A method for generating route selection scheme for multi-regional crossing projects based on UAV

Abstract

The present invention discloses a method for generating a multi-regional crossing engineering line selection scheme based on an unmanned aerial vehicle, comprising the following steps: S1, establishing a global virtual map according to the number N of electric towers erected and the direction of the line; S2, evenly dividing the global virtual map into N independent local maps; S3, the unmanned aerial vehicle obtains imaging pictures in the area according to the set path; S4, filling the images obtained by the unmanned aerial vehicle into the independent local map; S5, obtaining a global 3D virtual map after processing several independent local maps; S6, establishing a working condition model according to topographic survey data; and determining the best construction position of the electric tower in the independent local map; S7, establishing a construction plan adapted to environmental factors according to the dynamic parameter adjustment of the working condition model; S8, inputting the tool type and tool quantity of each working condition of the construction plan into the tool library model, and generating a corresponding list of preparatory tools. The scheme can significantly improve the efficiency of the early planning and design before the construction of the electric tower, and provide an accurate basis for the construction of the electric tower in the later stage.

Description

Technical Field

[0001] The present invention relates to the field of electric power construction planning and design, and in particular to a method for generating an electric tower erection plan based on an unmanned aerial vehicle. Background Art

[0002] Since many power line project paths are generally far away from residential areas, they are often laid along sparsely populated high mountainous and densely forested areas, in order to minimize the impact on the human living environment and avoid the huge increase in project costs and time costs caused by relocation, this has led to real difficulties such as complex engineering terrain conditions and difficult survey and design. If the previous transmission line survey operation method is adopted, it is necessary to cut down a large area of ​​path channels, which is neither environmentally friendly and efficient nor in line with the government's requirements for the "green mountains hanging white" remediation. At the same time, due to the non-aerial survey operation method, the path plan needs to be determined after obtaining on-site measurement data, resulting in high on-site labor intensity and low efficiency, and the determined path plan lacks a global view and integrity. As the line moves forward, the various new obstacles that emerge often have a subversive impact on the previously selected plan, which ultimately results in a huge amount of repeated work, difficulty in improving efficiency, and delayed construction period. Therefore, it is a general trend to use aerial survey methods to assist in the survey and design of power line projects.

[0003] With the advancement of drone aerial photography technology in recent years, more and more surveying and mapping work uses drones to obtain image data. Drones are small in size, flexible, highly efficient, and have low overall costs. They have obvious advantages in quickly acquiring high-resolution images in small areas and areas where flying is difficult. Due to the difficulty and safety and stability of the erection of power towers and the great influence of topography, it is difficult for actual engineering personnel to incorporate factors such as topography into the overall plan for comprehensive consideration; therefore, the construction period of power towers is long and the erection cost is high. At the same time, due to the long erection period of power towers and the large number of devices involved, it is difficult for construction personnel to estimate the actual required device list. Therefore, whether the preliminary planning and layout work of the tower construction is done accurately is particularly important for the difficulty of subsequent on-site construction and cost control of substation. Summary of the invention

[0004] The purpose of the present invention is to design a method for generating a line selection plan for a multi-region crossing project based on an unmanned aerial vehicle, to establish a virtual map and find the best installation position of an electric tower on the virtual map, to build a simulated electric tower in a working condition model, to determine the casting thickness of the tower base model according to terrain survey data, to improve the actual disaster resistance of the electric tower, and finally to generate a tool list through a tool library model to make the construction process safer and more efficient.

[0005] In order to achieve the above technical purpose, the present invention provides a technical solution, which is a method for generating a multi-region crossing engineering route selection plan based on an unmanned aerial vehicle, comprising the following steps:

[0006] S1. Set the size of the virtual map in proportion, determine the number N of towers erected in the virtual map and the direction of the lines; and establish a global virtual map;

[0007] S2, dividing the global virtual map into N independent local maps evenly, and editing and imaging each independent local map separately;

[0008] S3, setting the camera path of the drone; the drone obtains imaging pictures in the area according to the set path;

[0009] S4, after preprocessing, the image acquired by the drone is filled into an independent local image for 3D rendering imaging;

[0010] S5, after several independent local images are spliced ​​and processed with boundary contours, a global 3D virtual map is obtained;

[0011] S6. Input the terrain survey data into the global 3D virtual map, and then establish the working condition model; determine the best location for building the tower in the independent local map based on the terrain survey data;

[0012] S7. Establish a construction plan that adapts to environmental factors based on dynamic parameter adjustments of the working condition model;

[0013] S8. Input the tool type and tool quantity of each working condition of the construction plan into the tool library model to generate a corresponding list of prepared tools.

