Unmanned aerial vehicle planning method based on charging pile and charging pile

Abstract

The invention relates to the technical field of unmanned aerial vehicles, in particular to an unmanned aerial vehicle planning method based on a charging pile and the charging pile, and aims to solve the problem of how to modify an existing working path according to changes of an external environment when an unmanned aerial vehicle executes a detection task. The invention provides an unmanned aerial vehicle planning method, which comprises the following steps: determining the travel range of an unmanned aerial vehicle in various weathers according to a travel analysis result, and setting the basic number of unmanned aerial vehicles in a target area according to the travel range; determining a basic cruise path for the unmanned aerial vehicle to execute the detection task according to the weather forecast data and the travel range; when the unmanned aerial vehicle executes the detection task along the basic cruise path, a corrected cruise path is determined according to the actual weather data, and the correction duration of completing the detection task by the corrected cruise path is calculated; and adjusting the number of the unmanned aerial vehicles executing the detection task according to the time limit requirement and the correction duration of the detection task.

Description

Technical Field

[0001] This invention relates to the field of unmanned aerial vehicle (UAV) technology, and more specifically, to a UAV planning method based on charging piles and charging piles. Background Technology

[0002] In today's wave of technological development, drones play a crucial role in numerous fields, such as geographic surveying, agricultural monitoring, and power line inspection. As the application scenarios for drones continue to expand, the demand for them is also increasing. Currently, when drones perform tasks, they only plan their work based on the outdoor environment at the time of departure. When environmental changes occur during the mission, they cannot promptly adjust their working modes accordingly. This easily leads to drones frequently returning to charging stations during flight, significantly reducing the efficiency of completing inspection tasks. In cases of drastic environmental changes, they may even crash due to depleted battery power.

[0003] Therefore, how to reasonably modify the existing working path according to changes in the external environment when drones perform detection tasks, and ensure the drone's endurance while completing the task efficiently, is one of the problems that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0004] The problem this invention solves is: how to modify the existing working path according to changes in the external environment when a drone is performing a detection task.

[0005] To address the aforementioned problems, this invention provides a drone planning method based on charging piles. The method includes: installing charging piles under high-voltage power line towers; charging drones via these piles; analyzing the drone's travel distance after each charging cycle to obtain travel analysis results; determining the drone's travel range under various weather conditions based on the travel analysis results; setting a basic number of drones within a target area based on the travel range; determining a basic cruise path for the drone to perform detection tasks based on weather forecast data and the travel range; determining whether the basic cruise path needs correction based on actual weather data when the drone performs the detection task along the basic cruise path; if so, determining a corrected cruise path based on the drone's charging efficiency and the scope of the detection task, and calculating the correction time required to complete the detection task; adjusting the number of drones performing the detection task based on the time limit requirements and correction time; if not, continuing to perform the detection task along the basic cruise path.

[0006] Compared with existing technologies, the technical effects achieved by adopting this solution are as follows: By setting up charging piles under high-voltage power line towers, drones can have stable outdoor endurance; the acquisition of trip analysis results can provide information on the drone's operation in the current environment, improving the accuracy of the trip range; combining weather forecast data with the trip range makes the setting of the basic cruise path more reasonable, improving the drone's working efficiency while ensuring the drone's safety range; the acquisition of actual weather data allows the drone to make timely modifications to the basic cruise path based on real-time weather changes, avoiding the drone's inability to return smoothly due to sudden weather conditions; and the combination of correction time increases the number of drones that complete the detection task, ensuring the drone's safe operation while successfully completing the detection task.

[0007] In one embodiment of the present invention, a charging pile is installed under a high-voltage power line tower, and the drone is charged through the charging pile. The travel distance of the drone after each charging is analyzed to obtain the travel analysis results. Specifically, this includes: obtaining the flight route of the drone from the charging pile to the charging pile each time; determining the flight distance, flight speed, and power consumption of the drone for each trip based on the flight route; determining the power consumption per unit distance of the drone at different flight speeds under different weather conditions based on the weather conditions corresponding to the flight route; and calculating the safe flight distance and the maximum flight distance of the drone under different weather conditions based on the power consumption per unit distance, thus obtaining the travel analysis results.

[0008] Compared with existing technologies, the technical effects achieved by adopting this technical solution are as follows: by obtaining data from multiple drone flights, the optimal travel routes for drones under various weather conditions can be calculated, indirectly increasing the drone's working time. The setting of power consumption per unit distance allows for more accurate calculation of the drone's working time under different weather conditions. The calculation of safe flight distance and extreme flight distance can accurately determine the drone's working range under different weather conditions, making it easier to assign inspection tasks to the drone and ensuring that the drone can complete its tasks smoothly and return safely.

