Adaptive scene substation regional unmanned aerial vehicle inspection control device and method

Abstract

The application discloses a substation regional unmanned aerial vehicle (UAV) inspection control device and method, and belongs to the technical field of substation intelligent inspection. The device comprises an inspection parameter configuration module, which receives an inspection task and an inspection cycle set by an operation and maintenance personnel; a substation three-dimensional modeling control module, which controls the UAV to take off to perform substation three-dimensional modeling and coordinates the inspection points in the set region of the substation; an inspection control module, which controls the UAV to start the inspection according to the preset inspection cycle and the inspection task, and controls the deviation between the center of the inspection equipment of each inspection point and the image center collected by the UAV camera to be less than a set threshold range; and an inspection data analysis module, which analyzes the images collected by the UAV at each inspection point, judges whether there is abnormal data, and uploads the abnormal data. The application realizes the intelligent inspection of the substation by cooperation of the inspection control device and the UAV, can supplement the inspection points, automatically plans the flight path, and adjusts the center of the shooting object.

Description

Technical Field

[0001] This invention belongs to the field of online intelligent inspection technology for substations using unmanned aerial vehicles (UAVs), specifically relating to an adaptive scenario-based regional UAV inspection control device and method for substations. Background Technology

[0002] With the development of intelligent inspection technology, substation inspections are shifting from manual to intelligent methods. Current intelligent inspection methods primarily utilize tracked robots, wheeled robots, and camera-based image acquisition. However, due to the large number of inspection points in substations, some of which are hidden, existing methods using tracked or wheeled robots frequently experience inspection point misalignment, resulting in a relatively high failure rate. Furthermore, these methods are significantly affected by road conditions. Installing cameras requires trenching and wiring, necessitates power outages during construction, and has blind spots in some outdoor installations that cameras cannot cover. This makes it difficult to detect potential hazards and defects at higher locations, such as equipment tops and insulators.

[0003] Although substation inspections are beginning to shift towards intelligent inspections, they have not yet completely replaced manual inspections. A combination of manual and intelligent inspections is still required. Furthermore, the current situation of substations having a large number of maintenance personnel but a small number of operation and maintenance staff results in a heavy workload for each maintenance worker.

[0004] In summary, for substations with outdoor open equipment, there are many blind spots in the power grid inspection. Installing cameras cannot cover all points and is costly. Using wheeled robots is greatly affected by the environment and has a relatively high failure rate.

[0005] This is a shortcoming of the existing technology. Therefore, it is very necessary to provide an adaptive scenario-based substation regional drone inspection control device and method to address the above-mentioned defects in the existing technology. Summary of the Invention

[0006] In view of the shortcomings of existing technologies, such as the large number of outdoor open equipment in substations, the large number of blind spots in the inspection, the inability of cameras to cover all points, high cost, and the high failure rate of wheeled robots due to environmental influences, this invention provides an adaptive scenario-based substation regional drone inspection control device and method to solve the above technical problems.

[0007] In a first aspect, the present invention provides an adaptive scenario-based substation regional unmanned aerial vehicle (UAV) inspection control device, comprising:

[0008] The inspection parameter configuration module is used to receive the inspection tasks and inspection cycles set by the operation and maintenance personnel.

[0009] The substation 3D modeling control module is used to control the take-off of the drone to perform 3D modeling of the substation and to convert the coordinates of the inspection points within the designated area of ​​the substation.

[0010] The inspection control module is used to control the drone to plan the route to the substation and start the inspection according to the preset inspection cycle and inspection task. During the inspection, it controls the deviation between the center of the inspection equipment at each inspection point and the center of the image collected by the drone camera to be less than the set threshold range.

[0011] The inspection data analysis module analyzes images collected by the drone at each inspection point to determine if there is any abnormal data and uploads the abnormal data to the monitoring backend. The drone inspection control device connects wirelessly to the drone, is portable and mobile, and has vehicle-mounted capabilities. It can cover surrounding substations in a radial pattern from a specific substation, automatically constructing an inspection area, improving the effectiveness of off-site equipment inspection, and reducing the inspection workload of maintenance personnel.

[0012] Furthermore, the inspection parameter configuration module includes:

[0013] The patrol mission configuration unit is used to receive patrol missions configured for the drone by patrol personnel. Patrol missions include routine patrols, special patrols, and night patrols.

[0014] The patrol cycle configuration unit is used to receive the patrol cycle configured by the patrol personnel for the routine patrol of the drone;

[0015] The patrol point configuration unit is used to receive the patrol points configured for each patrol task.

