CN115986921A - Power distribution network inspection method and device, computer equipment and storage medium - Google Patents
Power distribution network inspection method and device, computer equipment and storage medium Download PDFInfo
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- CN115986921A CN115986921A CN202211595215.3A CN202211595215A CN115986921A CN 115986921 A CN115986921 A CN 115986921A CN 202211595215 A CN202211595215 A CN 202211595215A CN 115986921 A CN115986921 A CN 115986921A
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Abstract
The application relates to a power distribution network routing inspection method, a power distribution network routing inspection device, computer equipment and a storage medium. The method comprises the following steps: according to the power distribution network inspection method, line data, environment data, inspection unmanned aerial vehicle information and inspection tasks of a power distribution network to be inspected are obtained; processing the line data, the environment data, the information of the inspection unmanned aerial vehicle and the inspection task by applying a strategy output model to obtain an unmanned aerial vehicle control strategy; the unmanned aerial vehicle control strategy at least comprises an unmanned aerial vehicle inspection strategy; according to the unmanned aerial vehicle control strategy, the unmanned aerial vehicle is controlled to patrol the power distribution network to be patrolled and examined. In this application, owing to can obtain unmanned aerial vehicle through applying strategy output model and control the strategy, and then, control the unmanned aerial vehicle through unmanned aerial vehicle and treat to patrol and examine the distribution network and patrol and examine, compare in the manual work mode of patrolling and examining, control strategy control unmanned aerial vehicle through unmanned aerial vehicle and patrol and examine, when reduce cost, improved and treated to patrol and examine the efficiency that the distribution network was patrolled and examined.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to a method and an apparatus for routing inspection of a power distribution network, a computer device, and a storage medium.
Background
In recent years, in the power industry, inspection of a power distribution network is indispensable.
At present, inspection of power distribution network equipment and power distribution network equipment operating environment needs to be manually performed, for example, defects such as insulator damage, spacer slippage, pin nut loss, hardware fitting or wire clamp heating and the like in the power distribution network equipment are manually inspected, potential safety hazards such as illegal buildings, illegal trees, mechanical construction and the like in a power transmission channel in the power distribution network equipment operating environment are manually inspected, the manual inspection mode is high in cost, and the inspection efficiency of the power distribution network is low.
Therefore, how to improve the routing inspection efficiency of the power distribution network while reducing the routing inspection cost is a technical problem which needs to be solved urgently.
Disclosure of Invention
In view of the foregoing, it is necessary to provide an efficient power distribution network inspection method, device, computer device, and storage medium.
In a first aspect, the application provides a method for routing inspection of a power distribution network, which includes:
acquiring line data, environment data, inspection unmanned aerial vehicle information and inspection tasks of a power distribution network to be inspected;
processing the line data, the environment data, the information of the inspection unmanned aerial vehicle and the inspection task by applying a strategy output model to obtain an unmanned aerial vehicle control strategy; the unmanned aerial vehicle control strategy at least comprises an unmanned aerial vehicle inspection strategy;
according to the unmanned aerial vehicle control strategy, the unmanned aerial vehicle is controlled to patrol the power distribution network to be patrolled.
In one embodiment, the method for processing the line data, the environment data, the patrol unmanned aerial vehicle information and the patrol task by applying the policy output model to obtain the unmanned aerial vehicle control policy comprises the following steps:
performing normalization processing on the line data, the environment data, the inspection unmanned aerial vehicle information and the inspection task to obtain target data;
and processing the target data by applying a strategy output model to obtain an unmanned aerial vehicle control strategy.
In one embodiment, the unmanned aerial vehicle routing inspection strategy comprises: at least one of a power distribution network visual identification inspection strategy, a power distribution network modeling inspection strategy, a power distribution network remote inspection strategy, an unmanned aerial vehicle inspection control strategy and an unmanned aerial vehicle inspection communication strategy.
In one of them embodiment, according to unmanned aerial vehicle control strategy, control unmanned aerial vehicle treats that it patrols and examines the distribution network and patrol and examine, include:
controlling a visual module carried by an unmanned aerial vehicle to acquire visual data of the power distribution network according to a visual identification routing inspection strategy of the power distribution network;
identifying visual characteristics of the routing inspection line corresponding to the visual data of the power distribution network;
and determining a power distribution network inspection result according to the visual characteristics of the inspection line.
In one of them embodiment, according to unmanned aerial vehicle control strategy, control unmanned aerial vehicle treats that it patrols and examines the distribution network and patrol and examine, include:
according to a power distribution network modeling and inspection strategy, three-dimensional modeling is carried out on inspection data acquired in the inspection process of the unmanned aerial vehicle, and a power distribution network model is obtained;
determining the working condition of the routing inspection line according to the power distribution network model, and determining the cross spanning characteristics of the routing inspection line according to the working condition of the routing inspection line;
and determining a power distribution network inspection result according to the cross spanning characteristics of the inspection line.
In one embodiment, the method further comprises the following steps:
adjusting the unmanned aerial vehicle control strategy according to the power distribution network inspection result;
and updating and training the application strategy output model based on the line data, the environment data, the inspection unmanned aerial vehicle information, the inspection task and the adjusted unmanned aerial vehicle control strategy.
In a second aspect, the application further provides an inspection device for the power distribution network. The device includes:
the system comprises an acquisition module, a routing module and a routing module, wherein the acquisition module is used for acquiring line data, environment data, routing inspection unmanned aerial vehicle information and routing inspection tasks of a power distribution network to be routed;
the processing module is used for processing the line data, the environment data, the information of the inspection unmanned aerial vehicle and the inspection task by applying the strategy output model to obtain an unmanned aerial vehicle control strategy; the unmanned aerial vehicle control strategy at least comprises an unmanned aerial vehicle inspection strategy;
and the control module is used for controlling the unmanned aerial vehicle to patrol the power distribution network to be patrolled according to the unmanned aerial vehicle control strategy.
