An unmanned aerial vehicle automatic cruise detection method for line fault maintenance

Abstract

The application discloses a kind of unmanned aerial vehicle automatic cruise detection methods for line fault maintenance, comprising: opening unmanned aerial vehicle detection system, confirm the signal of unmanned aerial vehicle to be used and the signal of system can be normally connected, by the signal of system and unmanned aerial vehicle connection, with the aid of system, preset direction is introduced into the system of unmanned aerial vehicle;Start line detection unmanned aerial vehicle, check whether the flight mode in unmanned aerial vehicle system is opened.The process of line fault detection, unmanned aerial vehicle is positioned according to the information of fault point using three-point or four-point positioning method, and is positioned and identified, is framed and selected, corresponding angle positioning line is calculated using angle offset, the data graph of fault point is accurately transmitted, three-point or four-point angle positioning is used to ensure that magnification shooting can guarantee target point unchanged, and the risk factors that may occur in the inspection process are excluded, so that the accurate fault point and accident reason of line in the process of effective and rapid capture and investigation can be effectively and rapidly captured.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of unmanned aerial vehicle patrol, in particular to an unmanned aerial vehicle automatic cruise detection method for line fault maintenance. BACKGROUND

[0002] In the process of line fault maintenance, in order to avoid the unsafe hidden troubles caused by manual inspection, the unmanned aerial vehicle automatic cruise detection method is used for detection. In the process of checking the accident point in the unmanned aerial vehicle connection system, the focusing on the accident point may not be accurate, and the unmanned aerial vehicle itself may also be shaking. The photos taken when accurately querying the line fault may also be inaccurate. Because of the uncertain factors of the surrounding environment, manual inspection may also be affected by unsafe factors in the surrounding environment.

[0003] The existing patent CN 110989685 A proposes an unmanned aerial vehicle cruise system detection method, which includes: the unmanned aerial vehicle flies in the substation according to the preset line; wherein the unmanned aerial vehicle is connected with the base station arranged in the substation to realize positioning; the detection device is carried on the unmanned aerial vehicle and moves with the unmanned aerial vehicle to obtain the data on the detection point in the substation; finally the unmanned aerial vehicle or the detection device transmits the detected temperature or image data to the processing device in the substation, the processing device processes the temperature or image data and makes corresponding response; compared with the conventional human patrol mode, the unmanned aerial vehicle inspection improves the inspection efficiency and reduces the inspection cost.

[0004] The above-mentioned patent realizes the smooth transmission of temperature and image data to the detection point, so that the processing device processes the temperature or image data and makes corresponding response. However, the positioning of the fault point around the line cannot be ensured to be accurate. When the positioning of the fault point cannot be accurately ensured, the position of the fault point photographed by the system may not approach the accurate target point or deviate from the target point during the magnification process, thereby increasing the uncertain factors for analyzing the line fault. SUMMARY

[0005] To solve the above-mentioned problem that the target point may not be accurate or deviate from the target point during the magnification of the fault point in the process of line checking, the purpose of the present application is to provide an unmanned aerial vehicle automatic cruise detection method for line fault maintenance, which realizes the three-point or four-point angle positioning around the fault point to ensure that the target point does not change during magnification and shooting, and effectively and quickly captures the accurate fault point and accident reason of the line in the checking process.

[0006] The purpose of the present application is achieved by the following technical solutions:

[0007] An unmanned aerial vehicle automatic cruise detection method for line fault maintenance, comprising the following steps:

[0008] S1, start the unmanned aerial vehicle detection system, confirm that the signal of the unmanned aerial vehicle to be used can be normally connected with the signal of the system, through the signal connected by the system and the unmanned aerial vehicle, the preset direction is introduced into the system of the unmanned aerial vehicle by the system;

[0009] S2, start the line detection unmanned aerial vehicle, check whether the flight mode in the unmanned aerial vehicle system is opened, and adjust the unmanned aerial vehicle for test flight;

[0010] S3, the adjustment position angle of the unmanned aerial vehicle deviates according to the angle of the path line inspection, the laser distance device of the unmanned aerial vehicle detects the obstacle information in the flight environment of the unmanned aerial vehicle, obtains the GPS positioning information of the unmanned aerial vehicle, and observes whether the path information and the line path position of the unmanned aerial vehicle flight match from the system;

[0011] S4, detect whether the ambient temperature around the line fault reaches the ignition point of the combustible material, after the combustible material ignition point index around the system exceeds a certain standard, the system image curve rises, and real-time monitoring is carried out;