[0016] The substation 3D modeling control module includes:

[0017] The substation 3D modeling unit is used to control the take-off of drones and build a 3D reality model of the substation through a two-layer operation mode.

[0018] The inspection point coordinate construction unit is used to construct the coordinates of all inspection points within a spherical area of ​​the substation, using the substation gate as the three-dimensional coordinate origin and a set radius as the center. The UAV inspection control device can supplement existing substation monitoring with additional monitoring points, enabling timely and effective monitoring of the surrounding environment, especially floating objects and fire hazards, thus improving the construction of online intelligent substation inspection systems.

[0019] Furthermore, the inspection control module includes:

[0020] The patrol mission initiation unit is used to control the drone to initiate routine patrol missions according to the preset patrol cycle, or to receive instructions from maintenance personnel to initiate special patrol missions or night patrol missions.

[0021] The patrol point parsing unit is used to parse the configured patrol points from the patrol task;

[0022] The patrol path planning unit is used to plan the patrol path according to the principle of from near to far based on the coordinates of each patrol point in the quadrant of the world coordinate system, so as to minimize the travel trajectory of the UAV.

[0023] The inspection equipment center adjustment unit is used to control the drone to arrive at each inspection point in sequence according to the inspection trajectory, and adjust the deviation between the center of the inspection equipment and the center of the camera image at each inspection point until the deviation meets the requirements, and then save the camera image.

[0024] Secondly, the present invention provides an adaptive scenario-based regional UAV inspection control method for substations, comprising the following steps:

[0025] S1. Pre-set the inspection tasks and cycles for the drones using the drone inspection control device;

[0026] S2. The drone inspection control device controls the drone to take off and perform 3D modeling of the substation, and converts the coordinates of the inspection points within the designated area of ​​the substation.

[0027] S 3. The drone inspection control device controls the drone to plan the inspection route of the substation according to the preset inspection cycle and inspection task and start the inspection. During the inspection, the deviation between the center of the inspection equipment at each inspection point and the center of the image collected by the drone camera is less than the set threshold range.

[0028] S4. The UAV inspection and control device analyzes the images collected by the UAV at each inspection point, determines whether there is any abnormal data, and uploads the abnormal data to the monitoring backend.

[0029] Furthermore, the specific steps of step S1 are as follows:

[0030] S11. The drone inspection missions are pre-configured via the drone inspection control device. The inspection missions include routine inspections, special inspections, and nighttime inspections.

[0031] S12. Pre-configure the inspection cycle of the drone routine inspection via the drone inspection control device;

[0032] S13. Pre-configure inspection points for each inspection task using the drone inspection control device.

[0033] Furthermore, the specific steps of step S2 are as follows:

[0034] S21. The drone inspection control device controls the drone to take off and builds a three-dimensional real-scene model of the substation through a two-layer operation mode.

[0035] S22. The UAV inspection control device uses the substation gate as the three-dimensional coordinate origin, and uses the three-dimensional coordinate origin as the center and a set length as the radius of the substation area to regionalize the substation and construct the coordinates of all inspection points within the spherical area of ​​the substation.

[0036] Furthermore, the specific steps of step S21 are as follows:

[0037] S211. The drone inspection control device controls the drone to fly automatically and collect data on the overall space of the substation to form the overall framework of the substation.

[0038] S212. The drone inspection control device controls the drone to take additional photos of important equipment and concealed areas of the substation and supplement the model.

[0039] S213. The drone inspection control device controls the drone to take multi-angle photos of various equipment in the substation according to the set number of angles;

[0040] S214. The drone inspection control device takes photos of the overall framework of the substation, important equipment, and hidden areas, as well as multi-angle photos of each piece of equipment, to form a three-dimensional real-scene model of the substation.

[0041] Furthermore, the specific steps of step S22 are as follows:

[0042] S221. The transformation relationship between the world coordinate system, the UAV body coordinate system, the UAV camera coordinate system, the image coordinate system of the UAV-acquired images, and the pixel coordinate system of the UAV-acquired images is obtained by the UAV inspection and control device.

[0043] S222. The UAV inspection control device transforms the pixel coordinates of the images of each inspection point captured by the UAV into the image coordinates of each inspection point image according to the relationship between the pixel coordinate system and the image coordinate system.

[0044] S223. The UAV inspection control device transforms the image coordinates of each inspection point image captured by the UAV into the camera coordinates of each inspection point image according to the relationship between the image coordinate system and the UAV camera coordinate system;

[0045] S224. The UAV inspection control device transforms the camera coordinates of the images of each inspection point captured by the UAV into the body coordinates of the images of each inspection point according to the relationship between the UAV camera coordinate system and the UAV body coordinate system.