In a third aspect, the present application also provides a computer device. The computer device comprises a memory and a processor, the memory stores a computer program, and the processor realizes the following steps when executing the computer program:
acquiring line data, environment data, inspection unmanned aerial vehicle information and inspection tasks of a power distribution network to be inspected;
processing the line data, the environment data, the inspection unmanned aerial vehicle information and the inspection task by applying a strategy output model to obtain an unmanned aerial vehicle control strategy; the unmanned aerial vehicle control strategy at least comprises an unmanned aerial vehicle inspection strategy;
according to the unmanned aerial vehicle control strategy, the unmanned aerial vehicle is controlled to patrol the power distribution network to be patrolled.
In a fourth aspect, the present application further provides a computer-readable storage medium. The computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of:
acquiring line data, environment data, inspection unmanned aerial vehicle information and inspection tasks of a power distribution network to be inspected;
processing the line data, the environment data, the information of the inspection unmanned aerial vehicle and the inspection task by applying a strategy output model to obtain an unmanned aerial vehicle control strategy; the unmanned aerial vehicle control strategy at least comprises an unmanned aerial vehicle inspection strategy;
according to the unmanned aerial vehicle control strategy, the unmanned aerial vehicle is controlled to patrol the power distribution network to be patrolled.
In a fifth aspect, the present application further provides a computer program product. The computer program product comprising a computer program which when executed by a processor performs the steps of:
acquiring line data, environment data, inspection unmanned aerial vehicle information and inspection tasks of a power distribution network to be inspected;
processing the line data, the environment data, the information of the inspection unmanned aerial vehicle and the inspection task by applying a strategy output model to obtain an unmanned aerial vehicle control strategy; the unmanned aerial vehicle control strategy at least comprises an unmanned aerial vehicle inspection strategy;
according to the unmanned aerial vehicle control strategy, the unmanned aerial vehicle is controlled to patrol the power distribution network to be patrolled.
According to the method and the device for patrolling the power distribution network, the computer equipment and the storage medium, line data, environment data, patrolling unmanned aerial vehicle information and patrolling tasks of the power distribution network to be patrolled and examined are obtained; processing the line data, the environment data, the information of the inspection unmanned aerial vehicle and the inspection task by applying a strategy output model to obtain an unmanned aerial vehicle control strategy; the unmanned aerial vehicle control strategy at least comprises an unmanned aerial vehicle inspection strategy; according to the unmanned aerial vehicle control strategy, the unmanned aerial vehicle is controlled to patrol the power distribution network to be patrolled. In this application, owing to can obtain unmanned aerial vehicle through applying strategy output model and control the strategy, and then, control the strategy through unmanned aerial vehicle and can control unmanned aerial vehicle and treat to patrol and examine the distribution network and patrol and examine, compare in the manual work mode of patrolling and examining, control strategy through unmanned aerial vehicle and control unmanned aerial vehicle and patrol and examine, when reduce cost, improved and treated the efficiency of patrolling and examining the distribution network and patrolling and examining.
Drawings
Fig. 1 is an application environment diagram of a routing inspection method for a power distribution network according to this embodiment;
fig. 2 is a schematic flow chart of a first method for routing inspection of a power distribution network according to this embodiment;
fig. 3 is a schematic flowchart of a method for obtaining an unmanned aerial vehicle control policy according to this embodiment;
fig. 4 is a schematic flow chart of a first method for controlling an unmanned aerial vehicle to patrol a power distribution network to be patrolled, provided by this embodiment;
fig. 5 is a schematic flow chart of a second method for controlling an unmanned aerial vehicle to patrol a power distribution network to be patrolled according to this embodiment;
fig. 6 is a schematic flow diagram of a second method for routing inspection of a power distribution network according to this embodiment;
fig. 7 is a block diagram of an inspection device for a power distribution network according to the present embodiment;
fig. 8 is an internal structural diagram of the computer device provided in the present embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more clearly understood, the present application is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
An embodiment of the present application provides a computer device, which may be a terminal, and an internal structure diagram of the computer device may be as shown in fig. 1. The computer apparatus includes a processor, a memory, an input/output interface, a communication interface, a display unit, and an input device. The processor, the memory and the input/output interface are connected by a system bus, and the communication interface, the display unit and the input device are connected by the input/output interface to the system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The input/output interface of the computer device is used for exchanging information between the processor and an external device. The Communication interface of the computer device is used for performing wired or Wireless Communication with an external terminal, and the Wireless Communication may be implemented by Wireless-Fidelity (WIFI), a mobile cellular network, near Field Communication (NFC), or other technologies. The computer program is executed by a processor to implement a power scheduling method. The display unit of the computer device is used for forming a visual picture and can be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on a shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.
In one embodiment, as shown in fig. 2, there is provided a method for polling a power distribution network, applied to the terminal shown in fig. 1, the method including the following steps:
s201, line data and environment data of the power distribution network to be patrolled and examined, information of the unmanned aerial vehicle to be patrolled and examined and a patrolling task are obtained.
Optionally, in this embodiment, the power distribution network to be inspected is a power distribution network prepared for inspection, and the line data of the power distribution network to be inspected refers to data related to a line in the power distribution network to be inspected, for example, a condition of an insulator in the line of the power distribution network device. The environmental data of the power distribution network to be inspected refers to data related to the operating environment of the power distribution network to be inspected. Such as construction violations, trees violations, mechanical work, etc. within the power transmission channel. Patrol and examine unmanned aerial vehicle information refers to the information in the aspects such as the specification, model and the function of the unmanned aerial vehicle that is used for patrolling and examining of preparation. And the polling task controls the unmanned aerial vehicle to perform polling tasks. For example, the unmanned aerial vehicle is controlled to carry out tasks such as transmission line disaster patrol, emergency repair, live detection and intelligent auxiliary maintenance operation.
In this embodiment, to the distribution network that waits to patrol and examine, can wait to patrol and examine the image of distribution network through the sensor collection of arranging in the unmanned aerial vehicle, analyze this image, can acquire line data, the environmental data of this distribution network that waits to patrol and examine. Can acquire to patrol and examine unmanned aerial vehicle information according to terminal and unmanned aerial vehicle's interaction. The inspection task information of the unmanned aerial vehicle can be acquired in a mode of inputting the inspection task information to the terminal by the user.
