Power transmission and distribution line unmanned aerial vehicle inspection method and device based on satellite-ground fusion network

Abstract

The invention discloses a power transmission and distribution line unmanned aerial vehicle inspection method and device based on a satellite-ground fusion network, and the method comprises the steps: determining the inspection sequence of unmanned aerial vehicles in a power transmission and distribution line group according to wind directions and changes at different times; power transmission and distribution line sections which are firstly detected and finally detected in the flight of the unmanned aerial vehicle are determined, and the flight energy consumption from the last detection power transmission and distribution line to the first detection power transmission and distribution line is subtracted, and the flight energy consumption from the detection station to the first detection power transmission and distribution line and the flight energy consumption from the last detection power transmission and distribution line to the detection station are added; obtaining the flight energy consumption of the specified head-tail power transmission and distribution line; and comparing the flight energy consumption of the unmanned aerial vehicles under different head-tail combinations to obtain the first detected power transmission and distribution line and the last detected power transmission and distribution line in each flight, and obtaining the detection track of each flight of the unmanned aerial vehicles in combination with the inspection sequence of the unmanned aerial vehicles in the power transmission and distribution line groups. The influence of wind on unmanned aerial vehicle detection is reduced; the energy consumption in the data processing process is effectively reduced, and the inspection efficiency of the unmanned aerial vehicle is remarkably improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of power transmission and distribution line detection, and specifically relates to a power transmission and distribution line unmanned aerial vehicle inspection method and device based on a satellite-ground fusion network. Background Art

[0002] Patrol inspection (inspection) is the main means of operation maintenance and abnormal detection of power transmission and distribution lines, which can effectively prevent the occurrence of power transmission and distribution line equipment failures and safety hazards. Manual inspection has obvious limitations in the comprehensiveness and efficiency of power transmission and distribution line inspections, and cannot avoid the occurrence of equipment failures.

[0003] In recent years, drone inspections have been widely used in the field of power grid equipment inspections. However, in mountainous areas and post-disaster areas, when ground communication facilities are damaged, there may be no ground communication network coverage, which directly affects the efficiency and effectiveness of drone inspections of power transmission and distribution lines. At the same time, more efficient inspection methods are needed for mountainous areas and post-disaster areas. Summary of the invention

[0004] In view of this, the purpose of the present invention is to propose a method and device for UAV inspection of power transmission and distribution lines based on a satellite-ground fusion network, which can significantly improve the ability to quickly detect and identify typical faults of power transmission and distribution lines, improve the efficiency and effect of UAV inspection, and realize UAV inspection of power transmission and distribution lines in mountainous areas.

[0005] Based on the above purpose, the present invention provides a UAV inspection method for power transmission and distribution lines based on a satellite-ground fusion network, comprising:

[0006] Initialize the feasible combination of transmission line segments and distribution line segments, extract the detection energy consumption and processing energy consumption of the specified transmission and distribution lines from the storage library, and select several adjacent transmission and distribution lines to form a feasible combination according to the battery capacity of the drone;

[0007] The feasible combinations of transmission line segments and distribution line segments are grouped in an outside-in grouping manner; each section of the transmission and distribution line is allowed to be included in a grouping number greater than 1. After each grouping is determined, the transmission and distribution line of the specified section is deleted from the set to be grouped, and the remaining transmission and distribution lines are grouped until all transmission and distribution lines are grouped;

[0008] Determine the inspection order of drones within the transmission and distribution line grouping according to wind direction and changes at different times;

[0009] Determine the first and last detected power transmission and distribution line sections during the UAV flight, and obtain the flight energy consumption of the designated head and tail power transmission and distribution lines by subtracting the flight energy consumption from the last detected power transmission and distribution line to the first detected power transmission and distribution line, and adding the flight energy consumption from the detection station to the first detected power transmission and distribution line and the flight energy consumption from the last detected power transmission and distribution line to the detection station;

[0010] By comparing the flight energy consumption of drones under different head-tail combinations, the first and last transmission and distribution lines inspected in each flight are obtained. Combined with the inspection order of drones within the transmission and distribution line grouping, the inspection trajectory of each drone flight is obtained.

[0011] As a preferred solution of the power transmission and distribution line drone inspection method based on a satellite-ground fusion network, it also includes building a satellite-ground fusion network architecture, which includes a ground network and a satellite network. The ground network provides drone communication and data calculation through a detection station-oriented communication mode, and the satellite network provides drone communication through a satellite-oriented communication mode, and transmits the detection data received by the satellite in the satellite-oriented communication mode to a cloud server for processing.

[0012] As a preferred solution for the UAV inspection method of power transmission and distribution lines based on the satellite-ground fusion network, the three-dimensional Euclidean coordinate system is used to represent the position coordinates of the ground detection station and the height and horizontal coordinates of the power transmission and distribution lines; during the UAV inspection process, the hovering position of the UAV is consistent with the height of the power transmission and distribution lines;

[0013] The UAV flew J times to complete the inspection of M sections of power transmission and distribution lines in mountainous areas. Each flight of the UAV included the inspection process, data communication process, local calculation process and flight process.

[0014] As a preferred solution for the UAV inspection method of power transmission and distribution lines based on the satellite-ground fusion network, the UAV safety detection distance c is introduced during the inspection process. r , UAV safe detection distance c r The expression formula is:

[0015] c r =u ω s r

[0016] In the formula, u ω is the wind speed, s r Response time for drones;

[0017] The detection success rate of drones within a safe distance is Oq r for:

[0018]

[0019] Where λ is a parameter that reflects the performance of the camera.

[0020] As a preferred solution of the UAV inspection method for power transmission and distribution lines based on the satellite-ground fusion network, in the data communication process, the communication link between the UAV and the detection station is used as line-of-sight communication, and the channel gain f s It is expressed as:

[0021]

[0022] Where β0 is the channel gain at the reference distance c = 1m; c SR,s is the distance between the UAV and the detection station;

[0023] The data transmission rate of the drone is q s0 [m] is:

[0024]

[0025] Where A is the communication bandwidth, σ 2 is Gaussian white noise with zero mean, and O0[m] is the UAV communication power.

[0026] As a preferred solution for the UAV inspection method of power transmission and distribution lines based on the satellite-ground fusion network, during the local calculation process, the UAV adaptively adjusts the CPU calculation frequency e[m] according to the calculation task, and the calculation frequency e[m] and the calculation time s b [m], the computing task volume Q b [m] and computing energy consumption D b The formula for [m] is:

[0027]

[0028] D b [m] = θ t s b [m]e 3 [m]

[0029] In the formula, B t is the CPU cycles required to complete the computational task, θ t is the effective capacitance coefficient of the CPU.