[0046] S225. The UAV inspection control device transforms the body coordinates of the images of each inspection point captured by the UAV into the world coordinates of each inspection point image according to the relationship between the UAV body coordinate system and the world coordinate system.

[0047] Furthermore, the specific steps of step S3 are as follows:

[0048] S 31. The drone inspection control device controls the drone to start routine inspection tasks according to the preset inspection cycle, or receives instructions from maintenance personnel to start special inspection tasks or night inspection tasks.

[0049] S 32. The UAV inspection control device parses the configured inspection points from the inspection mission;

[0050] S 33. The UAV inspection control device plans the inspection path according to the quadrant of the world coordinate system based on the coordinates of each inspection point, following the principle of from near to far, so as to minimize the UAV's travel trajectory.

[0051] S 34. The drone inspection control device controls the drone to arrive at each inspection point in sequence according to the inspection trajectory, and adjusts the deviation between the center of the inspection equipment and the center of the camera image at each inspection point until the deviation meets the requirements, and then saves the camera image.

[0052] Furthermore, step S34 is as follows:

[0053] S 341. The UAV inspection control device controls the UAV to arrive at the inspection points in the pixel coordinate system in sequence according to the inspection trajectory, and collects the original images of each inspection device;

[0054] S 342. The UAV inspection control device performs grayscale processing on the original images of each inspection equipment collected, filters and reduces noise, and then uses edge detection to extract the outline of the inspection equipment.

[0055] S 343. The UAV inspection control device performs an asymptotic probabilistic Hough transformation on the outline of the inspected equipment to obtain a cluster of straight lines, and obtains the slope and intercept of each straight line in the world coordinate system.

[0056] S 344. The UAV inspection control device filters the straight line clusters based on the slope of any three center lines in different planes passing through the center of the inspection equipment and the angle between the three center lines and the horizontal axis of the pixel coordinate system. The filtered straight line clusters are classified into two categories: straight lines above and below the equipment at the inspection point. The center line of the inspection point is obtained by taking the center of the upper and lower straight lines.

[0057] S 345. The UAV inspection control device determines the deviation between the center of the inspection equipment and the center of the image captured by the camera based on the slope of the centerline of the inspection equipment in the image coordinate system and the intercept of the centerline of the inspection equipment with the two coordinate axes of the image coordinate system.

[0058] When the deviation exceeds the set threshold, proceed to step S 346;

[0059] When the deviation is less than or equal to the set threshold, proceed to step S 347;

[0060] S 346. The UAV inspection control device determines that the center of the inspected equipment is deviated from the center of the acquired image, and the information acquired by the inspected equipment cannot meet the requirements. The UAV position is adjusted, the image acquisition of the inspected equipment is carried out again, and the process returns to step S342.

[0061] S 347. The UAV inspection control device determines that the center of the inspected equipment is close to the center of the acquired image, and the acquired equipment information and status recognition rate of the inspected points meet the requirements.

[0062] The beneficial effects of this invention are as follows:

[0063] The present invention provides an adaptive scenario substation regional drone inspection control device and method. The drone inspection control device receives additional inspection points from inspection personnel and can automatically plan inspection routes to realize intelligent inspection of substations. It can radiate outwards from the substation to cover the surrounding area, automatically construct the inspection area, improve the inspection effect of external equipment of the substation, and reduce the inspection pressure of operation and maintenance personnel.

[0064] This invention can accurately locate the subject being photographed, ensuring it remains centered in the image and guaranteeing the accuracy of the data acquisition. This provides reliable support for intelligent recognition algorithms and avoids the point-of-view shift that often occurs after long-term camera patrols. Furthermore, this invention can be configured for regional patrols based on specific requirements. Multiple substations can be patrolled simultaneously using only a drone and a patrol control device, saving on intelligent patrol costs and alleviating patrol pressure.

[0065] Furthermore, the design principle of this invention is reliable, the structure is simple, and it has a very wide range of application prospects.

[0066] Therefore, it is evident that the present invention has outstanding substantive features and significant progress compared with the prior art, and the beneficial effects of its implementation are also obvious. Attached Figure Description

[0067] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0068] Figure 1 This is a schematic diagram of the adaptive scenario substation regional drone inspection control device of the present invention.

[0069] Figure 2 This is a flowchart of Embodiment 3 of the adaptive scenario substation regional drone inspection control method of the present invention.

[0070] Figure 3This is a flowchart of Embodiment 4 of the adaptive scenario substation regional UAV inspection control method of the present invention.