S202, processing the line data, the environment data, the information of the inspection unmanned aerial vehicle and the inspection task by applying the strategy output model to obtain an unmanned aerial vehicle control strategy.
Wherein, unmanned aerial vehicle controls the tactics and includes unmanned aerial vehicle at least and patrols and examines the tactics.
Optionally, the application of the policy output model refers to reasoning the line data, the environment data, the information of the unmanned aerial vehicle for inspection, the information of the inspection task and the like of the power distribution network, and then, outputting the model of the unmanned aerial vehicle control policy.
In this embodiment, the unmanned aerial vehicle control strategy is a strategy for controlling the operation of the unmanned aerial vehicle. The unmanned aerial vehicle control strategy can comprise an unmanned aerial vehicle inspection strategy, wherein the unmanned aerial vehicle inspection strategy refers to a strategy for controlling the unmanned aerial vehicle to inspect.
Optionally, the unmanned aerial vehicle routing inspection strategy includes: at least one of a power distribution network visual identification inspection strategy, a power distribution network modeling inspection strategy, a power distribution network remote inspection strategy, an unmanned aerial vehicle inspection control strategy and an unmanned aerial vehicle inspection communication strategy.
Optionally, the power distribution network visual identification inspection strategy is a strategy for fusing an unmanned aerial vehicle high-precision positioning technology and a visual tracking technology to realize high-definition image accurate acquisition of distribution line equipment. The power distribution network modeling inspection strategy is a strategy for obtaining the working condition of an inspection line by calculating a three-dimensional model and determining the cross spanning characteristics of the inspection line based on the working condition of the inspection line. The power distribution network remote inspection strategy can be a strategy that an unmanned aerial vehicle carries out remote control on a power distribution line in a power distribution network. The unmanned aerial vehicle inspection control strategy can be a strategy corresponding to large-scale emergency disaster investigation and inspection of the power distribution network by fixed-wing unmanned aerial vehicle control. The unmanned aerial vehicle inspection communication strategy can be a light-weight distribution network unmanned aerial vehicle autonomous inspection corresponding strategy based on 5G and Beidou.
In this embodiment, can be with the line data of distribution network, environmental data, patrol and examine information such as unmanned aerial vehicle information and the task of patrolling and examining input to application strategy output model, this application strategy output model reason the line data of distribution network, environmental data, patrol and examine information such as unmanned aerial vehicle information and the task of patrolling and examining, and then, output at least one kind of tactics in distribution network visual identification patrol and examine tactics, the distribution network modeling patrol and examine tactics, the long-range tactics of patrolling and examining of distribution network, unmanned aerial vehicle patrol and examine control strategy and unmanned aerial vehicle patrol and examine communication strategy.
S203, controlling the unmanned aerial vehicle to patrol the power distribution network to be patrolled according to the unmanned aerial vehicle control strategy.
Optionally, after at least one unmanned aerial vehicle control strategy output through the application strategy output model, a control instruction can be generated based on the unmanned aerial vehicle control strategy output by the application strategy output model, and the instruction is sent to the unmanned aerial vehicle to control the unmanned aerial vehicle to patrol the power distribution network to be patrolled.
According to the power distribution network inspection method, line data, environment data, inspection unmanned aerial vehicle information and inspection tasks of a power distribution network to be inspected are obtained; processing the line data, the environment data, the information of the inspection unmanned aerial vehicle and the inspection task by applying a strategy output model to obtain an unmanned aerial vehicle control strategy; the unmanned aerial vehicle control strategy at least comprises an unmanned aerial vehicle inspection strategy; according to the unmanned aerial vehicle control strategy, the unmanned aerial vehicle is controlled to patrol the power distribution network to be patrolled. In this application, owing to can obtain unmanned aerial vehicle through applying strategy output model and control the strategy, and then, control the unmanned aerial vehicle through unmanned aerial vehicle and treat to patrol and examine the distribution network and patrol and examine, compare in the manual work mode of patrolling and examining, control strategy control unmanned aerial vehicle through unmanned aerial vehicle and patrol and examine, when reduce cost, improved and treated to patrol and examine the efficiency that the distribution network was patrolled and examined.
In practical application, the unmanned aerial vehicle control strategy can further comprise a power distribution network operation and maintenance strategy. The power distribution network operation and maintenance strategy refers to a strategy for maintaining the power distribution network through the unmanned aerial vehicle. Optionally, the strategy output model is applied to reasoning line data, environment data, information of the inspection unmanned aerial vehicle and inspection tasks, a power distribution network operation and maintenance strategy is output, and the unmanned aerial vehicle can be controlled to maintain the power distribution network through the power distribution network operation and maintenance strategy.
In an optional implementation mode, after the unmanned aerial vehicle patrols and examines the power distribution network to be patrolled and examined to obtain a patrolling result, the unmanned aerial vehicle can update and train the application strategy output model. Optionally, the unmanned aerial vehicle control strategy can be adjusted according to the power distribution network inspection result; and updating and training the application strategy output model based on the line data, the environmental data, the information of the inspection unmanned aerial vehicle, the inspection task and the adjusted unmanned aerial vehicle control strategy.
In practical application, the unmanned aerial vehicle patrols and examines the power distribution network to be patrolled and examined to obtain a patrolling result, an error may exist between the patrolling result and an actual real patrolling result of the power distribution network to be patrolled and examined, and this embodiment can adjust inaccurate parameters existing in an unmanned aerial vehicle control strategy, so as to obtain the line data, the environmental data, the information of the patrolling and examined unmanned aerial vehicle and an accurate unmanned aerial vehicle control strategy corresponding to a patrolling and examining task, for example, the flight direction of the unmanned aerial vehicle and parameters such as the distance between the unmanned aerial vehicle and a target in the unmanned aerial vehicle control strategy are adjusted, and the application strategy output model is updated and trained based on the line data, the environmental data, the information of the patrolling and examining unmanned aerial vehicle and the patrolling and examining task, and the corresponding unmanned aerial vehicle control strategy after parameter adjustment is used for updating and training the application strategy output model, so that the high-accuracy of the patrolling and examining result of the power distribution network by the unmanned aerial vehicle can be ensured.
