A method for selecting the optimal construction path of towers in mountainous areas

Abstract

The present invention provides a method for selecting the optimal construction path of pole towers in mountainous areas, which relates to the technical field of power transmission line planning. In the process of line planning, the method reduces the difficulty of calculation by dividing the map into sections, adopts a path-finding algorithm to form an initial optimal path based on the path movement cost, and then combines the consideration of the actual impact range of the obstacle area to design a detour plan when the initial optimal path passes through the obstacle area; then, the path is screened according to the set principles to ensure that the pole towers of the optimal path consume less and the cost is lower; finally, the optimal paths of each section are spliced ​​to form an overall optimal construction path. Compared with the traditional site selection method, the method of the present invention effectively improves the calculation speed, and the final optimal construction path is more accurate in drawing and site selection, which greatly reduces the number of reworks and improves the efficiency of pole tower construction route site selection; the measurement results are more accurate, reducing the waste of redundant pole towers and reducing construction costs.

Description

Technical Field

[0001] The present invention relates to the technical field of power transmission line planning, and in particular to a method for selecting an optimal construction path for a tower in a mountainous area. Background Art

[0002] At present, most of the conventional shortest path calculation algorithms for transmission line projects are based on the A* search algorithm (A starsearch algorithm) or the BFS algorithm (Breadth-First-Search) to plan the tower path. However, for transmission lines that often pass through mountainous areas for construction, there are often obstacle areas in the mountainous areas that affect the construction of transmission towers. The obstacle areas may be areas with obstacles, land, grassland, hills, sand, minefields or environmental protection areas. Due to terrain and environmental restrictions or policy and regulatory restrictions, these obstacle areas cannot be used to build towers and usually require detours.

[0003] In the above-mentioned path planning method, the common addressing algorithm lacks information on path obstacle areas, which does not take into account the actual impact range of the obstacle area. The path needs to be corrected by manually modifying the calculation results many times. In addition, the calculation process is too long due to the expansion of the calculation range. It takes weeks or even months to perform a planning calculation using an 8-core 64G civilian computer. At the same time, due to the particularity of pole tower construction in mountainous areas, the traditional algorithm does not take into account the characteristics of mountainous areas, and the final planning result is difficult to achieve the optimization of pole tower construction in mountainous areas, that is, the most economical design. Summary of the invention

[0004] The present invention aims to solve at least one of the above-mentioned technical problems existing in the prior art.

[0005] To this end, the present invention provides a method for selecting an optimal construction path for a tower in a mountainous area.

[0006] The present invention provides a method for selecting an optimal construction path for a tower in a mountainous area, comprising:

[0007] Obtaining GIS map information of the construction address; the GIS map information at least includes the location of the peak, the height of the peak, the location of the obstacle area, and the range of the obstacle area; wherein the obstacle area is an area that needs to be avoided due to terrain conditions or policy and regulatory restrictions;

[0008] Grid the construction address and divide it into several grids to form a grid map;

[0009] Divide the construction site into sections according to the grid map, and design the path for each section;

[0010] A point is randomly selected as the starting point, and a pathfinding algorithm is used to find the initial optimal path based on the starting point; the pathfinding algorithm uses F, G and H value notation to represent the cost of path movement, where G represents the actual cost of moving from the previous node to the current node, H represents the estimated cost of moving the current node to the edge of the board, and F represents the total cost of node selection, that is, the sum of G and H; the starting point, current node and target node are all represented in grid units; the node with the lowest total cost is selected from the adjacent nodes of the current node as the next node until the current node reaches the edge of the board; each time a next node is determined, the path distance is accumulated to obtain the path distance of the initial optimal path;

[0011] The DREAD model is used to judge the threat level of the obstacle area, and the impact range of the obstacle area is determined according to the obstacle area range and threat level. When the initial optimal path passes through the impact range of the obstacle area, a detour design is performed according to the impact range of the obstacle area to obtain the optimal path. The path distance of the optimal path is the sum of the path distance of the initial optimal path and the detour distance.

