tower point cloud data can be indexed according to the number.

[0041] 106. Store the multiple tower point cloud data in order of the tower numbers to generate a tower point cloud data table for the transmission line.

[0042] According to the numbering of the tower space in step 105, the point cloud data of each tower of the transmission line are numbered and integrated and stored as a tower point cloud data table. The tower point cloud data table contains the tower point cloud data of the entire transmission line, and the tower point cloud data of each tower uses the center point of the tower itself as the origin. While the point cloud data of the entire transmission line is uniformly stored, it is convenient to retrieve and analyze the tower point cloud data corresponding to a single tower. The tower point cloud data table can output and save the tower point cloud model of the entire transmission line in the form of a csv file.

[0043] It can be seen that the automatic indexing method of the point cloud tower model of the present invention does not require manual intervention during the working process, and the indexing process does not rely on the line ledger archive at all. In other words, regardless of whether the ledger is correct, the present invention will independently construct the tower index based on the collected point cloud data, which is particularly suitable for some transmission lines with frequent modifications and complex tower conditions.

[0044] based on Figure 1 In the first embodiment shown, in the second embodiment of the present invention, a preferred solution for dividing the tower space is also provided. In this embodiment, step 102 specifically includes:

[0045] Detecting a height parameter of initial point cloud data in an initial grid space along a first horizontal direction, and dividing a plurality of tower spaces according to the height parameter of the initial point cloud data in the initial grid space;

[0046] Select a first direction perpendicular to the transmission line direction, and detect the height parameters of the initial point cloud data in the initial grid space, where the point cloud data with a sudden increase in height parameters above the ground can be confirmed as the tower space containing the tower. Specifically, construct a profile along the first direction such as Figure 2 After the section is drawn, the point clouds representing the towers in the transmission line can be confirmed based on the size and continuity of the height parameters of the point clouds in the section. These point clouds representing the towers have corresponding density grids in the initial grid space. The grids occupied by the point clouds representing the towers in the initial grid space are integrated within a certain range, which is the tower space occupied by the tower.

[0047] Based on the second embodiment of the present invention, in the third embodiment of the present invention, a method for accurately selecting the center point of the tower is also provided. In this embodiment, step 103 specifically includes:

[0048] The height parameters of the initial point cloud data in the tower space are detected along a second direction, and the maximum elevation point or the center of a line connecting multiple maximum elevation points is selected as the center point, wherein the second direction is perpendicular to the first direction.

[0049] A second direction perpendicular to the first direction is selected on the horizontal plane, and the height parameters of the point cloud in the tower space are detected along the section of the second direction. The elevation point with the largest height parameter is selected as the center point, or when there are multiple elevation points with the largest height parameters, the center of the line connecting these elevation points with the largest height parameters is selected as the center point, which is the center point of the actual structure of the tower. Figure 4 This is a schematic diagram of selecting the center of the line connecting the elevation points with the largest height parameters of the tower as the center point. It can be seen that this embodiment accurately selects multiple elevation points with peak values ​​of local height parameters by performing complex multi-point comprehensive analysis in the selected three-dimensional grid space, and then comprehensively analyzes them to determine the structural center of the tower. In this way, the center point of the physical structure of the tower can be determined with high precision, thereby ensuring the high consistency between the center point of the reconstructed tower point cloud data and the center point of the actual tower physical structure, and achieving the precise coincidence of the tower physical structure with the digital model. This technology greatly improves the accuracy and reliability of the determination of the center point of the tower, especially the accuracy on the two-dimensional map.

