CN113009929A - Unmanned aerial vehicle power grid line patrol control method - Google Patents
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Abstract
The utility model discloses an unmanned aerial vehicle power grid line patrol control method, which comprises the following steps: downloading map information of a routing inspection area, and setting a routing inspection flight route according to tower position information of the map information; carrying out inspection flight according to a set inspection flight route, acquiring image data of an inspection line and judging whether abnormality exists, and if the abnormality exists, returning abnormal information to a remote control center; when the routing inspection flight line is used for routing inspection flight, whether the theoretical endurance of the unmanned aerial vehicle is enough to complete the flight inspection task or not is judged in real time, and if the theoretical endurance of the unmanned aerial vehicle cannot be completed, a stop station within a communication range is searched. According to the unmanned aerial vehicle power grid line patrol control method, basic map information of a line patrol area can be provided for unmanned aerial vehicle cruising through the remote control center, meanwhile, the most reasonable patrol route is automatically planned for unmanned aerial vehicle line patrol through the remote control center, the patrol route is based on a straight line fitting algorithm, electric quantity can be saved to the greatest extent, and the problem of low efficiency caused by frequent charging is solved.
Description
Technical Field
The invention relates to the technical field of unmanned aerial vehicles, in particular to a power grid line patrol control method for an unmanned aerial vehicle.
Background
With the annual increase of Chinese power grid users, high-voltage power transmission lines are distributed all over the country. Data statistics shows that the total length of the power transmission line in China is 159 ten thousand kilometers or more by 2020, so the annual cost of power enterprises is increased year by year. The important ring of maintenance operation of power transmission line is exactly patrolling and examining of power line, and traditional electric wire netting is maintained and is mainly accomplished through artifical line patrol mode, and intensity of labour is big, inefficiency, and some circuits are caused the unusual difficulty of line patrol and danger by the topographic factor. With the development of science and technology, electric power enterprises are concerned more and more about maintaining power grids by adopting an automatic science and technology means. In the early days, electric power enterprises adopt manned helicopters or inspection robots to carry out electric power inspection tasks, but the scheme is relatively high in manufacturing cost. With the rapid development of the related technology of the unmanned aerial vehicle in recent years, the unmanned aerial vehicle has relatively perfect application conditions especially for special unmanned aerial vehicles in special fields. For example, the line patrol unmanned aerial vehicle that electric power enterprise can adopt receives the extensive concern in this field because of possessing advantages such as small and exquisite flexibility, easy control, low cost, functioning speed are fast, adaptability is strong. Relevant data show that the unmanned aerial vehicle inspection cost is only 30% of that of the manual inspection.
At present, common electric power line patrol unmanned aerial vehicle is mostly automatic line patrol fixed wing unmanned aerial vehicle, and this type of unmanned aerial vehicle is mainly applicable to daily operation on a large scale, but can not hover meticulous patrol near the suspected place of trouble, and flying speed is very fast relatively. In addition, the existing scheme mainly depends on manual remote control and low-speed close-range observation of towers, cables and the like to find defects and hidden dangers. This operation has a high risk due to the intervention of manual operations. For the power transmission line in the great mountains and mountains, operators need to raise heads all the time to pay attention to the unmanned aerial vehicle, and therefore certain risks exist.
Disclosure of Invention
In view of the above problems in the prior art, the present invention aims to provide a power grid line patrol control method for an unmanned aerial vehicle, which does not require manual close-range remote control of the unmanned aerial vehicle, ensures the personal safety of operators relatively, and has high line patrol efficiency.
In order to achieve the above object, an embodiment of the present invention provides an unmanned aerial vehicle power grid line patrol control method, including:
downloading map information of a routing inspection area, and setting a routing inspection flight route according to tower position information of the map information;
carrying out inspection flight according to a set inspection flight route, acquiring image data of an inspection line and judging whether abnormality exists, and if the abnormality exists, returning abnormal information to a remote control center;
when the routing inspection flight line is used for routing inspection flight, whether the theoretical endurance of the unmanned aerial vehicle is enough to complete the flight inspection task or not is judged in real time, and if the theoretical endurance of the unmanned aerial vehicle cannot be completed, a stop station within a communication range is searched.