[0012] When selecting and detouring nodes, determine whether the current node is a peak. If the node is a peak, determine whether the current peak is the highest peak in the section, accumulate the peak heights, and obtain the cumulative height of the optimal path;

[0013] Screening several optimal paths formed by several starting points in the section. The screening principles include: discarding the paths that do not pass through the highest peak in the section, and selecting the optimal path with the highest cumulative height as the optimal path in this section;

[0014] The optimal paths in adjacent blocks are spliced ​​using a feature-based image matching algorithm to obtain the optimal construction path of the tower at the construction address.

[0015] The method for selecting the optimal construction path of a tower in a mountainous area according to the above technical solution of the present invention may also have the following additional technical features:

[0016] In the above technical solution, the path finding algorithm is used to find the initial optimal path based on the starting point, including:

[0017] Determine whether the starting point is in the obstacle area. If the starting point is in the obstacle area, abandon the starting point and select a new starting point;

[0018] Starting from the starting grid, that is, the starting point is the current node, according to the F values ​​of all grids adjacent to the starting grid, at least one grid with the smallest F value is selected as the next node, and the path distance is accumulated;

[0019] Take the next node as the current node and determine whether the current node has reached the edge of the board. If it has not reached the edge of the board, select at least one grid with the smallest F value as the next node based on the F values ​​of all grids adjacent to the current node, and accumulate the path distance; if the current node has reached the edge of the board, select the connection line of each node as the initial optimal path, form a route map, and output the accumulated path distance as the path distance of this initial optimal path.

[0020] In the above technical solution, the path finding algorithm uses F, G and H value notation to represent the cost of path movement, including:

[0021] Assign G and H values ​​to each grid, where G is the actual cost of moving from the previous node to the current node according to the terrain and moving direction, and H is the estimated cost of moving from the current node to the edge of the plate;

[0022] The estimated cost of moving the current node to the edge of the board is the sum of the vertical distance between the current node and the edge of the board and the slope between the current node and the edge of the board in the vertical direction.

[0023] In the above technical solution, the use of the DREAD model to judge the threat level of the obstacle area includes:

[0024] The risk indicators of the obstacle area are summed up, and the sum result is used as the threat level of the obstacle area. The risk indicators include potential loss, reproducibility, availability, affected users and discoverability. The value range of each risk indicator is 0~1, so:

[0025]

[0026] in, Indicates the threat level of the obstacle area. Represents the value of the mth risk indicator.

[0027] In the above technical solution, the step of determining the impact range of the obstacle area according to the range of the obstacle area and the threat level includes:

[0028] The distance from the center of the obstacle area to the farthest edge of the obstacle area is taken as the actual radius of the obstacle area;

[0029] Calculate the radius of the obstacle area based on the actual radius of the obstacle area and the threat level:

[0030]

[0031] in, Indicates the radius of the obstacle area. Indicates the actual radius of the obstacle area;

[0032] In the center of the obstacle area The circular area with a radius of is the influence range of the obstacle area;

[0033] When the initial optimal path passes through the influence range of the obstacle area, the path is detoured along the edge of the influence range of the obstacle area until the initial optimal path does not interfere with the influence range of the obstacle area.

[0034] The above technical solution also includes:

[0035] Each time the obstacle area is bypassed, the bypass weight consumption is calculated and accumulated; when the accumulated bypass weight consumption exceeds the weight consumption threshold, the current path is abandoned and redesigned;

[0036] The calculation method of the detour weight consumption includes:

[0037]

[0038] in, represents the detour weight consumption, Represents the project weight factor. The higher the project weight factor, the greater the cost investment of this project and the longer the optional detour path.

[0039] In the above technical solution, the optimal paths in adjacent blocks are spliced ​​using a feature-based image matching algorithm to obtain the optimal construction path of the tower at the construction address, including:

[0040] Extract the feature points of the roadmap in two adjacent blocks to form a feature point set and ;in, Represents the nth feature point in a block, Represents the mth feature point in another section;

[0041] Use the BFMatcher matching algorithm to find the matching point pairs between the two feature point sets and form a matching point pair set ;in, , ;

[0042] The transformation matrix T between the two blocks is estimated based on the matching point pair set M. The transformation matrix is ​​used to transform the feature point set M by translation or rotation. Map the feature points in to new positions;

[0043] Determine the splicing scheme of the paths in the two sections based on the transformation matrix.