[0009] In one embodiment of the present invention, the travel range of the UAV under various weather conditions is determined based on the travel analysis results, and the basic number of UAVs in the target area is set according to the travel range. Specifically, this includes: acquiring historical weather data of the target area, calculating the average detection range of the UAV in the target area based on the historical weather data and the travel range; acquiring the detection range in the target area, dividing the detection range according to the average detection range, and determining the basic number of UAVs based on the number of sub-regions.

[0010] Compared with existing technologies, the technical effects achieved by adopting this technical solution are as follows: the acquisition of historical weather data enables the assessment of the overall working environment for future drone missions, determining a more reasonable average detection range and reducing the occurrence of drones being unable to reach certain locations within the target area during missions; the setting of the detection range allows for the reasonable selection of the execution range of the detection mission based on the environment around the high-voltage power line tower; the division of sub-regions clarifies the working area of ​​each drone, ensuring that the detection range is completely covered while also improving the working efficiency of the drones.

[0011] In one embodiment of the present invention, the basic cruise path for the UAV to perform a detection task is determined based on weather forecast data and travel range. Specifically, this includes: selecting the corresponding travel range based on weather forecast data; calculating the number of recharges required to perform the detection task based on the detection area of ​​the detection task; dividing the detection area into detection sub-areas based on the number of recharges, planning cruise sub-paths within the detection sub-areas, and generating the basic cruise path based on all the cruise sub-paths.

[0012] Compared with existing technologies, the technical effects achieved by adopting this technical solution are as follows: the selection of the flight range allows the drone to travel in a way that is more in line with the current weather conditions; the setting of the number of recharges allows the drone to charge reasonably according to different detection areas, ensuring that the drone can safely complete the detection task; the method of dividing the detection sub-areas in conjunction with the number of recharges reduces the distance the drone flies due to recharging, further improving the drone's working efficiency.

[0013] In one embodiment of the present invention, when the UAV performs a detection task along the basic cruise path, it is determined whether the basic cruise path needs to be corrected based on the actual weather data. Specifically, this includes: calculating the remaining battery power of the UAV each time it returns to the charging station based on the basic cruise path; calculating the range difference between the travel range corresponding to the weather forecast data and the actual weather data; calculating the consumption increment based on the range difference; when the consumption increment is less than or equal to the remaining battery power, the basic cruise path does not need to be corrected; when the consumption increment is greater than the remaining battery power, the basic cruise path needs to be corrected.

[0014] Compared with existing technologies, the technical effects achieved by this solution are as follows: the calculation of remaining power can provide a preliminary assessment of the drone's performance in detection tasks; the calculation of range difference can accurately determine the impact of actual weather data on the drone's performance in detection tasks; and the calculation of power consumption increment fully considers the drone's subsequent flight status under actual weather conditions. By comparing the power consumption increment with the remaining power, the safety of the drone is further ensured.

[0015] In one embodiment of the present invention, if so, a corrected cruise path is determined based on the charging efficiency of the UAV and the task range of the detection task, and the correction time for the corrected cruise path to complete the detection task is calculated. Specifically, this includes: selecting a charging compensation point on the remaining basic cruise path; calculating the minimum charging amount of the UAV based on the range difference and the charging path; calculating the shortest charging time based on the minimum charging amount and the charging efficiency; combining the shortest charging time with the position of the charging compensation point to determine the corrected cruise path; calculating the length difference between the corrected cruise path and the remaining basic cruise path; and calculating the correction time based on the length difference and the shortest charging time.

[0016] Compared with existing technologies, the technical effects achieved by this solution are as follows: the setting of charging compensation points allows the drone to rationally select the location to replenish power based on the changes in range difference during the execution of detection tasks, ensuring that the drone has sufficient power for the detection tasks and reducing the time wasted on replenishing power. The calculation of correction time can intuitively reflect the impact of charging compensation points on the execution of detection tasks, making it easier to adjust the drone's working mode accordingly.

[0017] In one embodiment of the present invention, a charging compensation point is selected on the remaining basic cruise path, and the minimum charging amount of the drone is calculated based on the range difference and the charging path. Specifically, this includes: calculating a first additional consumption caused by actual weather data based on the range difference; calculating a second additional consumption based on the distance between the charging compensation point and the charging pile; and calculating the minimum charging amount based on the first additional consumption and the second additional consumption.

