A method and device for collecting real-time point cloud of distribution network lines by drone

Abstract

The present application provides a method and device for real-time point cloud collection of distribution network lines by drones, which relates to the field of automated operation and maintenance technology and is used to improve the inspection efficiency of distribution network lines by drones. The method mainly includes: obtaining a digital elevation map in the target area; determining the position coordinates of each transmission tower in the distribution network line according to the digital elevation map; determining the point cloud data collection line according to the position coordinates and geographical location relationship of each transmission tower; controlling the flight of the drone according to the point cloud data collection line to collect the point cloud data and image data corresponding to the distribution network line; the distance of the drone from each transmission tower during flight exceeds the preset distance; constructing a distribution network line simulation model through the point cloud data and image data corresponding to the distribution network line and the attribute data of the distribution network line; determining whether the distribution network line has an abnormal operation according to the distribution network line simulation model.

Description

Technical Field

[0001] The present application relates to the field of automated operation and maintenance technology, and in particular to a method and device for collecting real-time point clouds of distribution network lines by drones. Background Art

[0002] The vast territory, complex and diverse population, and uneven resource distribution will result in a large number of substation facilities and transmission line networks being distributed in a complex and changeable outdoor environment, constantly exposed to severe weather such as wind, rain, and exposure to the sun. There are serious defects in the appearance of power equipment, which is prone to equipment failure, leading to power supply accidents and posing a serious threat to the life and property safety of power workers and users.

[0003] At present, the use of drones for inspections has replaced the manual inspection method of power transmission lines using telescopes or cameras. However, the commonly used manual inspection method of drones requires high technical skills of the pilots and is prone to the risk of collision with line equipment, making it impossible to effectively implement the power inspection of transmission lines using drones. Therefore, there is a problem in the relevant technology that there is a lack of automatic drone inspection planning when conducting refined inspections of distribution network lines. Summary of the invention

[0004] The embodiments of the present application provide a method and device for collecting real-time point clouds of distribution network lines by drones, which are used to improve the inspection efficiency of distribution network lines by drones.

[0005] An embodiment of the present invention provides a method for collecting real-time point clouds of distribution network lines by drones, the method comprising:

[0006] Acquire a digital elevation map in the target area, wherein the digital elevation map includes a height corresponding to each pixel point and a normalized vegetation index;

[0007] Determine the position coordinates of each transmission tower in the distribution network line according to the digital elevation map;

[0008] Determine the point cloud data collection line according to the position coordinates of each transmission tower and the geographical location relationship;

[0009] The drone is controlled to fly according to the point cloud data collection line to collect point cloud data and image data corresponding to the distribution network line; the distance between the drone and each transmission tower exceeds a preset distance during the flight;

[0010] Constructing a distribution network line simulation model through point cloud data and image data corresponding to the distribution network line and attribute data of the distribution network line;

[0011] Whether the distribution network line has an operational abnormality is detected according to the distribution network line simulation model.

[0012] In an optional embodiment provided by the present invention, the determining the position coordinates of each transmission tower in the distribution network line according to the digital elevation map includes:

[0013] Obtain a transmission tower marking map corresponding to the digital elevation map; the transmission tower marking map includes a plurality of transmission tower marking points, each transmission tower marking point being a position coordinate corresponding to a pixel point with the highest brightness within a preset area in the tower position marking map;

[0014] The transmission tower marking points in the transmission tower marking map are filtered according to the height corresponding to each pixel point in the digital elevation map, the normalized vegetation index, and the transmission tower height.

[0015] In an optional embodiment provided by the present invention, the step of determining a point cloud data collection route according to the position coordinates and geographical location relationship of each transmission tower includes:

[0016] Determine an initial acquisition line according to the position coordinates and geographical location relationship of each transmission tower; the initial acquisition line includes multiple acquisition points, each acquisition point is used to collect point cloud data and image data of a transmission tower;

[0017] Determine the bypass collection lines corresponding to each collection point through the height of each transmission tower and the altitude of the ground contact point;

[0018] The initial acquisition route and the fly-around acquisition routes of each acquisition point are sequentially connected according to the geographical location relationship to obtain the point cloud data acquisition route.