[0044] In the above technical solution, the step of estimating the transformation matrix between the two blocks according to the matching point pair set M includes:

[0045]

[0046] in, represents the error function, represents the Euclidean distance;

[0047] By minimizing the error function, the transformation matrix is ​​determined .

[0048] The above technical solution also includes:

[0049] Each block has 16 sides, each side represents a line-out direction. When blocks are spliced, the optimal path corresponding to the line-out direction of the optimal path in the current block is selected from several paths of adjacent blocks for splicing;

[0050] The 16 side surfaces of the block are the side surfaces covered by the fan-shaped area formed by two adjacent rays among the 16 rays emitted from the center of the block, and the angle between any two adjacent rays is 22.5 degrees.

[0051] The above technical solution also includes:

[0052] Estimate the wire consumption for the optimal construction path of each tower;

[0053] Among them, for a peak node without an adjacent peak node, the wire consumption of the peak node is obtained by multiplying the plane distance of the peak node by the height of the mountain;

[0054] For the road section between two non-directly adjacent peak nodes, the plane distance between the two peak nodes is used as the wire consumption of the road section;

[0055] For the road section between two directly adjacent mountain nodes, the plane distance between the two peaks multiplied by the height difference between the two peaks is used as the wire consumption of the road section.

[0056] In summary, due to the adoption of the above technical features, the beneficial effects of the present invention are:

[0057] Compared with traditional site selection methods, the method of the present invention effectively improves the calculation speed. At the same time, the site selection method of the present invention adds obstacle area calculation, and the final selection of the optimal construction path is more accurate in mapping and site selection, which greatly reduces the number of rework and improves the efficiency of site selection for tower construction routes. The calculation results are more accurate, with an accuracy improvement of more than 18% compared with traditional algorithms, which reduces the waste of redundant towers and reduces construction costs.

[0058] Additional aspects and advantages of the present invention will become apparent from the following description or may be learned by practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] The above and / or additional aspects and advantages of the present invention will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0060] Figure 1 is a flow chart of a method for selecting an optimal construction path for a tower in a mountainous area according to an embodiment of the present invention;

[0061] Figure 2 It is a schematic diagram of an optimal construction path for a pole tower formed after the blocks are spliced ​​in a method for selecting an optimal construction path for a pole tower in a mountainous area according to an embodiment of the present invention;

[0062] Figure 3 It is a schematic side view of a section in a method for selecting an optimal construction path for a pole tower in a mountainous area according to an embodiment of the present invention;

[0063] Figure 4 It is a schematic diagram of the path data accumulation process in a method for selecting an optimal construction path for a tower in a mountainous area according to an embodiment of the present invention. DETAILED DESCRIPTION

[0064] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0065] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0066] Refer to the following Figures 1 to 4 The following describes the optimal construction path site selection method for towers in mountainous areas provided in accordance with some embodiments of the present invention.

[0067] Some embodiments of the present application provide a method for selecting an optimal construction path for a tower in a mountainous area.

[0068] like Figure 1 As shown, the first embodiment of the present invention proposes a method for selecting the optimal construction path for towers in mountainous areas, including the following steps S1-S8. It can be understood that the order of steps S1-S8 is only a schematic representation, and those skilled in the art can adjust the order of steps as needed, and different steps can also be executed simultaneously.

[0069] S1. Obtain GIS map information of the construction address; the GIS map information at least includes the peak location, peak height, obstacle area location and obstacle area range; wherein the obstacle area is an area that needs to be avoided due to terrain conditions or policy and regulatory restrictions.

[0070] Specifically, the obstacle area may be an area with obstacles, land, grassland, hills, sand, minefield or environmental protection area. The location and scope of the obstacle area have been marked on the GIS map; it is understandable that the information on the GIS map also includes terrain and altitude information of each location.