[0018] Compared with existing technologies, the technical effects achieved by adopting this technical solution are as follows: First, the calculation of additional consumption fully considers the impact of weather changes on the operation of the drone; second, the calculation of additional consumption fully considers the power consumption required when the drone increases the number of charging cycles, thereby improving the accuracy of the minimum charging amount and enhancing the safety of the drone in performing detection tasks.

[0019] In one embodiment of the present invention, the number of drones performing the detection task is adjusted according to the time limit requirement and the correction duration of the detection task. Specifically, this includes: calculating the total execution time of the detection task based on the correction duration; when the total execution time is less than or equal to the time limit requirement, the drones in the target area perform the detection task according to the corrected cruise path; when the total execution time is greater than the time limit requirement, the number of drones performing the detection task is increased based on the time difference between the total execution time and the time limit requirement.

[0020] Compared with existing technologies, the technical effects achieved by adopting this technical solution are as follows: the calculation of total execution time can accurately obtain the impact of actual weather data on the execution of detection tasks; by adjusting the number of drones, the detection tasks can be successfully completed, thus improving the overall working efficiency of drones.

[0021] In one embodiment of the present invention, this application also provides a charging pile. The UAV planning method based on the charging pile described in the above embodiment charges under a high-voltage power line tower through the charging pile. The charging pile includes: a connecting column, which is connected to the high-voltage power line tower; a protective box, which is fixedly connected to the connecting column; a battery, which is disposed in the protective box; and a charging rod, which is disposed in the protective box. The UAV completes charging by cooperating with the charging rod.

[0022] Compared with existing technologies, the technical effects achieved by this solution are as follows: the connection column allows the charging column to be fixed to the high-voltage power tower and can be used to charge the battery using the high-voltage power tower; the protection box reduces the impact of the external environment on the charging pole and makes the charging of the drone more stable; and the combination of the charging pile and the high-voltage power tower greatly solves the problem of drone endurance. Attached Figure Description

[0023] Figure 1 This is one of the flowcharts for the UAV planning method of the present invention; Figure 2 This is the second flowchart of the UAV planning method of the present invention; Figure 3 This is the third flowchart of the UAV planning method of the present invention; Figure 4 This is a schematic diagram of the overall structure of the charging pile of the present invention.

[0024] Explanation of reference numerals in the attached figures: 100 - Charging pile; 110 - Connecting post; 120 - Protection box; 130 - Battery; 140 - Charging rod. Detailed Implementation

[0025] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0026] [First Embodiment] See Figure 1 In one specific embodiment, this application provides a drone planning method based on charging piles. The drone planning method includes: S100. Set up charging piles under high-voltage power line towers, and charge the drone through the charging piles. Analyze the drone's journey after each charge to obtain the journey analysis results. S200: Determine the flight range of the UAV under various weather conditions based on the flight analysis results, and set the basic number of UAVs in the target area based on the flight range; S300 determines the basic cruise path for the UAV to perform detection missions based on weather forecast data and flight range; S400: When the UAV performs a detection task along the basic cruise path, determine whether the basic cruise path needs to be corrected based on the actual weather data. S500, if so, then determine the corrected cruise path based on the drone's charging efficiency and the scope of the detection task, and calculate the correction time for the corrected cruise path to complete the detection task. S510. Adjust the number of drones performing the detection task according to the time limit requirements and correction time of the detection task; S600: If not, the UAV continues to perform the detection mission along the basic cruise path.

[0027] In step S100, in order to solve the problem of drone's endurance when working outdoors, a charging pile is set up under the high-voltage power line tower. The charging pile can store electricity through the high-voltage power line to ensure that the drone can be charged smoothly. When the drone leaves the charging pile after each charging and returns to the charging pile for charging, the flight data of the drone when flying in the environment near the high-voltage power line tower is obtained by analyzing the power consumption and flight distance of the drone during that trip.

[0028] In step S200, the travel range refers to the farthest distance that the drone can travel to and from the charging station under various weather conditions when it is fully charged. Typically, the number of drones is set at each charging station according to the distance between high-voltage power line towers.

[0029] It should be noted that when the charging station is first set up, the number of drones at the charging station will be adjusted based on the drones' flight data in the environment. When the drones are able to stably capture the images required for detection within a specified time, the final number of drones at the charging station will be determined based on the coverage of the images, which will serve as the base number.

[0030] In step S300, the distance that a drone can travel varies greatly under different weather conditions. Therefore, when a detection task is issued, it is necessary to obtain the weather conditions for the execution of the detection task based on weather forecast data. For example, if the next day the power line connecting two high-voltage power towers is to be inspected, and the drone is required to fly along the power line and take corresponding images, then on that night, it is necessary to determine how far the drones on both sides need to fly along the power line based on the weather forecast data and generate the corresponding basic cruise path.

