An unmanned aerial vehicle power grid inspection management and control system for digital twinning

Abstract

The application relates to the technical field of program control, in particular to a digital-twin-oriented unmanned aerial vehicle power grid inspection management and control system, which comprises an inspection space construction module, a flight rhythm arrangement module, an inspection task undertaking module, an inspection content locking module and a twin mapping management and control module; the inspection space construction module divides a line section according to a voltage direction; the flight rhythm arrangement module selects a tension stable section to arrange flight; the inspection task undertaking module matches available unmanned aerial vehicles to determine a task sequence; the inspection content locking module screens a fitting contour consistent area; the twin mapping management and control module establishes image and space mapping, identifies a concerned area and fuses a track to generate a management and control result. According to the application, voltage direction and tension change characteristics are introduced to realize matching optimization of line section and flight period, coordinate inspection objects, time conditions and execution resources, lock key areas based on image consistency, associate concerned results with a digital twin space, guarantee the traceability of an inspection process in time and space dimensions, and enhance the pertinence of inspection decision, the stability of execution and the coherence of management and control.

Description

Technical Field

[0001] This invention relates to the field of program control technology, and in particular to a drone-based power grid inspection and control system for digital twins. Background Technology

[0002] The field of programmable control technology encompasses the logical control and scheduling management of the issuance and execution of instructions for the operation of equipment. The core of this technology revolves around the programmed control of information acquisition, processing, and action execution. Its focus is on enabling logical judgment and operational execution of equipment, systems, or processes under specific conditions. Through the design of control flows, programmable control technology allows systems to operate autonomously or semi-autonomously according to preset rules. It is widely used in industrial automation, remote monitoring, and robot control. With the enhancement of computing power and the advancement of sensing technology, programmable control has gradually achieved higher levels of integration and intelligent development, driving the upgrading of intelligent systems and equipment across industries. This field not only focuses on the rigor and operability of control logic but also emphasizes the reliability design of control systems in terms of multi-source information fusion, environmental adaptability, and operational stability.

[0003] One type of unmanned aerial vehicle (UAV) power grid inspection and control system for digital twins refers to a program control system that combines 3D visualization modeling, path planning, and power equipment identification to enable UAVs to perform power grid inspection tasks. It primarily targets power grid line operation status monitoring, fault image recognition, and inspection task scheduling. Through digital twin modeling, a virtual space for the power grid is constructed, generating a 3D visual environment based on actual geographic data and power line parameters. Combined with map-based autonomous route planning, an inspection path is designated for the UAV. Image recognition and coordinate calibration are used to extract and locate targets such as power towers, conductors, and insulators. At the task execution level, the system controls the UAV to complete various shooting tasks sequentially along a predetermined route based on a set of task instructions and a priority ranking mechanism. The collected image data is then uploaded to a remote center, forming a closed-loop data processing flow. The system uses program control logic as the main thread, integrating information modeling, flight task configuration, and image acquisition processes.

[0004] Existing technologies organize inspections based on path planning and command scheduling. The inspections are mainly based on static models and predetermined task configurations. During operation, it is difficult to reflect the differences in line status over time. When the line is affected by environmental or load fluctuations, the inspection task still proceeds according to the preset process, which can easily lead to a mismatch between the inspection period and the line status. At the same time, task allocation relies more on sequence and priority control, and does not adequately consider the dynamic adaptation between execution resources and inspection objects, which may cause task overlap or scheduling conflicts. Although the inspection images are collected and transmitted, they lack continuous correlation expression at the spatial level, which limits the precision of subsequent analysis and centralized management. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of existing technologies by proposing a UAV power grid inspection and control system based on digital twins.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a drone-based power grid inspection and control system for digital twins, the system comprising: The inspection space construction module acquires voltage change information of conductor connection nodes within the inspection area, extracts location descriptions, determines the transmission line route, expands and compares the voltage change direction, divides the transmission line into segments, and corresponds to the voltage change direction distribution to obtain the voltage direction inspection space distribution results. The flight rhythm scheduling module obtains the tension change information of each transmission line segment and the voltage change direction in the voltage direction inspection spatial distribution results, identifies the tension stable section, schedules the UAV flight mission time, and obtains the flight time scheduling result of the tension flat section. The inspection task receiving module obtains the available flight time information of the UAV based on the flight time arrangement of each transmission line segment in the flight time arrangement result of the tension-relaxed section, filters the matching UAVs, determines the execution order of the inspection task, and obtains the corresponding relationship result of the UAV inspection task. The inspection content locking module acquires continuous images based on the execution arrangement information of each inspection task in the correspondence result of the UAV inspection tasks, extracts the contour changes of the hardware connection parts, filters consistent areas, determines the inspection focus area, and obtains the result of the continuous focus area of ​​the hardware contour.

[0007] As a further aspect of the present invention, the voltage pointing inspection spatial distribution results include transmission line spatial segmentation units, voltage pointing categories corresponding to each segment, and voltage pointing distribution characteristics in the inspection space; the flight time arrangement results for the tension-smooth section include the inspectable time intervals corresponding to the transmission line segments, the stability attribute identifiers of the time intervals, and the continuity characteristics of the time intervals; the UAV inspection task correspondence results include the allocation correspondence between inspection tasks and UAVs, the task-bearing identifiers of each transmission line segment, and the task execution sequence identifiers; and the continuous attention area results for hardware outlines include the continuous attention area range of the hardware connection parts, the outline stability identifier, and the set of key inspection units for hardware.

[0008] As a further embodiment of the present invention, the inspection space construction module includes a voltage change extraction submodule, a twin position association submodule, and a line pointing segmentation submodule; The voltage change extraction submodule obtains the voltage change information corresponding to the conductor connection nodes in the inspection area, monitors the voltage change direction of each conductor connection node during the inspection period, summarizes the voltage change direction identifiers corresponding to each connection node based on the change direction of the voltage change start state and end state identifiers, generates a node-level voltage change direction set, and obtains the node voltage change direction identifier set. The twin location association submodule, based on the node voltage change direction identifier set, calls the position description of the conductor connection node in the digital twin space, associates the position description with the corresponding transmission line spatial extension order, organizes the arrangement relationship of the nodes on the transmission line, forms a set of node position and line direction correspondence relationship, and obtains the line direction association sequence. The line pointing segmentation submodule compares the voltage change direction with the line direction association sequence based on the node voltage change direction identifier set, identifies the location of the node where the pointing direction changes, delineates the segment range of the transmission line within the inspection area, merges the voltage pointing performance of each segment, and generates the voltage pointing inspection spatial distribution result.