[0019] In an optional embodiment provided by the present invention, determining the bypass collection routes corresponding to the respective collection points according to the tower heights of the respective transmission towers and the altitudes of the ground contact points includes:

[0020] Calculate the height difference between the ground contact points of the previous transmission tower and the next transmission tower;

[0021] If the height difference is greater than a preset value, the end position corresponding to the fly-around collection line of the previous transmission tower is obtained;

[0022] If the corresponding end position of the fly-around collection line of the previous transmission tower is at the top of the transmission tower, the fly-around collection line of the next transmission tower starts from the bottom of the transmission tower and circles the transmission tower to the top of the transmission tower.

[0023] In an optional embodiment provided by the present invention, the controlling the flight of the drone according to the point cloud data acquisition line to collect point cloud data and image data corresponding to the distribution network line includes:

[0024] Determine the safety radius of each transmission tower according to the actual size of the transmission tower;

[0025] Control the drone to fly to each collection point according to the initial collection route;

[0026] When the drone flies to the corresponding collection point, the drone is controlled to fly along the circling collection route to collect point cloud data and image data of the corresponding transmission tower;

[0027] Wherein, the distance between the bypass collection line and the corresponding transmission tower is greater than the safety radius.

[0028] In an optional embodiment provided by the present invention, after the drone flies to the corresponding collection point and controls the drone to fly along the circling collection route to collect point cloud data and image data of the corresponding transmission tower, the method further includes:

[0029] Merging the point cloud data and the image data of the transmission tower to obtain a point cloud data set and an image data set;

[0030] Based on the image recognition technology, repeated image data in the image data set are filtered to obtain the point cloud data corresponding to the filtered transmission tower, and based on data clustering, the point cloud data set is filtered to obtain the point cloud data corresponding to the filtered transmission tower.

[0031] In an optional embodiment provided by the present invention, the construction of a distribution network line simulation model by using the point cloud data, image data corresponding to the distribution network line and the attribute data of the distribution network line includes:

[0032] Determine a three-dimensional image based on the point cloud data and image data corresponding to the distribution network line;

[0033] A distribution network line simulation model is constructed by using the three-dimensional stereoscopic image and the three-dimensional stereoscopic image.

[0034] In an optional embodiment provided by the present invention, the detecting whether the distribution network line has an operation abnormality according to the distribution network line simulation model includes:

[0035] Acquire the operation data of the distribution network line in real time;

[0036] The operation data is input into the distribution network line simulation model for simulation to obtain the detection result of the distribution network line.

[0037] In an optional embodiment provided by the present invention, the method further includes:

[0038] If the detection result of the distribution network line is abnormal, an abnormal alarm message is output.

[0039] In an optional embodiment provided by the present invention, after determining the fault occurring in the power system through the first power attribute data feature matrix and the second power attribute data feature matrix, the method further includes:

[0040] A repair strategy corresponding to the fault occurring in the power system is determined according to a preset mapping table.

[0041] An embodiment of the present invention provides a distribution network line drone real-time point cloud acquisition device, the device comprising:

[0042] An acquisition module is used to acquire a digital elevation map in the target area, wherein the digital elevation map includes a height corresponding to each pixel point and a normalized vegetation index;

[0043] A determination module, used to determine the position coordinates of each transmission tower in the distribution network line according to the digital elevation map;

[0044] The determination module is further used to determine the point cloud data collection line according to the position coordinates and geographical location relationship of each transmission tower;

[0045] A collection module is used to control the flight of the drone according to the point cloud data collection line to collect point cloud data and image data corresponding to the distribution network line; when the distance between the drone and each transmission tower exceeds a preset distance during flight;

[0046] A construction module, used to construct a distribution network line simulation model through point cloud data and image data corresponding to the distribution network line and attribute data of the distribution network line;

[0047] The detection module is used to detect whether the distribution network line has an operating abnormality according to the distribution network line simulation model.