[0030] As a preferred solution for the UAV inspection method of power transmission and distribution lines based on the satellite-ground fusion network, in the communication mode facing the inspection station, the UAV performs local calculations in the entire calculation offloading process until all the inspection data are processed; the UAV local calculation process includes the flight process from the inspection completion point to the data communication point. r0 [m] and data communication process s0[m];

[0031] In the satellite communication mode, the UAV performs local computing and computing offloading at the same time. If the UAV reaches the next section of the power transmission and distribution line before data processing is completed, it will hover and wait for all detection data to be processed before starting a new round of detection.

[0032] As a preferred solution of the UAV inspection method for power transmission and distribution lines based on the satellite-ground fusion network, during the flight process, the flight speed u of the UAV in each time slot s is obtained according to the flight trajectory p[s] of the UAV. t [s]:

[0033] u t [s]=||p[s+1]-p[s]|| / s

[0034] Where ||·|| is the Euclidean norm;

[0035] The flight energy consumption of drones e [s] includes propulsion energy consumption and overcoming its own gravitational potential energy:

[0036]

[0037] In the formula, l is the weight of the drone, f is the acceleration due to gravity, and s e is the flight time, r is the flight distance; u o is the relative propulsion speed of the UAV; u t is the flight speed of the drone.

[0038] The present invention also provides a UAV inspection device for power transmission and distribution lines based on a satellite-ground fusion network, comprising:

[0039] The feasible combination analysis module of the power transmission and distribution lines is used to initialize the feasible combination of the power transmission line segments and the distribution line segments, extract the detection energy consumption and processing energy consumption of the specified power transmission and distribution lines from the storage library, and select several adjacent power transmission and distribution lines to form a feasible combination according to the battery capacity of the drone;

[0040] The transmission and distribution line feasible combination grouping module is used to group the feasible combinations of transmission line segments and distribution line segments in an outside-in grouping manner; each section of the transmission and distribution line is allowed to be included in a grouping number greater than 1. After each grouping is determined, the transmission and distribution line of the specified section is deleted from the set to be grouped, and the remaining transmission and distribution lines are grouped until all the transmission and distribution lines are grouped;

[0041] The drone inspection sequence analysis module is used to determine the inspection sequence of drones within the transmission and distribution line group according to the wind direction and changes at different times;

[0042] The UAV flight energy consumption analysis module is used to determine the first and last detection of the power transmission and distribution line sections during the UAV flight, and obtain the flight energy consumption of the designated head and tail power transmission and distribution lines by subtracting the flight energy consumption from the last detection power transmission and distribution line to the first detection power transmission and distribution line, and adding the flight energy consumption from the detection station to the first detection power transmission and distribution line and the flight energy consumption from the last detection power transmission and distribution line to the detection station;

[0043] The UAV detection trajectory analysis module is used to compare the UAV flight energy consumption under different head-tail combinations, and obtain the first and last power transmission and distribution lines detected in each flight. Combined with the inspection order of UAVs within the transmission and distribution line grouping, the detection trajectory of each UAV flight is obtained.

[0044] As a preferred solution for the UAV inspection device for power transmission and distribution lines based on the satellite-ground fusion network, it also includes:

[0045] The satellite-ground fusion network construction module is used to construct a satellite-ground fusion network architecture, which includes a ground network and a satellite network. The ground network provides UAV communication and data calculation through a detection station-oriented communication mode, and the satellite network provides UAV communication through a satellite-oriented communication mode, and transmits the detection data received by the satellite in the satellite-oriented communication mode to the cloud server for processing.

[0046] From the above, it can be seen that the technical solution provided by the present invention initializes the feasible combination of transmission line segments and distribution line segments, extracts the detection energy consumption and processing energy consumption of the specified transmission and distribution lines from the storage library, and selects a number of adjacent transmission and distribution lines to form a feasible combination according to the battery capacity of the drone; adopts an outside-to-in grouping method to group the feasible combinations of transmission line segments and distribution line segments; each section of the transmission and distribution line is allowed to be included in a grouping greater than 1, and after each grouping is determined, the transmission and distribution line of the specified section is deleted from the set to be grouped, and the remaining transmission and distribution lines are grouped until all the transmission and distribution lines are grouped; according to the wind direction and change at different times, Optimize the inspection order of the UAV in the power transmission and distribution line group; determine the first and last power transmission and distribution line sections detected by the UAV during flight, and obtain the flight energy consumption of the designated head and tail power transmission and distribution lines by subtracting the flight energy consumption from the last detected power transmission and distribution line to the first detected power transmission and distribution line, and adding the flight energy consumption from the detection station to the first detected power transmission and distribution line and the flight energy consumption from the last detected power transmission and distribution line to the detection station; compare the flight energy consumption of the UAV under different head and tail combinations, and obtain the first and last detected power transmission and distribution lines in each flight, and combine the inspection order of the UAV in the power transmission and distribution line group to obtain the detection trajectory of each UAV flight. The present invention can optimize the detection area and detection order of the UAV, reduce the impact of wind on UAV detection, effectively reduce the energy consumption in the data processing process, and significantly improve the inspection efficiency of the UAV. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions in the present invention or related technologies, the following briefly introduces the drawings required for use in the embodiments or related technical descriptions. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0048] Figure 1 A schematic diagram of a method for unmanned aerial vehicle inspection of power transmission and distribution lines based on a satellite-ground fusion network provided in an embodiment of the present invention;

[0049] Figure 2 A schematic diagram of a satellite-ground fusion network architecture in a method for unmanned aerial vehicle inspection of power transmission and distribution lines based on a satellite-ground fusion network provided in an embodiment of the present invention;

[0050] Figure 3 A comparison chart of total energy consumption of drones using different algorithms and battery capacities provided by an embodiment of the present invention;

[0051] Figure 4 A comparison chart of energy consumption of using different algorithms to process drone data provided by an embodiment of the present invention;

[0052] Figure 5 An architecture diagram of a power transmission and distribution line drone inspection device based on a satellite-ground fusion network provided by an embodiment of the present invention;

[0053] Figure 6 Schematic diagram of the structure of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0054] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments and with reference to the accompanying drawings.

[0055] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the embodiments of the present invention should have the usual meanings understood by people with ordinary skills in the field to which the present invention belongs. The words "include" or "comprise" and the like used in the embodiments of the present invention mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, but do not exclude other elements or objects.

[0056] From the production end to the user end, electricity includes key links such as generation, transmission, transformation, distribution, and use. Each link is closely related to the stable operation of the power grid. The stability of the power grid is related to the normal operation of industrial production and residents' lives. Among them, transmission and distribution line failures are an important source of power grid accidents. In order to ensure that the transmission and distribution lines are always in a safe and reliable operating state, the equipment maintenance department must conduct regular inspections to eliminate equipment defects and safety hazards.