[0031] In step S400, as the continuous working time of the drone increases, the probability of weather changes during operation also increases. If the actual weather data and the weather forecast data change significantly during operation, causing the drone to face a power crisis if it flies along the basic cruise path, the basic cruise path needs to be corrected.

[0032] In step S500, the corrected cruise path modifies the basic cruise path by adding a return to the charging station to recharge, ensuring that the drone can safely perform the detection task. However, returning to the charging station to recharge will also increase the time for performing the detection task. Therefore, when the basic cruise path is replaced by the corrected cruise path, the time for the corrected cruise path to complete the detection task needs to be calculated again and recorded as the corrected time.

[0033] In step S510, for the corrected cruise route that cannot complete the inspection task on time, a corresponding reminder is sent to the management center in a timely manner. The time limit requirement for the inspection task can be modified according to the urgency of the inspection task. Such emergencies can be dealt with by adding drones, by cooperating with drones on adjacent high-voltage power line towers, or by having staff arrive on site to add drones to perform the inspection task.

[0034] In step S600, for drones that do not need to modify their basic cruise path, changes in actual weather data relative to weather forecast data will not affect the completion of the detection task.

[0035] By installing charging stations under high-voltage power line towers, drones can achieve stable outdoor endurance. The acquisition of flight path analysis results allows for the determination of the drone's operational status under current conditions, improving the accuracy of the flight path. Combining weather forecast data with the flight path allows for more rational setting of the basic cruise path, improving drone efficiency while ensuring safe operation. Acquiring actual weather data enables drones to promptly modify their basic cruise paths based on real-time weather changes, preventing them from failing to return smoothly due to unforeseen weather conditions. Increasing the correction time also increases the number of drones completing the testing task, ensuring both safe operation and successful completion of the testing mission.

[0036] [Second Embodiment] See Figure 2 In one specific embodiment, charging piles are installed under high-voltage power line towers, and the drone charges through these charging piles. The travel distance after each charging session is analyzed to obtain travel analysis results, which specifically include: S110. Obtain the flight path of the drone each time it departs from and returns to the charging station; S120. Determine the flight distance, flight speed, and power consumption of the drone for each trip based on the flight route; S130. Determine the power consumption per unit distance of the UAV when flying at different speeds under different weather conditions, based on the weather conditions corresponding to the flight route. S140. Calculate the safe and maximum flight distance of the UAV under different weather conditions based on the power consumption per unit distance, and obtain the trip analysis results.

[0037] In step S110, when calculating the flight path, it is not enough to only obtain the data from the planar angle; the vertical distance the UAV moves along the flight path must also be considered.

[0038] In step S120, the initial battery level is the battery level when the drone leaves the charging station, and the final battery level is the battery level when it returns to the charging station. The battery consumption is the difference between the initial battery level and the final battery level. The flight distance and flight speed are recorded by sensors installed on the drone.

[0039] In step S130, each trip of the drone is divided according to the weather. During the experimental phase, the drone will travel at different speeds depending on the weather, and the power consumption at different speeds will be recorded.

[0040] For example, when a drone travels in the rain, it flies 6 kilometers at speeds of 10m / s, 15m / s, 20m / s, and 25m / s during the experimental phase. The resulting power consumption is 40%, 47%, 40%, and 50% of the total power, respectively. The power consumption corresponding to these four speeds is 0.067 / km, 0.078 / km, 0.067 / km, and 0.083 / km, respectively. The speed with the lowest power consumption is selected first, and the fastest speed with the same power consumption is selected as the standard flight speed of the drone. The power consumption corresponding to the standard flight speed is recorded as the power consumption per unit distance.

[0041] It should be noted that during the experimental phase, more precise flight speeds can be used for testing, and detailed tests need to be conducted for each weather condition to obtain the power consumption per unit distance that is consistent with the drone's flight under the current environment.

[0042] In step S140, the maximum flight distance of the UAV at standard flight speed is obtained based on the power consumption per unit distance. A safety factor is determined based on the power consumption per unit distance, denoted as N, and the power consumption per unit distance is denoted as E1. The safety factor and the power consumption per unit distance satisfy the following relationship: When 0 < E1 ≤ 0.05, N = 0.95; When 0.05 < E1 ≤ 0.1, N = 0.9; When 0.1 < E1 ≤ 0.2, N = 0.8; When E1 > 0.2, N = 0.75.