[0009] As a further embodiment of the present invention, the flight rhythm arrangement module includes a tension information acquisition submodule, a tension change discrimination submodule, and a flight time matching submodule; The tension information acquisition submodule, based on the voltage direction inspection spatial distribution results of each transmission line segment and the corresponding voltage change direction, obtains the conductor tension change information associated with the transmission line segment, monitors the conductor tension change status over time during the inspection period, arranges the tension change records in chronological order, forms a time series set of tension changes corresponding to the line segment, and generates a time series set of conductor tension changes. The tension change discrimination submodule, based on the time series set of conductor tension changes, judges the direction of tension change within a continuous time segment, compares the tension change trend of adjacent time segments, identifies segments where the change direction is consistent and no sudden shift occurs, marks the start and end positions of each segment, and summarizes them to form a set of continuous tension state segments, thus obtaining tension flat time segments. The flight time matching submodule, based on the tension-smooth time interval and the associated time requirements of the inspection tasks of each transmission line segment, matches the start and end range of the time interval, limits the UAV inspection flight time to the corresponding time interval, organizes it into a flight time arrangement sequence corresponding to the line segment, and generates the flight time arrangement result of the tension-smooth section.

[0010] As a further embodiment of the present invention, the inspection task receiving module includes a flight time acquisition submodule, an availability status filtering submodule, and a task sequence association submodule; The flight time acquisition submodule obtains the current available flight time information of the UAV based on the flight time arrangement of each transmission line segment in the flight time arrangement result of the tension-smooth section, collects the start time and end time of each UAV, organizes them into a sequence of available flight time for the UAV, establishes a time axis correspondence with the flight time arrangement of the line segment, and generates a sequence of available flight time for the UAV. The available status filtering submodule, based on the available flight time sequence of the UAV, compares the overlap of the start and end ranges of the time axis for the flight time arrangement of each transmission line segment, determines the continuity of the UAV's status within the interval from the start to the end of the flight time arrangement, filters UAVs that are available in all time periods, and summarizes them to form a set of UAVs corresponding to each line segment, thus obtaining the UAV association set of each line segment. The task sequence association submodule, based on the line segment UAV association set and the arrangement order of the transmission line segments in the inspection area, organizes the correspondence between UAVs and line segments, arranges the inspection task execution order according to the timeline, establishes the matching relationship between UAVs and inspection tasks, and generates the UAV inspection task correspondence result.

[0011] As a further embodiment of the present invention, the inspection content locking module includes an image sequence acquisition submodule, a hardware outline extraction submodule, and a region of interest filtering submodule; The image sequence acquisition submodule acquires continuous images during the inspection process of the UAV inspection task according to the execution arrangement information of each inspection task in the UAV inspection task correspondence result, arranges the image frames in the order of image acquisition time, associates the image frames with the corresponding power line segment identifiers, organizes them to form the image time sequence corresponding to the line segment, and generates the line segment image sequence set. The hardware outline extraction submodule, based on the line segment image sequence set, acquires the image region of the hardware connection part of the transmission line segment for each image frame, detects the boundary shape change of the hardware connection part, extracts the corresponding outline position description in each image frame, and summarizes them to form a time-ordered outline position set to obtain the hardware outline position sequence. The attention area filtering submodule compares the consistency of contour position changes in adjacent image frames based on the hardware contour position sequence, filters areas with consistent contour positions, marks the corresponding spatial range in continuous images, summarizes them to form a set of continuous attention areas in the inspection process, and generates a result of continuous attention areas for hardware contours.

[0012] As a further aspect of the present invention, the system further includes: The twin mapping control module establishes a mapping relationship between the position of each inspection focus area in the continuous image and the transmission line in the digital twin space based on the position description of each inspection focus area in the continuous focus area result of the hardware outline. It identifies the continuous focus area and forms the UAV power grid inspection control result. The results of the UAV power grid inspection and control include the identification of the line's area of ​​interest in the digital twin space, the status information associated with the inspection task, and the fusion information of the UAV's flight trajectory.

[0013] As a further embodiment of the present invention, the twin mapping control module includes a location mapping acquisition submodule, a spatial association establishment submodule, and a control information fusion submodule; The location mapping acquisition submodule obtains the location description of each inspection area of ​​interest in the continuous image based on the continuous interest area result of the hardware outline, collects the image coordinate information corresponding to the location description, associates the transmission line segment identifier, organizes the correspondence between image position and line number, forms the set of interest area position correspondence, and generates image position association sequence. The spatial association establishment submodule, based on the image location association sequence, calls the transmission line location description in the digital twin space, compares the arrangement order of image coordinates and twin coordinates, determines the consistency of spatial correspondence, establishes the mapping relationship between image location and twin space line location, and obtains the twin space location mapping set; The control information fusion submodule, based on the twin spatial location mapping set, introduces inspection task execution information and UAV flight trajectory information, integrates the route location and flight path time sequence, identifies the status of the continuously monitored route area, summarizes and forms the spatial control relationship of the inspection process, and generates UAV power grid inspection control results.

[0014] Compared with the prior art, the advantages and positive effects of the present invention are as follows: In this invention, by introducing a correlation between voltage change direction and line spatial orientation, the inspected object possesses distinguishable state segmentation attributes, and physical state characteristics are integrated into spatial representation. Simultaneously, by combining the continuous and stable characteristics of tension changes in the time dimension, the inspection period is constrained and matched to ensure that flight arrangements are consistent with the line status. At the task configuration level, the coordination and correspondence between the inspected object, time conditions, and execution resources are achieved. At the inspection content level, key attention areas based on continuous image consistency are formed, and the attention results are uniformly identified and associated with the line position in the digital twin space. This makes the inspection behavior traceable and consistent in both spatial and temporal dimensions, thereby enhancing the pertinence of inspection decisions, the stability of the execution process, and the overall coherence of control results. Attached Figure Description

[0015] Figure 1 This is a flowchart of the method of the present invention; Figure 2 This is a flowchart illustrating the acquisition process of the inspection space construction module of the present invention. Figure 3 This is a flowchart illustrating the acquisition process of the flight rhythm scheduling module of the present invention. Figure 4 This is a flowchart illustrating the acquisition process of the inspection task receiving module of this invention. Figure 5 This is a flowchart illustrating the acquisition process of the inspection content locking module of the present invention. Figure 6 This is a flowchart illustrating the acquisition process of the twin mapping control module of the present invention. Detailed Implementation

[0016] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0017] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0018] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning.