[0071] Figure 4 This is a schematic diagram illustrating the process of performing three-dimensional modeling of a substation and converting the coordinates of inspection points within a designated area of ​​the substation according to the present invention.

[0072] Figure 5 This is a schematic diagram illustrating the process of adjusting the deviation between the center of the inspection equipment and the center of the image acquired by the camera according to the present invention.

[0073] Figure 6 This is a schematic diagram showing the relationship between the five coordinate systems in Embodiment 4 of the present invention.

[0074] Figure 7 This is a schematic diagram of the center line of the inspection object in Embodiment 4 of the present invention. Detailed Implementation

[0075] To enable those skilled in the art to better understand the technical solutions of this invention, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this invention.

[0076] Example 1:

[0077] For substations with numerous outdoor open-type equipment requiring power grid inspection, resulting in many blind spots, installing cameras cannot cover all locations and is costly. Using wheeled robots is also problematic due to their susceptibility to environmental influences and relatively high failure rate. For example... Figure 1 As shown, the present invention provides an adaptive scenario substation regional drone inspection control device, comprising:

[0078] The inspection parameter configuration module is used to receive the inspection tasks and inspection cycles set by the operation and maintenance personnel.

[0079] The substation 3D modeling control module is used to control the take-off of the drone to perform 3D modeling of the substation and to convert the coordinates of the inspection points within the designated area of ​​the substation.

[0080] The inspection control module is used to control the drone to plan the route to the substation and start the inspection according to the preset inspection cycle and inspection task. During the inspection, it controls the deviation between the center of the inspection equipment at each inspection point and the center of the image collected by the drone camera to be less than the set threshold range.

[0081] The inspection data analysis module is used to analyze images collected by the drone at each inspection point, determine whether there is any abnormal data, and upload the abnormal data to the monitoring backend.

[0082] By upgrading and modifying a traditional drone controller and combining it with the functions of a drone nest, this application presents a portable drone inspection and control device for substations. This device can set inspection tasks, establish inspection cycles, and upload abnormal data to the monitoring backend via wireless network.

[0083] Example 2:

[0084] For substations with numerous outdoor open-type equipment requiring power grid inspection, resulting in many blind spots, installing cameras cannot cover all locations and is costly. Using wheeled robots is also problematic due to their susceptibility to environmental influences and relatively high failure rate. For example... Figure 1 As shown, the present invention provides an adaptive scenario substation regional drone inspection control device, comprising:

[0085] The inspection parameter configuration module is used to receive inspection tasks and inspection cycles set by maintenance personnel; the inspection parameter configuration module includes:

[0086] The patrol mission configuration unit is used to receive patrol missions configured for the drone by patrol personnel. Patrol missions include routine patrols, special patrols, and night patrols.

[0087] The patrol cycle configuration unit is used to receive the patrol cycle configured by the patrol personnel for the routine patrol of the drone;

[0088] The patrol point configuration unit is used to receive the patrol points configured for each patrol task.

[0089] The substation 3D modeling control module is used to control the takeoff of a drone to perform 3D modeling of the substation, and to convert the coordinates of inspection points within a designated area of ​​the substation. The substation 3D modeling control module includes:

[0090] The substation 3D modeling unit is used to control the take-off of drones and build a 3D reality model of the substation through a two-layer operation mode.

[0091] The inspection point coordinate construction unit is used to construct the coordinates of all inspection points within the spherical area of ​​the substation, with the substation gate as the three-dimensional coordinate origin and the substation area radius as the three-dimensional coordinate origin.

[0092] The inspection control module is used to control the drone to plan its route and initiate the inspection of the substation according to the preset inspection cycle and tasks. During the inspection, it controls the deviation between the center of the inspection equipment at each inspection point and the center of the image captured by the drone's camera to be less than a set threshold range. The inspection control module includes:

[0093] The patrol mission initiation unit is used to control the drone to initiate routine patrol missions according to the preset patrol cycle, or to receive instructions from maintenance personnel to initiate special patrol missions or night patrol missions.

[0094] The patrol point parsing unit is used to parse the configured patrol points from the patrol task;

[0095] The patrol path planning unit is used to plan the patrol path according to the principle of from near to far based on the coordinates of each patrol point in the quadrant of the world coordinate system, so as to minimize the travel trajectory of the UAV.

[0096] The inspection equipment center adjustment unit is used to control the drone to arrive at each inspection point in sequence according to the inspection trajectory, and adjust the deviation between the center of the inspection equipment and the center of the camera image at each inspection point until the deviation meets the requirements, and then save the camera image.