[0014] In this scheme, firstly, the size of the virtual map is determined in proportion to the area where the electric towers are actually built, and the actual sampling area of ​​the virtual map is determined according to the number of electric towers in the area; secondly, the designed global virtual map is evenly divided into N independent local maps, and the best construction position of the electric tower in the independent local map is found by comparing geological parameters, wherein the image data of the independent local map is obtained by drones, and the geological data is obtained by manual survey or historical records; then, the specific tower foundation construction plan is determined according to the specific geological parameters of the construction location to improve the actual disaster resistance of the electric tower; finally, the list of construction preparation tools is determined according to the generated construction plan, making the construction process safer and more efficient.

[0015] Preferably, in S1, the positions of the 1st tower and the Nth tower are determined, and they are connected with arrowed lines to determine the direction and distance S of the wiring, and a global virtual map is established with the distance S as the length and S / N as the width.

[0016] Preferably, in S3, the drone performs a search using a local graph as a search unit, including the following steps:

[0017] The local image is a square with a side length of S / N, which is cut into M small squares of equal length;

[0018] Determine the center point of each small square and use the center point of each small square as the drone camera detection point;

[0019] The flight altitude of the drone is set according to the terrain and altitude; and the zoom ratio of the captured image is determined according to the flight altitude.

[0020] Preferably, S4 includes the following steps:

[0021] S41, obtaining image data of M small square areas, and scaling the images to a uniform standard size according to the flight altitude of the UAV;

[0022] S42, cutting the image by the boundary surrounded by the small squares, rotating and splicing the cut images of the same size to obtain independent local images.

[0023] Preferably, the topographic survey data includes the type and attributes of the terrain, wherein the type includes at least one of high mountains, waters, plains and deserts, and the terrain attributes include the type and thickness of geological rock formations and the historical water level in the waters; the basic settlement value is calculated according to the type and thickness of the geological rock formations.

[0024] Preferably, S6 comprises the following steps:

[0025] The topographic survey data in each small square area is obtained, and the overall map of the small square area is further rendered and marked; after processing, several small square areas are obtained into independent local images, and the topographic survey data in the independent local images are analyzed to obtain the best tower installation point with the minimum foundation settlement value and farthest from the water.

[0026] Preferably, S7 comprises the following steps:

[0027] When the locations of all the tower erection points are determined, the dynamic parameters in the working condition model are adjusted to meet the tower construction specifications; the working condition model includes a tower model and a tower base model, and the tower model includes tower body attributes, connection medium attributes, and adjacent attributes; the tower body attributes include: tower base elevation, tower positioning height, and hardware string length; the connection medium attributes include conductor specific gravity and line turning angle; the adjacent attributes include: spanning span, spanned object elevation, and cross span angle;

[0028] The tower foundation model determines the pouring thickness of the tower foundation according to the geological foundation settlement value of the tower construction location.

[0029] Preferably, in S8, specific construction data is determined based on the tower model and the tower base model, the construction data including the types and quantities of all tools required to build the tower, and a construction data list is exported through a tool library model.

[0030] Beneficial effects of the present invention: The method for generating a multi-regional crossing engineering line selection plan based on an unmanned aerial vehicle designed by the present invention establishes a virtual map and finds the best installation position of the electric tower on the virtual map, builds a simulated electric tower in the working condition model, determines the casting thickness of the tower base model according to the terrain survey data, improves the actual disaster resistance of the electric tower, and finally generates a tool list through the tool library model, making the construction process safer and more efficient. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 The present invention is a flowchart of a method for generating a route selection plan for a multi-regional crossing project based on an unmanned aerial vehicle. DETAILED DESCRIPTION

[0032] In order to make the objectives, technical solutions 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 implementation method described herein is only an optimal embodiment of the present invention, which is only used to explain the present invention and does not limit the scope of protection of the present invention. All other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0033] Example: Figure 1 As shown in the figure, the method for generating a multi-region crossing engineering line selection scheme based on drones includes the following steps:

[0034] S1. Set the size of the virtual map in proportion, determine the number N of towers erected in the virtual map and the direction of the lines; and establish a global virtual map.