[0048] The present invention provides a method and device for real-time point cloud collection of distribution network lines by unmanned aerial vehicles. First, a digital elevation map of a target area is obtained, wherein the digital elevation map includes the height and normalized vegetation index corresponding to each pixel point; then, the position coordinates of each transmission tower in the distribution network line are determined according to the digital elevation map; the point cloud data collection line is determined according to the position coordinates and geographical location relationship of each transmission tower; the unmanned aerial vehicle is controlled to fly according to the point cloud data collection line to collect point cloud data and image data corresponding to the distribution network line; during the flight of the unmanned aerial vehicle, the distance from each transmission tower exceeds the preset distance; a distribution network line simulation model is constructed through the point cloud data and image data corresponding to the distribution network line and the attribute data of the distribution network line; finally, whether the distribution network line has an abnormal operation is detected according to the distribution network line simulation model. Compared with the existing method of collecting relevant data of distribution network lines by unmanned aerial vehicles manually operated, the present invention determines the point cloud data collection line according to the position coordinates and geographical location relationship of each transmission tower, and then controls the unmanned aerial vehicle to fly according to the point cloud data collection line to collect point cloud data and image data corresponding to the distribution network line, so that the inspection efficiency and data collection efficiency of the unmanned aerial vehicle on the distribution network line can be improved through the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 A flow chart of a method for collecting real-time point cloud of a distribution network line by drone provided in this application;

[0050] Figure 2 This is a structural diagram of a distribution network line drone real-time point cloud acquisition device provided in this application. DETAILED DESCRIPTION

[0051] In order to better understand the above-mentioned technical scheme, the technical scheme of the embodiments of the present application is described in detail below through the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present application and the specific features in the embodiments are detailed descriptions of the technical scheme of the embodiments of the present application, rather than limitations on the technical scheme of the present application. In the absence of conflict, the embodiments of the present application and the technical features in the embodiments may be combined with each other.

[0052] See also Figure 1 As shown, a distribution network line UAV real-time point cloud acquisition method provided by an embodiment of the present invention, the execution process of the method is as follows:

[0053] S101, obtaining a digital elevation map within a target area.

[0054] The digital elevation map is a digital surface model (DSM), which includes the height of objects such as buildings, bridges and trees on the surface. That is, each pixel in the digital elevation map has a corresponding height value, which can be represented by the brightness value of the pixel. The greater the brightness of the pixel, the higher the height value it represents. The digital elevation map includes the height corresponding to each pixel and the normalized vegetation index.

[0055] S102: Determine the position coordinates of each transmission tower in the distribution network according to the digital elevation map.

[0056] After obtaining the digital elevation map, the embodiment can determine the position coordinates of each transmission tower by analyzing the brightness value of each pixel in the digital elevation map. Specifically, first obtain the position coordinates corresponding to the pixel with the highest brightness in the preset area of ​​the digital elevation map, and then determine the position coordinates of the obtained pixel as the transmission tower.

[0057] In an optional embodiment provided by the present invention, the determining the position coordinates of each transmission tower in the distribution network line according to the digital elevation map includes:

[0058] S1021, obtaining a transmission tower marking map corresponding to the digital elevation map.

[0059] The transmission tower marking map includes a plurality of transmission tower marking points, and each transmission tower marking point is the position coordinate corresponding to the pixel with the highest brightness in a preset area in the tower position marking map.

[0060] S1022: filtering the transmission tower marking points in the transmission tower marking map according to the height corresponding to each pixel point in the digital elevation map, the normalized vegetation index, and the transmission tower height.

[0061] Among them, the Normalized Difference Vegetation Index (NDVI) quantifies vegetation by measuring the difference between near-infrared (strongly reflected by vegetation) and red light (absorbed by vegetation). The range of NDVI is always -1 to +1. But there are no clear boundaries for each type of land cover. For example, when the value is negative, it is likely water. On the other hand, if the NDVI value is close to +1, it is likely lush green leaves. However, when the NDVI is close to zero, there are no green leaves and it may even be an urbanized area. Specifically, the Normalized Vegetation Index: NDVI = (NIR-R) / (NIR+R), NIR is the reflectance value of the near-infrared band, and R is the reflectance value of the red light band.

[0062] Since the larger the NDVI value, the more vegetation coverage there is, the present embodiment can detect the vegetation coverage area by setting a reasonable threshold value. If the NDVI corresponding to a certain transmission pole tower marking point in the transmission pole tower marking map is in a larger area, it means that the transmission pole tower marking point is a vegetation point (such as a tree, etc.), that is, the transmission pole tower marking point is inaccurate, and therefore the transmission pole tower marking point needs to be removed from the transmission pole tower marking map.

