Track correction method for distribution network unmanned aerial vehicle autonomous inspection

Abstract

The invention relates to a track correction method for distribution network unmanned aerial vehicle autonomous inspection, and the method comprises the steps: generating an optimal flight path of an inspection unmanned aerial vehicle according to an inspection position and flight parameters of the unmanned aerial vehicle; afterwards, when the unmanned aerial vehicle inspects, the remote sensing monitoring assembly is used for shooting distribution network lines and equipment, the GPS positioning module is used for obtaining position data of the unmanned aerial vehicle, and then the background server judges the track of the unmanned aerial vehicle according to the received position data and the pole tower and the distribution network equipment in the image data as reference objects. The actual flight route of the inspection unmanned aerial vehicle is generated; and finally, comparing the optimal flight path with the actual flight path, and when the deviation value is greater than a preset threshold value, sending a deviation correction instruction by using a deviation correction module. And finally, a correction track is formulated according to the correction instruction by using an internal calibration assembly of the unmanned aerial vehicle, and meanwhile, a correction motor is controlled to perform correction operation of the unmanned aerial vehicle. The device has the advantages of high efficiency, accuracy and good use effect.

Description

Technical Field

[0001] The present invention belongs to the technical field of distribution network inspection, and in particular relates to a trajectory correction method for autonomous inspection of a distribution network unmanned aerial vehicle. Background Art

[0002] Distribution network refers to the power grid that receives electric energy from the transmission network or regional power plants, distributes it locally or step by step according to the voltage to various users through distribution facilities. It is composed of overhead lines, cables, towers, distribution transformers, disconnectors, reactive power compensators and some ancillary facilities, and plays an important role in distributing electric energy in the power grid. Distribution network lines are generally exposed outdoors, and they will inevitably be affected by the natural and social environment during operation. In particular, extreme weather such as lightning and storms may destroy or damage distribution network equipment, or cause accidents such as electric shock. At the same time, problems such as theft, random wiring, and deliberate destruction may also affect the normal operation of distribution equipment and even lead to safety accidents. Therefore, it is necessary to regularize the distribution network lines. Time inspection, traditional power inspection methods usually rely on manual inspection and equipment detection. During the specific operation, the labor intensity of the staff is high, the inspection efficiency is low, and under the harsh external environment, the personal safety of the inspection personnel cannot be guaranteed, and there is a great risk. Therefore, most of the existing inspection work is completed through autonomous inspection by drones. However, when drones perform autonomous inspection tasks, they are prone to problems such as weak drone signals, lack of accuracy, and large operation errors caused by meteorological or environmental factors, which reduce the quality of inspection operations and pose a great risk to flight safety. In order to solve the above problems, it is necessary to develop an efficient, accurate and effective trajectory correction method for autonomous inspection of distribution network drones. Summary of the invention

[0003] The purpose of the present invention is to overcome the shortcomings of the prior art and to provide a trajectory correction method for autonomous inspection of a distribution network UAV which is efficient, accurate and has good use effect.

[0004] The object of the present invention is achieved by: a trajectory correction method for autonomous inspection of a distribution network UAV, comprising the following steps: Step 1: Generate the best flight route for the inspection drone through 3D imaging software based on the take-off and landing position, flight speed, and flight altitude of the inspection drone, as well as the location of key distribution network towers; Step 2: Input the best flight route generated in step 1 into the drone, and fly the drone to perform inspection operations. During the inspection process, the remote sensing monitoring component inside the drone can be used to shoot the distribution network lines and distribution network equipment, and the built-in GPS positioning module can be used to obtain the location data of the drone. After that, the image data, location data and status information of the drone are transmitted to the background server in real time through the wireless transmission module; Step 3: After receiving the real-time image data, real-time location data and real-time status information of the drone, the backend server first uses its internal processing module to perform weighted average grayscale processing and filtering noise reduction processing on the image data; then, based on the received location data and the towers and distribution network equipment in the image data as reference objects, the running trajectory of the drone is analyzed and judged. Finally, the actual flight route of the inspection drone is generated through the three-dimensional imaging software; Step 4: Compare the optimal flight route of the inspection drone with the actual flight route of the inspection drone. When the inspection drone deviates abnormally, the deviation value can be calculated by the deviation correction module inside the background server. When the deviation value is less than the preset threshold, no adjustment is made. When the deviation value is greater than the preset threshold, the deviation correction module is used to issue a deviation correction instruction. Step 5: After issuing the correction instruction, the background server can transmit the instruction to the inspection drone through the wireless transmission module, thereby starting the calibration component inside the inspection drone. At this time, the calibration component first formulates a correction trajectory according to the deviation value, and then adjusts the position and height of the inspection drone according to the correction trajectory and by controlling the correction motor fixed to the outside of the inspection drone, so that it returns to the optimal flight route.