[0057] At present, patrol inspection (patrol inspection) is the main means of operation and maintenance and abnormal detection of power transmission and distribution lines. It can effectively prevent the occurrence of power transmission and distribution line equipment failures and safety hazards. Manual patrol inspection has obvious limitations in the comprehensiveness and efficiency of power transmission and distribution line inspection, and cannot avoid the occurrence of equipment failures. At the same time, the development of social economy has higher and higher requirements for the power supply reliability of the power system, and also puts forward higher requirements for the quality and efficiency of power grid equipment inspection. To solve this problem, drone inspection has been widely used in the field of power grid equipment inspection in recent years. Due to its simple operation, easy to carry, strong hovering ability, and applicability to a variety of working environments, it can effectively improve work efficiency and reduce labor intensity.

[0058] However, in mountainous areas and post-disaster areas, when ground communication facilities are damaged, there may be no ground communication network coverage, which directly affects the efficiency and effectiveness of drone inspection of power transmission and distribution lines. Therefore, for the above-mentioned areas, it is necessary to build a satellite-ground fusion network consisting of satellite networks and ground networks. The satellite-ground fusion network can provide safe and reliable communication guarantee for drone inspection of power transmission and distribution lines in mountainous areas and post-disaster areas.

[0059] In related technologies, exploration and research on satellite-ground integrated networking have also been carried out for drone inspection of power transmission and distribution lines in mountainous areas, mainly including: Zeybek et al. proposed a multi-perspective stereo vision technology, which uses ground control points collected by the differential global positioning system to provide reliable positioning information for drone trajectory planning: Zeybek et al. proposed a multi-perspective stereo vision technology, which uses ground control points collected by the differential global positioning system to provide reliable positioning information for drone trajectory planning. et al. evaluated the applicability of unmanned aerial vehicle laser scanning (ULS) in detailed mapping of forest environments and proposed a more reasonable trajectory planning scheme for UAV inspections. Jakovljevic et al. proposed a method to classify point cloud data collected by UAV laser scanning and lidar, and constructed a new method to generate ground digital elevation models. This provides technical support for trajectory optimization risk assessment during UAV inspections. Wu et al. designed a multi-source data fusion method in multi-target collaborative navigation, improved the stability and accuracy of positioning services, and realized inspection trajectory planning and scheduling. Dai et al. established a multivariate fusion model based on joint Kalman filtering to improve the reliability and accuracy of autonomous navigation and positioning in complex scenarios. Lange et al. proposed a cascade controller structure that can use dedicated optical flow sensors to stabilize speed and determine position. Brandao et al. proposed a vision-based line detection algorithm to provide position information for detection trajectory schemes. Liu et al. proposed the use of Q-Learning algorithm to optimize the deployment positions of multiple UAVs and achieved optimal scheduling. Xu et al. proposed a UAV trajectory planning method for continuous hovering flight. Zhang et al. proposed an iterative trajectory and scheduling optimization algorithm. In this task, multiple drones collaborate to complete data collection for the same inspection task and transmit the collected data to the base station respectively. Li et al. proposed a three-dimensional inspection environment model and constructed an improved bidirectional ant colony and discrete honey badger algorithm to perform preliminary planning of drone trajectories. Ahmed et al. proposed an automatic inspection strategy for overhead transmission lines based on drones, which can provide drone inspection paths and realize autonomous path planning of drones. Li et al. proposed an intelligent inspection platform for transmission and distribution lines based on drones and analyzed and verified it in multiple test sets. Zhan et al. proposed a drone scheduling and trajectory optimization solution.

[0060] From the above reference analysis, it can be seen that a lot of research results have been achieved in the planning and scheduling of drone inspection trajectories for power transmission and distribution in mountainous areas. However, the existing technology does not consider the impact of wind on drone flight energy consumption, nor does it jointly optimize drone flight trajectories and data processing. In addition, it does not fully consider the communication problems when the ground network in mountainous areas is unreliable or unavailable.

[0061] In view of this, the present invention proposes a satellite-ground fusion network framework based on the consideration of the impact of wind on detection accuracy and energy consumption, which effectively integrates the air network and the ground network, can provide efficient and low-cost communication services, and can also provide uninterrupted seamless communication services. Then, considering the changes in wind speed and direction, the present invention proposes a UAV inspection method for power transmission and distribution lines based on a satellite-ground fusion network, which can optimize the UAV detection area and detection sequence and reduce the impact of wind on UAV detection. The simulation experimental results show that the present invention can effectively reduce the energy consumption in the data processing process and significantly improve the efficiency of UAV inspections.

[0062] The characteristics of the present invention are that according to the characteristics of the UAV inspection of power transmission and distribution lines in mountainous areas in terms of communication service scope, data processing energy consumption, environmental interference, etc., a satellite-ground fusion network architecture that meets the requirements of UAV intelligent inspection of power transmission and distribution lines in mountainous areas is constructed, the UAV inspection trajectory and scheduling mode are jointly optimized, and a low-complexity UAV inspection method for power transmission and distribution lines is constructed, which can achieve the goal of minimizing the energy consumption of UAV data processing. The following is the specific content of the embodiments of the present invention.

[0063] See also Figure 1 The embodiment of the present invention provides a method for unmanned aerial vehicle inspection of power transmission and distribution lines based on a satellite-ground fusion network, comprising the following steps:

[0064] S1, initialize the feasible combination of transmission line segments and distribution line segments, extract the detection energy consumption and processing energy consumption of the specified transmission and distribution lines from the storage library, and select several adjacent transmission and distribution lines to form a feasible combination according to the battery capacity of the drone;

[0065] S2. Group the feasible combinations of transmission line segments and distribution line segments by using a grouping method from outside to inside; each section of the transmission and distribution line is allowed to be included in a grouping number greater than 1. After each grouping is determined, the transmission and distribution line of the specified section is deleted from the set to be grouped, and the remaining transmission and distribution lines are grouped until all the transmission and distribution lines are grouped;

[0066] S3. Determine the inspection order of drones within the power transmission and distribution line grouping according to wind direction and changes at different times;

[0067] S4. Determine the power transmission and distribution line sections that are first detected and last detected by the UAV during flight, and obtain the flight energy consumption of the designated head and tail power transmission and distribution lines by subtracting the flight energy consumption from the last detected power transmission and distribution line to the first detected power transmission and distribution line, and adding the flight energy consumption from the detection station to the first detected power transmission and distribution line and the flight energy consumption from the last detected power transmission and distribution line to the detection station;

[0068] S5. Compare the flight energy consumption of drones under different head-tail combinations, and obtain the first and last transmission and distribution lines detected in each flight. Combined with the inspection order of drones within the transmission and distribution line grouping, the detection trajectory of each drone flight is obtained.

[0069] In this embodiment, step S0 is also included, constructing a satellite-ground fusion network architecture, which includes a ground network and a satellite network. The ground network provides UAV communication and data calculation through a detection station-oriented communication mode, and the satellite network provides UAV communication through a satellite-oriented communication mode, and transmits the detection data received by the satellite in the satellite-oriented communication mode to the cloud server for processing.