[0063] Since the digital elevation map in this embodiment has a height value corresponding to each pixel point, after obtaining the transmission tower marking map, this embodiment filters the tower marking points that do not belong to the tower height according to the height values ​​corresponding to the transmission tower marking points in the digital elevation map. For example, if the height of the transmission tower is 20 meters, the height value corresponding to the transmission tower marking point in the digital elevation map is determined, and then the transmission tower marking points whose height values ​​are obviously higher than 20 meters or 20 meters are filtered, and specifically, the transmission tower marking points whose height values ​​are not within 18-22 meters can be filtered.

[0064] In this embodiment, after filtering the transmission tower marker points in the transmission tower marker map by using the height corresponding to each pixel point in the digital elevation map, the normalized vegetation index, and the transmission tower height, in order to further improve the accuracy of determining the transmission tower marker points, the preset linear fitting formula can also be used to filter the marker points that do not belong to the transmission tower. The preset linear fitting formula is:

[0065] y=ax+bx 2 +x 3

[0066] Among them, a and b are constant coefficients, x represents the horizontal coordinate of the transmission tower mark point, and y represents the fitting vertical coordinate of the transmission tower mark point. The preset linear fitting formula is obtained by fitting a large amount of data.

[0067] In this embodiment, after the transmission tower marking points are obtained by filtering in step S1022, the position coordinates of each transmission tower marking point are obtained, and then the horizontal coordinates of each transmission tower marking point are input into the above linear fitting formula to obtain the fitting vertical coordinates, and then the distance between the fitting vertical coordinates and the actual vertical coordinates is compared to see whether it is greater than the preset distance. If it is greater than the preset distance, it means that the position coordinates do not belong to the transmission tower marking point, that is, the transmission tower marking point needs to be filtered out; if it is less than or equal to the preset distance, there is no need to filter the transmission tower marking point. The preset distance can be set according to actual needs, such as 3 meters, 4 meters, etc., and this embodiment does not make specific restrictions on this.

[0068] S103, determining a point cloud data collection route according to the position coordinates and geographical location relationship of each transmission tower.

[0069] Among them, the geographical location relationship is used to represent the arrangement order of each transmission tower. The position coordinates of all transmission towers are sequentially connected according to the geographical location relationship to obtain a point cloud data collection line, and then the drone is controlled to fly along the point cloud data collection line to collect point cloud data corresponding to the distribution network line. The distribution network line includes transmission lines and transmission towers. The transmission towers are used to connect the transmission lines.

[0070] In an optional embodiment provided by the present invention, the step of determining a point cloud data collection route according to the position coordinates and geographical location relationship of each transmission tower includes:

[0071] S1031, determining an initial data collection line according to the position coordinates and geographical location relationship of each transmission tower.

[0072] The initial acquisition line includes multiple acquisition points, each of which is used to collect point cloud data and image data of a transmission tower. It should be noted that when the drone in this embodiment collects data from the transmission tower, it needs to use the same acquisition angle for data collection, that is, use the same shooting angle to obtain the point cloud data and image data of the transmission tower.

[0073] In this embodiment, in addition to collecting point cloud data and image data of the transmission tower through the drone, the point cloud data of the transmission line between two transmission towers can also be collected, that is, after obtaining the initial collection line, the point cloud data of the transmission line is collected according to the initial collection line, that is, flying from the top of one transmission tower to the top of another transmission tower according to the initial collection line, thereby realizing the drone flying along the transmission line to collect the point cloud data of the transmission line. In this embodiment, by collecting the point cloud data of the transmission line, it can be determined whether the transmission line is abnormal, that is, the foreign objects hanging on the transmission line can be determined by the point cloud data corresponding to the transmission line, thereby improving the safety of the transmission line.

[0074] S1032, determining the bypass collection lines corresponding to the respective collection points according to the tower heights of the transmission towers and the altitudes of the ground contact points.

[0075] The circumnavigation collection route is the route that the drone flies around the transmission tower, so as to realize the all-round collection of point cloud data and image data of the transmission tower. In this embodiment, the circumnavigation collection route can be a spiral ascending route, a spiral descending route, or a flight route from multiple angles of the transmission tower, such as a flight route from the front from top to bottom, and a flight route from the back from bottom to top. This embodiment does not make specific limitations on this.