[0005] A detection component is provided at the front end of the inspection drone, wherein the detection component is used to detect obstacles on the moving route of the inspection drone. When an obstacle is detected blocking the moving route, the detection component sends an obstacle avoidance signal to the correction motor, thereby adjusting the position and height of the inspection drone through the correction motor to achieve obstacle avoidance operation.

[0006] The real-time status information of the UAV in step 2 includes the vertical speed, horizontal speed and heading angle of the UAV.

[0007] The inspection drone is provided with an electronic bird repeller inside, which can be used to drive away the flying birds around the inspection drone.

[0008] The beneficial effects of the present invention are as follows: the present invention sets a remote sensing monitoring component and a GPS positioning module, and the remote sensing monitoring component can be used to shoot distribution network lines and distribution network equipment, and the GPS positioning module can be used to obtain the position data of the UAV, so that the background server can analyze and judge the operation trajectory of the UAV according to the received position data and based on the poles, towers and distribution network equipment in the image data as reference objects, and finally generate the actual flight route of the inspection UAV; by setting the correction module, it can be used to calculate the deviation value between the actual flight route and the optimal flight route; by setting the calibration component, the calibration component can be used to formulate the correction trajectory according to the correction instruction, and after the correction trajectory is formulated, the correction motor is controlled to perform the correction operation of the UAV; in general, the present invention has the advantages of high efficiency, accuracy and good use effect. DETAILED DESCRIPTION

[0009] The present invention is further described below.

[0010] Embodiment: A method for correcting the trajectory of a distribution network UAV autonomous inspection comprises the following steps: Step 1: Generate the best flight route for the inspection drone through 3D imaging software based on the take-off and landing position, flight speed, and flight altitude of the inspection drone, as well as the location of key distribution network towers; Step 2: Input the best flight route generated in step 1 into the drone, and fly the drone to perform inspection operations. During the inspection process, the remote sensing monitoring component inside the drone can be used to photograph the distribution network lines and distribution network equipment, and the built-in GPS positioning module can be used to obtain the location data of the drone. After that, the image data, location data and status information of the drone taken by the drone are transmitted to the background server in real time through the wireless transmission module; the status information of the drone includes the vertical speed, horizontal speed and heading angle of the drone; Step 3: After receiving the real-time image data, real-time location data and real-time status information of the drone, the backend server first uses its internal processing module to perform weighted average grayscale processing and filtering noise reduction processing on the image data; then, based on the received location data and the towers and distribution network equipment in the image data as reference objects, the running trajectory of the drone is analyzed and judged. Finally, the actual flight route of the inspection drone is generated through the three-dimensional imaging software; Step 4: Compare the optimal flight route of the inspection drone with the actual flight route of the inspection drone. When the inspection drone deviates abnormally, the deviation value can be calculated by the deviation correction module inside the background server. When the deviation value is less than the preset threshold, no adjustment is made. When the deviation value is greater than the preset threshold, the deviation correction module is used to issue a deviation correction instruction. Step 5: After issuing the correction instruction, the background server can transmit the instruction to the inspection drone through the wireless transmission module, thereby starting the calibration component inside the inspection drone. At this time, the calibration component first formulates a correction trajectory according to the deviation value, and then adjusts the position and height of the inspection drone according to the correction trajectory and by controlling the correction motor fixed to the outside of the inspection drone, so that it returns to the optimal flight route.

[0011] The front end of the inspection drone is provided with a detection component, and an electronic bird repeller is arranged inside. The detection component is used to detect obstacles on the moving route of the inspection drone. When an obstacle is detected blocking the moving route, the detection component sends an obstacle avoidance signal to the correction motor, so that the position and height of the inspection drone are adjusted by the correction motor to achieve obstacle avoidance operation; the electronic bird repeller can be used to drive away flying birds around the inspection drone.