[0019] In this embodiment of the invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0020] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0021] Please see Figure 1 This invention provides a technical solution: a drone-based power grid inspection and control system for digital twins, the system comprising: The inspection space construction module acquires voltage change information corresponding to conductor connection nodes within the inspection area, extracts the position description of the conductor connection nodes in the digital twin space, determines the transmission line direction corresponding to the position description, expands and compares the voltage change direction along the transmission line direction, extracts the directional representation of the voltage change direction on the transmission line direction, and divides the transmission line range within the inspection area into segments based on the spatial directional relationship formed between the voltage change direction and the transmission line direction, so that each transmission line segment corresponds to a unique voltage change direction distribution in the digital twin space, thus obtaining the voltage direction inspection space distribution result. The flight rhythm scheduling module obtains conductor tension change information associated with each transmission line segment based on the voltage direction inspection spatial distribution results of each transmission line segment and the corresponding voltage change direction. It observes the continuous change process of conductor tension during the inspection period in chronological order, identifies the time segment in which the conductor tension maintains the same direction of change and does not show sudden changes during the continuous change process, and schedules the flight time of the UAV to perform the transmission line segment inspection task within the time segment range to obtain the flight time scheduling result of the tension flat section. The inspection task receiving module obtains the available flight time information of the UAV based on the flight time arrangement of each transmission line segment in the flight time arrangement results of the tension-relaxed section. It compares the start and end range of the flight time arrangement and the available flight time of the UAV on the time axis, and filters out the UAVs that are available from the start to the end of the flight time arrangement. Based on the correspondence between the filtered UAVs and the transmission line segments, it determines the execution order of the inspection tasks and obtains the correspondence results of the UAV inspection tasks. The inspection content locking module, based on the execution arrangement information of each inspection task in the correspondence result of the UAV inspection task, obtains continuous images collected by the UAV during the inspection process, extracts the outline of the hardware connection parts of the corresponding transmission line segment along the time sequence of the images, filters the areas in the continuous images where the outline position of the hardware connection parts of the transmission line remains consistent, determines the inspection focus area based on the filtering results, and obtains the continuous focus area result of the hardware outline. The twin mapping control module, based on the position description of each inspection focus area in the continuous image of the hardware outline continuous focus area results, obtains the corresponding position description of the transmission line in the digital twin space, establishes a mapping relationship between the position of the inspection focus area in the image and the spatial position of the transmission line in the digital twin space, identifies the transmission line area that is continuously monitored during the inspection in the digital twin space, and introduces the inspection task execution information and UAV flight trajectory information according to the mapping relationship to form the UAV power grid inspection control results.

[0022] The voltage pointing inspection spatial distribution results include the transmission line spatial segmentation units, the voltage pointing category corresponding to each segment, and the distribution characteristics of voltage pointing in the inspection space. The flight time arrangement results for the tension-smooth section include the inspectable time intervals corresponding to the transmission line segments, the stability attribute identifiers of the time intervals, and the continuity characteristics of the time intervals. The UAV inspection task correspondence results include the allocation correspondence between inspection tasks and UAVs, the task-bearing identifiers of each transmission line segment, and the task execution sequence identifiers. The continuous attention area results for fitting outlines include the continuous attention area range of the fitting connection parts, the outline stability identifiers, and the set of key inspection units for fittings. The UAV power grid inspection and control results include the line attention area identifiers in the digital twin space, the inspection task association status information, and the UAV flight trajectory fusion information.

[0023] Please see Figure 2 The inspection space construction module includes a voltage change extraction submodule, a twin position association submodule, and a line pointing segmentation submodule; The voltage change extraction submodule obtains the voltage change information corresponding to the conductor connection nodes in the inspection area, monitors the voltage change direction of each conductor connection node during the inspection period, summarizes the voltage change direction identifiers corresponding to each connection node based on the change direction of the voltage change start state and end state identifiers, generates a node-level voltage change direction set, and obtains the node voltage change direction identifier set. Obtain voltage change information corresponding to conductor connection nodes within the inspection area, and retrieve all data within the tested area numbered [number missing] through the data interaction port of the digital twin interface connected to the power grid SCADA (Supervisory Control and Data Acquisition) system. The real-time operating parameters of the wire connection nodes are set to a sampling frequency of [value missing]. And continuously record The voltage values ​​for each sampling period are used to construct the node voltage time sequence matrix. Each row in the matrix corresponds to the voltage value of a physical node at different sampling moments. For any node... Extract its voltage value at the first sampling instant. Voltage value at the last sampling instant Perform interpolation Introducing a voltage fluctuation judgment benchmark value This benchmark value is based on the rated voltage level of the transmission line. of To configure, if the line's rated voltage is 110kV, then... Set to 0.55kV, and calculate the difference. absolute value and Perform numerical comparison, when When the voltage state of the node is determined to remain stable, When the voltage at a given node shows a positive increasing trend, a direction indicator is assigned. ,when When the node voltage is determined to be decreasing in a negative direction, a direction indicator is assigned. For example, if the voltage of node A is 110.2kV at the start of sampling and 109.5kV at the end, the difference is calculated to be -0.7kV. Given If the difference is negative, then the voltage change direction at node A is determined to be the direction of voltage decrease. (This is relevant to the matrix.) The above calculation and logical judgment process is executed one by one for all nodes. The numerical direction identifiers of all nodes are stored according to the node number index to form a structured data table containing the voltage state trend of all nodes, and the node voltage change direction identifier set is obtained.