[0076] Specifically, the method of determining the circumnavigation collection lines corresponding to each collection point through the tower height of each transmission tower and the altitude of the ground contact point includes: calculating the height difference between the altitude of the ground contact point of the previous transmission tower and the next transmission tower; if the height difference is greater than the preset value, obtaining the end position corresponding to the circumnavigation collection line of the previous transmission tower; if the end position corresponding to the circumnavigation collection line of the previous transmission tower is at the top of the transmission tower, the circumnavigation collection line of the next transmission tower starts from the bottom of the transmission tower and circles the transmission tower to the top of the transmission tower. The preset value is a value set according to actual needs, which can be 10 meters, 20 meters, 30 meters, etc., and this embodiment does not specifically limit this.

[0077] In another embodiment provided by the present invention, the inclination angle of the two transmission towers can also be calculated based on the line connecting the ground contact points of the previous transmission tower and the next transmission tower. If the inclination angle is greater than a preset angle, the end position corresponding to the fly-around collection line of the previous transmission tower is obtained; if the end position corresponding to the fly-around collection line of the previous transmission tower is at the top of the transmission tower, the fly-around collection line of the next transmission tower starts from the bottom of the transmission tower and surrounds the transmission tower to the top of the transmission tower.

[0078] In this embodiment, whether it is based on the height difference of the transmission tower above sea level or the detour collection route determined based on the inclination angle of the transmission tower, it is to make the distance from the previous transmission tower to the next transmission tower of the drone as short as possible, thereby improving the operating efficiency of the drone through this embodiment, that is, improving the inspection efficiency of the drone and the efficiency of data collection.

[0079] In another embodiment provided by the present invention, the fly-around collection route can be a round-trip path, that is, the round-trip path includes a flight path from the front from top to bottom and a flight path from the back from bottom to top, that is, the fly-around collection paths corresponding to all transmission towers are round-trip paths, and the point cloud data and image data of each transmission tower are collected in sequence by flying along the sub-paths.

[0080] S1033, sequentially connecting the initial acquisition route and the fly-by acquisition routes of each acquisition point according to the geographical location relationship to obtain the point cloud data acquisition route.

[0081] For example, the target area includes transmission towers 1 to 10 arranged in sequence, the initial acquisition line is the connection line between transmission towers 1 to 10, and the bypass acquisition line is the line for collecting the corresponding transmission towers. In this embodiment, the initial acquisition lines of all transmission towers and the bypass acquisition lines of each collection point are connected in sequence according to the geographical location relationship, so that the point cloud data acquisition line can be obtained.

[0082] S104, controlling the drone to fly according to the point cloud data collection line to collect point cloud data and image data corresponding to the distribution network line.

[0083] Among them, the distance between the drone and each transmission tower during flight exceeds the preset distance, thereby ensuring the safety of the drone flight.

[0084] In an optional embodiment provided by the present invention, the drone is controlled to fly according to the point cloud data collection line to collect the point cloud data and image data corresponding to the distribution network line, including: determining the safety radius of each transmission tower according to the actual size of the transmission tower; controlling the drone to fly to each collection point according to the initial collection line; and controlling the drone to fly according to the circumnavigation collection line when the drone flies to the corresponding collection point to collect the point cloud data and image data of the corresponding transmission tower. The distance between the circumnavigation collection line and the corresponding transmission tower is greater than the safety radius.

[0085] Furthermore, after the drone is controlled to fly along the circling collection route when the drone flies to the corresponding collection point to collect the point cloud data and image data of the corresponding transmission tower, the method further includes: merging the point cloud data and image data of the transmission tower to obtain a point cloud data set and an image data set; filtering the repeated image data in the image data set based on the image recognition technology to obtain the filtered point cloud data corresponding to the transmission tower, and filtering the point cloud data set based on data clustering to obtain the filtered point cloud data corresponding to the transmission tower. In this embodiment, filtering the point cloud data set and the image data set can ensure the accuracy of the obtained point cloud data and image data, thereby improving the accuracy of the distribution network line simulation model constructed subsequently.

[0086] S105, constructing a distribution network line simulation model through the point cloud data and image data corresponding to the distribution network line and the attribute data of the distribution network line.

[0087] In an optional embodiment provided by the present invention, the distribution network line simulation model is constructed by using the point cloud data, image data and attribute data of the distribution network line corresponding to the distribution network line, including: determining a three-dimensional stereo image according to the point cloud data and image data corresponding to the distribution network line; and constructing the distribution network line simulation model through the three-dimensional stereo image and the three-dimensional stereo image.

[0088] S106: Detect whether the distribution network line has an operational abnormality according to the distribution network line simulation model.