[0071] S2. Grid the construction address and divide it into several grids to form a grid map. Each grid represents the minimum step node in the path planning process. The smaller the grid, the more accurate the calculation, but the greater the amount of calculation. In a specific embodiment, each grid represents a square area with a side length of 1m.

[0072] S3. Divide the construction site into sections according to the grid map and design the path for each section.

[0073] In step S3, the path planning calculation for a large area is divided into planning calculations in several relatively smaller areas by segmenting the blocks, which can effectively reduce the difficulty of calculation and improve the efficiency of calculation. In a specific embodiment, each block includes 1000*1000 grids.

[0074] S4. Randomly select a point as the starting point, and use a path-finding algorithm to find the initial optimal path based on the starting point; the path-finding algorithm uses F, G and H value notation to represent the cost of path movement, where G represents the actual cost of moving from the previous node to the current node, H represents the estimated cost of moving the current node to the edge of the board, and F represents the total cost of node selection, that is, the sum of G and H; the starting point, current node and target node are all represented in grid units; select the node with the lowest total cost among the adjacent nodes of the current node as the next node, until the current node reaches the edge of the board; each time a next node is determined, the path distance is accumulated to obtain the path distance of the initial optimal path.

[0075] In some embodiments, step S4 includes:

[0076] Determine whether the starting point is in the obstacle area. If so, abandon the starting point and select a new starting point. That is, after randomly selecting the starting point, first determine whether the starting point is in the obstacle area. If so, reselect the starting point.

[0077] Starting from the starting grid, that is, the starting point is the current node, according to the F values ​​of all grids adjacent to the starting grid, select at least one grid with the smallest F value as the next node, and accumulate the path distance; it should be noted that the adjacent referred to in this disclosure includes the adjacent in the positive direction (upper, lower, left, right) and the adjacent in the diagonal direction (upper left, lower left, upper right and lower right).

[0078] Take the next node as the current node and determine whether the current node has reached the edge of the board. If it has not reached the edge of the board, select at least one grid with the smallest F value as the next node based on the F values ​​of all grids adjacent to the current node, and accumulate the path distance; if the current node has reached the edge of the board, select the connection line of each node as the initial optimal path, form a route map, and output the accumulated path distance as the path distance of this initial optimal path.

[0079] Through the above method, based on a starting point, at least one initial optimal path will be generated, and because the F value of the grid adjacent to the current node is the same, multiple initial optimal paths will also be generated. It should be noted that the starting point can be located at the edge of the board or in the middle of the board. When the starting point is located at the edge of the board, the initial optimal path formed enters from the edge of the board and passes through the edge of the board.

[0080] In a specific embodiment, the path cost calculation includes:

[0081] The G value and H value of each grid are assigned in advance, where the G value is the actual cost of moving from the previous node to the current node according to the terrain and the moving direction, and the H value is the estimated cost of moving the current node to the edge of the plate; it can be understood that the assignment here is not the actual cost, but a relative reference value given according to the complexity of the terrain and the moving direction between nodes; when the terrain conditions are the same, the G value between two adjacent grids in the positive direction is smaller than the G value between two adjacent grids in the diagonal direction; similarly, the G value between two grids with complex terrain conditions is larger than that between two grids with simple terrain conditions; based on the above principles, the G value and H value can be assigned to each grid in the plate;

[0082] In some cases, the influence of terrain complexity on the G value may be ignored. For example, the G value may be directly assigned as the distance between two adjacent grids. The estimated cost of moving the current node to the edge of the plate, i.e., the H value, may be the sum of the vertical distance between the current node and the plate edge and the vertical slope between the current node and the plate edge. Since the plate edge has four edges, when selecting the H value, the closest plate edge may be selected according to the direction of travel, or the H value corresponding to the specified plate edge may be directly selected for judgment.

[0083] It should be noted that in step S4, not only one starting point is selected, but several starting points are randomly selected according to setting requirements to form several initial optimal paths corresponding to each starting point.