[0043] Let the standard flight speed be F1, the safe flight distance be F2, and the maximum flight distance be F2. The specific formulas for calculating the maximum flight distance and the safe flight distance are as follows: F1 = 1 ÷ E1 × N; F2=F1+N×(1÷E1-F1); For example, in the current environment, E1 = 0.05, the safe flight distance of the drone is F1 = 1 ÷ 0.05 × 0.9 = 18 km, and the maximum flight distance of the drone is F2 = 18 + (1 ÷ 0.05 - 18) × 0.9 = 19.8 km.

[0044] By collecting data from multiple drone flights, the optimal flight path for drones under various weather conditions can be calculated, indirectly increasing the drone's working time. The setting of power consumption per unit distance allows for more accurate calculation of the drone's working time in different weather conditions. The calculation of safe flight distance and maximum flight distance can accurately determine the drone's working range in different weather conditions, making it easier to assign inspection tasks to the drone and ensuring that the drone can complete its tasks smoothly and return safely.

[0045] [Third Embodiment] In one specific embodiment, the flight range of the drone under various weather conditions is determined based on the flight analysis results, and a basic number of drones in the target area is set according to the flight range, specifically including: S210. Obtain historical weather data for the target area, and calculate the average detection range of the UAV within the target area based on the historical weather data and flight range. S220. Obtain the detection range within the target area, divide the detection range according to the average detection range, and determine the basic quantity based on the number of sub-regions.

[0046] In steps S210 and S220, historical weather data is the number of days in the target area under various weather conditions in the past year. The number of days under various weather conditions is used as a weight, and combined with the power consumption per unit distance and the standard flight speed corresponding to various weather conditions, the average detection range of the target area is obtained.

[0047] The scope of inspection is determined by the environment surrounding the high-voltage power line tower. Some high-voltage power line towers are located in remote areas with relatively simple surrounding environments, resulting in a smaller scope to be inspected. Drones under these high-voltage power line towers are mainly responsible for inspecting the transmission lines. For high-voltage power line towers with complex surrounding environments, different scopes to be inspected are selected based on the environment. For target areas with smaller scopes to be inspected, the scope that a single drone can complete in a single day is used as a sub-region during the division process. For target areas with larger scopes to be inspected, the scope that a single drone can complete in a single day is used as the base, and the scope is rounded up to ensure that these scopes completely cover the target area. Sub-regions are then divided according to the coverage method to obtain the base number.

[0048] Acquiring historical weather data allows for the assessment of the overall working environment for future drone missions, determining a more reasonable average detection range, and reducing the occurrence of drones being unable to reach certain locations within the target area during missions. Setting the detection range allows for the reasonable selection of the detection mission's execution range based on the environment surrounding the high-voltage power line tower. The division of sub-regions clarifies the working area of ​​each drone, ensuring that the detection range is fully covered while also improving the drone's working efficiency.

[0049] [Fourth Embodiment] See Figure 3 In one specific embodiment, the basic cruise path for the UAV to perform the detection mission is determined based on weather forecast data and the flight range, specifically including: S310. Select the corresponding travel range based on weather forecast data; S320. Calculate the number of times the detection task needs to be recharged based on the detection area of ​​the detection task; S330. Divide the detection area into detection sub-areas according to the number of recharge cycles, plan cruise sub-paths within the detection sub-areas, and generate a basic cruise path based on all cruise sub-paths.

[0050] In step S310, weather forecast data is usually acquired one hour before the UAV performs the detection work. For example, if the UAV needs to perform the detection work at 9:00 a.m. today, the corresponding weather forecast data is acquired at 8:00 a.m. today. Based on the weather conditions given in the weather forecast data, such as wind speed, temperature and wind direction, the flight range is determined in combination with the standard flight speed and power consumption per unit distance.

[0051] In step S320, when the detection area is small, the drone does not need to return to the charging station for recharging while performing the detection task. After the drone completes the task, it can return to the charging station for charging. When the detection area is large, the drone needs to complete the detection task in segments. After each segment is completed, it should return to the charging station for charging first. When calculating the number of recharging times, the maximum detection area for each trip is calculated based on the travel range. The ratio of the coverage area of ​​the detection area to the maximum detection area is rounded up to obtain the number of recharging times.

[0052] In step S330, the number of recharges corresponds to the number of times the drone returns to the charging station. When dividing the detection sub-regions, the number of detection sub-regions is usually one more than the number of recharges. When planning the cruise sub-path, the drone is made to recharge at a location close to the charging station in each detection sub-region to reduce the distance caused by recharging. The cruise sub-paths in each detection sub-region are combined, and the round-trip path for each charging is added to obtain the basic cruise path.