[0097] The inspection data analysis module is used to analyze images collected by the drone at each inspection point, determine whether there is any abnormal data, and upload the abnormal data to the monitoring backend.

[0098] Example 3:

[0099] For substations with numerous outdoor open-type equipment requiring power grid inspection, resulting in many blind spots, installing cameras cannot cover all locations and is costly. Using wheeled robots is also problematic due to their susceptibility to environmental influences and relatively high failure rate. For example... Figure 2 As shown, this invention provides an adaptive scenario-based regional UAV inspection control method for substations, comprising the following steps:

[0100] S1. Pre-set the inspection tasks and cycles for the drones using the drone inspection control device;

[0101] S2. The drone inspection control device controls the drone to take off and perform 3D modeling of the substation, and converts the coordinates of the inspection points within the designated area of ​​the substation.

[0102] S 3. The drone inspection control device controls the drone to plan the inspection route of the substation according to the preset inspection cycle and inspection task and start the inspection. During the inspection, the deviation between the center of the inspection equipment at each inspection point and the center of the image collected by the drone camera is less than the set threshold range.

[0103] S4. The UAV inspection and control device analyzes the images collected by the UAV at each inspection point, determines whether there is any abnormal data, and uploads the abnormal data to the monitoring backend.

[0104] Example 4:

[0105] For substations with numerous outdoor open-type equipment requiring power grid inspection, resulting in many blind spots, installing cameras cannot cover all locations and is costly. Using wheeled robots is also problematic due to their susceptibility to environmental influences and relatively high failure rate. For example... Figure 3 As shown, this invention provides an adaptive scenario-based regional UAV inspection control method for substations, comprising the following steps:

[0106] S1. Pre-set the inspection tasks and cycles for the drone using the drone inspection control device; the specific steps of step S1 are as follows:

[0107] S11. The drone inspection missions are pre-configured via the drone inspection control device. The inspection missions include routine inspections, special inspections, and nighttime inspections.

[0108] S12. Pre-configure the inspection cycle of the drone routine inspection via the drone inspection control device;

[0109] S13. Pre-configure inspection points for each inspection task using the drone inspection control device;

[0110] S2. The UAV inspection control device controls the UAV to take off and perform 3D modeling of the substation, and converts the coordinates of the inspection points within the designated area of ​​the substation; the specific steps of step S2 are as follows:

[0111] S21. The drone inspection control device controls the drone to take off and builds a 3D reality model of the substation through a two-layer operation mode; such as... Figure 4 As shown, the specific steps of step S21 are as follows:

[0112] S211. The drone inspection control device controls the drone to fly automatically and collect data on the overall space of the substation to form the overall framework of the substation.

[0113] S212. The drone inspection control device controls the drone to take additional photos of important equipment and concealed areas of the substation to supplement the model; for example, taking additional photos of lightning rods, portal frames, and roof leaks to supplement the model.

[0114] S213. The drone inspection control device controls the drone to take multi-angle photos of each piece of equipment in the substation according to a set number of angles; multi-angle photos ensure the integrity of the model;

[0115] S214. The drone inspection control device takes photos of the overall framework of the substation, important equipment, and hidden areas, as well as multi-angle photos of each piece of equipment, to form a three-dimensional real-scene model of the substation.

[0116] S22. The UAV inspection control device uses the substation gate as the three-dimensional coordinate origin, and uses the three-dimensional coordinate origin as the center, with a set length, such as 5 kilometers, as the radius of the substation area to regionalize the substation, constructing the coordinates of all inspection points within the substation's spherical area; for example... Figure 4 As shown, the specific steps of step S22 are as follows:

[0117] S221. The transformation relationship between the world coordinate system, the UAV body coordinate system, the UAV camera coordinate system, the image coordinate system of the UAV-acquired images, and the pixel coordinate system of the UAV-acquired images is obtained by the UAV inspection and control device.

[0118] S222. The UAV inspection control device transforms the pixel coordinates of the images of each inspection point captured by the UAV into the image coordinates of each inspection point image according to the relationship between the pixel coordinate system and the image coordinate system.

[0119] S223. The UAV inspection control device transforms the image coordinates of each inspection point image captured by the UAV into the camera coordinates of each inspection point image according to the relationship between the image coordinate system and the UAV camera coordinate system;

[0120] S224. The UAV inspection control device transforms the camera coordinates of the images of each inspection point captured by the UAV into the body coordinates of the images of each inspection point according to the relationship between the UAV camera coordinate system and the UAV body coordinate system.

[0121] S225. The UAV inspection control device transforms the body coordinates of the images of each inspection point captured by the UAV into the world coordinates of each inspection point image according to the relationship between the UAV body coordinate system and the world coordinate system.