[0070] See also Figure 2 Specifically, since the power transmission and distribution lines are located in remote mountainous areas, many places are not covered by reliable ground communication networks. In order to provide flexible, efficient and seamless communication services for UAV intelligent inspection of power transmission and distribution lines, the present invention adopts a satellite-ground fusion network architecture to provide data communication and computing services for UAV intelligent inspection. The satellite-ground fusion network architecture consists of two parts: the ground network and the satellite network. On the ground, the limited communication network covered by the ground base station provides communication and computing services for UAVs within a limited range. In the sky, multiple low-Earth orbit (LEO) satellites provide uninterrupted communication services for mountain power transmission and distribution lines. The detection data received by the satellite will be transmitted to the cloud server for processing.

[0071] Among them, in the satellite-ground fusion network, the drone provides typical fault and tree obstacle detection services for M sections of mountainous power transmission and distribution lines, and then analyzes and processes the detection data. Due to the limited battery capacity of the drone, the drone needs to fly J times to complete the detection of the mountainous power transmission and distribution lines. The sets of M sections of transmission and distribution lines and J flights are represented as [1,2,...,M] and [1,2,...,J] respectively. Each flight includes four processes: takeoff, detection, calculation and unloading, and charging. After the drone takes off from the detection location, it needs to fly to the power transmission and distribution lines in sequence according to the scheduling trajectory. After arriving near the transmission and distribution lines, the drone begins to detect. Using the high-definition camera carried by the drone to take photos and videos, the drone can obtain the surface condition of the transmission and distribution lines. After the detection is completed, the drone processes the detection data through local calculation or data communication. The drone can select the best data to transmit to the detection station or satellite. Considering the timeliness of the inspection data, all inspection data must be processed before the next section of the transmission and distribution line begins to be inspected. After the inspection data is processed, the drone flies to the next section of the transmission and distribution line and starts the inspection work. When all the transmission and distribution lines required for the inspection are inspected, the drone returns to the inspection station to charge. When the drone is fully charged, it starts the next inspection mission. When all the transmission and distribution lines are inspected, the drone completes the established inspection mission.

[0072] In this embodiment, in order to better represent the location distribution, a three-dimensional Euclidean coordinate system is used to represent the location coordinates of the ground detection station, the height and horizontal coordinates of the power transmission and distribution line; during the drone detection process, the hovering position of the drone is consistent with the height of the power transmission and distribution line;

[0073] The UAV flew J times to complete the inspection of M sections of power transmission and distribution lines in mountainous areas. Each flight of the UAV included the inspection process, data communication process, local calculation process and flight process.

[0074] Specifically, to simplify the problem, the location of the ground detection station is set to k SR =(0,0,G0). The height of the transmission and distribution line is set to y m , the horizontal coordinate is k m =(w m ,x m ). During the detection process, it is assumed that the hovering position of the drone is at a height y of the power transmission and distribution line. m Considering that wind speed usually increases with the increase of flight altitude, in order to reduce the energy consumption of the drone during flight. Assuming that the drone flies at the minimum safe altitude yr during flight, the horizontal plane coordinate of the s time slot is p[s] = (w s ,x s ). The distance between the drone and the detection station c SR,s and the distance c between the drone and the transmission and distribution line m m,s It is expressed as:

[0075]

[0076] Due to the limited battery capacity of the drone, the drone needs to fly J times to complete the inspection of M sections of mountain transmission and distribution lines. In each flight, there are inspection processes, data communication processes, local computing processes and flight processes.

[0077] Specifically, during the detection process, assuming that the detection time of the drone is s c is a constant that is only related to the size of the fan blades. In order to ensure the accuracy of the detection, the UAV needs to be as close to the surface of the power transmission and distribution line as possible to more accurately collect the image data of the power transmission and distribution line. However, considering that the wind direction may change at any time, once wind shear occurs during the detection process, it is very easy to cause the UAV to collide with the power transmission and distribution line. In order to avoid this situation, the safe detection distance c is introduced. r =u ω s r . Where u is the wind speed, s ris the drone response time. Limited by the camera performance, the detection accuracy of the drone will decrease as the distance between the drone and the power transmission and distribution line increases. In order to better reflect the relationship between the detection distance and detection accuracy, a probabilistic detection model is established. The detection success rate of the drone within the safe distance is:

[0078]

[0079] Where λ is a parameter that reflects the performance of the camera.

[0080] Specifically, during the data communication process, assuming that the communication link between the UAV and the detection station is line-of-sight communication, the channel gain can be expressed as:

[0081]

[0082] Where β0 is the channel gain at the reference distance c = 1m. According to the UAV communication power O0[m], the data transmission rate q s0 [m] can be obtained:

[0083]

[0084] Where A is the communication bandwidth, σ 2 is a Gaussian white noise with a mean of zero. It can be obtained that when the UAV uses the detection station to offload calculations, under the conditions of communication power O0[m] and data communication time s0[m], the data transmission volume Q s0 [m] and communication energy consumption D s0 [m] are:

[0085]

[0086] However, in actual transmission environments, as the transmission distance increases, the transmission path still contains non-line-of-sight communication, which will lead to a decrease in transmission reliability. In order to simplify this problem, the present invention uses the line-of-sight communication success rate to represent the probability of successful data transmission Oq s0 [m], that is:

[0087]

[0088] In the formula, c s0 =290lg(y r )-433, for height y r And the communication power is o0 = 232lg (y r )-0.96. According to equations (2) and (7), the probability of reliable detection and successful transmission of the transmission and distribution line is:

[0089] Oq rtb [m] = Oq r*O s0 [m] (8)

[0090] Therefore, if the UAV uses the detection station for data communication, when the wind speed is high, the safety distance of the UAV increases accordingly, thereby reducing the detection accuracy. In order to ensure the effectiveness of data detection and transmission, the UAV needs to be as close to the detection station as possible to improve the reliability of data transmission. For the satellite communication mode, long-distance communication is used. Assuming that its transmission rate q r0 It is linearly related to the transmission power O0[m] and is much smaller than q s0 When the UAV uses the satellite for computation offloading, under the conditions of communication power O0[m] and data communication time s0[m], the data transmission volume Q r0 [m] and communication energy consumption D r0 [m]:

[0091]

[0092] During the communication process, if the UAV adopts the communication mode facing the inspection station, then the UAV must fly to the inspection station for high-reliability and high-speed data transmission. At the same time, under the same transmission power O0[m], the transmission rate q of satellite communication r0 Much lower than the transmission rate q of the detection station communication s0 Therefore, if the communication mode towards the detection station is selected, the communication mode towards the satellite will only lead to higher power consumption. Since the two communication modes have different energy consumption characteristics, it is necessary to select an energy-saving and efficient communication mode in actual work.