[0053] The selection of the flight range allows the drone to travel in a way that is more in line with the current weather conditions. The setting of the number of recharges allows the drone to charge reasonably according to different detection areas, ensuring that the drone can safely complete the detection task. The method of dividing the detection sub-areas in conjunction with the number of recharges reduces the distance the drone flies due to recharging, further improving the drone's working efficiency.

[0054] [Fifth Embodiment] In one specific embodiment, when the UAV performs a detection task along the basic cruise path, it determines whether the basic cruise path needs to be corrected based on actual weather data, specifically including: S410: Calculate the remaining battery power of the drone each time it returns to the charging station based on the basic cruise path; S420, Calculate the range difference between the travel range corresponding to the weather forecast data and the actual weather data; S430: Calculate the consumption increment based on the range difference. When the consumption increment is less than or equal to the remaining battery power, the basic cruise path does not need to be corrected. When the consumption increment is greater than the remaining battery power, the basic cruise path needs to be corrected.

[0055] In steps S410 to S440, the power consumption difference and speed difference per unit distance corresponding to the weather forecast data and the actual weather data are calculated, the current power of the drone when the weather change is detected is obtained, and the range difference is calculated based on the current power and the power consumption difference.

[0056] Let the current battery level be V1, the remaining battery level be V2, and the power consumption per unit distance corresponding to the weather forecast data be E. 11 The actual weather data corresponds to a power consumption per unit distance of E. 12The range difference is F0, and the formula for calculating the range difference is as follows: F0 = (V1 - V2) ÷ E 11 -(V1-V2)÷E 12 .

[0057] For example, the power consumption per unit distance corresponding to weather forecast data is 0.08 / km, the power consumption per unit distance corresponding to actual weather data at standard flight speed is 0.09 / km, the current power is 53%, and the remaining power is 30%. At this time, F0 = 23 × 0.09 - 23 × 0.08 = 0.23km.

[0058] In step S430, when the consumption increment is less than or equal to the remaining power, it means that the remaining power is sufficient to support the impact of the actual weather data, and the drone can successfully return to the charging station. When the consumption increment is greater than the remaining power, it means that the actual weather data has a significant impact, and if the basic cruise path is not corrected, there may be a risk that the drone will not be able to return to the charging station.

[0059] The calculation of remaining battery power allows for a preliminary assessment of the drone's performance in detection tasks. The calculation of range difference accurately reflects the impact of actual weather data on the drone's performance in detection tasks. The calculation of consumption increment fully considers the drone's subsequent flight status under actual weather conditions. By comparing the consumption increment with the remaining battery power, the safety of the drone is further ensured.

[0060] [Sixth Embodiment] In a specific embodiment, if so, the corrected cruise path is determined based on the UAV's charging efficiency and the task range of the detection mission, and the correction time for completing the detection mission using the corrected cruise path is calculated, specifically including: S501. Select a charging compensation point on the remaining basic cruise path, and calculate the minimum charging amount of the drone based on the range difference and the charging path. S502. Calculate the shortest charging time based on the minimum charging amount and charging efficiency, and combine the shortest charging time with the location of the charging compensation point to determine the corrected cruise path. S503. Calculate the length difference between the corrected cruise path and the remaining basic cruise path, and calculate the corrected duration based on the length difference and the shortest charging time.

[0061] In step S501, after the drone flies to the charging compensation point, it returns directly to the charging pile for charging. The larger the range difference, the larger the corresponding minimum charging amount, ensuring that the drone's power can cope with the impact of the range difference.

[0062] In step S502, the charging efficiency of the drone is updated according to the drone's charging record to ensure the accuracy of the shortest charging time. The drone's dwell time at the charging station is estimated based on the shortest charging time, and a corrected cruise path is formed by combining the location of the charging compensation point.

[0063] In step S503, when calculating the length difference, the length of the flight path of the drone from the charging compensation point to the charging pile for charging and back needs to be calculated together.

[0064] The setting of charging compensation points allows the drone to rationally select the location to replenish power based on changes in range difference during the execution of detection tasks. This ensures that the drone has sufficient power for the detection tasks and reduces the time wasted on replenishing power. The calculation of correction time can intuitively reflect the impact of charging compensation points on the execution of detection tasks, making it easy to adjust the drone's working mode accordingly.

[0065] [Seventh Embodiment] In one specific embodiment, a charging compensation point is selected on the remaining basic cruise path, and the minimum charging amount for the drone is calculated based on the range difference and the charging path. Specifically, this includes: S501a, Calculate the first additional cost resulting from actual weather data based on the range difference; S501b, Calculate the second additional consumption based on the distance between the charging compensation point and the charging pile; S501c: Calculate the minimum charging amount based on the first additional consumption and the second additional consumption.