[0122] The coordinates of the patrol points are calculated based on the captured images, involving five coordinate systems: world, aircraft, camera, image, and pixel. The relationship between these five coordinate systems is as follows: Figure 6 As shown;

[0123] Since the pixel coordinates are known, the coordinates of the inspection points are represented by world coordinates. Therefore, the relationship between world coordinates and pixel coordinates is as follows:

[0124]

[0125] In the formula: dx and dy are the physical dimensions per unit pixel, u0 and v0 are the center coordinates of the plane in pixel coordinates, u and v are pixel coordinates, x and y are image coordinates, f is the focal length of the drone camera, and Xw, Yw, and Zw are world coordinates. This represents the rotation matrix and translation amount from the body coordinate system to the camera coordinate system, and is related to the camera's mounting position on the UAV. The rotation matrix and translation vector from the world coordinate system to the body coordinate system are determined by the UAV's position and real-time quaternions;

[0126] S3. The drone inspection control device controls the drone to plan the inspection route for the substation according to the preset inspection cycle and inspection task, and starts the inspection. During the inspection, the deviation between the center of the inspection equipment at each inspection point and the center of the image captured by the drone camera is controlled to be less than a set threshold range; the specific steps of step S3 are as follows:

[0127] S 31. The drone inspection control device controls the drone to start routine inspection tasks according to the preset inspection cycle, or receives instructions from maintenance personnel to start special inspection tasks or night inspection tasks.

[0128] S 32. The UAV inspection control device parses the configured inspection points from the inspection mission;

[0129] S 33. The UAV inspection control device plans the inspection path according to the quadrant of the world coordinate system based on the coordinates of each inspection point, following the principle of from near to far, so as to minimize the UAV's travel trajectory.

[0130] S 34. The drone inspection control device controls the drone to sequentially reach each inspection point according to the inspection trajectory, and adjusts the deviation between the center of the inspection equipment and the center of the camera image at each inspection point until the deviation meets the requirements, then saves the camera image; such as Figure 5 As shown, the specific steps of step S34 are as follows:

[0131] S 341. The UAV inspection control device controls the UAV to arrive at the inspection points in the pixel coordinate system in sequence according to the inspection trajectory, and collects the original images of each inspection device;

[0132] S 342. The UAV inspection control device performs grayscale processing on the original images of each inspection equipment collected, filters and reduces noise, and then uses the Canny edge detection method to extract the outline of the inspection equipment.

[0133] S 343. The UAV inspection control device performs an asymptotic probabilistic Hough transformation on the outline of the inspected equipment to obtain a series of straight lines as a family of straight lines, and obtains the slope and intercept of each straight line in the world coordinate system.

[0134] S 344. The UAV inspection control device filters the straight line clusters based on the slope of any three center lines in different planes passing through the center of the inspection equipment and the angle between the three center lines and the horizontal axis of the pixel coordinate system. The filtered straight line clusters are classified using the k-means clustering algorithm, and divided into two categories of straight lines above and below the equipment at the inspection point. The center line of the inspection point is obtained by taking the center of the upper and lower straight lines.

[0135] S 345. The UAV inspection control device determines the deviation between the center of the inspection equipment and the center of the image captured by the camera based on the slope of the centerline of the inspection equipment in the image coordinate system and the intercept of the centerline of the inspection equipment with the two coordinate axes of the image coordinate system.

[0136] When the deviation exceeds the set threshold, proceed to step S 346;

[0137] When the deviation is less than or equal to the set threshold, proceed to step S 347;

[0138] S 346. The UAV inspection control device determines that the center of the inspected equipment is deviated from the center of the acquired image, and the information acquired by the inspected equipment cannot meet the requirements. The UAV position is adjusted, the image acquisition of the inspected equipment is carried out again, and the process returns to step S342.

[0139] S 347. The UAV inspection control device determines that the center of the inspected equipment is close to the center of the acquired image, and the acquired equipment information and status recognition rate of the inspected points meet the requirements.

[0140] Transform the centerline of the inspected object from the pixel coordinate system to the image coordinate system and calculate the slope k of the centerline. c and the intercepts b of the horizontal and vertical axes x b y ,like Figure 7 As shown, this allows for the evaluation of the extraction effect;

[0141] b x b y The larger the absolute value, the more the centerline of the inspected object deviates from the image center, resulting in less equipment information being collected and a greater deviation; b x b y The smaller the absolute value, the closer the center line of the inspected object is to the center of the image, the more equipment information is collected, and the higher the status recognition rate.