[0089] In an optional embodiment provided by the present invention, detecting whether the distribution network line has an operating abnormality based on the distribution network line simulation model includes: acquiring operating data of the distribution network line in real time; inputting the operating data into the distribution network line simulation model for simulation to obtain a detection result of the distribution network line.

[0090] Furthermore, if the detection result of the distribution network line is abnormal, an abnormal alarm message is output. The alarm message can be output on the administrator screen interface, or can be a sound prompt alarm message, or can be sent to the client corresponding to the corresponding regional manager, which is not specifically limited in this embodiment.

[0091] The embodiment of the present invention provides a method for real-time point cloud collection of distribution network lines by drones, firstly obtaining a digital elevation map of a target area, wherein the digital elevation map includes the height and normalized vegetation index corresponding to each pixel point; then determining the position coordinates of each transmission tower in the distribution network line according to the digital elevation map; determining the point cloud data collection line according to the position coordinates and geographical location relationship of each transmission tower; controlling the drone to fly according to the point cloud data collection line to collect point cloud data and image data corresponding to the distribution network line; the distance of the drone from each transmission tower during flight exceeds the preset distance; constructing a distribution network line simulation model through the point cloud data and image data corresponding to the distribution network line and the attribute data of the distribution network line; finally, detecting whether the distribution network line has an abnormal operation according to the distribution network line simulation model. Compared with the existing method of collecting relevant data of distribution network lines by drones manually operated, the present invention determines the point cloud data collection line according to the position coordinates and geographical location relationship of each transmission tower, and then controls the drone to fly according to the point cloud data collection line to collect point cloud data and image data corresponding to the distribution network line, so that the inspection efficiency and data collection efficiency of the distribution network line by drones can be improved through the present invention.

[0092] In one embodiment, a distribution network line drone real-time point cloud acquisition device is provided, and the automated operation and maintenance system fault diagnosis and repair device corresponds to the automated operation and maintenance system fault diagnosis and repair method described above. Figure 2 As shown, the device comprises:

[0093] An acquisition module 21 is used to acquire a digital elevation map in a target area, wherein the digital elevation map includes a height corresponding to each pixel point and a normalized vegetation index;

[0094] A determination module 22, configured to determine the position coordinates of each transmission tower in the distribution network line according to the digital elevation map;

[0095] The determination module 22 is further used to determine the point cloud data collection line according to the position coordinates and geographical location relationship of each transmission tower;

[0096] The acquisition module 23 is used to control the flight of the drone according to the point cloud data acquisition line to collect point cloud data and image data corresponding to the distribution network line; the distance between the drone and each transmission tower exceeds a preset distance during the flight;

[0097] A construction module 24, configured to construct a distribution network line simulation model by using the point cloud data and image data corresponding to the distribution network line and the attribute data of the distribution network line;

[0098] The detection module 25 is used to detect whether the distribution network line has an abnormal operation according to the distribution network line simulation model.

[0099] In an optional embodiment provided by the present invention, the determining the position coordinates of each transmission tower in the distribution network line according to the digital elevation map includes:

[0100] Obtain a transmission tower marking map corresponding to the digital elevation map; the transmission tower marking map includes a plurality of transmission tower marking points, each transmission tower marking point being a position coordinate corresponding to a pixel point with the highest brightness within a preset area in the tower position marking map;

[0101] The transmission tower marking points in the transmission tower marking map are filtered according to the height corresponding to each pixel point in the digital elevation map, the normalized vegetation index, and the transmission tower height.

[0102] In an optional embodiment provided by the present invention, the determination module 22 is specifically configured to:

[0103] Determine an initial acquisition line according to the position coordinates and geographical location relationship of each transmission tower; the initial acquisition line includes multiple acquisition points, each acquisition point is used to collect point cloud data and image data of a transmission tower;

[0104] Determine the bypass collection lines corresponding to each collection point through the height of each transmission tower and the altitude of the ground contact point;

[0105] The initial acquisition route and the fly-around acquisition routes of each acquisition point are sequentially connected according to the geographical location relationship to obtain the point cloud data acquisition route.

[0106] In an optional embodiment provided by the present invention, the determination module 22 is specifically configured to:

[0107] Calculate the height difference between the ground contact points of the previous transmission tower and the next transmission tower;

[0108] If the height difference is greater than a preset value, the end position corresponding to the fly-around collection line of the previous transmission tower is obtained;

[0109] If the corresponding end position of the fly-around collection line of the previous transmission tower is at the top of the transmission tower, the fly-around collection line of the next transmission tower starts from the bottom of the transmission tower and circles the transmission tower to the top of the transmission tower.