[0024] The twin location association submodule, based on the node voltage change direction identifier set, calls the position description of the conductor connection node in the digital twin space, associates the position description with the corresponding transmission line spatial extension order, organizes the arrangement relationship of the node on the transmission line, forms a set of correspondence between node position and line direction, and obtains the line direction association sequence; Based on the node voltage change direction identifier set, the unique identification code of each node in the above node voltage change direction identifier set is input through the digital twin 3D model database retrieval interface. Retrieve and extract the geometric coordinate parameters of each node in a virtual three-dimensional spatial coordinate system constructed based on GIS (Geographic Information System). Based on the topology connection table in the transmission line design drawings, the physical connection attributes between each node are identified. Taking the power source side of the transmission line as the starting reference point, the coordinates of each node are traversed sequentially along the physical path of current transmission to construct a spatial coordinate sequence reflecting the physical orientation of the transmission line. ,in Represents the coordinates of the first node. Represents the coordinates of the end node, such as node Coordinates are The adjacent and downstream node Coordinates are Nodes are determined based on this spatial adjacency relationship. To node The spatial extension vector identifies the direction of the previously obtained node voltage change, i.e., its value. or With spatial coordinate sequence The corresponding nodes are mapped and bound one-to-one, generating a multidimensional array containing node spatial location information, the node's sequence index value in the entire line, and the node's voltage change characteristic value, for example, forming a tuple. The multidimensional array is rearranged in ascending order of sequence index values ​​to ensure that the data arrangement strictly follows the actual physical direction of the transmission line, forming a set of correspondences between node positions and line directions, and obtaining the line direction association sequence.

[0025] The line pointing segmentation submodule compares the voltage change direction with the line direction association sequence based on the node voltage change direction identifier set and the line direction association sequence, identifies the location of the node where the pointing changes, delineates the segment range of the transmission line in the inspection area, merges the voltage pointing performance of each segment, and generates the voltage pointing inspection spatial distribution results. Based on the association sequence between the node voltage change direction identifier set and the line direction, a linear scan program is initiated to sequentially read the voltage change direction identifier values ​​of two adjacent nodes along the line direction association sequence. and Perform logical XOR operations or numerical comparison operations if and The values ​​are equal, for example, both are equal. or all If the two nodes are in the same voltage change characteristic range, the program will continue reading the next pair of nodes. and The values ​​are not equal, for example and Then it is determined that at node With nodes A sudden change in voltage direction occurred within the line segment; this location was marked as the segmentation cut-off point, and the node was extracted. coordinates With nodes coordinates The spatial geometric center coordinates of the cutting point are calculated using linear interpolation. The transmission line model in the digital twin space is segmented using the coordinates of the cutting point as the boundary. The first segment is defined as the range from the start point of the sequence to the first cutting point, and subsequent segments are defined as the range from the previous cutting point to the next cutting point. If the direction indicators of all nodes in the entire line are consistent, no segmentation is performed, and the entire line is regarded as a complete interval. For example, if the voltage direction changes from rising to falling at the 5th node, the line between the 1st and 5th nodes is divided into a "voltage rise characteristic segment", and the line between the 5th and 10th nodes (assuming the 10th node is the next change point) is divided into a "voltage fall characteristic segment". The entire sequence of all nodes in the line is traversed until the end. The voltage change direction indicators of each segment interval are bound to the uniform voltage change indicators of the internal nodes. A mapping table describing the start and end coordinates of each segment space and its corresponding unique voltage change direction attribute is constructed to generate the voltage direction inspection spatial distribution results.

[0026] Please see Figure 3 The flight rhythm arrangement module includes a tension information acquisition submodule, a tension change discrimination submodule, and a flight time matching submodule; The tension information acquisition submodule, based on the voltage direction inspection spatial distribution results of each transmission line segment and the corresponding voltage change direction, obtains the conductor tension change information associated with the transmission line segment, monitors the conductor tension change status over time during the inspection period, arranges the tension change records in chronological order, forms the tension change time series set corresponding to the line segment, and generates the conductor tension change time series set. Based on the voltage direction of the spatial distribution of the transmission line segments and their corresponding voltage changes, the online monitoring terminal of the transmission line calls the real-time data interface of the tension sensor or fiber optic grating sensor installed at the conductor fittings corresponding to the spatial location of each segment, and sets the tension data sampling period. For 5 minutes, during the set 24-hour inspection preparation period, the mechanical tension values ​​of each conductor segment are continuously read. For each transmission line segment, a timestamp-based system is established. The indexed tension data table contains a series of tension values ​​sorted by acquisition time. Calculate the tension change between two adjacent sampling times. If a certain segment is in The tension at any given time is 5000N. If the time is 5020N, ​​then For each segment, the tension change at all adjacent moments is calculated. These changes are arranged in chronological order to construct a numerical sequence reflecting the dynamic fluctuation characteristics of the tension in that segment throughout the entire preparation period. At the same time, auxiliary parameters such as ambient temperature and wind speed collected by micro-weather stations for that segment are associated for subsequent verification. The tension numerical sequences of all segments are bound and encapsulated with their corresponding segment IDs to form a multi-dimensional data structure containing spatial segment identifiers, timestamp sequences, and corresponding tension change values. This ensures that each tension change record can be accurately traced back to its corresponding physical line segment and the specific time of occurrence, generating a time series set of conductor tension changes.

[0027] The tension change discrimination submodule, based on the time series set of conductor tension changes, judges the direction of tension change within a continuous time segment, compares the tension change trend of adjacent time segments, identifies segments with consistent change direction and no sudden shift, marks the start and end positions of each segment, and summarizes them to form a set of continuous tension state segments, thus obtaining the tension flat time segment. Based on the time series of conductor tension changes, a threshold for determining the direction of tension change is set. It is 10N; That is when When a significant change in tension is identified, the amount of tension change is examined for each time segment within the time series. The sign and absolute value of the continuous A time slice (e.g.) Within 30 minutes The signs of the values ​​are consistent (all positive or all negative) and their absolute values ​​are all less than the tension mutation warning value. (Set to 50N), then the continuous time segment is determined to be a section with relatively low tension, for example, during the period from 10:00 to 10:30, a certain line segment... If the values ​​are +12N, +15N, +11N, +13N, +14N, and +10N respectively, and all are positive and less than 50N, then this 30-minute period is identified as a gently rising segment. Conversely, if the following values ​​appear in the sequence... Sign flip (e.g., from +20N to -15N) or single change exceeding (For example, if a sudden change of +80N occurs), then that time point is determined to be a non-gradual tension point. The recording of the current gradual tension segment is interrupted, and the detection of a new gradual tension segment restarts from the next time slice after that interruption. The program traverses the entire time series, extracts all continuous time segments that meet the above gradual tension conditions, and records their start timestamps. and end timestamp And the average tension change rate within that section, outputting a series of parameters such as... for each transmission line section. The list of time intervals yields the time periods when tension is low.