On the basis of the foregoing embodiment, in order to understand the obtaining of the unmanned aerial vehicle control policy in S202, the following implementation manner for obtaining the unmanned aerial vehicle control policy is provided in this embodiment, and specifically as shown in fig. 3, the implementation manner includes the following steps:
s301, carrying out normalization processing on the line data, the environment data, the information of the inspection unmanned aerial vehicle and the inspection task to obtain target data.
Optionally, after line data of the power distribution network to be patrolled and examined, data of the environment where the power distribution network to be patrolled and examined are located, and information of the patrol unmanned aerial vehicle and the patrol task are collected, the line data, the environment data, the information of the patrol unmanned aerial vehicle and the patrol task can be cleaned, normalization processing is carried out on the cleaned line data, environment data, the information of the patrol unmanned aerial vehicle and data corresponding to the patrol task, target data with standard formatting is obtained, and the target data can be conveniently identified by applying a strategy output model.
S302, processing the target data by applying the strategy output model to obtain the unmanned aerial vehicle control strategy.
Optionally, the target data is identified and inferred by the application strategy output model, and the unmanned aerial vehicle application strategy of the power distribution network to be patrolled and examined is output.
In this embodiment, through carrying out the normalization to line data, environmental data, patrol and examine unmanned aerial vehicle information and patrol and examine the task, obtain the target data, guaranteed the accuracy of target data, and then, handle the target data through applying the strategy output model, can obtain comparatively accurate unmanned aerial vehicle and control the strategy.
In practical application, before the application strategy output model is applied, the application strategy output model needs to be trained, and the specific training process comprises the steps of obtaining line data, environment data, inspection unmanned aerial vehicle information, inspection task and other historical service data of the power distribution network, cleaning the service data, and carrying out normalization processing on the cleaned historical service data to obtain the historical service data with a standard format. And acquiring the historical inspection strategy of the unmanned aerial vehicle corresponding to the historical service data in the standard format. Inputting historical service data into an original strategy output model, reasoning the input historical service data by the original strategy output model, outputting a historical prediction routing inspection strategy of the unmanned aerial vehicle, calculating a loss function between the historical routing inspection strategy of the unmanned aerial vehicle and the historical prediction routing inspection strategy of the unmanned aerial vehicle, and performing iterative training on the original strategy output model according to the loss function; and obtaining the application strategy output model until the original strategy output model after iterative training is converged.
For the further to unmanned aerial vehicle treat to patrol and examine the power distribution network understand, this embodiment gives a control unmanned aerial vehicle and treats to patrol and examine the power distribution network and carry out the realizable mode of patrolling and examining, specifically as shown in fig. 4, include following step:
s401, controlling a visual module carried by the unmanned aerial vehicle to acquire visual data of the power distribution network according to a power distribution network visual identification routing inspection strategy.
Optionally, the visual module is a module for acquiring a visual image related to the power distribution network. For example, a camera module, a laser radar module, and the like are possible. The power distribution network visual identification inspection strategy can be a strategy corresponding to a front end identification following wire flight self-adaptive inspection mode and a strategy corresponding to an autonomous fine inspection mode of a multi-rotor unmanned aerial vehicle. Specifically, can follow the strategy that wire flight self-adaptation patrols and examines the mode and correspond through the front end discernment, the camera module that the intelligent chip that control unmanned aerial vehicle carried on corresponds, treat to patrol and examine the circuit of patrolling and examining of distribution network and gather in real time to acquire the distribution network visual data that corresponds including the image of patrolling and examining the circuit. Or, can independently become more meticulous through the strategy that many rotor unmanned aerial vehicle made a fine tour that the mode corresponds, the laser radar module of control unmanned aerial vehicle lift-launch, independently treat to patrol and examine the distribution network and make a fine tour, gather the point cloud data that the distribution network visual data that includes the circuit of patrolling and examining corresponds.
S402, identifying visual characteristics of the routing inspection line corresponding to the visual data of the power distribution network.
Optionally, the visual features refer to observable surface features involved in the inspection line in the inspection image.
In this embodiment, suppose that the power distribution network is patrolled and examined based on the strategy that front end identification follow wire flight self-adaptation patrols and examines the mode and corresponds, can be after obtaining power distribution network visual data, the circuit of patrolling and examining in the patrol and examine image that the discernment power distribution network visual data corresponds to obtain the visual characteristic of patrolling and examining the circuit. After the power distribution network visual data are obtained based on the strategy corresponding to the autonomous fine inspection mode of the multi-rotor unmanned aerial vehicle, the high-precision point cloud data of the inspection line can be identified after the power distribution network visual data are obtained.
Specifically, aiming at the visual data of the power distribution network, the visual characteristics of the routing inspection line are extracted from the visual data of the power distribution network through a data extraction algorithm, or a model for extracting the visual characteristics of the routing inspection line is trained in advance to reason the visual data of the power distribution network based on the model, so that the visual characteristics of the routing inspection line can be obtained.
For example, for high-precision laser point cloud data, a three-dimensional map model can be constructed by using the high-precision laser point cloud data in a line corridor as a basis, and spatial parameters corresponding to key features such as tower components and the like are extracted through the three-dimensional map model to obtain visual features such as simulated flight and air routes.
And S403, determining a power distribution network inspection result according to the visual characteristics of the inspection line.
Optionally, after the visual characteristics of the routing inspection line are obtained, it may be determined whether the routing inspection line includes characteristics such as line obstacles and potential safety hazards of the line environment. For example, the method can be used for identifying whether equipment defects such as wireless head sticks, damaged insulators, spacer bar slippage, pin and nut loss, hardware fittings or wire clamps heating and the like exist under towers in a power distribution network, and whether safety hazards exist in illegal buildings, illegal trees, mechanical construction and the like in a power transmission channel.