[0093] Specifically, in the local computing process, in order to use energy more efficiently, the drone can adaptively adjust the CPU computing frequency e[m] according to the computing task. b [m], the computing task volume Q b [m] and computing energy consumption D b [m]:

[0094]

[0095] In the formula, B t is the CPU cycles required to complete the computational task, θ t is the effective capacitance coefficient of the CPU.

[0096] Among them, in the partial computing offload mode, the drone can use data communication and local computing to process data at the same time. Therefore, the constraints on detection data processing are:

[0097]

[0098] In the formula, Qm is the detection task VSm of the power transmission and distribution line, and its value is related to the size of the power transmission and distribution line. σ={0,1} is the data communication mode selection. σ=0 means that the UAV adopts the detection station communication mode. σ=1 means that the UAV adopts the satellite communication mode. According to the selection of data communication mode, the data processing energy consumption of the power transmission and distribution line VSm is:

[0099] D o [m] = D b [m]+(1-s[m])D s0 [m]+s[m]D r0 [m] (12)

[0100] In the communication mode for the inspection station, the UAV can perform local calculations during the entire computation offloading process until all the inspection data are processed. Therefore, the UAV local calculation process includes the flight process from the inspection completion point to the data communication point. r0 [m] and data communication process s0[m]. It can be concluded that in the communication mode facing the detection station, the calculation time of the drone is s b [m] = s r0 [m]+s0[m]. The line detection and data processing time of a certain transmission and distribution line VSm is S o,s0 [m] = s c +s r0 [m]+s0[m]+s 0r [m].

[0101] In the satellite-oriented communication mode, the drone can also perform local computing and computation offloading at the same time. If the drone reaches the next section of the transmission and distribution line before the data processing is completed, it still needs to hover and wait for all the detection data to be processed before starting a new round of detection. b [m] = s0[m] = s e [m], the energy consumption in the data processing process is the smallest, and the detection and data processing time VSm of a certain section of the transmission and distribution line is S o,s0 [m] = s c +s b [m].

[0102] According to the unloading mode, the total flight time of the jth flight is

[0103]

[0104] In the formula, s e1 [j] is the flight time of the UAV from the inspection station to the first transmission and distribution line to be inspected in the jth flight mission. j is the set of transmission and distribution lines that need to be inspected in the jth flight mission.

[0105] Specifically, during the flight of the drone, according to the flight trajectory p[s] of the drone, the flight speed of the drone in each time slot s can be obtained:

[0106] u t [s]=||p[s+1]-p[s]|| / s (14)

[0107] In the formula, ||·|| is the Euclidean norm. Therefore, for a given j-time flight mission trajectory, the corresponding flight time can be obtained: S c [j]=p[j] / u t .

[0108] During the flight, the drone also needs to overcome the wind speed u ω Therefore, the relative propulsion speed of the drone is u o =u t -u ω Based on safety considerations, the maximum propulsion speed of the drone is set to u max During the flight, the energy consumption of the drone is not only used to provide propulsion, but also to overcome its own gravitational potential energy. Therefore, the flight energy consumption of the drone consists of two parts: propulsion energy consumption and overcoming its own gravitational potential energy, namely:

[0109]

[0110] In the formula, l is the weight of the drone, f is the acceleration due to gravity, and s e is the flight time, and r is the flight distance. During the detection process, in order to ensure the detection accuracy, the drone needs to be detected in hovering mode, that is, the drone needs to overcome wind resistance during the detection process and keep the relative ground speed at 0.

[0111] According to the UAV flight energy consumption and the data processing energy consumption of each section of the power transmission and distribution line in the J flight mission, the total energy consumption of the J flight mission is:

[0112]

[0113] Due to the limited battery capacity of the drone, the energy consumption of the drone in each flight mission is limited to:

[0114]

[0115] Where D t is the battery capacity of the drone. After each mission, the drone needs to return to the inspection station to recharge. For the jth mission, the charging power c b The charging time under bg [j] = D j / c b.

[0116] In this embodiment, in step S1, in each flight, since the starting point and the end point of the drone are both inspection stations, the drone can not only fly back and forth between a certain section of power transmission and distribution line and the inspection station, but also provide services for up to j adjacent sections of power transmission and distribution lines. Due to the limited battery capacity of the drone, there are:

[0117]

[0118] In the formula, c m is the distance between a certain transmission and distribution line m and the detection station, r avg,m is the average distance between a certain transmission and distribution line m and the adjacent transmission and distribution line, D c,m is the detection energy consumption of the UAV, D oqn,m is the data processing energy consumption of the drone, and L is the number of power transmission and distribution lines. In this step, the detection energy consumption D of a power transmission and distribution line can be extracted from the repository. c,m and processing energy consumption D oqn,m By calculating formula (18), at most j adjacent transmission and distribution lines can be selected to form a feasible combination.

[0119] In this embodiment, during the grouping process of step S2, if a section of the power transmission and distribution line far from the detection station is omitted, only detecting it will generate a large amount of flight energy consumption. Therefore, in the grouping process, an outside-in grouping method is adopted. In addition, in order to complete the detection of all power transmission and distribution lines more quickly, each section of the power transmission and distribution line can be included in multiple groups. Therefore, after each group is determined, a section of the power transmission and distribution line in the group will be deleted from the set to be grouped, and then the remaining power transmission and distribution lines will be grouped until all the power transmission and distribution lines are grouped.

[0120] In this embodiment, in step S3, for a given power transmission and distribution line group, the inspection order within the group is determined. On the one hand, a reasonable flight direction can reduce the flight energy consumption caused by headwind. On the other hand, the difference in wind speed and wind direction at different times will also affect the flight energy consumption. Therefore, it is necessary to determine the inspection order within the group according to the wind direction at different times and possible changes.

[0121] In this embodiment, in steps S4 and S5, in order to obtain the detection trajectory of each flight, it is also necessary to determine the power transmission and distribution line sections that should be detected first and last in the flight. By subtracting the flight energy consumption from the last detected power transmission and distribution line to the first detected power transmission and distribution line, and adding the flight energy consumption from the detection station to the first detected power transmission and distribution line and the flight energy consumption from the last detected power transmission and distribution line to the detection station. In this way, the flight energy consumption of different head and tail power transmission and distribution lines can be obtained. By comparing the flight energy consumption under different head and tail combinations, the power transmission and distribution line that should be detected first and the power transmission and distribution line that should be detected last in each flight can be obtained. Then, combined with the group detection order, the detection trajectory of each flight can be obtained.

[0122] In a possible embodiment, due to wind changes, different UAV scheduling will affect flight energy consumption. Therefore, it is necessary to optimize the flight scheduling of UAVs. Generally speaking, wind changes have a certain regularity, that is, the wind speed is higher in the morning and evening, and the wind speed is weaker at noon. Therefore, the periodic change of wind speed is combined with the flight energy consumption of different flights. For example, when the wind speed is higher, flights with lower flight energy consumption are arranged, and when the wind speed is lower, flights with higher flight energy consumption are arranged.