[0142] S4. The UAV inspection and control device analyzes the images collected by the UAV at each inspection point, determines whether there is any abnormal data, and uploads the abnormal data to the monitoring backend.

[0143] Although the present invention has been described in detail with reference to the accompanying drawings and preferred embodiments, the invention is not limited thereto. Various equivalent modifications or substitutions can be made to the embodiments of the invention by those skilled in the art without departing from the spirit and essence of the invention, and such modifications or substitutions should all be within the scope of the invention. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the invention should also be covered within the protection scope of the invention. Therefore, the protection scope of the invention should be determined by the scope of the claims.

Claims

1. A method for adaptive scenario-based regional UAV inspection control of substations, characterized in that, Includes the following steps: S1. Pre-set the inspection tasks and cycles for the drones using the drone inspection control device; S2. The drone inspection control device controls the drone to take off and perform 3D modeling of the substation, and converts the coordinates of the inspection points within the designated area of ​​the substation. S3. The drone inspection control device controls the drone to plan the inspection route of the substation according to the preset inspection cycle and inspection task and start the inspection. During the inspection, the deviation between the center of the inspection equipment at each inspection point and the center of the image collected by the drone camera is less than the set threshold range. The specific steps of step S3 are as follows: S31. The drone inspection control device controls the drone to start routine inspection tasks according to the preset inspection cycle, or receives instructions from maintenance personnel to start special inspection tasks or night inspection tasks. S32. The UAV inspection control device analyzes the configured inspection points from the inspection mission; S33. The UAV inspection control device plans the inspection path according to the coordinates of each inspection point in the quadrant of the world coordinate system, following the principle of from near to far, so as to minimize the UAV's travel trajectory. S34. The drone inspection control device controls the drone to arrive at each inspection point in sequence according to the inspection trajectory, and adjusts the deviation between the center of the inspection equipment and the center of the camera image at each inspection point until the deviation meets the requirements, and saves the camera image. The specific steps of step S34 are as follows: S341. The UAV inspection control device controls the UAV to arrive at the inspection points in the pixel coordinate system in sequence according to the inspection trajectory, and collects the original images of each inspection device. S342. The UAV inspection control device performs grayscale processing on the original images of each inspection equipment collected, filters and reduces noise, and then uses edge detection to extract the outline of the inspection equipment. S343. The UAV inspection control device performs an asymptotic probabilistic Hough transformation on the outline of the inspected equipment to obtain a cluster of straight lines, and obtains the slope and intercept of each straight line in the world coordinate system. S344. The UAV inspection control device filters the straight line clusters based on the slope of any three center lines in different planes passing through the center of the inspected equipment and the angle between the three center lines and the horizontal axis of the pixel coordinate system. The filtered straight line clusters are classified into two categories: straight lines above and below the equipment at the inspection point. The center line of the inspection point is obtained by taking the center of the upper and lower straight lines. S345. The UAV inspection control device determines the deviation between the center of the inspection equipment and the center of the image captured by the camera based on the slope of the centerline of the inspection equipment in the image coordinate system and the intercept of the centerline of the inspection equipment with the two coordinate axes of the image coordinate system. S4. The UAV inspection and control device analyzes the images collected by the UAV at each inspection point, determines whether there is any abnormal data, and uploads the abnormal data to the monitoring backend.

2. The adaptive scenario-based substation regional UAV inspection control method as described in claim 1, characterized in that, The specific steps of step S1 are as follows: S11. The drone inspection missions are pre-configured via the drone inspection control device. The inspection missions include routine inspections, special inspections, and nighttime inspections. S12. Pre-configure the inspection cycle of the drone routine inspection via the drone inspection control device; S13. Pre-configure inspection points for each inspection task using the drone inspection control device.

3. The adaptive scenario-based substation regional UAV inspection control method as described in claim 1, characterized in that, The specific steps of step S2 are as follows: S21. The drone inspection control device controls the drone to take off and builds a three-dimensional real-scene model of the substation through a two-layer operation mode. S22. The UAV inspection control device uses the substation gate as the three-dimensional coordinate origin, and uses the three-dimensional coordinate origin as the center and a set length as the radius of the substation area to regionalize the substation, constructing the coordinates of all inspection points within the spherical area of ​​the substation.

4. The adaptive scenario-based substation regional UAV inspection control method as described in claim 3, characterized in that, The specific steps of step S21 are as follows: S211. The drone inspection control device controls the drone to fly automatically and collect data on the overall space of the substation to form the overall framework of the substation. S212. The drone inspection control device controls the drone to take additional photos of important equipment and concealed areas of the substation and supplement the model. S213. The drone inspection control device controls the drone to take multi-angle photos of various equipment in the substation according to the set number of angles; S214. The drone inspection control device takes photos of the overall framework of the substation, important equipment, and hidden areas, as well as multi-angle photos of each piece of equipment, to form a three-dimensional real-scene model of the substation.