[0028] The flight time matching submodule, based on the time intervals of the tension-smooth time zone and the time requirements associated with the inspection tasks of each transmission line segment, matches the start and end range of the time intervals and limits the UAV inspection flight time to the corresponding time intervals, organizes them into a sequence of flight time arrangements for line segments, and generates flight time arrangement results for the tension-smooth time zone. Based on the time intervals when tension eases, the estimated time required for drone inspection tasks for each transmission line segment is obtained. For example, if a segment is 2km long and the drone inspection speed is 10m / s, then Iterate through all the time intervals where the tension eases for that segment. Calculate the time span of each segment ,Will and Perform numerical comparisons and retain only those that satisfy the criteria. The conditional section, among which For safety redundancy time (set to 300s to handle takeoff, landing, and emergencies), if a smooth section spans 30 minutes (1800s), the mission time is 200s, and the redundancy is 300s, then... If the conditions are met, the segment is marked as a valid flight window. For segments that meet the conditions, the planned takeoff time of the drone will be... Set at the start time of the segment End time Set as If the calculated Exceeding the current flat section If the current window fails, the next window is tried to ensure that the flight mission falls entirely within a time range with smooth tension and no sudden changes. A specific flight schedule is generated for each transmission line segment, which includes the segment ID, suggested takeoff time, expected landing time, and corresponding index of the smooth tension segment. Finally, the scheduling information of all segments is integrated to generate the flight time arrangement result for the smooth tension segment.

[0029] Please see Figure 4 The inspection task receiving module includes a flight time acquisition submodule, an availability status filtering submodule, and a task sequence association submodule. The flight time acquisition submodule obtains the information on the available flight time of the UAV based on the flight time arrangement of each transmission line segment in the flight time arrangement results of the tension-relaxed section. It collects the start and end times of each UAV, organizes them into a sequence of available flight time of the UAV, establishes a time axis correspondence with the flight time arrangement of the line segment, and generates a sequence of available flight time of the UAV. Based on the flight time schedule for each transmission line segment in the flight time arrangement results for the tension-relaxed section, the drone scheduling database is accessed through the hangar management terminal, targeting the drones numbered... to For each drone, retrieve its current status log uploaded by the BMS (Battery Management System) and extract the information including battery percentage. Last maintenance end time Expected time of the next mandatory maintenance and the current task occupancy status indicator Parameters such as these are used to set the minimum available battery power threshold for the drone. The percentage is 30%, if a certain drone or (Indicating busy) If so, mark that time period as unavailable. For those that meet the requirements... and drones; Calculate its theoretical maximum range ,in This is the flight time coefficient per unit of battery power (e.g., 0.5 minutes / %). ,but Minutes, combined with the current time The executable start time of the drone was calculated. ( (Set the takeoff preparation time to 10 minutes) and the executable end time. At the same time, check Is it less than To ensure that the maintenance cycle is not exceeded, the effective time window for each drone will be calculated. Structured encapsulation was performed to construct a drone availability schedule, incorporating task requirement time periods from the segmented flight time scheduling of power transmission lines. The available timetable for drones is mapped to the same standard time axis coordinate system with the time period required for the mission, and the corresponding position of each time point is marked to form an intuitive time overlap relationship map, generating a sequence of available flight time periods for drones.

[0030] The available status filtering submodule, based on the sequence of available flight time periods for UAVs, compares the overlap of the start and end ranges of the time axis for the flight time arrangement of each transmission line segment, determines the continuity of the UAV's status within the interval from the start to the end of the flight time arrangement, filters UAVs that are available in all time periods, and summarizes them to form a set of UAVs corresponding to each line segment, thus obtaining the UAV association set of each line segment. Based on the available flight time sequence of UAVs, the task time windows specified in the segmented flight time arrangements for each power transmission line are determined. The matching and filtering process is initiated to iterate through the available time windows of each drone. Perform a dual logical check: the first check is a range inclusion verification, checking whether the condition is met simultaneously. and The first requirement is that the available time slots for drones must completely cover the mission's required time slots. For example, if the mission requirement is 10:00-10:20, drone A is available from 09:50-10:30, which meets the requirement. However, drone B is available from 10:10-10:40, which overlaps but has a later start point, thus failing to meet the requirement. The second criterion is a state continuity verification, checking the... Check whether there are any maintenance interruption markers or planned communication blackouts within the closed interval, ensuring that the drone's status parameters are continuous and without interruption risk during this time period. For drones that pass the above dual verification, add their IDs to the candidate resource list of the current transmission line segment. If multiple available drones are matched for a certain segment (e.g., UAV_A, UAV_C), then select the drones based on their remaining power. The drones are sorted in a two-level order from high to low. If none of the drones meet the conditions, the task is marked as "requiring manual intervention" or "postponed scheduling". Finally, all segments and their corresponding strictly screened candidate drone lists are summarized to construct key-value pair structured data, where the key is the line segment number and the value is an array of drone IDs sorted by priority, thus obtaining the line segment drone association set.