In this embodiment, based on distribution network visual identification patrols and examines the tactics, the visual module that control unmanned aerial vehicle carried on gathers distribution network visual data, and is concrete, can control unmanned aerial vehicle and carry out accurate collection to distribution lines equipment to based on the data of gathering, confirm to patrol and examine whether including characteristics such as the potential safety hazard of circuit obstacle and circuit environment in the circuit, very big improvement unmanned aerial vehicle efficiency and the benefit of patrolling and examining like this, be favorable to promoting unmanned aerial vehicle independently to patrol and examine popularization and application.
Optionally, this embodiment provides the achievable way that the second control unmanned aerial vehicle patrols and examines the distribution network of treating patrolling and examining, specifically as shown in fig. 5, includes following step:
s501, carrying out three-dimensional modeling on the inspection data acquired in the inspection process of the unmanned aerial vehicle according to a power distribution network modeling inspection strategy to obtain a power distribution network model.
Optionally, the power distribution network modeling inspection strategy may be a strategy corresponding to a distribution network line crossing measurement inspection mode based on unmanned aerial vehicle modeling. The method can control the unmanned aerial vehicle P4-RTK to collect a target line based on a strategy corresponding to a distribution network line cross crossing measurement routing inspection mode modeled by the unmanned aerial vehicle, and three-dimensional modeling is carried out on collected routing inspection data to obtain a distribution network model.
S502, determining the working condition of the routing inspection line according to the power distribution network model, and determining the cross spanning characteristic of the routing inspection line according to the working condition of the routing inspection line.
Optionally, the power distribution network model is operated through a preset software algorithm to obtain the working condition of the routing inspection line, and the cross spanning characteristic of the routing inspection line is determined based on the working condition of the routing inspection line. Specifically, the LiPowerline software is used for analyzing the working condition of the routing inspection line, and the cross span of the line can be accurately measured.
S503, determining a power distribution network inspection result according to the cross spanning characteristics of the inspection line.
In the method and the device, whether the cross crossing phenomenon exists between the inspection lines can be judged according to the cross crossing characteristics of the inspection lines, and if the cross crossing phenomenon exists, the characteristics of potential safety hazards and the like of line obstacles and line environments in the inspection lines can be determined.
In the application, according to a power distribution network modeling inspection strategy, the cross spanning characteristic of the unmanned aerial vehicle inspection distribution network line is obtained, and the efficiency of obtaining the cross spanning characteristic of the inspection line is improved.
In practical application, the unmanned aerial vehicle can be controlled to patrol the disaster area based on a strategy corresponding to a large-scale emergency disaster investigation and patrol mode of the distribution network of the fixed-wing unmanned aerial vehicle. Specifically, the unmanned aerial vehicle carries a 1920P × 1080P optical zoom visible light CMOS sensor with the resolution 30 times, so that the remote target observation capability is improved; or the unmanned aerial vehicle carries an uncooled focal plane thermal imaging sensor, so that the unmanned aerial vehicle has the night target detection capability; shooting a line target in real time to obtain evidence; and to target data record storage, be convenient for afterwards analysis and save, can realize unmanned aerial vehicle and patrol and examine in the universe of joining in marriage net, solve the emergent problem of patrolling and examining behind the natural disasters such as earthquake, mud-rock flow, mountain fire, serious icing.
Optionally, the unmanned aerial vehicle is controlled to patrol the patrol line based on a strategy corresponding to the autonomous patrol mode of the intelligent unmanned aerial vehicle nest of the distribution line. Power supply unmanned on duty airports (machine nests) are respectively arranged at two ends of the transformer substation, a central control system is arranged in the machine nests, the machine nests are arranged at two ends of the transformer substation and used for placing unmanned aerial vehicles, and charging piles, meteorological stations and data transmission modules are arranged in the machine nests. The unmanned aerial vehicle is controlled to execute the polling task through the central control system, specifically, the central control system is established to control the unmanned aerial vehicle to automatically start up, take off and autonomously patrol and check according to a preset air route from a nest for flying, the unmanned aerial vehicle can be carried with a high-resolution sensor to control the unmanned aerial vehicle to acquire distribution line data, and the unmanned aerial vehicle can accurately land in different places (including other nests) after the task is completed; the control nest is used for automatically charging the unmanned aerial vehicle and automatically transmitting data; and the control cloud end automatically and intelligently analyzes data and automatically uploads results to the control platform, so that intelligent control of multi-machine collaborative autonomous inspection is realized. The defects and hidden dangers in the data collected by inspection can be automatically identified by using an artificial intelligence identification technology, data statistics, analysis and recording are carried out in real time, early warning is actively predicted, and auxiliary decision is provided for distribution line management.
Optionally, the unmanned aerial vehicle is controlled to inspect the inspection line based on a strategy corresponding to an autonomous inspection mode of the light distribution network unmanned aerial vehicle of 5G and Beidou, and specifically, the unmanned aerial vehicle autonomous inspection mobile application realizes task execution; providing edge end guarantee capability based on an unmanned aerial vehicle ground station device and an AI control terminal; the autonomous inspection control platform realizes remote control and stronger computing power; the accurate position service network and the 5G communication network provide network guarantee for positioning and communication.
On the basis of the foregoing embodiments, this embodiment provides an optional implementation manner of a routing inspection method for a power distribution network, and as shown in fig. 6, the method includes the following steps:
s601, obtaining line data and environment data of the power distribution network to be patrolled and examined, patrolling and examining unmanned aerial vehicle information and patrolling and examining tasks.
S602, carrying out normalization processing on the line data, the environment data, the inspection unmanned aerial vehicle information and the inspection task to obtain target data.
And S603, processing the target data by applying the strategy output model to obtain the unmanned aerial vehicle control strategy.
Optionally, the unmanned aerial vehicle routing inspection strategy includes: at least one of a power distribution network visual identification inspection strategy, a power distribution network modeling inspection strategy, a power distribution network remote inspection strategy, an unmanned aerial vehicle inspection control strategy and an unmanned aerial vehicle inspection communication strategy.