[0012] When the present invention is used, first, according to the take-off and landing position, flight speed, and flight altitude of the inspection drone, and in conjunction with the position of the key distribution network pole tower, the optimal flight route of the inspection drone is generated through three-dimensional imaging software. After that, the generated optimal flight route is input into the drone, and the drone is released to perform inspection operations. During the inspection of the drone, the distribution network line and distribution network equipment can be photographed using its internal remote sensing monitoring component, and the location data of the drone can be obtained using its built-in GPS positioning module. Then, the image data, location data, and status information of the drone taken by the drone are transmitted to the background server in real time through the wireless transmission module. Then, the image data are subjected to weighted average grayscale processing and filtering noise reduction processing using the processing module inside the background server; and then, according to the received location data, and based on the pole tower and distribution network equipment in the image data as reference objects, the operation trajectory of the drone is analyzed and judged. Finally, the actual flight route of the inspection drone is generated through the three-dimensional imaging software. After completing the above operations, the optimal flight route of the inspection drone is compared with the actual flight route of the inspection drone. When the inspection drone shows abnormal deviation, the deviation value can be calculated by the deviation correction module inside the background server. When the deviation value is less than the preset threshold, no adjustment is made. When the deviation value is greater than the preset threshold, the deviation correction module is used to issue a deviation correction instruction. Finally, the deviation correction instruction issued by the deviation correction module is transmitted to the inspection drone through the wireless transmission module, thereby starting the calibration component inside the inspection drone. At this time, the calibration component first formulates a deviation correction trajectory according to the deviation value, and then adjusts the position and height of the inspection drone according to the deviation correction trajectory and by controlling the deviation correction motor fixedly installed on the outside of the inspection drone, so that it returns to the optimal flight route; at the same time, the detection component at the front end of the inspection drone can detect obstacles on the moving route of the inspection drone. When it is detected that there is an obstacle blocking the moving route, the detection component sends an obstacle avoidance signal to the deviation correction motor, thereby adjusting the position and height of the inspection drone through the deviation correction motor to achieve obstacle avoidance operation, and using the electronic bird repellent inside the inspection drone, the flying birds around the inspection drone can be driven away; in general, the present invention has the advantages of high efficiency, accuracy and good use effect.

[0013] 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 above embodiments, a person skilled in the art should understand that the specific implementation modes of the present invention can still be modified or replaced by equivalents, and any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be included in the scope of the claims of the present invention.

Claims

1. A trajectory correction method for autonomous inspection of a distribution network UAV, characterized in that: The following steps are involved: Step 1: Generate the best flight route for the inspection drone through 3D imaging software based on the take-off and landing position, flight speed, and flight altitude of the inspection drone, as well as the location of key distribution network towers; Step 2: Input the best flight route generated in step 1 into the drone, and fly the drone to perform inspection operations. During the inspection process, the remote sensing monitoring component inside the drone can be used to shoot the distribution network lines and distribution network equipment, and the built-in GPS positioning module can be used to obtain the location data of the drone. After that, the image data, location data and status information of the drone are transmitted to the background server in real time through the wireless transmission module; Step 3: After receiving the real-time image data, real-time location data and real-time status information of the drone, the backend server first uses its internal processing module to perform weighted average grayscale processing and filtering noise reduction processing on the image data; then, based on the received location data and the towers and distribution network equipment in the image data as reference objects, the running trajectory of the drone is analyzed and judged. Finally, the actual flight route of the inspection drone is generated through the three-dimensional imaging software; Step 4: Compare the optimal flight route of the inspection drone with the actual flight route of the inspection drone. When the inspection drone deviates abnormally, the deviation value can be calculated by the deviation correction module inside the background server. When the deviation value is less than the preset threshold, no adjustment is made. When the deviation value is greater than the preset threshold, the deviation correction module is used to issue a deviation correction instruction. Step 5: After issuing the correction instruction, the background server can transmit the instruction to the inspection drone through the wireless transmission module, thereby starting the calibration component inside the inspection drone. At this time, the calibration component first formulates a correction trajectory according to the deviation value, and then adjusts the position and height of the inspection drone according to the correction trajectory and by controlling the correction motor fixed to the outside of the inspection drone, so that it returns to the optimal flight route.

2. A method for correcting the trajectory of a distribution network UAV autonomous inspection as claimed in claim 1, characterized in that: A detection component is provided at the front end of the inspection drone, wherein the detection component is used to detect obstacles on the moving route of the inspection drone. When an obstacle is detected blocking the moving route, the detection component sends an obstacle avoidance signal to the correction motor, thereby adjusting the position and height of the inspection drone through the correction motor to achieve obstacle avoidance operation.

3. A method for correcting the trajectory of a distribution network UAV autonomous inspection as claimed in claim 1, characterized in that: The real-time status information of the UAV in step 2 includes the vertical speed, horizontal speed and heading angle of the UAV.

4. A method for correcting the trajectory of a distribution network UAV autonomous inspection as claimed in claim 1, characterized in that: The inspection drone is provided with an electronic bird repeller inside, which can be used to drive away the flying birds around the inspection drone.