[0031] The task sequence association submodule, based on the line segment drone association set and the arrangement order of the transmission line segments in the inspection area, organizes the correspondence between drones and line segments, arranges the execution order of inspection tasks according to the timeline, establishes the matching relationship between drones and inspection tasks, and generates the drone inspection task correspondence result. Based on the association set of UAVs for each line segment and the arrangement order of the transmission line segments within the inspection area, the topological connection order of each segment in physical space is read. And the corresponding tension-smooth flight time arrangement for each segment. Construct a global task execution linked list. For each node (i.e., a line segment) in the linked list, select the highest priority drone from its corresponding candidate drone list. Lock the resource and perform a resource conflict detection. By two adjacent segments (such as and Select both at the same time, and the task time periods of both are also selected. and There are overlaps or intervals on the timeline that are shorter than the minimum interval for drone relocation and charging. (Set to 30 minutes), then the conflict resolution mechanism will be triggered, and the conflict will be preserved. right Occupation, forced Select the second-best drone from its candidate list, or adjust it while ensuring the tension is smooth. After resolving all conflicts, the execution time is determined, and the task sequence of each UAV during the entire inspection cycle is confirmed. A specific scheduling instruction table is generated, which clearly records operation instructions such as "UAV_A performs segment 1 inspection from 10:00 to 10:20 and segment 3 inspection from 10:50 to 11:10". This ensures that the task execution order is strictly consistent with the timeline logic and generates the corresponding result of UAV inspection tasks.

[0032] Please see Figure 5 The inspection content locking module includes an image sequence acquisition submodule, a hardware outline extraction submodule, and a region of interest filtering submodule; The image sequence acquisition submodule acquires continuous images during the inspection process of the UAV inspection task based on the execution arrangement information of each inspection task in the correspondence result of the UAV inspection task. It arranges the image frames in the order of image acquisition time, associates the image frames with the corresponding power line segment identifiers, organizes them into a time sequence of images corresponding to the line segments, and generates a set of line segment image sequences. Based on the inspection task execution schedule information in the drone inspection task correspondence results, the drone data is read via the drone's onboard high-throughput data link download or real-time transmission interface. During the execution of specific transmission line segmentation tasks, the raw video stream data captured by the onboard high-definition visible light zoom camera is used to set frame rate sampling parameters. 30 frames per second; Segmenting a continuous video stream into discrete sequences of static image frames. The EXIF ​​metadata header information of each frame of the image is parsed to extract the GPS location coordinates contained therein. The shooting azimuth angle obtained through IMU (Inertial Measurement Unit) Pitch angle And shooting timestamps accurate to the millisecond level With this timestamp Using the baseline key, all discrete image frames are linearly sorted along the time axis. Simultaneously, based on GPS location coordinates, it is determined whether the geographical area covered by the image frame falls within the preset transmission line segment. If a frame falls within the bounding box of a segment, that frame is marked as belonging to that segment. Effective inspection images, all belonging to the same segment Furthermore, the image frames arranged in chronological order and their corresponding metadata are encapsulated into an independent data packet. For example, the images from frame 100 to frame 500 belonging to "110kV line A section" are packaged to construct an image dataset indexed by the line segment ID, generating a line segment image sequence set.

[0033] The hardware outline extraction submodule, based on the line segment image sequence set, acquires the image region of the hardware connection part of the transmission line segment for each image frame, detects the boundary shape change of the hardware connection part, extracts the corresponding outline position description in each image frame, and summarizes them to form a time-ordered outline position set to obtain the hardware outline position sequence. Based on the image sequence set of line segments, each frame of the sequence is retrieved sequentially. Set grayscale threshold (For example, 128) Perform binarization preprocessing on the image, apply the Canny edge detection operator to scan the entire image, extract all high-frequency edge features in the image, and use a pre-trained geometric feature template of "insulator strings and fittings" (containing typical geometric shape parameters such as U-shaped hanging rings and ball-head hanging rings) to perform sliding window matching on the edge feature map and calculate the matching confidence. Set confidence threshold It is 0.85; reserve The area is selected as a candidate area for the hardware connection part. For each extracted candidate region Calculate the coordinates of the four vertices of its circumscribed rectangle. and the coordinates of the geometric center point Simultaneously, the gradient direction histogram (HOG) feature vectors of edge pixels within this region are calculated. The coordinate information is combined with the feature vector to describe the outline position of the hardware in the frame image. For example, in frame 50, the center of the hardware is identified at pixel coordinates (1024, 768), and the feature vector is a set of 128-dimensional values. The program automatically traverses every frame in the entire image sequence and extracts all the relevant features. The data is stored in a dynamic array according to the frame number, forming a data stream that reflects the movement trajectory and shape changes of the fitting in the field of view, thus obtaining the fitting outline position sequence.

[0034] The focus area filtering submodule compares the consistency of contour position changes in adjacent image frames based on the hardware contour position sequence, filters areas with consistent contour positions, marks the corresponding spatial range in continuous images, summarizes them to form a set of continuous focus areas in the inspection process, and generates continuous focus area results for hardware contours. Based on the sequence of hardware outline positions, set the size of the continuity determination window. It consists of 5 frames, meaning that the current frame is examined each time. and the following 4 frames Calculate the coordinates of the center point of the hardware between two adjacent frames within the calculation window. Euclidean distance and feature vectors cosine similarity If in consecutive Intra-frame displacement between adjacent frames All are less than the maximum allowable displacement threshold (Set to 1% of the image diagonal length, such as 20 pixels), and feature similarity. All are higher than the similarity benchmark. (Set to 0.95), then the area is determined to be a "visually stable area of ​​interest," meaning that the drone gimbal stably tracked and filmed the specific hardware during this time period, and the stable area of ​​interest is recorded in the first frame. The starting coordinate range and the last frame End coordinate range and the total number of frames that this state lasts. ,like If the effective attention duration exceeds the preset threshold (e.g., 60 frames, i.e., continuous attention for more than 2 seconds), the spatial pixel range corresponding to the continuous image segment is marked as the key inspection content. Those unstable areas that flash by or are blurred due to jitter are removed. All pixel areas marked as "stable attention" are summarized to generate the continuous attention area result of the hardware outline.