S604, controlling a visual module carried by the unmanned aerial vehicle to acquire visual data of the power distribution network according to a power distribution network visual identification routing inspection strategy in the unmanned aerial vehicle control strategy.
And S605, identifying the visual characteristics of the routing inspection line corresponding to the visual data of the power distribution network.
S606, determining a power distribution network inspection result according to the visual characteristics of the inspection line.
S607, the unmanned aerial vehicle control strategy is adjusted according to the power distribution network inspection result.
S607, updating and training the application strategy output model based on the line data, the environment data, the inspection unmanned aerial vehicle information, the inspection task and the adjusted unmanned aerial vehicle control strategy.
Optionally, besides determining the power distribution network inspection result in the above-mentioned manner of S604-S606, determining the power distribution network inspection result in an implementation manner may further include
The method comprises the steps of firstly, carrying out three-dimensional modeling on routing inspection data acquired in the routing inspection process of the unmanned aerial vehicle according to a power distribution network modeling routing inspection strategy to obtain a power distribution network model.
And step two, determining the working condition of the routing inspection line according to the power distribution network model, and determining the cross spanning characteristic of the routing inspection line according to the working condition of the routing inspection line.
And step three, determining a power distribution network inspection result according to the cross spanning characteristics of the inspection line.
It should be understood that, although the steps in the flowcharts related to the embodiments as described above are sequentially displayed as indicated by arrows, the steps are not necessarily performed sequentially as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a part of the steps in the flowcharts related to the embodiments described above may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, and the execution order of the steps or stages is not necessarily sequential, but may be rotated or alternated with other steps or at least a part of the steps or stages in other steps.
Based on the same inventive concept, the embodiment of the application also provides a power distribution network inspection device for realizing the power dispatching method. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme and the beneficial effect recorded in the method, so that specific limitations in one or more embodiments of the power scheduling device provided below can refer to the limitations in the above power scheduling method, and are not described again here.
In one embodiment, as shown in fig. 7, there is provided an inspection apparatus 1 for a power distribution network, including:
the acquiring module 701 is used for acquiring line data, environment data, information of the inspection unmanned aerial vehicle and inspection tasks of the power distribution network to be inspected;
the processing module 702 is configured to process the line data, the environment data, the information of the inspection unmanned aerial vehicle and the inspection task by applying the policy output model, so as to obtain an unmanned aerial vehicle control policy; the unmanned aerial vehicle control strategy at least comprises an unmanned aerial vehicle inspection strategy;
and the control module 703 is used for controlling the unmanned aerial vehicle to patrol the power distribution network to be patrolled according to the unmanned aerial vehicle control strategy.
In one embodiment, the processing module 702 is specifically configured to:
performing normalization processing on the line data, the environment data, the inspection unmanned aerial vehicle information and the inspection task to obtain target data;
and processing the target data by applying a strategy output model to obtain an unmanned aerial vehicle control strategy.
In one embodiment, the unmanned aerial vehicle routing inspection strategy comprises: the power distribution network visual identification polling strategy, the power distribution network modeling polling strategy, the power distribution network remote polling strategy, the unmanned aerial vehicle polling control strategy and the unmanned aerial vehicle polling communication strategy.
In one embodiment, the control module 703 includes:
the control unit is used for controlling a visual module carried by the unmanned aerial vehicle to acquire visual data of the power distribution network according to the visual identification routing inspection strategy of the power distribution network;
the identification unit is used for identifying the visual characteristics of the routing inspection line corresponding to the visual data of the power distribution network;
and the first determining unit is used for determining the power distribution network inspection result according to the visual characteristics of the inspection line.
In one embodiment, the control module 703 includes:
the modeling unit is used for carrying out three-dimensional modeling on the routing inspection data acquired in the routing inspection process of the unmanned aerial vehicle according to a power distribution network modeling routing inspection strategy to obtain a power distribution network model;
the second determining unit is used for determining the working condition of the routing inspection line according to the power distribution network model and determining the cross spanning characteristics of the routing inspection line according to the working condition of the routing inspection line;
and the third determining unit is used for determining the power distribution network inspection result according to the cross spanning characteristics of the inspection line.
In one embodiment, the system further includes an update module, where the update module is specifically configured to:
adjusting the unmanned aerial vehicle control strategy according to the power distribution network inspection result;
and updating and training the application strategy output model based on the line data, the environmental data, the information of the inspection unmanned aerial vehicle, the inspection task and the adjusted unmanned aerial vehicle control strategy.
Each module in the power scheduling apparatus may be wholly or partially implemented by software, hardware, and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as shown in fig. 8. The computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless communication can be realized through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. The computer program is executed by a processor to implement the power scheduling method. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on a shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.
It will be appreciated by those skilled in the art that the configuration shown in fig. 8 is a block diagram of only a portion of the configuration associated with the present application, and is not intended to limit the computing device to which the present application may be applied, and that a particular computing device may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided, comprising a memory and a processor, the memory having a computer program stored therein, the processor implementing the following steps when executing the computer program:
acquiring line data, environment data, inspection unmanned aerial vehicle information and inspection tasks of a power distribution network to be inspected; processing the line data, the environment data, the information of the inspection unmanned aerial vehicle and the inspection task by applying a strategy output model to obtain an unmanned aerial vehicle control strategy; the unmanned aerial vehicle control strategy at least comprises an unmanned aerial vehicle inspection strategy; according to the unmanned aerial vehicle control strategy, the unmanned aerial vehicle is controlled to patrol the power distribution network to be patrolled and examined.
In one embodiment, the method includes the steps of processing line data, environment data, inspection unmanned aerial vehicle information and inspection tasks by applying a strategy output model to obtain an unmanned aerial vehicle control strategy, and includes the following steps: performing normalization processing on the line data, the environment data, the inspection unmanned aerial vehicle information and the inspection task to obtain target data; and processing the target data by applying a strategy output model to obtain an unmanned aerial vehicle control strategy.