[0084] In addition, when the path touches the edge of the block, it can be determined whether there is an adjacent block in the specified direction according to the position of the block. If there is, the end point of the path is used as the exit point of the block, and the path planning of the next adjacent block is carried out. If there is no adjacent block, it indicates that the path planning of all blocks has been completed. In some embodiments, when selecting the starting point of the current block in the path planning of the next block, a corresponding selection can be made based on the end points of each path that can enter the current block in the previous block. Of course, this selection is only to simplify the planning process, and it is not a necessary step.

[0085] S5. Use the DREAD model to judge the threat level of the obstacle area, and determine the impact range of the obstacle area according to the obstacle area range and the threat level; when the initial optimal path passes through the impact range of the obstacle area, a detour design is performed according to the impact range of the obstacle area to obtain the optimal path, and the path distance of the optimal path is the sum of the path distance of the initial optimal path and the detour distance.

[0086] Specifically, the impact range of the obstacle zone is the area where poles and towers cannot be built at all due to the obstacle zone; although the range of the obstacle zone has been marked on the map, in actual situations, depending on the type of obstacle zone and the degree of obstacle, its impact range may be larger or smaller than the actual range. For example, for a swamp, the swamp range marked on the map is 500m*500m, but depending on the depth of the swamp, its actual impact range is also different. The deeper the swamp, the larger the actual impact range of the swamp will be, and it may exceed the marked range; the shallower the swamp, the smaller the actual impact range of the swamp will be, and even within the swamp range marked on the map, it is not completely impossible to build poles and towers. Similarly, for nature reserves, the scope of nature reserves is not completely unusable, and needs to be distinguished according to policies and protection levels. Therefore, the present disclosure uses the DREAD model to judge the threat level of the obstacle zone. The higher the threat level, the larger the actual impact range of the obstacle zone, and the lower the threat level, the smaller the actual impact range of the obstacle zone.

[0087] The DREAD model is a commonly used risk assessment model. In some embodiments, the DREAD model includes five risk indicators, including potential loss, reproducibility, exploitability, affected users, and discoverability.

[0088] Potential loss refers to how much loss there is if the defect is exploited; reproducibility refers to how difficult it is to repeat the attack; exploitability refers to how difficult it is to launch an attack; affected users refers to how many users are affected in a rough percentage; discoverability refers to the probability of other adverse situations occurring in the area; these risk indicators can be given in advance through on-site investigations, and the value range of each risk indicator is 0~1; that is, for this disclosure, the risk indicator value of each obstacle area is a known value;

[0089] The risk indicators of the obstacle area are summed up, and the sum result is used as the threat level of the obstacle area, then:

[0090]

[0091] in, Indicates the threat level of the obstacle area. Represents the value of the mth risk indicator.

[0092] The risk level indicates the impact of the actual situation of the obstacle area on its impact range.

[0093] In some embodiments, the distance from the center of the obstacle area to the farthest edge of the obstacle area is used as the actual radius of the obstacle area;

[0094] Calculate the radius of the obstacle area based on the actual radius of the obstacle area and the threat level:

[0095]

[0096] in, Indicates the radius of the obstacle area. Indicates the actual radius of the obstacle area;

[0097] In the center of the obstacle area The circular area with a radius of is the influence range of the obstacle area;

[0098] When the initial optimal path passes through the influence range of the obstacle area, the path is detoured along the edge of the influence range of the obstacle area until the initial optimal path does not interfere with the influence range of the obstacle area.

[0099] In other embodiments, the area of ​​the obstacle zone may also be used as an impact indicator, that is, the area of ​​the obstacle zone is enlarged or reduced year-on-year according to the threat level, so as to determine the impact range of the obstacle zone.

[0100] S6. When performing node selection and detour, determine whether the current node is a peak. If the node is a peak, determine whether the current peak is the highest peak in the section, accumulate the peak heights, and obtain the cumulative height of the optimal path.

[0101] After the above steps S4 to S6, several optimal paths in each section and the cumulative distance and cumulative height of each optimal path can be obtained. In some embodiments, the peak height can also be used to select the tower type, and the peak height is used to determine whether the current node is a turning point or a highest point, and then the turning point tower or the highest point tower is selected.