[0012] S5, after excluding external unstable factors, the unmanned aerial vehicle monitoring system identifies the path positioning opening image monitoring and shooting of the line, which is divided into early, middle and late stages, and the scene around the path of the line is sampled and uploaded into the system;

[0013] S6, collect the current flight information of the unmanned aerial vehicle, differentially process the GPS positioning information of the unmanned aerial vehicle, obtain the measured three-dimensional track data of the unmanned aerial vehicle, and perform three-point or four-point positioning mode around the line;

[0014] S7, the flight path is in the range of identifying line faults, and three-point or four-point angle positioning is performed around the fault point; when the identified line fault is a long strip, the line is a long square point, and the two ends and two sides of the line fault are positioned, and the line on the other side of the line fault is positioned opposite to the A and B long strips, and the two points are respectively point C and point D, and the A, B, C and D four-point line is marked, when the line fault is three-point positioning, the wider part of the fault is identified, two points are determined, and the A, B, C three-point line is connected;

[0015] S8, after the unmanned aerial vehicle confirms the positioning image of the line fault part, the three-point or four-point compression is determined, the camera lens is automatically adjusted to determine the most accurate position size for shooting, and the shooting is uploaded into the system.

[0016] Further, the flight image path in the adjustment system in S2 makes the unmanned aerial vehicle fly along the path to see whether it is in a normal state, if it is in a normal state, it can be normally started, and if it deviates from the path track, the unmanned aerial vehicle system needs to be re-detected and set.

[0017] Further, the GPS positioning of the unmanned aerial vehicle first captures the approximate path position, flies along the GPS positioning information, identifies the obstacles, and then bypasses the obstacles.

[0018] Further, the temperature detection carried by the unmanned aerial vehicle in S4 can measure the temperature around the line, and when the temperature exceeds the standard point, the cooling measure of the part is started, and when the temperature of the part is reduced, the unmanned aerial vehicle can approach the line fault point.

[0019] Further, the angle positioning algorithm is:

[0020]

[0021] is the angle of the path of the line relative to the vertical direction of the unmanned aerial vehicle, ri is the lateral distance between the extension path position of the line and the image position in the image of the camera of the unmanned aerial vehicle in the air, is the lateral picture of the camera of the unmanned aerial vehicle.

[0022] Further, the d ri The line center position is positive on the right side of the image, and negative on the left side in the opposite direction, The right tilt is positive, and the left tilt is negative.

[0023] The unmanned aerial vehicle system further comprises a functional device, a flight control device, a charging module, an image shooting module, a data transmission module and a navigation positioning module, and the charging module is further connected with a ground charging station;

[0024] It includes a photography control system and a communication and power system, and the photography control system includes a patrol management, a patrol live broadcast, a communication module, a storage module and an image data module.

[0025] The photography control system and the communication and power system are further connected with a communication and power system, and the communication and power system includes a communication module, a control module, an FIP module and a battery replacement module. Further, the patrol management, the patrol live broadcast and the communication module are classified into a group and connected together with the storage module, the image data module includes a classification and analysis module, the patrol management, the patrol live broadcast and the communication module are connected with the communication and power system through data transmission, and the image data is connected with the FTP module through image transmission.

[0026] Further, the communication module of the communication and power system is connected with a communication module, a control module, an FTP module and a battery replacement module, and the control module is connected with a reading path, a shooting photo and a transmission photo module.

[0027] The present application has the following advantages:

[0028] 1. The UAV automatic cruise detection method for line fault maintenance uses three-point or four-point positioning to identify and locate fault points based on their information. The UAV then selects the fault points, calculates the corresponding angle positioning lines using angle offset, and accurately transmits the fault point data map. Three-point or four-point angle positioning ensures that the target point remains unchanged during magnified shooting.

[0029] 2. The line fault maintenance uses an automatic cruise detection method of drones. By detecting external environmental factors such as temperature and oxygen, the line itself is checked after eliminating external natural environmental factors. The process proceeds from the outside to the inside, eliminating potential dangerous factors during the inspection. It can effectively and quickly capture the accurate fault point and cause of the accident during the inspection. Attached Figure Description

[0030] Figure 1 This is a schematic diagram of the unmanned aerial vehicle (UAV) system modules of the present invention;

[0031] Figure 2 This is a schematic diagram of data transmission between the UAV and the overall system of the present invention;

[0032] Figure 3 This is a schematic diagram of the process of the present invention;

[0033] Figure 4 This is a line graph of the angular distance positioning data of the present invention. Detailed Implementation

[0034] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0035] An example of the UAV automatic cruise detection method for line fault maintenance is as follows:

[0036] Please see Figures 1-4 An automatic cruise detection method for line fault maintenance using a drone includes the following steps:

[0037] S1. Activate the drone detection system to confirm that the signal of the drone to be used can be connected normally with the signal of the system. Through the signal of the connection between the system and the drone, the preset direction is introduced into the drone's system by the system.