In one embodiment, the unmanned aerial vehicle routing inspection strategy comprises: the power distribution network visual identification polling strategy, the power distribution network modeling polling strategy, the power distribution network remote polling strategy, the unmanned aerial vehicle polling control strategy and the unmanned aerial vehicle polling communication strategy.
In one of them embodiment, according to unmanned aerial vehicle control strategy, control unmanned aerial vehicle treats that it patrols and examines the distribution network and patrol and examine, include: controlling a visual module carried by an unmanned aerial vehicle to acquire visual data of the power distribution network according to a visual identification routing inspection strategy of the power distribution network; identifying visual characteristics of the routing inspection line corresponding to the visual data of the power distribution network; and determining a power distribution network inspection result according to the visual characteristics of the inspection line.
In one of them embodiment, according to unmanned aerial vehicle control strategy, control unmanned aerial vehicle treats that it patrols and examines the distribution network and patrol and examine, include: according to a power distribution network modeling and inspection strategy, three-dimensional modeling is carried out on inspection data acquired in the unmanned aerial vehicle inspection process to obtain a power distribution network model; determining the working condition of the routing inspection line according to the power distribution network model, and determining the cross spanning characteristic of the routing inspection line according to the working condition of the routing inspection line; and determining a power distribution network inspection result according to the cross spanning characteristics of the inspection line.
In one embodiment, the method further comprises the following steps: adjusting the unmanned aerial vehicle control strategy according to the power distribution network inspection result; and updating and training the application strategy output model based on the line data, the environment data, the inspection unmanned aerial vehicle information, the inspection task and the adjusted unmanned aerial vehicle control strategy.
In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of: acquiring line data, environment data, inspection unmanned aerial vehicle information and inspection tasks of a power distribution network to be inspected; processing the line data, the environment data, the information of the inspection unmanned aerial vehicle and the inspection task by applying a strategy output model to obtain an unmanned aerial vehicle control strategy; the unmanned aerial vehicle control strategy at least comprises an unmanned aerial vehicle inspection strategy; according to the unmanned aerial vehicle control strategy, the unmanned aerial vehicle is controlled to patrol the power distribution network to be patrolled and examined.
In one embodiment, the method includes the steps of processing line data, environment data, inspection unmanned aerial vehicle information and inspection tasks by applying a strategy output model to obtain an unmanned aerial vehicle control strategy, and includes the following steps: performing normalization processing on the line data, the environment data, the inspection unmanned aerial vehicle information and the inspection task to obtain target data; and processing the target data by applying a strategy output model to obtain an unmanned aerial vehicle control strategy.
In one embodiment, the unmanned aerial vehicle inspection strategy comprises: the power distribution network visual identification polling strategy, the power distribution network modeling polling strategy, the power distribution network remote polling strategy, the unmanned aerial vehicle polling control strategy and the unmanned aerial vehicle polling communication strategy.
In one of them embodiment, according to unmanned aerial vehicle control strategy, control unmanned aerial vehicle treats that it patrols and examines the distribution network and patrol and examine, include: controlling a visual module carried by an unmanned aerial vehicle to acquire visual data of the power distribution network according to a visual identification routing inspection strategy of the power distribution network; identifying visual characteristics of the routing inspection line corresponding to the visual data of the power distribution network; and determining a power distribution network inspection result according to the visual characteristics of the inspection line.
In one of them embodiment, according to unmanned aerial vehicle control strategy, control unmanned aerial vehicle treats that it patrols and examines the distribution network and patrol and examine, include: according to a power distribution network modeling and inspection strategy, three-dimensional modeling is carried out on inspection data acquired in the unmanned aerial vehicle inspection process to obtain a power distribution network model; determining the working condition of the routing inspection line according to the power distribution network model, and determining the cross spanning characteristic of the routing inspection line according to the working condition of the routing inspection line; and determining a power distribution network inspection result according to the cross spanning characteristics of the inspection line.
In one embodiment, the method further comprises the following steps: adjusting the unmanned aerial vehicle control strategy according to the power distribution network inspection result; and updating and training the application strategy output model based on the line data, the environment data, the inspection unmanned aerial vehicle information, the inspection task and the adjusted unmanned aerial vehicle control strategy.
The present application also provides a computer program product. Computer program product comprising a computer program which, when executed by a processor, performs the steps of: acquiring line data, environment data, inspection unmanned aerial vehicle information and inspection tasks of a power distribution network to be inspected; processing the line data, the environment data, the information of the inspection unmanned aerial vehicle and the inspection task by applying a strategy output model to obtain an unmanned aerial vehicle control strategy; the unmanned aerial vehicle control strategy at least comprises an unmanned aerial vehicle inspection strategy; according to the unmanned aerial vehicle control strategy, the unmanned aerial vehicle is controlled to patrol the power distribution network to be patrolled.
In one embodiment, the method includes the steps of processing line data, environment data, inspection unmanned aerial vehicle information and inspection tasks by applying a strategy output model to obtain an unmanned aerial vehicle control strategy, and includes the following steps: performing normalization processing on the line data, the environment data, the inspection unmanned aerial vehicle information and the inspection task to obtain target data; and processing the target data by applying a strategy output model to obtain an unmanned aerial vehicle control strategy.
In one embodiment, the unmanned aerial vehicle inspection strategy comprises: the power distribution network visual identification polling strategy, the power distribution network modeling polling strategy, the power distribution network remote polling strategy, the unmanned aerial vehicle polling control strategy and the unmanned aerial vehicle polling communication strategy.
In one of them embodiment, according to unmanned aerial vehicle control strategy, control unmanned aerial vehicle treats that it patrols and examines the distribution network and patrol and examine, include: controlling a visual module carried by an unmanned aerial vehicle to acquire visual data of the power distribution network according to a visual identification routing inspection strategy of the power distribution network; identifying visual characteristics of the routing inspection line corresponding to the visual data of the power distribution network; and determining a power distribution network inspection result according to the visual characteristics of the inspection line.