[0050] Based on any one of the first, second and third embodiments, in the fourth embodiment of the present invention, the tower point cloud data is further aligned with the vertical coordinate axis. Based on any one of the above embodiments, please refer to Figure 5, a fourth embodiment of the present invention comprises:

[0051] 501. Acquire initial point cloud data of the transmission line, and input the initial point cloud data into an initial grid space;

[0052] 502 confirming a plurality of tower spaces in the initial grid space according to the initial point cloud data;

[0053] 503, according to the initial point cloud data in each tower space, respectively confirm the center point of each tower space;

[0054] 504. Detect the plane distribution of the initial point cloud data in the tower space along the vertical direction to confirm the direction of the plane coordinate axis;

[0055] Construct one or more cross-sections along the vertical direction, detect the plane distribution and shape of the point cloud in these planes, and confirm a set of rectangular coordinate axis directions that best fit the point cloud distribution. It is understandable that due to the complex terrain of the transmission line and the variety of tower types, the towers are usually not installed accurately in a straight line, so the plane coordinate axis directions corresponding to each tower space may not be the same.

[0056] 505. Taking the corresponding center point of the target tower space as the origin of the horizontal coordinate axis, reconstruct the initial point cloud data in the tower space according to the direction of the plane coordinate axis to generate tower point cloud data.

[0057] Taking the center point of each tower space as the origin, the initial point cloud data in each tower space is remapped according to the direction of the plane coordinate axis and reconstructed to obtain the tower point cloud data. After reconstruction, each tower point cloud data is uniformly stored in its own spatial rectangular coordinate system to facilitate analysis of a single tower point cloud data.

[0058] 506. According to the coordinate distribution of the center point of the tower space in the initial grid space, number the towers for the tower point cloud data corresponding to each tower space;

[0059] 507. Store the plurality of tower point cloud data in order of tower numbers to generate a tower point cloud data table for the transmission line.

[0060] If, on the basis of this embodiment, combined with the aforementioned second and third embodiments, it is possible to ensure to the greatest extent that the center point of the pole tower model fits the actual physical structure of the pole tower. The present invention performs complex multi-point comprehensive analysis in each dimension in the three-dimensional grid space, which can ensure that the center point of each pole tower point cloud data is highly consistent with the physical structure of the actual pole tower. Through this comprehensive method, not only can the center point of the pole tower be accurately determined, but also the geometric shape of the pole tower can be effectively matched, further improving the fit between the point cloud data and the actual physical structure. . According to the index system established by the present invention, engineers can directly obtain a standardized pole tower model with the center of the physical structure of the pole tower as the origin. Through precise structural center positioning and standardized processing procedures, this model enables engineers to easily access and analyze each individual pole tower point cloud model, and seamlessly integrate and import the pole tower model into lightning protection calculation and engineering design software, greatly simplifying the processing flow of laser point cloud data, and facilitating subsequent analysis of transmission line engineering design and lightning protection calculation. Please refer to Figure 6 The present invention also provides an embodiment of an automatic indexing device for a point cloud tower model, the device comprising:

[0061] The acquisition device 601 is used to acquire the initial point cloud data of the transmission line and input the initial point cloud data into the initial grid space;

[0062] A first confirmation unit 602 is used to confirm a plurality of tower spaces in the initial grid space according to the initial point cloud data;

[0063] The second confirmation unit 603 is used to confirm the center point of each tower space according to the initial point cloud data in each tower space;

[0064] A generating unit 604 is used to reconstruct the initial point cloud data in each of the tower spaces with the center point corresponding to the tower space as the origin to generate a plurality of tower point cloud data, each of which corresponds to a tower space;

[0065] A numbering unit 605 is used to number the tower point cloud data corresponding to each tower space according to the coordinate distribution of the center point of the tower space in the initial grid space;

[0066] The storage unit 606 is used to store the plurality of pole tower point cloud data in the order of the pole tower numbers to generate a pole tower point cloud data table of the transmission line.