[0123] In a possible embodiment, during the grouping process, the outer grouping of the grouping is first performed, and the optimal power transmission and distribution lines are selected for combination. There are suboptimal solutions in the grouping close to the center, which will reduce the overall detection efficiency. Therefore, it is necessary to optimize and reorganize the suboptimal solutions in the grouping. For the cross-grouping of a certain section of power transmission and distribution lines in the detection flight trajectory, it can be separated from the existing combination. Then, it is reallocated to the group adjacent to the section of power transmission and distribution lines. When there is no cross-grouping in all combinations, the flight sorties can be split and reallocated when the wind speed is high.

[0124] In a possible embodiment, the wind speed changes during the day and the corresponding power transmission and distribution line grouping scheme are recorded in the storage library. After the drone completes the data processing optimization, it is also necessary to update the data transmission volume, data communication mode and data processing energy consumption of each section of the power transmission and distribution line in the storage library.

[0125] In order to verify the effectiveness of the UAV inspection algorithm proposed in this invention, relevant experiments were carried out using the Jingwei M30 UAV. The take-off weight of the UAV with the equipment is about 4kg, and it can carry two batteries. A certain section of the power transmission and distribution line is selected as the inspection object. Its height is 40 meters and its width is 8. In terms of satellite communication, it is assumed that during the data transmission process, there is always a low-earth orbit satellite to provide full coverage of communication services for the power transmission and distribution line inspection area, and its transmission rate is 10Mbps.

[0126] In order to verify the effectiveness of the detection trajectory planning and UAV scheduling optimization algorithm proposed in this invention, the total energy required for UAV detection under different schemes and battery capacities is given in this invention. Comparison Algorithm 1: Fixed detection algorithm. Comparison Algorithm 2: UAV detection trajectory planning algorithm. Comparison Algorithm 3: Algorithm proposed in this invention.

[0127] like Figure 3 As shown in the figure, the performance of the UAV inspection scheme proposed by the present invention is better than the other two control methods. This shows that the joint optimization of UAV trajectory planning and scheduling is effective. In all algorithms, when the battery capacity of the UAV is low, only a single section of the power transmission and distribution line can be detected in a single flight. When the battery capacity increases slightly, the total energy consumption of the UAV remains unchanged in the initial stage. However, as the battery capacity further increases, the number of power transmission and distribution lines that can be detected by the UAV in a single flight increases, the number of flights decreases, and the total energy consumption of the UAV decreases rapidly. When the battery capacity of the UAV increases to a certain critical value, more power transmission and distribution lines cannot be detected in each flight. At this time, as the battery capacity increases, the weight of the UAV will also increase, resulting in an increase in the total flight energy consumption.

[0128] In order to further verify the effectiveness of the algorithm proposed in this invention, see Figure 4 , which shows the energy consumption performance comparison results of UAV data processing under different algorithms.

[0129] Comparison Algorithm 1: All UAVs perform local calculations. The UAVs perform local calculations on all detection data at a fixed CPU frequency.

[0130] Comparison Algorithm 2: All transmitted to the detection station. The UAV transmits all detection data to the detection station for processing.

[0131] Comparison Algorithm 3: Transmit all to satellite. The drone transmits all detection data to the satellite for processing.

[0132] The algorithm proposed in the present invention utilizes a satellite-ground fusion network to transmit and process data.

[0133] like Figure 4As shown in the figure, compared with other comparative algorithms, the UAV used by the algorithm proposed in the present invention has the lowest energy consumption. This is because the algorithm proposed in the present invention can select different communication modes for data processing according to actual conditions. At the same time, trajectory and scheduling optimization also further improve the data processing efficiency. In the satellite-oriented communication mode, when the amount of data is small, the UAV can significantly reduce the flight energy consumption during data communication by using satellite communication. When the amount of data is large, due to the low transmission efficiency of satellite communication, the UAV will consume more time during data transmission. In the communication mode oriented to the detection station, since the UAV needs to fly to the communication point for communication, even if the amount of data transmitted is small, a large amount of flight energy will be consumed during the flight. With the increase of data volume, some power transmission and distribution lines close to the detection station can select the detection station for data communication. In addition, in all local computing schemes, as the amount of data increases, the energy consumption of UAV processing will also increase rapidly. Compared with the scheme that uses satellite communication in its entirety, the energy consumption increase of this process is much smaller. It can be seen that compared with the data processing energy consumption, the flight energy consumption of the UAV is the most important factor affecting the data processing energy consumption.

[0134] In summary, the embodiment of the present invention constructs a satellite-ground fusion network architecture, which includes a ground network and a satellite network. The ground network provides drone communication and data calculation through a detection station-oriented communication mode, and the satellite network provides drone communication through a satellite-oriented communication mode, and transmits the detection data received by the satellite in the satellite-oriented communication mode to the cloud server for processing. Initialize the feasible combination of transmission line segments and distribution line segments, extract the detection energy consumption and processing energy consumption of the specified transmission and distribution lines from the storage library, and select a number of adjacent transmission and distribution lines to form a feasible combination according to the battery capacity of the drone; group the feasible combinations of transmission line segments and distribution line segments using an outside-to-in grouping method; each section of the transmission and distribution line is allowed to be included in a grouping greater than 1, and after each grouping is determined, delete the specified section of the transmission and distribution line from the set to be grouped, and group the remaining transmission and distribution lines until all the transmission and distribution lines are grouped; determine the transmission and distribution line segmentation according to the wind direction and changes at different times. The inspection order of the drones in the group; determine the power transmission and distribution line sections that are first detected and last detected during the drone flight, and obtain the flight energy consumption of the designated head and tail power transmission and distribution lines by subtracting the flight energy consumption from the last detected power transmission and distribution line to the first detected power transmission and distribution line, and adding the flight energy consumption from the detection station to the first detected power transmission and distribution line and the flight energy consumption from the last detected power transmission and distribution line to the detection station; compare the flight energy consumption of the drones under different head and tail combinations, and obtain the first detected power transmission and distribution line and the last detected power transmission and distribution line in each flight, and combine the inspection order of the drones in the power transmission and distribution line group to obtain the detection trajectory of each drone flight. The present invention can optimize the drone detection area and detection order, reduce the impact of wind on drone detection; can effectively reduce energy consumption in the data processing process, and significantly improve the efficiency of drone inspections.

[0135] It should be noted that the method of the embodiment of the present invention can be performed by a single device, such as a computer or a server. The method of this embodiment can also be applied in a distributed scenario and completed by multiple devices cooperating with each other. In the case of such a distributed scenario, one of the multiple devices can only perform one or more steps in the method of the embodiment of the present invention, and the multiple devices will interact with each other to complete the described method.