Preferably, before downloading the map information of the patrol area, the system is powered on and initialized, and after the initialization is successful, the system is in communication connection with the remote control center.
Preferably, when the communication connection with the remote control center is established, the communication connection with a ground control vehicle is also established, the ground control vehicle at least comprises a second communication unit and a control intervention unit, the second communication unit is used for establishing the communication connection with the first communication unit of the unmanned aerial vehicle, and the control intervention unit is configured to perform manual intervention on the flight mission of the unmanned aerial vehicle according to user operation.
Preferably, the returning of the abnormal information further comprises returning the abnormal information to the ground control vehicle, and the remote control center forwards the abnormal information to a mobile terminal carried by a worker when receiving the abnormal information.
Preferably, map information of a routing inspection area is downloaded, the map information represents a preset routing inspection area, the map information at least comprises tower position information on a routing inspection line, and the remote control center further comprises a path planning unit, wherein the path planning unit is configured to plan a routing inspection flight line based on a linear regression algorithm according to the tower position information of the corresponding preset routing inspection area downloaded by the unmanned aerial vehicle; and the unmanned aerial vehicle performs inspection flight according to the inspection flight route.
Preferably, the linear regression algorithm is a regression line algorithm.
Preferably, when planning the patrol flight route, the path planning unit is configured to establish a projection coordinate system by using the map information, use the remote control center as an origin, use a geographic azimuth as a horizontal axis and a vertical axis of the projection coordinate system, project the geographic position information of the tower as a scatter point on the projection coordinate system, perform linear fitting based on a least square method on the scatter point, and set the maximum dispersion of the linear fitting to be smaller than the range of the visual distance of the image acquisition unit when performing the linear fitting.
Preferably, the searching for a stop within the communication range includes:
modifying the routing inspection flight path, and stopping to the nearest stop station according to the laser guidance;
and starting the standby unmanned aerial vehicle at the stop station to continue to perform inspection flight according to the planned flight route.
Preferably, the determining whether there is an abnormality includes:
the method comprises the steps that collected image data of an inspection line are uploaded to a cloud server, the cloud server at least comprises an image analysis unit and a first storage unit, and the image analysis unit is configured to be an image analysis unit which analyzes the image data collected by the image collection unit to obtain abnormal information; the first storage unit is configured to store an image frame containing abnormality information.
Preferably, when the image analysis unit of the cloud server determines that an abnormal condition occurs, the image analysis unit stores an image frame containing abnormal information to the first storage unit, and feeds the abnormal condition back to the remote control center and the ground control vehicle respectively.
Compared with the prior art, the unmanned aerial vehicle power grid line patrol control method can provide basic map information of a line patrol area for unmanned aerial vehicle cruising through the remote control center, and simultaneously automatically plans the most reasonable patrol route for unmanned aerial vehicle line patrol through the remote control center, wherein the patrol route is based on a straight line fitting algorithm, so that electric quantity can be saved to the maximum degree, and the problem of low efficiency caused by frequent charging is avoided.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
This document provides an overview of various implementations or examples of the technology described in this disclosure, and is not a comprehensive disclosure of the full scope or all features of the disclosed technology.
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Fig. 1 is a basic flow diagram of the unmanned aerial vehicle power grid line patrol control method.
Fig. 2 is a flowchart of a method of an embodiment of the unmanned aerial vehicle power grid line patrol control method of the present invention.
Fig. 3 is a schematic diagram of the principle of the unmanned aerial vehicle power grid line patrol control method in implementation.
Fig. 4 is a system block diagram of the unmanned aerial vehicle power grid line patrol control method implemented in the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present disclosure more clear, the technical solutions of the embodiments of the present disclosure will be described below clearly and completely with reference to the accompanying drawings of the embodiments of the present disclosure.
It is to be understood that the described embodiments are only a few embodiments of the present disclosure, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the described embodiments of the disclosure without any inventive step, are within the scope of protection of the disclosure.
To maintain the following description of the embodiments of the present disclosure clear and concise, a detailed description of known functions and known components have been omitted from the present disclosure.