[0066] In steps S501a to S501c, the first additional consumption is denoted as H1. The first additional consumption, the range difference, and the unit distance power consumption corresponding to the actual weather data satisfy the following relationship: H1=F0÷E 12 .

[0067] For example, if the range difference is 0.5km and the power consumption per unit distance is 0.1 / km, then the drone's first additional consumption is 5% of the maximum power.

[0068] Let the second additional consumption be H2, and the distance between the charging compensation point and the charging pile be L. The second additional consumption and the distance between the charging compensation point and the charging pile satisfy the following relationship: H2=2L÷E 12 .

[0069] For example, if the distance between the charging compensation point and the charging pile is 0.1km, and the power consumption per unit distance is 0.1 / km, then the second additional consumption of the drone is 1% of the maximum power.

[0070] Let the minimum charge be H0, where H0 = H1 + H2.

[0071] The calculation of the first additional consumption fully considers the impact of weather changes on the operation of the drone. The calculation of the second additional consumption fully considers the power consumption required when the drone increases the number of charging times, which improves the accuracy of the minimum charging amount and enhances the safety of the drone in performing detection tasks.

[0072] [Eighth Embodiment] In one specific embodiment, the number of drones performing the detection task is adjusted according to the time limit requirements and correction duration of the detection task, specifically including: S511. Calculate the total execution time of the detection task based on the correction duration; S512. When the total execution time is less than or equal to the time limit requirement, the UAVs in the target area shall perform the detection task according to the corrected cruise path. When the total execution time is greater than the time limit requirement, the number of UAVs performing the detection task shall be increased according to the time difference between the total execution time and the time limit requirement.

[0073] In steps S511 to S512, the increase in the number of charging times will inevitably lead to a slower completion rate of the detection task. Therefore, it is necessary to calculate the total execution time based on the correction time. For some important detection tasks, it is necessary to increase the number of drones to perform the detection tasks. The added drones will perform detection in reverse according to the corrected cruise path to ensure that the detection tasks are completed as soon as possible. The added drones can be deployed by staff when they arrive at the site, can be drones that have already completed the sub-area detection tasks in the same target area restarting their work, or can be drones in adjacent target areas working across areas.

[0074] It should be noted that as long as the drone can complete the detection task within the time limit by following the corrected cruise path, there is no need to increase the number of drones performing the corresponding detection task, so as to avoid frequent drone scheduling and disruption of the drone's own work rhythm.

[0075] The calculation of total execution time can accurately determine the impact of actual weather data on the execution of detection tasks. By adjusting the number of drones, the detection tasks can be completed smoothly, thus improving the overall work efficiency of the drones.

[0076] [Ninth Embodiment] See Figure 4This application also provides a charging pile 100. The drone planning method based on the charging pile 100 described in the above embodiments charges the drone under a high-voltage power line tower using the charging pile 100. The charging pile 100 includes: a connecting column 110 connected to the high-voltage power line tower; a protective box 120 fixedly connected to the connecting column 110; a storage battery 130 housed inside the protective box 120; and a charging rod 140 housed inside the protective box 120. The drone completes charging by cooperating with the charging rod 140.

[0077] There are designated parking areas for drones around the high-voltage power line towers. When the drones are not in use after charging, they can wait in the parking areas. When the drones return from a testing mission, they can be charged by using a snap-fit ​​structure on the top of the drone to engage with the charging rod 140.

[0078] The connection post 110 allows the charging pile 100 to be fixed to the high-voltage power tower and can be used with the battery 130 to charge via the high-voltage power tower. The protection box 120 reduces the impact of the external environment on the charging pole 140 and makes the charging of the drone more stable. By using the charging pile 100 in conjunction with the high-voltage power tower, the problem of drone battery life is greatly solved.

[0079] While the present invention has been disclosed above, it is not limited thereto. Any person skilled in the art can make various modifications and alterations without departing from the spirit and scope of the invention; therefore, the scope of protection of the present invention should be determined by the scope defined in the claims.