[0035] In S1, the positions of the 1st tower and the Nth tower are determined, and they are connected by arrowed lines to determine the direction and distance S of the wiring, and a global virtual map is established with the distance S as the length and S / N as the width.

[0036] S2. The global virtual map is evenly divided into N independent local maps, and each independent local map is edited and imaged separately.

[0037] S3. Set the camera path of the drone; the drone obtains imaging pictures in the area according to the set path.

[0038] In S3, the drone searches in local graphs as search units, including the following steps:

[0039] The local image is a square with a side length of S / N, which is cut into M small squares of equal length;

[0040] Determine the center point of each small square and use the center point of each small square as the drone camera detection point;

[0041] The flight altitude of the drone is set according to the terrain and altitude; and the zoom ratio of the captured image is determined according to the flight altitude.

[0042] S4. After preprocessing, the image acquired by the drone is filled into an independent local image for 3D rendering imaging.

[0043] S4 includes the following steps:

[0044] S41, obtaining image data of M small square areas, and scaling the images to a uniform standard size according to the flight altitude of the UAV;

[0045] S42, cutting the image by the boundary surrounded by the small squares, rotating and splicing the cut images of the same size to obtain independent local images.

[0046] S5. After several independent local images are stitched and their boundary contours are processed, a global 3D virtual map is obtained.

[0047] S6. Input the terrain survey data into the global 3D virtual map, and then establish the working condition model; determine the best location for constructing the tower in the independent local map based on the terrain survey data.

[0048] S6 includes the following steps:

[0049] The topographic survey data in each small square area is obtained, and the overall map of the small square area is further rendered and marked; after processing, several small square areas are obtained into independent local images, and the topographic survey data in the independent local images are analyzed to obtain the best tower installation point with the minimum foundation settlement value and farthest from the water.

[0050] The topographic survey data includes the type and attributes of the terrain, wherein the type includes at least one of high mountains, water areas, plains, and deserts, and the topographic attributes include the type and thickness of geological rock layers and the historical water level in the water area; the basic settlement value is calculated according to the type and thickness of the geological rock layers.

[0051] S7. Establish a construction plan that adapts to environmental factors based on the dynamic parameter adjustments of the working condition model.

[0052] S7 includes the following steps:

[0053] When the locations of all the tower erection points are determined, the dynamic parameters in the working condition model are adjusted to meet the tower construction specifications; the working condition model includes a tower model and a tower base model, and the tower model includes tower body attributes, connection medium attributes, and adjacent attributes; the tower body attributes include: tower base elevation, tower positioning height, and hardware string length; the connection medium attributes include conductor specific gravity and line turning angle; the adjacent attributes include: spanning span, spanned object elevation, and cross span angle;

[0054] The tower foundation model determines the pouring thickness of the tower foundation according to the geological foundation settlement value of the tower construction location.

[0055] S8. Input the tool type and tool quantity of each working condition of the construction plan into the tool library model to generate a corresponding list of prepared tools.

[0056] In S8, specific construction data is determined according to the tower model and the tower base model, wherein the construction data includes the types and quantities of all tools required to build the tower, and a construction data list is exported through a tool library model.

[0057] In this embodiment, first, the size of the virtual map is determined in proportion according to the area where the electric tower is actually built (the collected data is modeled by aerial triangulation data processing software to generate a panoramic map with a three-dimensional scene. This technology is a conventional modeling skill of general technicians in this field and will not be repeated), and the actual sampling area of ​​the virtual map is determined according to the number of electric towers in the area; secondly, the designed global virtual map is evenly divided into N independent local maps, and the best construction position of the electric tower in the independent local map is found by the comparison method of geological parameters, wherein the image data of the independent local map is obtained by drone, and the geological data is obtained by manual survey or historical records; then, according to the specific geological parameters of the construction location, a specific tower base construction plan is determined (the tower model and the tower base model can be imported into the model through BIM software, and this technology is a conventional modeling skill of general technicians in this field and will not be repeated), so as to improve the actual disaster resistance of the electric tower; finally, a list of construction preparation tools is determined according to the generated construction plan, so that the construction process is safer and more efficient.