5. The adaptive scenario-based substation regional UAV inspection control method as described in claim 3, characterized in that, The specific steps of step S22 are as follows: S221. The transformation relationship between the world coordinate system, the UAV body coordinate system, the UAV camera coordinate system, the image coordinate system of the UAV-acquired images, and the pixel coordinate system of the UAV-acquired images is obtained by the UAV inspection and control device. S222. The UAV inspection control device transforms the pixel coordinates of the images of each inspection point captured by the UAV into the image coordinates of each inspection point image according to the relationship between the pixel coordinate system and the image coordinate system. S223. The UAV inspection control device transforms the image coordinates of each inspection point image captured by the UAV into the camera coordinates of each inspection point image according to the relationship between the image coordinate system and the UAV camera coordinate system; S224. The UAV inspection control device transforms the camera coordinates of the images of each inspection point captured by the UAV into the body coordinates of the images of each inspection point according to the relationship between the UAV camera coordinate system and the UAV body coordinate system. S225. The UAV inspection control device transforms the body coordinates of the images of each inspection point captured by the UAV into the world coordinates of each inspection point image according to the relationship between the UAV body coordinate system and the world coordinate system.

6. The adaptive scenario-based substation regional UAV inspection control method as described in claim 1, characterized in that, When the deviation exceeds the set threshold, proceed to step S346; When the deviation is less than or equal to the set threshold, proceed to step S347; S346. The UAV inspection control device determines that the center of the inspected equipment is deviating from the center of the acquired image, and the information acquired by the inspected equipment cannot meet the requirements. The UAV position is adjusted, and the image acquisition of the inspected equipment is carried out again. The process returns to step S342. S347. The UAV inspection control device determines that the center of the inspected equipment is close to the center of the acquired image, and the acquired equipment information and status recognition rate of the inspected points meet the requirements.

7. An adaptive scenario-based substation regional UAV inspection control device, executing the method described in any one of claims 1-6, characterized in that, include: The inspection parameter configuration module is used to receive the inspection tasks and inspection cycles set by the operation and maintenance personnel. The substation 3D modeling control module is used to control the take-off of the drone to perform 3D modeling of the substation and to convert the coordinates of the inspection points within the designated area of ​​the substation. The inspection control module is used to control the drone to plan the route to the substation and start the inspection according to the preset inspection cycle and inspection task. During the inspection, it controls the deviation between the center of the inspection equipment at each inspection point and the center of the image collected by the drone camera to be less than the set threshold range. The inspection data analysis module is used to analyze images collected by the drone at each inspection point, determine whether there is any abnormal data, and upload the abnormal data to the monitoring backend.

8. The adaptive scenario substation regional UAV inspection control device as described in claim 7, characterized in that, The inspection parameter configuration module includes: The patrol mission configuration unit is used to receive patrol missions configured for the drone by patrol personnel. Patrol missions include routine patrols, special patrols, and night patrols. The patrol cycle configuration unit is used to receive the patrol cycle configured by the patrol personnel for the routine patrol of the drone; The patrol point configuration unit is used to receive the patrol points configured for each patrol task. The substation 3D modeling control module includes: The substation 3D modeling unit is used to control the take-off of drones and build a 3D real-scene model of the substation through a two-layer operation mode. The inspection point coordinate construction unit is used to construct the coordinates of all inspection points within the spherical area of ​​the substation, with the substation gate as the three-dimensional coordinate origin, the substation area as the center of the three-dimensional coordinate origin, and a set length as the radius of the substation area.

9. The adaptive scenario substation regional UAV inspection control device as described in claim 7, characterized in that, The inspection control module includes: The patrol mission initiation unit is used to control the drone to initiate routine patrol missions according to the preset patrol cycle, or to receive instructions from maintenance personnel to initiate special patrol missions or night patrol missions. The patrol point parsing unit is used to parse the configured patrol points from the patrol task; The patrol path planning unit is used to plan the patrol path according to the principle of from near to far based on the coordinates of each patrol point in the quadrant of the world coordinate system, so as to minimize the travel trajectory of the UAV. The inspection equipment center adjustment unit is used to control the drone to arrive at each inspection point in sequence according to the inspection trajectory, and adjust the deviation between the center of the inspection equipment and the center of the camera image at each inspection point until the deviation meets the requirements, and then save the camera image.

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