Claims

1. A drone planning method based on charging piles, characterized in that, The drone planning method includes: Charging piles are installed under high-voltage power line towers, and drones are charged through the charging piles. The travel distance of the drones after each charging is analyzed to obtain travel analysis results. Based on the trip analysis results, the travel range of the UAV under various weather conditions is determined, and the basic number of the UAV in the target area is set according to the travel range; The basic cruise path for the UAV to perform its detection mission is determined based on weather forecast data and the stated travel range; When the drone performs the detection task along the basic cruise path, it is determined whether the basic cruise path needs to be corrected based on the actual weather data. If so, a corrected cruise path is determined based on the charging efficiency of the UAV and the task range of the detection task, and the correction time for the corrected cruise path to complete the detection task is calculated. The number of drones performing the detection task is adjusted according to the time limit requirements of the detection task and the correction duration. If not, the drone continues to perform the detection task along the basic cruise path.

2. The UAV planning method according to claim 1, characterized in that, The process involves installing charging stations under high-voltage power line towers, allowing drones to charge via these stations, and analyzing the drone's travel distance after each charge to obtain travel analysis results, specifically including: Obtain the flight path of the drone each time it departs from and returns to the charging station; The flight distance, flight speed, and power consumption of the drone for each trip are determined based on the flight route. Based on the weather conditions corresponding to the flight route, determine the power consumption per unit distance for the UAV to fly at different flight speeds under different weather conditions; The safe and maximum flight distances of the UAV under different weather conditions are calculated based on the power consumption per unit distance, and the trip analysis results are obtained.

3. The UAV planning method according to claim 2, characterized in that, The step of determining the flight range of the UAV under various weather conditions based on the flight analysis results, and setting the basic number of UAVs in the target area based on the flight range, specifically includes: Acquire historical weather data for the target area, and calculate the average detection range of the UAV within the target area based on the historical weather data and the flight range; Obtain the detection range within the target area, divide the detection range according to the average detection range, and determine the basic quantity based on the number of sub-regions.

4. The UAV planning method according to claim 3, characterized in that, The determination of the basic cruise path for the UAV to perform the detection mission based on weather forecast data and the travel range specifically includes: Select the corresponding travel range based on the weather forecast data; The number of times the detection task needs to be replenished is calculated based on the detection area of ​​the detection task. The detection area is divided into detection sub-areas based on the number of recharge cycles, and a cruise sub-path is planned within the detection sub-areas. The basic cruise path is generated based on all the cruise sub-paths.

5. The UAV planning method according to claim 4, characterized in that, When the drone performs the detection task along the basic cruise path, determining whether the basic cruise path needs to be corrected based on actual weather data specifically includes: The remaining battery power of the drone is calculated each time it returns to the charging station based on the basic cruise path; Calculate the range difference between the forecast data and the actual weather data corresponding to the travel range; The consumption increment is calculated based on the range difference. When the consumption increment is less than or equal to the remaining battery power, the basic cruise path does not need to be corrected. When the consumption increment is greater than the remaining battery power, the basic cruise path needs to be corrected.

6. The UAV planning method according to claim 5, characterized in that, If so, then a corrected cruise path is determined based on the charging efficiency of the UAV and the task range of the detection task, and the correction time for the corrected cruise path to complete the detection task is calculated, specifically including: On the remaining basic cruise path, select a charging compensation point, and calculate the minimum charging amount of the drone based on the range difference and the charging path. The shortest charging time is calculated based on the minimum charging amount and the charging efficiency. The shortest charging time is then combined with the location of the charging compensation point to determine the corrected cruise path. Calculate the length difference between the corrected cruise path and the remaining basic cruise path, and calculate the corrected duration based on the length difference and the shortest charging time.

7. The UAV planning method according to claim 6, characterized in that, The step of selecting a charging compensation point on the remaining basic cruise path and calculating the minimum charging amount of the drone based on the range difference and the charging path specifically includes: Calculate the first additional cost resulting from the actual weather data based on the range difference; The second additional consumption is calculated based on the distance between the charging compensation point and the charging pile; The minimum charging amount is calculated based on the first additional consumption and the second additional consumption.

8. The UAV planning method according to claim 6, characterized in that, The adjustment of the number of drones performing the detection task based on the time limit requirements of the detection task and the correction duration specifically includes: The total execution time of the detection task is calculated based on the corrected duration. When the total execution time is less than or equal to the time limit requirement, the UAV in the target area executes the detection task according to the corrected cruise path; When the total execution time exceeds the time limit requirement, the number of drones performing the detection task is increased based on the time difference between the total execution time and the time limit requirement.

9. A charging pile, characterized in that, The drone planning method based on charging piles as described in any one of claims 1 to 8 uses the charging piles for charging, wherein the charging piles include: A connecting column, which is connected to the high-voltage power line tower; The protective box is fixedly connected to the connecting post; A storage battery, wherein the storage battery is disposed within the protective box; A charging rod is installed inside the protective box, and the drone completes charging by cooperating with the charging rod.

Images