[0038] S2. Start the line test drone, check whether the flight mode of the drone system is turned on, and try adjusting the drone to conduct a test flight;

[0039] S3, the adjustment position offset angle of the unmanned aerial vehicle is deflected according to the angle of the path line inspection, the laser distance device of the unmanned aerial vehicle detects the obstacle information in the flight environment of the unmanned aerial vehicle, obtains the GPS positioning information of the unmanned aerial vehicle, and observes whether the path information and the line path position of the flight of the unmanned aerial vehicle match from the system;

[0040] S4, whether the ambient temperature around the line fault reaches the combustible point of combustible material is detected, after the combustible point index of the surrounding combustible material exceeds a certain standard, the system image curve is displayed upward, and real-time monitoring is performed;

[0041] S5, after excluding external unstable factors, the unmanned aerial vehicle monitoring system identifies the path positioning of the line to start image monitoring and shooting, which is divided into three stages of early, middle and late, and the scene around the path of the line is sampled and uploaded to the system;

[0042] S6, the current flight information of the unmanned aerial vehicle is collected, the GPS positioning information of the unmanned aerial vehicle is differentially processed, three-dimensional track data of the unmanned aerial vehicle is obtained, three-point or four-point positioning mode is performed around the line;

[0043] S7, the flight path is in the range of identifying the line fault, and three-point or four-point angle positioning is performed around the fault point; when the identified line fault is a long strip, the line is a long square point, and the two ends and the two sides of the line fault are positioned, and the line on the side of the line fault is positioned A and B long strip, and the opposite line of A and B on the other side of the line fault is positioned two points C and D, and the line of A, B, C and D is marked, when the identified line fault is three-point positioning, the wider part of the fault is identified, two points are determined, and the smaller point of the line fault is also marked on the line of A, B, C three points, and the line between A, B and C is connected;

[0044] S8, after the unmanned aerial vehicle confirms the positioning image of the line fault part, the three-point or four-point compression is determined, the camera lens is automatically adjusted to determine the most accurate position and size for shooting, and the shooting is uploaded to the system;

[0045] The unmanned aerial vehicle main body module further comprises a function device, a flight control device, a charging module, an image shooting module, a data transmission module and a navigation positioning module, and the charging module is further connected with a ground charging station;

[0046] The unmanned aerial vehicle main body module further comprises a function device, a flight control device, a charging module, an image shooting module, a data transmission module and a navigation positioning module, and the charging module is further connected with a ground charging station;

[0047] The photography control system is further connected with a communication and power system, and the communication and power system comprises a communication module, a control module, an FIP module and a switching battery module.

[0048] In S2, the flight image path in the adjustment system is adjusted, so that the UAV flies along the path to check whether it is in a normal state, and if so, the UAV can be normally started, and if not, the UAV system needs to be re-detected and set.

[0049] In S3, the UAV is positioned by GPS, and first captures a rough path position, flies along the GPS positioning information, and identifies and bypasses obstacles.

[0050] In S4, the temperature around the line is measured by the temperature control detection carried by the UAV, and when the temperature exceeds a standard point, the part is cooled, and when the temperature of the part is reduced, the UAV can approach the line fault point.

[0051] In S5, the angle algorithm is:

[0052]

[0053] is the angle of the path of the line relative to the vertical direction of the UAV, d ri is the horizontal distance between the extension path position of the line in the image of the camera of the UAV in the air and the image position, is the horizontal picture of the camera of the UAV.

[0054] In S6, d ri The line center position is positive on the right side of the image position, and negative on the left side, The right side tilt is positive, and the left side tilt is negative.

[0055] The following table is the task allocation probability matching label data of the distribution network repair personnel:

[0056] 10° 20° 30° 40° 50° 70 cm 30 cm 30 cm 40 cm 65 cm

[0057] As shown in the above table, according to the angle offset, the positioned distance changes.

[0058] In S7, the inspection management, inspection live broadcast and communication module are classified into a group and connected together with the storage module, the image data module comprises a classification and analysis module, the inspection management, inspection live broadcast and communication module are connected with the communication and power system through data transmission, and the image data is connected with the FTP module through image transmission.

[0059] In S8, the communication and power system communication module is connected with the communication module, the control module, the FTP module and the battery replacement module, and the control module is connected with the reading path, the photographing and the photograph transmission module.