[0136] It should be noted that some embodiments of the present invention are described above. In some cases, the actions or steps recorded can be performed in an order different from that in the above embodiments and still achieve the desired results. In addition, the process depicted in the accompanying drawings does not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0137] See also Figure 5Based on the same inventive concept, corresponding to any of the above-mentioned embodiments and methods, an embodiment of the present invention further provides a UAV inspection device for power transmission and distribution lines based on a satellite-ground fusion network, which includes:

[0138] The power transmission and distribution line feasible combination analysis module 100 is used to initialize the feasible combination of the power transmission line segment and the distribution line segment, extract the detection energy consumption and processing energy consumption of the specified power transmission and distribution line from the storage library, and select a number of adjacent power transmission and distribution lines to form a feasible combination according to the battery capacity of the drone;

[0139] The transmission and distribution line feasible combination grouping module 200 is used to group the feasible combinations of transmission line segments and distribution line segments in an outside-in grouping manner; each section of the transmission and distribution line is allowed to be included in a grouping number greater than 1, and after each grouping is determined, the transmission and distribution line of the specified section is deleted from the set to be grouped, and the remaining transmission and distribution lines are grouped until all the transmission and distribution lines are grouped;

[0140] The drone inspection sequence analysis module 300 is used to determine the inspection sequence of drones within the power transmission and distribution line group according to the wind direction and changes at different times;

[0141] The UAV flight energy consumption analysis module 400 is used to determine the power transmission and distribution line segments detected first and last during the UAV flight, and obtain the flight energy consumption of the designated head and tail power transmission and distribution lines by subtracting the flight energy consumption from the last detected power transmission and distribution line to the first detected power transmission and distribution line, and adding the flight energy consumption from the detection station to the first detected power transmission and distribution line and the flight energy consumption from the last detected power transmission and distribution line to the detection station;

[0142] The drone detection trajectory analysis module 500 is used to compare the drone flight energy consumption under different head-tail combinations, obtain the first and last power transmission and distribution lines detected in each flight, and combine the inspection order of drones within the power transmission and distribution line group to obtain the detection trajectory of each drone flight.

[0143] In this embodiment, it also includes:

[0144] The satellite-ground fusion network construction module 600 is used to construct a satellite-ground fusion network architecture, which includes a ground network and a satellite network. The ground network provides UAV communication and data calculation through a detection station-oriented communication mode, and the satellite network provides UAV communication through a satellite-oriented communication mode, and transmits the detection data received by the satellite in the satellite-oriented communication mode to the cloud server for processing.

[0145] The device of the above-mentioned embodiment is used to implement a corresponding UAV inspection method for power transmission and distribution lines based on a satellite-ground fusion network in any of the above-mentioned embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0146] Based on the same inventive concept, corresponding to any of the above-mentioned embodiments and methods, the present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method for unmanned aerial vehicle inspection of power transmission and distribution lines based on a satellite-ground fusion network as described in any of the above embodiments is implemented.

[0147] Figure 6 A more specific schematic diagram of the hardware structure of an electronic device provided in this embodiment is shown, and the device may include: a processor 710, a memory 720, an input / output interface 730, a communication interface 740, and a bus 750. The processor 710, the memory 720, the input / output interface 730, and the communication interface 740 are connected to each other in communication within the device through the bus 750.

[0148] The processor 710 can be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.

[0149] The memory 720 may be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage device, dynamic storage device, etc. The memory 720 may store an operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented by software or firmware, the relevant program codes are stored in the memory 720 and are called and executed by the processor 710.

[0150] The input / output interface 730 is used to connect the input / output module to realize information input and output. The input / output module can be configured as a component in the device (not shown in the figure), or it can be externally connected to the device to provide corresponding functions. The input device may include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output device may include a display, a speaker, a vibrator, an indicator light, etc.

[0151] The communication interface 740 is used to connect a communication module (not shown) to realize communication interaction between the device and other devices. The communication module can realize communication through a wired mode (such as USB, network cable, etc.) or a wireless mode (such as mobile network, WIFI, Bluetooth, etc.).

[0152] The bus 750 comprises a pathway that transmits information between the various components of the device (eg, the processor 710 , the memory 720 , the input / output interface 730 , and the communication interface 740 ).

[0153] It should be noted that, although the above device only shows the processor 710, the memory 720, the input / output interface 730, the communication interface 740 and the bus 750, in the specific implementation process, the device may also include other components necessary for normal operation. In addition, it can be understood by those skilled in the art that the above device may also only include the components necessary for implementing the embodiments of the present specification, and does not necessarily include all the components shown in the figure.

[0154] The electronic device of the above-mentioned embodiment is used to implement a corresponding UAV inspection method for power transmission and distribution lines based on a satellite-ground fusion network in any of the above-mentioned embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0155] Based on the same inventive concept, corresponding to any of the above-mentioned embodiment methods, the present invention also provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute a method for unmanned aerial vehicle inspection of power transmission and distribution lines based on a satellite-ground fusion network as described in any of the above embodiments.

[0156] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, read-only compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device.

[0157] The computer instructions stored in the storage medium of the above embodiment are used to enable the computer to execute a method for unmanned aerial vehicle inspection of power transmission and distribution lines based on a satellite-ground fusion network as described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0158] Those skilled in the art should understand that the discussion of any of the above embodiments is merely illustrative and is not intended to imply that the scope of the present invention is limited to these examples. Under the concept of the present invention, the technical features in the above embodiments or different embodiments may be combined, the steps may be implemented in any order, and there are many other variations of different aspects of the embodiments of the present invention as described above, which are not provided in detail for the sake of simplicity.

[0159] In addition, to simplify the description and discussion, and in order not to obscure the embodiments of the present invention, known power / ground connections to integrated circuit (IC) chips and other components may or may not be shown in the provided figures. In addition, the devices may be shown in the form of block diagrams to avoid obscuring the embodiments of the present invention, and this also takes into account the fact that the details of the implementation of these block diagram devices are highly dependent on the platform on which the embodiments of the present invention will be implemented (i.e., these details should be fully within the scope of understanding of those skilled in the art). Where specific details (e.g., circuits) are set forth to describe exemplary embodiments of the present invention, it will be apparent to those skilled in the art that embodiments of the present invention may be implemented without these specific details or with variations in these specific details. Therefore, these descriptions should be considered illustrative rather than restrictive.

[0160] Although the invention has been described in conjunction with specific embodiments of the invention, many replacements, modifications and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may use the embodiments discussed.

[0161] The embodiments of the present invention are intended to cover all such substitutions, modifications and variations that fall within the scope of the claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiments of the present invention should be included in the protection scope of the present invention.