In the present invention, an unmanned aerial vehicle power grid line patrol control method provided in an aspect of an embodiment of the present invention includes: downloading map information of a routing inspection area, and setting a routing inspection flight route according to tower position information of the map information; carrying out inspection flight according to a set inspection flight route, acquiring image data of an inspection line and judging whether abnormality exists, and if the abnormality exists, returning abnormal information to a remote control center; when the routing inspection flight line is used for routing inspection flight, whether the theoretical endurance of the unmanned aerial vehicle is enough to complete the flight inspection task or not is judged in real time, and if the theoretical endurance of the unmanned aerial vehicle cannot be completed, a stop station within a communication range is searched.
Specifically, as shown in fig. 1, in one embodiment, as shown in fig. 1, includes: s102, the unmanned aerial vehicle downloads map information of the inspection area and sets an inspection flight route according to position information of a tower in the map information; s103, performing inspection flight according to the set inspection flight route; s104, judging whether the residual electric quantity of the unmanned aerial vehicle can finish the flight inspection task, if so, entering S105, otherwise, entering S108, and searching for a stop in a communication range; and S105, collecting the image data of the inspection line and judging whether the inspection line is abnormal or not (S106), if so, entering S107, and returning abnormal information.
Fig. 2 is a flow chart illustrating another embodiment of the present invention, and as shown in fig. 2, before downloading the map information of the inspection area, the method may further include performing system power-on initialization, and after the initialization is successful, establishing a communication connection with a remote control center. As further shown in fig. 3 and 4, in the present invention, the towers 40 are linearly arranged, the ground control vehicle 10 driven by the operator can be deployed on the road 70 near the inspection line, after the initialization of the unmanned aerial vehicle system is successful, the ground control vehicle can establish a connection with the third communication unit 21 of the remote control center 20, and when the communication connection is established, the method can further include establishing a communication connection with a ground control vehicle 10, where the ground control vehicle 10 at least includes the second communication unit 11 for establishing a communication connection with the first communication unit 32 of the unmanned aerial vehicle and a control intervention unit 12, and the control intervention unit 12 is configured to perform manual intervention on the flight mission of the unmanned aerial vehicle according to a user operation. Specifically, in the present invention, since no manual intervention is required when the unmanned aerial vehicle inspection task is executed, in order to ensure the safety of the workers, the ground control vehicle 10 can accompany the road 70 closest to the inspection line, and the unmanned aerial vehicle 30 simultaneously transmits the acquired image information to the ground control vehicle 10, so that the ground control vehicle 10 can perform manual intervention control on the unmanned aerial vehicle 30 through the returned image information. Specifically, the unmanned aerial vehicle 30 further includes a GPS positioning module 33, the GPS positioning module 33 is configured to acquire the position information of the unmanned aerial vehicle 30 in real time, and send the position information to a ground control vehicle 10 through the first communication module 32, the ground control vehicle 10 at least includes a second communication unit 11 and a control intervention unit 12, which are used for establishing communication connection with the first communication unit 32, and the control intervention unit 12 is configured to perform manual intervention on the flight mission of the unmanned aerial vehicle 30 according to user operation.
In other embodiments, the returning of the abnormal information further includes returning the abnormal information to the ground control vehicle 10, and the remote control center 20 forwards the abnormal information to the mobile terminal 50 carried by the worker 60 when receiving the abnormal information. When receiving the abnormality information, the worker 60 can immediately drive to the corresponding tower 40 to perform abnormality processing.
In other applications, as an optimization, map information of an inspection area is downloaded, the map information represents a preset inspection area, the map information at least includes tower position information on an inspection line, the remote control center 20 further includes a path planning unit 22, and the path planning unit is configured to plan an inspection flight route based on a linear regression algorithm according to the tower position information of the corresponding preset inspection area downloaded by the unmanned aerial vehicle; and the unmanned aerial vehicle performs inspection flight according to the inspection flight route. Specifically, in the present invention, the linear regression algorithm is a regression line algorithm. More specifically, when planning the patrol flight path, the path planning unit 23 is configured to establish a projection coordinate system by using the map information, use the remote control center 20 as an origin, use a geographic azimuth (for example, use a geographic azimuth south as a vertical coordinate, use a geographic azimuth east as a horizontal coordinate) as a horizontal axis and a vertical axis of the projection coordinate system, project the geographic position information of the tower as a scatter point on the projection coordinate system, perform linear fitting based on a least square method on the scatter point, and set a maximum dispersion of the linear fitting to be smaller than a visual range of the image acquisition unit when performing the linear fitting. Therefore, when the unmanned aerial vehicle is used for line inspection, the position of the tower is not required to be used as an inspection target point to design a flight path, an optimum straight-line flight path is set among a plurality of towers, and the visual range of the tower where the flight path is located is within the visual range of the image acquisition unit.