[0035] Please see Figure 6 The twin mapping control module includes a location mapping acquisition submodule, a spatial association establishment submodule, and a control information fusion submodule; The location mapping acquisition submodule obtains the location description of each inspection area of ​​interest in the continuous image based on the continuous interest area results of the hardware outline, collects the image coordinate information corresponding to the location description, associates the transmission line segment identifier, organizes the correspondence between image location and line number, forms the set of interest area location correspondence, and generates the image location association sequence. Based on the continuous region of interest results of the hardware outline, the metadata of each image region marked as "stable region of interest" is extracted, and the coordinates of the center point of the region in the image coordinate system are read. and the unique identifier of the corresponding image frame Query this Associated transmission line segment ID ; Establish a triplet data structure containing image pixel coordinates, frame index, and the physical segment ID to which it belongs. For example, if the fitting at coordinates (500, 300) in the 200th frame of an image at a certain moment belongs to the 3rd section of a 110kV line, then a record is generated. For all extracted areas of interest, group them according to their respective segment IDs, and then further group them according to... The values ​​are sorted from smallest to largest to construct a structured list. For each item in the list, the camera intrinsic parameter matrix recorded by the UAV flight control system at the time the image frame was captured is further obtained. (Including focal length) Principal point coordinates ) and extrinsic parameter matrix (Including rotation matrix) Translation vector These parameters are stored together in the location description record to ensure that the pixel position of each point of interest corresponds one-to-one with its spatial pose parameters at the time of shooting. Finally, the prepared dataset containing pixel coordinates, physical segmentation and camera parameters is encapsulated to generate an image location association sequence.

[0036] The spatial association establishment submodule, based on the image location association sequence, calls the transmission line location description in the digital twin space, compares the arrangement order of image coordinates and twin coordinates, judges the consistency of spatial correspondence, establishes the mapping relationship between image location and twin space line location, and obtains the twin space location mapping set; Based on the image location association sequence, a coordinate inverse projection calculation program is initiated for each image location point in the sequence. Using the camera intrinsic parameter matrix and extrinsic parameter matrix Constructing ray equations from the pixel plane to three-dimensional space ,in As a depth factor, it also calls the corresponding segment in the digital twin database. The 3D model data was used to extract the 3D geometric mesh model of all conductors and hardware components within the segment. Integrating ray equations with mesh models Perform spatial intersection operations to calculate the coordinates of the intersection points between the ray and the surface of the 3D model. Set spatial distance tolerance threshold The distance is 0.5 meters. If the calculated intersection point... Coordinates of predefined key nodes (such as insulator attachment points) in the twin model Euclidean distance between If the image's focus point is successfully mapped to the specific digital twin node, it is determined that the mapping is successful. For example, if the calculated intersection coordinates are (100.5, 200.2, 50.1), and the coordinates of a hanging point in the model are (100.0, 200.0, 50.0), and the distance is less than 0.5 meters, the match is confirmed. If multiple intersections exist, the intersection closest to the camera is selected as the valid mapping point. If no intersection is calculated or the distances are all greater than 0.5 meters, the mapping is considered complete. If a point fails to match, it is marked as a mapping failure and logged in the exception log. All successfully matched pairs are then logged. The images are stored in a mapping table according to time sequence. This table clarifies which specific three-dimensional coordinate point in the digital twin world corresponds to the visual focus in each frame of the image, thus obtaining a set of twin spatial location mappings.

[0037] The control information fusion submodule, based on the twin spatial location mapping set, introduces inspection task execution information and UAV flight trajectory information, integrates the route location and flight path time sequence, identifies the status of the continuously monitored route area, summarizes and forms the spatial control relationship of the inspection process, and generates UAV power grid inspection control results; Based on the twin spatial location mapping set, load the digital twin scene engine and map the 3D coordinate points in the mapping set. Instantiated rendering is performed in a virtual scene to generate visual "hotspot" markers, while importing the actual flight trajectory data of the drone. In addition, the inspection task execution status log (such as "completed" or "anomaly detected") will be displayed on the timeline of the digital twin space, showing the flight trajectory points. and hot topics Synchronous playback is correlated, and the line-of-sight vector between the drone's position and the focus area at each moment is calculated. The line-of-sight relationship is dynamically displayed in the virtual scene as connecting lines, and is considered when continuous attention exceeds a threshold time. For a line area (e.g., 5 seconds), a highlight color layer (e.g., a red semi-transparent bounding box) is superimposed on the digital model, and the corresponding voltage and tension historical data curves are displayed. The visual attention of the physical world, the drone's movement trajectory, and the electrical and mechanical properties of the line itself are spatiotemporally fused in a unified digital three-dimensional space to construct a full-element control view that includes "where to look (trajectory)," "where to look (hotspot)," and "what to look at (attributes)," generating drone power grid inspection and control results.

[0038] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A drone-based power grid inspection and control system for digital twins, characterized in that, The system includes: The inspection space construction module acquires voltage change information of conductor connection nodes within the inspection area, extracts location descriptions, determines the transmission line route, expands and compares the voltage change direction, divides the transmission line into segments, and corresponds to the voltage change direction distribution to obtain the voltage direction inspection space distribution results. The flight rhythm scheduling module obtains the tension change information of each transmission line segment and the voltage change direction in the voltage direction inspection spatial distribution results, identifies the tension stable section, schedules the UAV flight mission time, and obtains the flight time scheduling result of the tension flat section. The inspection task receiving module obtains the available flight time information of the UAV based on the flight time arrangement of each transmission line segment in the flight time arrangement result of the tension-relaxed section, filters the matching UAVs, determines the execution order of the inspection task, and obtains the corresponding relationship result of the UAV inspection task. The inspection content locking module acquires continuous images based on the execution arrangement information of each inspection task in the correspondence result of the UAV inspection tasks, extracts the contour changes of the hardware connection parts, filters consistent areas, determines the inspection focus area, and obtains the result of the continuous focus area of ​​the hardware contour.

2. The UAV power grid inspection and control system based on digital twins according to claim 1, characterized in that: The voltage pointing inspection spatial distribution results include the transmission line spatial segmentation units, the voltage pointing category corresponding to each segment, and the distribution characteristics of voltage pointing in the inspection space. The flight time arrangement results for the tension-smooth section include the inspectable time intervals corresponding to the transmission line segments, the stability attribute identifiers of the time intervals, and the continuity characteristics of the time intervals. The UAV inspection task correspondence results include the allocation correspondence between inspection tasks and UAVs, the task-bearing identifiers of each transmission line segment, and the task execution sequence identifiers. The continuous attention area results for the hardware outline include the continuous attention area range of the hardware connection parts, the outline stability identifier, and the set of key inspection units for the hardware.