[0067] See also Figure 7 The present application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, so that when the processor executes the computer program in the memory, the automatic indexing method of any point cloud tower model corresponding to the first to fourth embodiments described above is implemented. Figure 7 , the computer device may include one or more central processing units (CPU) 701 and a memory 705, in which one or more application programs or data are stored. Among them, the memory 705 can be a volatile storage or a persistent storage. The program stored in the memory 705 may include one or more modules, each of which may include a series of instruction operations in the computer device. Furthermore, the central processing unit 701 can be configured to communicate with the memory 705 and execute a series of instruction operations in the memory 705 on the computer device 700. The computer device 700 may also include one or more power supplies 702, one or more wired or wireless network interfaces 703, one or more input and output interfaces 704, and / or, one or more operating systems, such as Windows ServerTM, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM, etc. The central processing unit 701 can perform the corresponding operations in the aforementioned embodiments, and the specific details are not repeated here. Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0068] The specific implementations of the automatic indexing device and calculation and equipment of the point cloud tower model of the present invention correspond to the embodiments of the automatic indexing method of the point cloud tower model described above, and will not be repeated here.

[0069] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0070] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0071] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0072] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0073] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, read-only memory), random access memory (RAM, random access memory), disk or optical disk and other media that can store program code.

Claims

1. A method for automatically indexing a point cloud tower model, characterized in that: include: Acquire initial point cloud data of the transmission line, and input the initial point cloud data into an initial grid space; According to the initial point cloud data, confirming a plurality of tower spaces in the initial grid space; According to the initial point cloud data in each tower space, the center point of each tower space is confirmed respectively; Taking the center point corresponding to each of the tower spaces as the origin, reconstructing the initial point cloud data in the tower space to generate a plurality of tower point cloud data, each of which corresponds to a tower space; According to the coordinate distribution of the center point of the tower space in the initial grid space, numbering the tower point cloud data corresponding to each tower space; The plurality of pole tower point cloud data are stored in the order of the pole tower numbers to generate a pole tower point cloud data table for the transmission line.

2. The automatic indexing method of point cloud tower model according to claim 1, characterized in that: The density grid of the initial grid space is a square.

3. The automatic indexing method of point cloud tower model according to claim 2, characterized in that: The density grid side length of the initial grid space is 5 cm.

4. The automatic indexing method of point cloud tower model according to claim 1, characterized in that: The step of confirming a plurality of tower spaces in the initial grid space according to the initial point cloud data comprises: A height parameter of the initial point cloud data in the initial grid space is detected along a first horizontal direction, and a plurality of tower spaces are divided according to the height parameter of the initial point cloud data in the initial grid space.

5. The automatic indexing method of point cloud tower model according to claim 4, characterized in that: The method of respectively confirming the center point of each tower space according to the initial point cloud data in each tower space includes: The height parameters of the initial point cloud data in the tower space are detected along a second direction, and a maximum elevation point or a center of a line connecting multiple maximum elevation points is selected as a center point, wherein the second direction is perpendicular to the first direction.

6. The automatic indexing method of point cloud tower model according to claim 1, characterized in that: The method of reconstructing the initial point cloud data in the tower space by taking the center point corresponding to each tower space as the origin to generate a plurality of tower point cloud data includes: Detecting the plane distribution of the initial point cloud data in the tower space along the vertical direction, and selecting the plane coordinate axis direction corresponding to each tower space; The corresponding center point of each target tower space is used as the origin of the horizontal coordinate axis, and the initial point cloud data in the tower space is reconstructed according to the direction of the plane coordinate axis to generate a plurality of tower point cloud data.

7. An automatic indexing device for a point cloud tower model, characterized in that: include: An acquisition device, used for acquiring initial point cloud data of the transmission line and inputting the initial point cloud data into an initial grid space; A first confirmation unit, configured to confirm a plurality of tower spaces in the initial grid space according to the initial point cloud data; The second confirmation unit is used to confirm the center point of each tower space according to the initial point cloud data in each tower space; A generating unit, configured to reconstruct the initial point cloud data in the pole tower space with the center point corresponding to each pole tower space as the origin, and generate a plurality of pole tower point cloud data, each of which corresponds to a pole tower space; A numbering unit, used for numbering the tower point cloud data corresponding to each tower space according to the coordinate distribution of the center point of the tower space in the initial grid space; The storage unit is used to store the plurality of pole tower point cloud data in the order of the pole tower numbers to generate a pole tower point cloud data table for the transmission line.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the method for automatically indexing the point cloud tower model according to any one of claims 1 to 6 is implemented.

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