In the method of the present invention, the searching for a stop within the communication range may specifically include: modifying the routing inspection flight path, and stopping to the nearest stop station according to the laser guidance; and starting the standby unmanned aerial vehicle at the stop station to continue to perform inspection flight according to the planned flight route. The docking station 40 of the present invention is disposed on a part of towers on the inspection line at a preset distance, and at least includes a guiding laser emitting module 41 for emitting laser light and a charging interface 42 for charging the unmanned aerial vehicle 30. In the embodiment of the present invention, the guiding laser emitting module 41 may be a vehicle-scale LiDAR integrated laser emitting module, and the guiding laser receiving module 34 is a laser receiving module for receiving LiDAR integrated laser light. In fact like this, unmanned aerial vehicle 30 is patrolling and examining the time, and need not fly to the shaft tower by accident and remove to berth, and only need according to actual continuation of the journey demand, according to laser beam's guide, is close to the stop 40 and charges. In view of the safety and reliability of the unmanned aerial vehicle 30 during docking charging, the charging interface 42 provided on the docking station 40 may be designed as a magnetic-type interface or a wireless charging interface based on the QI charging protocol. Of course, the drone 30, when not sufficiently endurance to support the inspection mission, may still cause the inspection mission to be interrupted even though charged via the fast charging protocol. In some preferred embodiments, therefore, a parking apron may be provided at the docking station, the parking apron being configured to park the spare drone, the spare drone 30 being configured to relay the flight while the drone is parked for charging, thereby continuing to complete the routing inspection mission.
The determining whether there is an abnormality in the method of the present invention may specifically include: the method comprises the steps that collected image data of an inspection line are uploaded to a cloud server, the cloud server at least comprises an image analysis unit and a first storage unit, and the image analysis unit is configured to be an image analysis unit which analyzes the image data collected by the image collection unit to obtain abnormal information; the first storage unit is configured to store an image frame containing abnormality information. The image analysis unit 81 at least comprises an image analysis unit 81 and a first storage unit 82, and the image analysis unit 81 is configured to analyze the image data acquired by the image acquisition unit 31 to obtain abnormal information; the first storage unit 82 is configured to store image frames containing abnormality information. The image analysis unit 81 may analyze the image information by using a neural network algorithm model, specifically, the neural network algorithm module may be configured based on a plurality of first data sets, where the plurality of first data sets respectively represent different abnormal situations, and set a corresponding number of forward neural networks (FFNs) according to the number of the first data sets, each FFN corresponds to one abnormal type, the number of input nerves of each network is 8, the number of output nerves of each network is 2, and each network uses Back Propagation (BP) supervised training, and trains using 10 to 30 abnormal situations (e.g., circuit foreign objects, plastic bags, branches, etc.) with different standard forms until the error variance is less than 20%. For the acquisition of the intake amount, the same neural network can be used for supervised training with reference, for example, for foreign matters, standard references such as common plastic bags and kites are set for supervised training, and the identification accuracy is improved. Further, it is to be understood that the above algorithm is merely exemplary, and that any machine-recognition based algorithm may be suitable for use with the present invention, such as a Convolutional Neural Network (CNN) or a Recurrent Neural Network (RNN).
As shown in fig. 4, in the implementation of the method of the present invention, since the foreign matters, animals, or animal nests on the route need to be further processed during the inspection process, the unmanned aerial vehicle 30 preferably further includes a mounting device 35, and the mounting device 35 optionally includes a flaming device or a cutting device for damaging the foreign matters on the inspection route. In another application scenario, when the processing by the mounting device 10 is not available, the processing is performed manually, and the ground staff may not know the condition of the abnormal line well due to the problem of view. Also, in some cases, animals such as birds may be parked on the tower. Thus, in some embodiments, it is contemplated that the drone 30 may further include a speaker 36 for transmitting a boot password to the ground or playing high frequency drive away audio to wildlife on the patrol route.