[0058] The specific implementation described above is a preferred implementation of the method for generating a tower erection plan based on a drone of the present invention, and is not intended to limit the specific implementation scope of the present invention. The scope of the present invention includes but is not limited to this specific implementation. All equivalent changes made to the shape and structure of the present invention are within the protection scope of the present invention.

Claims

1. A method for generating a multi-regional crossing engineering route selection scheme based on drones, characterized in that: The steps include: S1. Set the size of the virtual map in proportion, determine the number N of towers erected in the virtual map and the direction of the lines; and establish a global virtual map; S2, dividing the global virtual map into N independent local maps evenly, and editing and imaging each independent local map separately; S3, setting the camera path of the drone; the drone obtains imaging pictures in the area according to the set path; S4, after preprocessing, the image acquired by the drone is filled into an independent local image for 3D rendering imaging; S5, after several independent local images are spliced ​​and processed with boundary contours, a global 3D virtual map is obtained; S6. Input the terrain survey data into the global 3D virtual map, and then establish the working condition model; determine the best location for building the tower in the independent local map based on the terrain survey data; S7. Establish a construction plan that adapts to environmental factors based on dynamic parameter adjustments of the working condition model; S8. Input the tool type and tool quantity of each working condition of the construction plan into the tool library model to generate a corresponding list of prepared tools.

2. The method for generating a multi-regional crossing engineering route selection scheme based on an unmanned aerial vehicle according to claim 1, characterized in that: In S1, the positions of the 1st and Nth towers are determined, and they are connected by arrowed lines to determine the direction and distance S of the wiring, and a global virtual map is established with the distance S as the length and S / N as the width.

3. The method for generating a multi-regional crossing engineering route selection scheme based on an unmanned aerial vehicle according to claim 2 is characterized in that: In S3, the drone searches in local graphs as search units, including the following steps: The local image is a square with a side length of S / N, which is cut into M small squares of equal length; Determine the center point of each small square and use the center point of each small square as the drone camera detection point; The flight altitude of the drone is set according to the terrain and altitude; and the zoom ratio of the captured image is determined according to the flight altitude.

4. The method for generating a multi-regional crossing engineering route selection scheme based on an unmanned aerial vehicle according to claim 3 is characterized in that: S4 includes the following steps: S41, obtaining image data of M small square areas, and scaling the images to a uniform standard size according to the flight altitude of the UAV; S42, cutting the image by the boundary surrounded by the small squares, rotating and splicing the cut images of the same size to obtain independent local images.

5. The method for generating a multi-regional crossing engineering route selection scheme based on an unmanned aerial vehicle according to claim 1, 3 or 4, characterized in that: The topographic survey data includes the type and attributes of the terrain, wherein the type of terrain includes at least one of high mountains, water areas, plains, and deserts, and the topographic attributes include the type and thickness of geological rock formations and the historical water level in the water area; the basic settlement value is calculated according to the type and thickness of the geological rock formations.

6. The method for generating a multi-regional crossing engineering route selection scheme based on an unmanned aerial vehicle according to claim 5 is characterized in that: S6 includes the following steps: Obtain the topographic survey data within each small square area, and further render and mark the overall map of the small square area; After processing, several small square areas are obtained into independent local images. By analyzing the terrain survey data in the independent local images, the best tower installation point with the minimum foundation settlement value and farthest from the water is obtained.

7. The method for generating a multi-regional crossing engineering route selection scheme based on an unmanned aerial vehicle according to claim 1 or 6, characterized in that: S7 includes the following steps: When the locations of all tower erection points are determined, the dynamic parameters in the working condition model are adjusted to meet the tower construction specifications; The working condition model includes a tower model and a tower base model, wherein the tower model includes tower body attributes, connection medium attributes, and adjacency attributes; The tower attributes include: tower base elevation, tower positioning height, and hardware string length; the connection medium attributes include conductor specific gravity and line turning angle; the adjacent attributes include: spanning span, spanned object elevation, and cross-span angle; The tower foundation model determines the pouring thickness of the tower foundation according to the geological foundation settlement value of the tower construction location.

8. The method for generating a multi-regional crossing engineering route selection scheme based on an unmanned aerial vehicle according to claim 7 is characterized in that: In S8, specific construction data is determined according to the tower model and the tower base model, wherein the construction data includes the types and quantities of all tools required to build the tower, and a construction data list is exported through a tool library model.

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