[0102] S7. Filter several optimal paths formed by several starting points in the section. The filtering principle includes: discarding the path that does not pass through the highest peak in the section, and selecting the optimal path with the highest cumulative height as the optimal path in this section.

[0103] It should be noted that research has found that for pole tower construction in mountainous areas, when the path passes through the highest peak at least once, the wiring cost can be effectively reduced; at the same time, the more peaks the path passes through, or the greater the cumulative height of the path, the fewer pole towers are needed for the path and the lower the wiring cost. Based on this principle, several paths in each section are screened to obtain the optimal path, which can simplify subsequent calculations and save the cost of pole tower construction.

[0104] S8. Use a feature-based image matching algorithm to splice the optimal paths in adjacent blocks to obtain the optimal construction path of the tower at the construction address.

[0105] The purpose of step S8 is to select two appropriate optimal paths from several optimal paths in two adjacent blocks for splicing; and to form a complete path by making slight changes to the two optimal paths in two adjacent blocks. The optimal construction path of the tower is not just one, but there are multiple paths, and each path has the following characteristics: Figure 2 The path image, cumulative distance, cumulative altitude and the cumulative value of detour weight consumption mentioned in the subsequent embodiments can be provided for reference and selection by designers.

[0106] In some embodiments, step S8 includes:

[0107] Extract the feature points of the roadmap in two adjacent blocks to form a feature point set and ;in, Represents the nth feature point in a block, Indicates the mth feature point in another section. It should be noted that the feature point can be a tower corner point, edge, closest point, etc.

[0108] Use the BFMatcher matching algorithm to find the matching point pairs between the two feature point sets and form a matching point pair set ;in, , ; When there are no matching point pairs between the two optimal paths, it means that the two paths cannot be spliced;

[0109] The transformation matrix T between the two blocks is estimated based on the matching point pair set M. The transformation matrix is ​​used to transform the feature point set M by translation or rotation. The feature points in are mapped to new positions; specifically:

[0110]

[0111] in, represents the error function, represents the Euclidean distance;

[0112] By minimizing the above error function, the transformation matrix is ​​determined .

[0113] After obtaining the transformation matrix, the splicing scheme of the paths in the two sections is determined according to the transformation matrix. In the system, it is displayed as the translation and rotation operations of the sections according to the transformation matrix. In the actual application process, the changes on the sections are converted into changes in the tower angles, tower connection points, and adapter designs.

[0114] In some embodiments, Figure 3 As shown, each block has 16 sides, each side represents a line-out direction. When blocks are spliced, the optimal path corresponding to the line-out direction of the optimal path in the current block is selected from several paths of adjacent blocks for splicing;

[0115] The 16 side surfaces of the block are the side surfaces covered by the fan-shaped area formed by two adjacent rays among the 16 rays emitted from the center of the block, and the angle between any two adjacent rays is 22.5 degrees.

[0116] In some embodiments, in order to control the line cost caused by detouring the obstacle area, the method further includes:

[0117] A weight consumption threshold is given in advance; for example, 10;

[0118] Each time the obstacle area is bypassed, the bypass weight consumption is calculated and accumulated; when the accumulated bypass weight consumption exceeds the weight consumption threshold, the current path is abandoned and redesigned;

[0119] The calculation method of the detour weight consumption includes:

[0120]

[0121] in, represents the detour weight consumption, Represents the project weight factor. The higher the project weight factor, the greater the cost investment of this project and the longer the optional detour path.

[0122] It is understandable that the accumulation of detour weight consumption is not for one section, but for the overall path planning. As long as the accumulated weight consumption reaches the weight consumption threshold, it means that the cost of detour in the current path planning scheme is too high, and the route is directly abandoned and no subsequent planning of the route is carried out.

[0123] In a specific embodiment, Figure 4 As shown, during the path planning process, the path length Kr1, the height of the mountain passed by Km1, and the detour weight consumption Kx1 of a path corresponding to each starting point K are accumulated, and finally the cumulative height SKm, cumulative length SKr, cumulative weight consumption SKx and path graph of the path are obtained.