The above embodiments are only exemplary embodiments of the present invention, and are not intended to limit the present invention, and the scope of the present invention is defined by the claims. Various modifications and equivalents may be made by those skilled in the art within the spirit and scope of the present invention, and such modifications and equivalents should also be considered as falling within the scope of the present invention.
Claims (10)
1. The unmanned aerial vehicle power grid line patrol control method comprises the following steps:
downloading map information of a routing inspection area, and setting a routing inspection flight route according to tower position information of the map information;
carrying out inspection flight according to a set inspection flight route, acquiring image data of an inspection line and judging whether abnormality exists, and if the abnormality exists, returning abnormal information to a remote control center;
when the routing inspection flight line is used for routing inspection flight, whether the theoretical endurance of the unmanned aerial vehicle is enough to complete the flight inspection task or not is judged in real time, and if the theoretical endurance of the unmanned aerial vehicle cannot be completed, a stop station within a communication range is searched.
2. The method of claim 1, wherein the system is initialized by power-up before the map information of the inspection area is downloaded, and after the initialization is successful, the system is in communication connection with the remote control center.
3. The method according to claim 1, further comprising establishing a communication connection with a ground control vehicle when establishing a communication connection with a remote control center, the ground control vehicle comprising at least a second communication unit for establishing a communication connection with the first communication unit of the drone and a control intervention unit configured to perform manual intervention on the mission of the drone according to user operation.
4. The method according to claim 1, wherein returning the abnormal information further comprises returning the abnormal information to the ground control vehicle, and the remote control center forwards the abnormal information to a mobile terminal carried by a worker when receiving the abnormal information.
5. The method according to claim 1, downloading map information of an inspection area, wherein the map information represents a preset inspection area and at least comprises tower position information on an inspection line, and the remote control center further comprises a path planning unit, wherein the path planning unit is configured to plan an inspection flight line based on a linear regression algorithm according to the tower position information of the corresponding preset inspection area downloaded by the unmanned aerial vehicle; and the unmanned aerial vehicle performs inspection flight according to the inspection flight route.
6. The method of claim 5, wherein the linear regression algorithm is a regression line algorithm.
7. The method according to claim 5, wherein the path planning unit is configured to establish a projection coordinate system by using the map information when planning a patrol flight route, use the remote control center as an origin, use a geographic azimuth as a horizontal axis and a vertical axis of the projection coordinate system, project geographic position information of the tower as a scatter point on the projection coordinate system, perform linear fitting based on a least square method for the scatter point, and set a maximum dispersion of the linear fitting to be smaller than a visual range of the image acquisition unit when performing the linear fitting.
8. The method of claim 1, finding a stop within communication range, comprising:
modifying the routing inspection flight path, and stopping to the nearest stop station according to the laser guidance;
and starting the standby unmanned aerial vehicle at the stop station to continue to perform inspection flight according to the planned flight route.
9. The method of claim 1, determining whether an anomaly exists, comprising:
the method comprises the steps that collected image data of an inspection line are uploaded to a cloud server, the cloud server at least comprises an image analysis unit and a first storage unit, and the image analysis unit is configured to be an image analysis unit which analyzes the image data collected by the image collection unit to obtain abnormal information; the first storage unit is configured to store an image frame containing abnormality information.
10. The method of claim 9, wherein when the image analysis unit of the cloud server determines that an abnormal situation occurs, the image analysis unit stores an image frame containing abnormal information into the first storage unit, and feeds the abnormal situation back to a remote control center and a ground control vehicle respectively.
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| CN113628499A (en) * | 2021-09-02 | 2021-11-09 | 浙江图盛输变电工程有限公司温州科技分公司 | Collaborative virtual operation training platform for unmanned aerial vehicle power grid operation and inspection |
| CN114326807A (en) * | 2021-12-29 | 2022-04-12 | 宁夏超高压电力工程有限公司 | Unmanned aerial vehicle substation inspection method and system and readable storage medium |
| CN114527782A (en) * | 2021-11-19 | 2022-05-24 | 嘉兴恒创电力设计研究院有限公司 | Unmanned aerial vehicle flight path planning method and system based on power grid map |
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