Claims

1. A UAV inspection method for power transmission and distribution lines based on a satellite-ground fusion network, where: include: Initialize the feasible combination of transmission line segments and distribution line segments, extract the detection energy consumption and processing energy consumption of the specified transmission and distribution lines from the storage library, and select several adjacent transmission and distribution lines to form a feasible combination according to the battery capacity of the drone; The feasible combinations of transmission line segments and distribution line segments are grouped in an outside-in grouping manner; each section of the transmission and distribution line is allowed to be included in a grouping number greater than 1. After each grouping is determined, the transmission and distribution line of the specified section is deleted from the set to be grouped, and the remaining transmission and distribution lines are grouped until all transmission and distribution lines are grouped; Determine the inspection order of drones within the transmission and distribution line grouping according to wind direction and changes at different times; Determine the first and last detected power transmission and distribution line sections during the UAV flight, and obtain the flight energy consumption of the designated head and tail power transmission and distribution lines by subtracting the flight energy consumption from the last detected power transmission and distribution line to the first detected power transmission and distribution line, and adding the flight energy consumption from the detection station to the first detected power transmission and distribution line and the flight energy consumption from the last detected power transmission and distribution line to the detection station; By comparing the flight energy consumption of drones under different head-tail combinations, the first and last transmission and distribution lines inspected in each flight are obtained. Combined with the inspection order of drones within the transmission and distribution line grouping, the inspection trajectory of each drone flight is obtained.

2. The method for UAV inspection of power transmission and distribution lines based on satellite-ground fusion network according to claim 1, wherein: It also includes building a satellite-ground fusion network architecture, which includes a ground network and a satellite network. The ground network provides drone communication and data calculation through a detection station-oriented communication mode, and the satellite network provides drone communication through a satellite-oriented communication mode, and transmits the detection data received by the satellite in the satellite-oriented communication mode to a cloud server for processing.

3. The power transmission and distribution line drone inspection method based on satellite-ground fusion network according to claim 2, wherein: Use the three-dimensional Euclidean coordinate system to represent the location coordinates of the ground detection station and the height and horizontal coordinates of the transmission and distribution lines; During the drone inspection process, the drone’s hovering position is consistent with the height of the power transmission and distribution lines; The UAV flew J times to complete the inspection of M sections of power transmission and distribution lines in mountainous areas. Each flight of the UAV included the inspection process, data communication process, local calculation process and flight process.

4. The method for UAV inspection of power transmission and distribution lines based on satellite-ground fusion network according to claim 3, wherein: During the inspection process, the drone safety detection distance c is introduced r , UAV safe detection distance c r The expression formula is: c r =u ω s r In the formula, u ω is the wind speed, s r Response time for drones; The detection success rate of drones within a safe distance is Oq r for: Where λ is a parameter that reflects the performance of the camera.

5. The method for UAV inspection of power transmission and distribution lines based on satellite-ground fusion network according to claim 3, wherein: In the data communication process, the communication link between the UAV and the detection station is used as line-of-sight communication, and the channel gain f s It is expressed as: Where β0 is the channel gain at the reference distance c = 1m; c SR,s is the distance between the UAV and the detection station; The data transmission rate of the drone is q s0 [m] is: Where A is the communication bandwidth, σ 2 is Gaussian white noise with zero mean, and O0[m] is the UAV communication power.

6. The method for UAV inspection of power transmission and distribution lines based on satellite-ground fusion network according to claim 3, wherein: During the local computing process, the drone adaptively adjusts the CPU computing frequency e[m] according to the computing task, and the computing frequency e[m] and computing time s b [m], the computing task volume Q b [m] and computing energy consumption D b The formula for [m] is: D b [m]=θ t s b [m]e 3 [m] In the formula, B t is the CPU cycles required to complete the computational task, θ t It is the effective capacitance coefficient of the CPU.

7. The method for UAV inspection of power transmission and distribution lines based on satellite-ground fusion network according to claim 6, wherein: In the detection station-oriented communication mode, the UAV performs local calculations during the entire computation offloading process until all detection data are processed; the UAV local calculation process includes the flight process from the detection completion point to the data communication point. r0 [m] and data communication process s0[m]; In the satellite communication mode, the UAV performs local computing and computing offloading at the same time. If the UAV reaches the next section of the power transmission and distribution line before data processing is completed, it will hover and wait for all detection data to be processed before starting a new round of detection.

8. The method for UAV inspection of power transmission and distribution lines based on satellite-ground fusion network according to claim 3, wherein: During the flight process, according to the flight trajectory p[s] of the drone, the flight speed u of the drone in each time slot s is obtained. t [s]: u t [s]=||p[s+1]-p[s]|| / s Where ||·|| is the Euclidean norm; The flight energy consumption of drones e [s] includes propulsion energy consumption and overcoming its own gravitational potential energy: In the formula, l is the weight of the drone, f is the acceleration due to gravity, and s e is the flight time, r is the flight distance; u o is the relative propulsion speed of the UAV; u t is the flight speed of the drone.

9. UAV inspection device for power transmission and distribution lines based on satellite-ground fusion network, including: include: The feasible combination analysis module of the power transmission and distribution lines is used to initialize the feasible combination of the power transmission line segments and the distribution line segments, extract the detection energy consumption and processing energy consumption of the specified power transmission and distribution lines from the storage library, and select several adjacent power transmission and distribution lines to form a feasible combination according to the battery capacity of the drone; A transmission and distribution line feasible combination grouping module is used to group feasible combinations of transmission line segments and distribution line segments in an outside-to-inside grouping manner; Each section of the transmission and distribution line is allowed to be included in a grouping number greater than 1. After each grouping is determined, the transmission and distribution line of the specified section is deleted from the set to be grouped, and the remaining transmission and distribution lines are grouped until all the transmission and distribution lines are grouped; The drone inspection sequence analysis module is used to determine the inspection sequence of drones within the transmission and distribution line group according to the wind direction and changes at different times; The UAV flight energy consumption analysis module is used to determine the first and last detection of the power transmission and distribution line sections during the UAV flight, and obtain the flight energy consumption of the designated head and tail power transmission and distribution lines by subtracting the flight energy consumption from the last detection power transmission and distribution line to the first detection power transmission and distribution line, and adding the flight energy consumption from the detection station to the first detection power transmission and distribution line and the flight energy consumption from the last detection power transmission and distribution line to the detection station; The UAV detection trajectory analysis module is used to compare the UAV flight energy consumption under different head-tail combinations, and obtain the first and last power transmission and distribution lines detected in each flight. Combined with the inspection order of UAVs within the transmission and distribution line grouping, the detection trajectory of each UAV flight is obtained.

10. The UAV inspection device for power transmission and distribution lines based on satellite-ground fusion network according to claim 9, wherein: Also includes: The satellite-ground fusion network construction module is used to construct a satellite-ground fusion network architecture, which includes a ground network and a satellite network. The ground network provides UAV communication and data calculation through a detection station-oriented communication mode, and the satellite network provides UAV communication through a satellite-oriented communication mode, and transmits the detection data received by the satellite in the satellite-oriented communication mode to the cloud server for processing.

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