[0124] In some embodiments, the method further includes step S9.

[0125] S9. Estimate the wire consumption of the optimal construction path for each tower;

[0126] Specifically, for a peak node that does not have an adjacent peak node, the wire consumption of the peak node is obtained by multiplying the plane distance of the peak node by the height of the mountain;

[0127] For the road section between two non-directly adjacent peak nodes, the plane distance between the two peak nodes is used as the wire consumption of the road section;

[0128] For the road section between two directly adjacent mountain nodes, the plane distance between the two peaks multiplied by the height difference between the two peaks is used as the wire consumption of the road section.

[0129] It is understandable that the above estimation is not the actual wire consumption, but the theoretical value of relative wire consumption calculated after considering the path conditions. The output wire consumption results can be used to compare and evaluate the wire consumption of different paths. Appropriate redundancy should also be made in the final production according to the local climate conditions, the quality management capabilities of the construction team, etc.

[0130] In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0131] Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for selecting the optimal construction path of a tower in a mountainous area, characterized in that: include: Obtain GIS map information of the construction address; The GIS map information includes at least the location of the mountain peak, the height of the mountain peak, the location of the obstacle area and the range of the obstacle area; wherein the obstacle area is an area that needs to be avoided due to terrain conditions or policy and regulatory restrictions; Grid the construction address and divide it into several grids to form a grid map; Divide the construction site into sections according to the grid map, and design the path for each section; A point is randomly selected as the starting point, and a pathfinding algorithm is used to find the initial optimal path based on the starting point; the pathfinding algorithm uses F, G and H value notation to represent the cost of path movement, where G represents the actual cost of moving from the previous node to the current node, H represents the estimated cost of moving the current node to the edge of the board, and F represents the total cost of node selection, that is, the sum of G and H; the starting point, current node and target node are all represented in grid units; the node with the lowest total cost is selected from the adjacent nodes of the current node as the next node until the current node reaches the edge of the board; each time a next node is determined, the path distance is accumulated to obtain the path distance of the initial optimal path; The DREAD model is used to judge the threat level of the obstacle area, and the impact range of the obstacle area is determined according to the obstacle area range and threat level. When the initial optimal path passes through the impact range of the obstacle area, a detour design is performed according to the impact range of the obstacle area to obtain the optimal path. The path distance of the optimal path is the sum of the path distance of the initial optimal path and the detour distance. When selecting and detouring nodes, determine whether the current node is a peak. If the node is a peak, determine whether the current peak is the highest peak in the section, accumulate the peak heights, and obtain the cumulative height of the optimal path; Screening several optimal paths formed by several starting points in the section. The screening principles include: discarding the paths that do not pass through the highest peak in the section, and selecting the optimal path with the highest cumulative height as the optimal path in this section; The optimal paths in adjacent blocks are spliced ​​using a feature-based image matching algorithm to obtain the optimal construction path of the tower at the construction address.

2. The method for selecting the optimal construction path of a tower in a mountainous area according to claim 1, characterized in that: The path finding algorithm is used to find the initial optimal path based on the starting point, including: Determine whether the starting point is in the obstacle area. If the starting point is in the obstacle area, abandon the starting point and select a new starting point; Starting from the starting grid, that is, the starting point is the current node, according to the F values ​​of all grids adjacent to the starting grid, at least one grid with the smallest F value is selected as the next node, and the path distance is accumulated; Take the next node as the current node and determine whether the current node has reached the edge of the board. If it has not reached the edge of the board, select at least one grid with the smallest F value as the next node based on the F values ​​of all grids adjacent to the current node, and accumulate the path distance; if the current node has reached the edge of the board, select the connection line of each node as the initial optimal path, form a route map, and output the accumulated path distance as the path distance of this initial optimal path.

3. The method for selecting the optimal construction path of a tower in a mountainous area according to claim 2, characterized in that: The path finding algorithm uses F, G and H value notation to represent the cost of path movement, including: Assign G and H values ​​to each grid, where G is the actual cost of moving from the previous node to the current node according to the terrain and moving direction, and H is the estimated cost of moving from the current node to the edge of the plate; The estimated cost of moving the current node to the edge of the board is the sum of the vertical distance between the current node and the edge of the board and the slope between the current node and the edge of the board in the vertical direction.