3. The UAV power grid inspection and control system based on digital twins according to claim 1, characterized in that: The inspection space construction module includes a voltage change extraction submodule, a twin position association submodule, and a line direction segmentation submodule; The voltage change extraction submodule obtains the voltage change information corresponding to the conductor connection nodes in the inspection area, monitors the voltage change direction of each conductor connection node during the inspection period, summarizes the voltage change direction identifiers corresponding to each connection node based on the change direction of the voltage change start state and end state identifiers, generates a node-level voltage change direction set, and obtains the node voltage change direction identifier set. The twin location association submodule, based on the node voltage change direction identifier set, calls the position description of the conductor connection node in the digital twin space, associates the position description with the corresponding transmission line spatial extension order, organizes the arrangement relationship of the nodes on the transmission line, forms a set of node position and line direction correspondence relationship, and obtains the line direction association sequence. The line pointing segmentation submodule compares the voltage change direction with the line direction association sequence based on the node voltage change direction identifier set, identifies the location of the node where the pointing direction changes, delineates the segment range of the transmission line within the inspection area, merges the voltage pointing performance of each segment, and generates the voltage pointing inspection spatial distribution result.

4. The UAV power grid inspection and control system based on digital twins according to claim 1, characterized in that: The flight rhythm scheduling module includes a tension information acquisition submodule, a tension change discrimination submodule, and a flight time matching submodule; The tension information acquisition submodule, based on the voltage direction inspection spatial distribution results of each transmission line segment and the corresponding voltage change direction, obtains the conductor tension change information associated with the transmission line segment, monitors the conductor tension change status over time during the inspection period, arranges the tension change records in chronological order, forms a time series set of tension changes corresponding to the line segment, and generates a time series set of conductor tension changes. The tension change discrimination submodule, based on the time series set of conductor tension changes, judges the direction of tension change within a continuous time segment, compares the tension change trend of adjacent time segments, identifies segments where the change direction is consistent and no sudden shift occurs, marks the start and end positions of each segment, and summarizes them to form a set of continuous tension state segments, thus obtaining tension flat time segments. The flight time matching submodule, based on the tension-smooth time interval and the associated time requirements of the inspection tasks of each transmission line segment, matches the start and end range of the time interval, limits the UAV inspection flight time to the corresponding time interval, organizes it into a flight time arrangement sequence corresponding to the line segment, and generates the flight time arrangement result of the tension-smooth section.

5. The UAV power grid inspection and control system based on digital twins according to claim 1, characterized in that: The inspection task receiving module includes a flight time acquisition submodule, an availability status filtering submodule, and a task sequence association submodule. The flight time acquisition submodule obtains the current available flight time information of the UAV based on the flight time arrangement of each transmission line segment in the flight time arrangement result of the tension-smooth section, collects the start time and end time of each UAV, organizes them into a sequence of available flight time for the UAV, establishes a time axis correspondence with the flight time arrangement of the line segment, and generates a sequence of available flight time for the UAV. The available status filtering submodule, based on the available flight time sequence of the UAV, compares the overlap of the start and end ranges of the time axis for the flight time arrangement of each transmission line segment, determines the continuity of the UAV's status within the interval from the start to the end of the flight time arrangement, filters UAVs that are available in all time periods, and summarizes them to form a set of UAVs corresponding to each line segment, thus obtaining the UAV association set of each line segment. The task sequence association submodule, based on the line segment UAV association set and the arrangement order of the transmission line segments in the inspection area, organizes the correspondence between UAVs and line segments, arranges the inspection task execution order according to the timeline, establishes the matching relationship between UAVs and inspection tasks, and generates the UAV inspection task correspondence result.

6. The UAV power grid inspection and control system based on digital twins according to claim 1, characterized in that: The inspection content locking module includes an image sequence acquisition submodule, a hardware outline extraction submodule, and a region of interest filtering submodule. The image sequence acquisition submodule acquires continuous images during the inspection process of the UAV inspection task according to the execution arrangement information of each inspection task in the UAV inspection task correspondence result, arranges the image frames in the order of image acquisition time, associates the image frames with the corresponding power line segment identifiers, organizes them to form the image time sequence corresponding to the line segment, and generates the line segment image sequence set. The hardware outline extraction submodule, based on the line segment image sequence set, acquires the image region of the hardware connection part of the transmission line segment for each image frame, detects the boundary shape change of the hardware connection part, extracts the corresponding outline position description in each image frame, and summarizes them to form a time-ordered outline position set to obtain the hardware outline position sequence. The attention area filtering submodule compares the consistency of contour position changes in adjacent image frames based on the hardware contour position sequence, filters areas with consistent contour positions, marks the corresponding spatial range in continuous images, summarizes them to form a set of continuous attention areas in the inspection process, and generates a result of continuous attention areas for hardware contours.

7. The UAV power grid inspection and control system based on digital twins according to claim 1, characterized in that: The system also includes: The twin mapping control module establishes a mapping relationship between the position of each inspection focus area in the continuous image and the transmission line in the digital twin space based on the position description of each inspection focus area in the continuous focus area result of the hardware outline. It identifies the continuous focus area and forms the UAV power grid inspection control result. The results of the UAV power grid inspection and control include the identification of the line's area of ​​interest in the digital twin space, the status information associated with the inspection task, and the fusion information of the UAV's flight trajectory.

8. The UAV power grid inspection and control system for digital twins according to claim 7, characterized in that: The twin mapping control module includes a location mapping acquisition submodule, a spatial association establishment submodule, and a control information fusion submodule. The location mapping acquisition submodule obtains the location description of each inspection area of ​​interest in the continuous image based on the continuous interest area result of the hardware outline, collects the image coordinate information corresponding to the location description, associates the transmission line segment identifier, organizes the correspondence between image position and line number, forms the set of interest area position correspondence, and generates image position association sequence. The spatial association establishment submodule, based on the image location association sequence, calls the transmission line location description in the digital twin space, compares the arrangement order of image coordinates and twin coordinates, determines the consistency of spatial correspondence, establishes the mapping relationship between image location and twin space line location, and obtains the twin space location mapping set; The control information fusion submodule, based on the twin spatial location mapping set, introduces inspection task execution information and UAV flight trajectory information, integrates the route location and flight path time sequence, identifies the status of the continuously monitored route area, summarizes and forms the spatial control relationship of the inspection process, and generates UAV power grid inspection control results.

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