[0110] In an optional embodiment provided by the present invention, the acquisition module 23 is specifically used for:

[0111] Determine the safety radius of each transmission tower according to the actual size of the transmission tower;

[0112] Control the drone to fly to each collection point according to the initial collection route;

[0113] When the drone flies to the corresponding collection point, the drone is controlled to fly along the circling collection route to collect point cloud data and image data of the corresponding transmission tower;

[0114] Wherein, the distance between the bypass collection line and the corresponding transmission tower is greater than the safety radius.

[0115] In an optional embodiment provided by the present invention, the acquisition module 23 is specifically used for:

[0116] Merging the point cloud data and the image data of the transmission tower to obtain a point cloud data set and an image data set;

[0117] Based on the image recognition technology, repeated image data in the image data set are filtered to obtain the point cloud data corresponding to the filtered transmission tower, and based on data clustering, the point cloud data set is filtered to obtain the point cloud data corresponding to the filtered transmission tower.

[0118] In an optional embodiment provided by the present invention, the construction module 24 is specifically used to:

[0119] Determine a three-dimensional image based on the point cloud data and image data corresponding to the distribution network line;

[0120] A distribution network line simulation model is constructed by using the three-dimensional stereoscopic image and the three-dimensional stereoscopic image.

[0121] In an optional embodiment provided by the present invention, the detection module 25 is specifically used for:

[0122] Acquire the operation data of the distribution network line in real time;

[0123] The operation data is input into the distribution network line simulation model for simulation to obtain the detection result of the distribution network line.

[0124] In an optional embodiment provided by the present invention, if the detection result of the distribution network line is abnormal, abnormal alarm information is output.

[0125] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0126] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0127] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention.