4. The method for selecting the optimal construction path of a tower in a mountainous area according to claim 1, characterized in that: The DREAD model is used to judge the threat level of the obstacle area, including: The risk indicators of the obstacle area are summed up, and the sum result is used as the threat level of the obstacle area. The risk indicators include potential loss, reproducibility, availability, affected users and discoverability. The value range of each risk indicator is 0~1, so: in, Indicates the threat level of the obstacle area. Represents the value of the mth risk indicator.

5. The method for selecting the optimal construction path of a tower in a mountainous area according to claim 4, characterized in that: Determining the impact range of the obstacle area according to the range of the obstacle area and the threat level includes: The distance from the center of the obstacle area to the farthest edge of the obstacle area is taken as the actual radius of the obstacle area; Calculate the radius of the obstacle area based on the actual radius of the obstacle area and the threat level: in, Indicates the radius of the obstacle area. Indicates the actual radius of the obstacle area; In the center of the obstacle area The circular area with a radius of is the influence range of the obstacle area; When the initial optimal path passes through the influence range of the obstacle area, the path is detoured along the edge of the influence range of the obstacle area until the initial optimal path does not interfere with the influence range of the obstacle area.

6. The method for selecting the optimal construction path of a tower in a mountainous area according to claim 4, characterized in that: Also includes: Each time you bypass an obstacle area, calculate the bypass weight consumption and accumulate the bypass weight consumption; When the detour weight consumption cumulative value exceeds the weight consumption threshold, the current path is abandoned and redesigned; The calculation method of the detour weight consumption includes: in, represents the detour weight consumption, Represents the project weight factor. The higher the project weight factor, the greater the cost investment of this project and the longer the optional detour path.

7. The method for selecting the optimal construction path of a tower in a mountainous area according to claim 2, characterized in that: The method of using a feature-based image matching algorithm to splice the optimal paths in adjacent blocks to obtain the optimal construction path of the tower at the construction address includes: Extract the feature points of the roadmap in two adjacent blocks to form a feature point set and ;in, Represents the nth feature point in a block, Represents the mth feature point in another section; Use the BFMatcher matching algorithm to find the matching point pairs between the two feature point sets and form a matching point pair set ;in, , ; The transformation matrix T between the two blocks is estimated based on the matching point pair set M. The transformation matrix is ​​used to transform the feature point set M by translation or rotation. Map the feature points in to new positions; Determine the splicing scheme of the paths in the two sections based on the transformation matrix.

8. The method for selecting the optimal construction path of a tower in a mountainous area according to claim 7, characterized in that: The estimating the transformation matrix between the two blocks according to the matching point pair set M includes: in, represents the error function, represents the Euclidean distance; By minimizing the error function, the transformation matrix is ​​determined .

9. The method for selecting the optimal construction path of a tower in a mountainous area according to claim 8, characterized in that: Also includes: Each block has 16 sides, each side represents a line-out direction. When blocks are spliced, the optimal path corresponding to the line-out direction of the optimal path in the current block is selected from several paths of adjacent blocks for splicing; The 16 side surfaces of the block are the side surfaces covered by the fan-shaped area formed by two adjacent rays among the 16 rays emitted from the center of the block, and the angle between any two adjacent rays is 22.5 degrees.

10. The method for selecting the optimal construction path of a tower in a mountainous area according to claim 1, characterized in that: Also includes: Estimate the wire consumption for the optimal construction path of each tower; Among them, for a peak node without an adjacent peak node, the wire consumption of the peak node is obtained by multiplying the plane distance of the peak node by the height of the mountain; For the road section between two non-directly adjacent peak nodes, the plane distance between the two peak nodes is used as the wire consumption of the road section; For the road section between two directly adjacent mountain nodes, the plane distance between the two peaks multiplied by the height difference between the two peaks is used as the wire consumption of the road section.

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