[0060] While embodiments of the application have been shown and described, it is to be understood that the application is not limited to the details of the embodiments described, since numerous changes, modifications, substitutions and variations can be made thereto without departing from the spirit and scope of the application as defined by the appended claims and their equivalents.

Claims

1. A method for automatic cruise detection of line faults using an unmanned aerial vehicle (UAV), characterized in that: Includes the following steps: S1. Activate the drone detection system to confirm that the signal of the drone to be used can be connected normally with the signal of the system. Through the signal of the connection between the system and the drone, the preset direction is introduced into the system of the drone. S2. Start the line test drone, check whether the flight mode of the drone system is turned on, and try adjusting the drone to conduct a test flight; S3. The drone's position offset angle is adjusted according to the angle of the path inspection. The drone's laser rangefinder detects obstacle information in the drone's flight environment, obtains the drone's GPS positioning information, and observes whether the drone's flight path information and the line path position match from the system. S4. Detect whether the ambient temperature around the circuit fault reaches the ignition point of flammable materials. If the ignition point index of the surrounding flammable materials exceeds a certain standard, the system image curve will rise, and real-time monitoring will be performed. S5. After eliminating external unstable factors, the UAV monitoring system identifies the route path and starts image monitoring and shooting. It samples the scene around the route path in three stages: morning, noon and evening and uploads the images to the system. S6. Collect the current flight information of the UAV, differentially process the GPS positioning information of the UAV, obtain the measurement three-dimensional trajectory data of the UAV, and perform three-point positioning mode or four-point positioning mode around the route. S7. Flight path: Within the area where the line fault is identified, perform three-point or four-point angular positioning around the fault point; when the identified line fault is long and narrow, the line is a long rectangular block, and points are located at both ends and sides of the line fault. Points A and B are located on one side of the line, and then points C and D are located on the opposite side of A and B on the other side of the line fault. Connect the four points A, B, C and D. When the line fault is a three-point positioning, identify the wider part of the fault, locate two points, and also mark the smaller point of the line fault by connecting the three points. Connect the three points together. S8. After the drone confirms the location of the fault in the line, it compresses the image using three or four points and the camera lens automatically adjusts to determine the most accurate position and size for shooting and uploading to the system. The angle positioning algorithm is as follows: ； The angle of deviation of the route relative to the vertical direction of the drone. This refers to the lateral distance between the location of the extended path of the line and the image location in an image taken by a camera from the air by a drone. This is a horizontal view from a drone camera; d ri The center of the line is considered positive when it is to the right of the image, and negative when it is to the left. Tilting to the right is positive, and tilting to the left is negative.

2. The method for automatic cruise detection of line faults using a UAV for maintenance according to claim 1, characterized in that: In S2, the flight image path in the system is adjusted so that the UAV flies along the path to see if it is in a normal state. If it is in a normal state, it can be started normally. If it deviates from the path, the system settings of the UAV need to be re-checked.

3. The method for automatic cruise detection of line faults using a UAV for maintenance according to claim 2, characterized in that: The drone's GPS positioning first captures the approximate path location, then flies along the GPS positioning information, identifies obstacles, and then avoids the obstacles.

4. The method for automatic cruise detection of line faults using a UAV for maintenance according to claim 1, characterized in that: In S4, the drone carries a connected temperature control sensor to measure the temperature around the line. When the temperature exceeds the standard point, cooling measures are activated for that part. Once the temperature of the part decreases, the drone approaches the fault point on the line.

5. The method for automatic cruise detection of line faults using a UAV for maintenance according to claim 1, characterized in that: The unmanned aerial vehicle (UAV) system includes functional devices, flight control devices, a charging module, an image and photography module, a data transmission module, and a navigation and positioning module. The charging module is also connected to a ground charging station. The functional devices include a photography control system and a communication and power system. The photography control system includes a patrol management, patrol live broadcast, communication module, storage module and image data module. The photography control system is connected to a communication and power system, which includes a communication module, a control module, an FTP module, and a battery swapping module.

6. The method for automatic cruise detection of line faults using a UAV for maintenance according to claim 5, characterized in that: The inspection management, inspection live streaming, and communication modules are grouped together and connected to the storage module. The image data module includes a classification and analysis module. The inspection management, inspection live streaming, and communication modules are connected to the communication and power systems via data transmission. The image data is connected to the FTP module via image transmission.

7. The method for automatic cruise detection of line faults using an unmanned aerial vehicle (UAV) according to claim 6, characterized in that: The communication module of the communication and power system is connected to a control module, an FTP module, and a battery swapping module. The control module is connected to a path reading, photo taking, and photo transmission module.

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