Claims

1. A method for collecting real-time point cloud of distribution network lines by drone, characterized in that: The method comprises: S101, obtaining a digital elevation map in a target area, wherein the digital elevation map includes a height corresponding to each pixel point and a normalized vegetation index; S102, determining the position coordinates of each transmission tower in the distribution network line according to the digital elevation map; S103, determining a point cloud data collection line according to the position coordinates and geographical location relationship of each transmission tower; S104, controlling the drone to fly according to the point cloud data collection line to collect point cloud data and image data corresponding to the distribution network line; the distance between the drone and each transmission tower exceeds a preset distance during the flight; S105, constructing a distribution network line simulation model through the point cloud data and image data corresponding to the distribution network line and the attribute data of the distribution network line; S106, detecting whether the distribution network line has an operating abnormality according to the distribution network line simulation model; In S102, determining the position coordinates of each transmission tower in the distribution network line according to the digital elevation map includes: S1021, obtaining a transmission tower marking map corresponding to the digital elevation map; the transmission tower marking map includes a plurality of transmission tower marking points, each transmission tower marking point being a position coordinate corresponding to a pixel point with the highest brightness within a preset area in the tower position marking map; S1022, filtering the transmission pole tower marking points in the transmission pole tower marking map by using the height corresponding to each pixel point in the digital elevation map, the normalized vegetation index, and the transmission pole tower height; after filtering the transmission pole tower marking points in the transmission pole tower marking map by using the height corresponding to each pixel point in the digital elevation map, the normalized vegetation index, and the transmission pole tower height, filtering the marking points that do not belong to the transmission pole tower by using a preset linear fitting formula, the preset linear fitting formula is: ； in, is a constant coefficient, Represents the horizontal coordinate of the transmission tower marker point, Represents the fitted ordinate of the transmission tower marker point. The preset linear fitting formula is obtained by fitting a large amount of data. After the transmission tower marking points are obtained through filtering in step S1022, the position coordinates of each transmission tower marking point are obtained, and then the abscissa of each transmission tower marking point is input into the above linear fitting formula to obtain the fitted ordinate, and then the distance between the fitted ordinate and the actual ordinate is compared to see whether it is greater than the preset distance. If it is greater than the preset distance, it means that the position coordinate does not belong to the transmission tower marking point, that is, the transmission tower marking point needs to be filtered out; if it is less than or equal to the preset distance, there is no need to filter the transmission tower marking point; In step S103, determining the point cloud data collection line according to the position coordinates and geographical location relationship of each transmission tower includes: S1031, determining an initial acquisition line according to the position coordinates and geographical location relationship of each transmission tower; the initial acquisition line includes a plurality of acquisition points, each of which is used to collect point cloud data and image data of a transmission tower; S1032, determining the bypass collection lines corresponding to the respective collection points according to the tower heights of the respective transmission towers and the altitudes of the ground contact points; the determining the bypass collection lines corresponding to the respective collection points according to the tower heights of the respective transmission towers and the altitudes of the ground contact points includes: Calculate the height difference between the ground contact points of the previous transmission tower and the next transmission tower; If the height difference is greater than a preset value, the end position corresponding to the fly-around collection line of the previous transmission tower is obtained; If the corresponding end position of the fly-around collection line of the previous transmission tower is at the top of the transmission tower, the fly-around collection line of the next transmission tower starts from the bottom of the transmission tower and circles the transmission tower to the top of the transmission tower; The inclination angles of the two transmission towers are calculated based on the line connecting the ground contact points of the previous transmission tower and the next transmission tower. If the inclination angle is greater than the preset angle, the end position corresponding to the fly-around acquisition line of the previous transmission tower is obtained; if the end position corresponding to the fly-around acquisition line of the previous transmission tower is at the top of the transmission tower, the fly-around acquisition line of the next transmission tower starts from the bottom of the transmission tower and circles the transmission tower to the top of the transmission tower; S1033, sequentially connecting the initial acquisition route and the fly-by acquisition routes of each acquisition point according to the geographical location relationship to obtain the point cloud data acquisition route; In S104, the drone is controlled to fly according to the point cloud data acquisition line to collect point cloud data and image data corresponding to the distribution network line, including: Determine the safety radius of each transmission tower according to the actual size of the transmission tower; Control the drone to fly to each collection point according to the initial collection route; When the drone flies to the corresponding collection point, the drone is controlled to fly along the circling collection route to collect point cloud data and image data of the corresponding transmission tower; Wherein, the distance between the bypass collection line and the corresponding transmission tower is greater than the safety radius; After the drone is controlled to fly along the circling collection route when the drone flies to the corresponding collection point to collect point cloud data and image data of the corresponding transmission tower, the method further includes: Merging the point cloud data and the image data of the transmission tower to obtain a point cloud data set and an image data set; Based on the image recognition technology, repeated image data in the image data set are filtered to obtain the point cloud data corresponding to the filtered transmission tower, and based on data clustering, the point cloud data set is filtered to obtain the point cloud data corresponding to the filtered transmission tower.

2. The method according to claim 1, characterized in that The method of constructing a distribution network line simulation model by using the point cloud data and image data corresponding to the distribution network line and the attribute data of the distribution network line comprises: Determine a three-dimensional image based on the point cloud data and image data corresponding to the distribution network line; A distribution network line simulation model is constructed by using the three-dimensional stereoscopic image and the three-dimensional stereoscopic image.

3. The method according to claim 2, characterized in that The detecting whether the distribution network line has an operation abnormality according to the distribution network line simulation model includes: Acquire the operation data of the distribution network line in real time; The operation data is input into the distribution network line simulation model for simulation to obtain the detection result of the distribution network line.

4. The method according to claim 3, characterized in that The method further comprises: If the detection result of the distribution network line is abnormal, an abnormal alarm message is output.

5. A distribution network line drone real-time point cloud acquisition device according to any one of claims 1 to 4, characterized in that: The device comprises: An acquisition module is used to acquire a digital elevation map in the target area, wherein the digital elevation map includes a height corresponding to each pixel point and a normalized vegetation index; A determination module, used to determine the position coordinates of each transmission tower in the distribution network line according to the digital elevation map; The determination module is further used to determine the point cloud data collection line according to the position coordinates and geographical location relationship of each transmission tower; A collection module is used to control the flight of the drone according to the point cloud data collection line to collect point cloud data and image data corresponding to the distribution network line; when the distance between the drone and each transmission tower exceeds a preset distance during flight; A construction module, used to construct a distribution network line simulation model through point cloud data and image data corresponding to the distribution network line and attribute data of the distribution network line; The detection module is used to detect whether the distribution network line has an operating abnormality according to the distribution network line simulation model.

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