In one of them embodiment, according to unmanned aerial vehicle control strategy, control unmanned aerial vehicle treats that it patrols and examines the distribution network and patrol and examine, include: according to a power distribution network modeling and inspection strategy, three-dimensional modeling is carried out on inspection data acquired in the unmanned aerial vehicle inspection process to obtain a power distribution network model; determining the working condition of the routing inspection line according to the power distribution network model, and determining the cross spanning characteristics of the routing inspection line according to the working condition of the routing inspection line; and determining a power distribution network inspection result according to the cross spanning characteristics of the inspection line.
In one embodiment, the method further comprises the following steps: adjusting the unmanned aerial vehicle control strategy according to the power distribution network inspection result; and updating and training the application strategy output model based on the line data, the environment data, the inspection unmanned aerial vehicle information, the inspection task and the adjusted unmanned aerial vehicle control strategy.
It should be noted that the data referred to in the present application (including but not limited to data for analysis, stored data, presented data, etc.) are data authorized by the user or fully authorized by each party.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a non-volatile computer-readable storage medium, and can include the processes of the embodiments of the methods described above when the computer program is executed. Any reference to memory, database, or other medium used in the embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include a Read-Only Memory (ROM), a magnetic tape, a floppy disk, a flash Memory, an optical Memory, a high-density embedded nonvolatile Memory, a resistive Random Access Memory (ReRAM), a Magnetic Random Access Memory (MRAM), a Ferroelectric Random Access Memory (FRAM), a Phase Change Memory (PCM), a graphene Memory, and the like. Volatile Memory can include Random Access Memory (RAM), external cache Memory, and the like. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), for example. The databases referred to in various embodiments provided herein may include at least one of relational and non-relational databases. The non-relational database may include, but is not limited to, a block chain based distributed database, and the like. The processors referred to in the various embodiments provided herein may be, without limitation, general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, or the like.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present application. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.
Claims (10)
1. A method for routing inspection of a power distribution network is characterized by comprising the following steps:
acquiring line data, environment data, inspection unmanned aerial vehicle information and inspection tasks of a power distribution network to be inspected;
processing the line data, the environment data, the inspection unmanned aerial vehicle information and the inspection task by applying a strategy output model to obtain an unmanned aerial vehicle control strategy; the unmanned aerial vehicle control strategy at least comprises an unmanned aerial vehicle inspection strategy;
and controlling the unmanned aerial vehicle to inspect the power distribution network to be inspected according to the unmanned aerial vehicle control strategy.
2. The method of claim 1, wherein the processing the line data, the environmental data, the patrol unmanned aerial vehicle information, and the patrol mission by applying the policy output model to obtain the unmanned aerial vehicle handling policy comprises:
performing normalization processing on the line data, the environment data, the inspection unmanned aerial vehicle information and the inspection task to obtain target data;
and processing the target data through the application strategy output model to obtain an unmanned aerial vehicle control strategy.
3. The method of claim 1 or 2, wherein the drone patrol policy comprises: the power distribution network visual identification polling strategy, the power distribution network modeling polling strategy, the power distribution network remote polling strategy, the unmanned aerial vehicle polling control strategy and the unmanned aerial vehicle polling communication strategy.
4. The method according to claim 3, wherein the controlling the unmanned aerial vehicle to inspect the power distribution network to be inspected according to the unmanned aerial vehicle control strategy comprises:
controlling a visual module carried by the unmanned aerial vehicle to acquire visual data of the power distribution network according to a visual identification routing inspection strategy of the power distribution network;
identifying visual characteristics of the routing inspection line corresponding to the visual data of the power distribution network;
and determining a power distribution network inspection result according to the visual characteristics of the inspection line.
5. The method according to claim 3, wherein the controlling the unmanned aerial vehicle to patrol the power distribution network to be patrolled according to the unmanned aerial vehicle control strategy comprises:
according to a power distribution network modeling and inspection strategy, three-dimensional modeling is carried out on inspection data acquired in the unmanned aerial vehicle inspection process to obtain a power distribution network model;
determining the working condition of the routing inspection line according to the power distribution network model, and determining the cross spanning characteristic of the routing inspection line according to the working condition of the routing inspection line;
and determining a power distribution network inspection result according to the cross spanning characteristics of the inspection line.
6. The method of claim 1, further comprising:
adjusting the unmanned aerial vehicle control strategy according to the power distribution network inspection result;
and updating and training the application strategy output model based on the line data, the environment data, the inspection unmanned aerial vehicle information, the inspection task and the adjusted unmanned aerial vehicle control strategy.
7. The utility model provides a patrol and examine device of distribution network, its characterized in that, the device includes:
the system comprises an acquisition module, a routing module and a routing module, wherein the acquisition module is used for acquiring line data, environment data, routing inspection unmanned aerial vehicle information and routing inspection tasks of a power distribution network to be routed;
the processing module is used for processing the line data, the environment data, the information of the inspection unmanned aerial vehicle and the inspection task by applying the strategy output model to obtain an unmanned aerial vehicle control strategy; the unmanned aerial vehicle control strategy at least comprises an unmanned aerial vehicle inspection strategy;
and the control module is used for controlling the unmanned aerial vehicle to inspect the power distribution network to be inspected according to the unmanned aerial vehicle control strategy.
8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 6.
9. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 6.
10. A computer program product comprising a computer program, characterized in that the computer program realizes the steps of the method of any one of claims 1 to 6 when executed by a processor.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117728408A (en) * | 2024-02-18 | 2024-03-19 | 国网四川省电力公司电力应急中心 | Post-disaster recovery management system for power distribution network |
| CN117728408B (en) * | 2024-02-18 | 2024-04-26 | 国网四川省电力公司电力应急中心 | Post-disaster recovery management system for power distribution network |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117728408A (en) * | 2024-02-18 | 2024-03-19 | 国网四川省电力公司电力应急中心 | Post-disaster recovery management system for power distribution network |
| CN117728408B (en) * | 2024-02-18 | 2024-04-26 | 国网四川省电力公司电力应急中心 | Post-disaster recovery management system for power distribution network |
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