Photovoltaic panel cleaning control method and system based on fan blade airflow of unmanned aerial vehicle

Abstract

The invention discloses a photovoltaic panel cleaning control method and system based on fan blade airflow of an unmanned aerial vehicle, and belongs to the technical field of photovoltaic cleaning. According to the photovoltaic panel cleaning control method based on the fan blade airflow of the unmanned aerial vehicle, by integrating a flight control system, a cleaning system and a sensor system, the efficient and accurate automatic cleaning process can be achieved. Various photovoltaic panel pollution conditions can be flexibly handled in different cleaning modes by optimizing flight path planning, dynamically adjusting flight attitudes and controlling angles and power of fan blades in real time in combination with dirt and obstacle data provided by a sensor system. By means of the method, the cleaning efficiency is improved, the problems of low efficiency and high cost possibly caused in traditional manual cleaning are solved, meanwhile, the cleaning intensity and the flight path are intelligently adjusted, energy consumption is reduced, the cleaning quality of the photovoltaic panel can be effectively improved, the service life of the photovoltaic panel can be effectively prolonged, and finally the purpose of improving the photovoltaic power generation efficiency is achieved; the method has remarkable technical advantages and wide application prospects.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of photovoltaic cleaning technology, and in particular to a photovoltaic panel cleaning control method and system based on the airflow of drone fan blades. Background Art

[0002] Photovoltaic equipment will accumulate dust and dirt when exposed to the outdoor environment for a long time, affecting its power generation efficiency. Traditional cleaning methods usually require manual participation or ground cleaning equipment, which are not only inefficient but also costly.

[0003] Therefore, this application proposes a control method for cleaning photovoltaic equipment using the airflow of UAV motor blades, focusing on the design of key control aspects such as flight path control, flight attitude control, angle adjustment and working mode control of the UAV during the cleaning process, so as to improve cleaning efficiency and automation level. Summary of the invention

[0004] The embodiment of the present application provides a photovoltaic panel cleaning control method and system based on the airflow of the UAV fan blades. The technical solution is as follows:

[0005] According to one aspect of the present application, a photovoltaic panel cleaning control method based on the airflow of a UAV wind blade is provided, the system comprising a flight control system, a cleaning system and a sensor system, the method comprising:

[0006] In the flight control system, a predetermined path for target cleaning is designed based on the layout of the photovoltaic array, the size and spacing of the panels;

[0007] In the sensor system, the dirt condition of the photovoltaic panel and the surrounding obstacle data are monitored in real time by visual sensors and laser radars;

[0008] In response to finding that there is an area that hinders flight or requires enhanced cleaning, dynamically adjusting the predetermined cleaning path through the flight control system to avoid obstacles and change the cleaning area;

[0009] During the cleaning predetermined path flight process, adjusting the flight attitude through the flight control system;

[0010] Instructing the cleaning system to adjust the angle of the fan blades through the flight control system;

[0011] In the flight control system, the fan blade speed and the fan blade power are dynamically adjusted according to the feedback of the sensor system;

[0012] The flight control system, the cleaning system and the sensor system coordinate to execute the control of the cleaning mode.

[0013] Optionally, in the flight control system, a predetermined target cleaning path is designed according to the layout of the photovoltaic array, the size and spacing of the panels, including:

[0014] Based on the distribution and size of the photovoltaic panels, a preliminary flight route is generated through a path planning algorithm;

[0015] Dynamically analyze the photovoltaic array and adjust the planned path in real time based on the on-site environment;

[0016] The feasibility of the path planning is simulated and verified through the flight control system.

[0017] Optionally, in the sensor system, real-time monitoring of the dirt condition of the photovoltaic panel and surrounding obstacle data is performed by visual sensors and laser radars, including:

[0018] In the sensor system, surface condition data of the photovoltaic panel is collected by activating the visual sensor and the laser radar and performing a preliminary scan;

[0019] In the sensor system, the type and distribution of dirt on the photovoltaic panel are analyzed by image recognition technology to provide real-time feedback to the flight control system;

[0020] The laser radar detects surrounding obstacle data in real time, provides real-time obstacle avoidance information for subsequent flight path adjustment, and avoids collisions or route obstructions during flight.

[0021] Optionally, in response to finding that there is an area that hinders flight or requires enhanced cleaning, dynamically adjusting the predetermined cleaning path through the flight control system includes:

[0022] Based on the feedback from the sensor system, obstacles or heavily polluted areas are identified through the flight control system, and the flight route is updated in real time;

[0023] For heavily polluted areas, the flight control system is used to extend the flight time over the area and increase the airflow intensity, and to adjust the blade angle and speed to improve the cleaning effect of the area;

[0024] The flight control system optimizes path planning according to different cleaning demand priorities under multi-threading.

[0025] Optionally, during the cleaning predetermined path flight process, adjusting the flight attitude through a flight control system includes:

[0026] During the cleaning flight along the predetermined path, the tilt angle of the drone is adjusted by the flight control system, and the adjustment condition is based on whether the airflow can directly act on the dirt on the photovoltaic panel;

[0027] Coordinate the altitude sensor in the sensor system with the flight control system to control the flight altitude, wherein the purpose of controlling the flight altitude is to control the distance between the UAV and the photovoltaic panel;

[0028] A closed-loop control strategy is adopted in the flight control system and the flight attitude of the UAV is adjusted in real time.

[0029] Optionally, instructing the cleaning system to adjust the angle of the wind blades through the flight control system includes:

[0030] adjusting the inclination angle of the wind blades according to the real-time feedback of the sensor system through the flight control system;

[0031] During the cleaning process, the angle of the fan blades is fine-tuned by the flight control system according to the tilt angle of the panel;

[0032] According to the actual cleaning effect and panel contamination, the fan blade angle is dynamically adjusted through the cooperation of the flight control system and the cleaning system.

[0033] Optionally, the predetermined cleaning path adopts a serpentine or grid pattern.

[0034] Optionally, the cleaning mode includes a standard mode, an enhanced mode and a smart mode;

[0035] The method further comprises:

[0036] detecting the contamination condition of the cleaning area by means of the sensor system;

[0037] In response to the cleaning area being an area where dirt is evenly distributed, triggering the standard mode through the sensor system and starting the cleaning system to perform standard cleaning according to the predetermined cleaning path;

[0038] In response to the cleaning area being a severely polluted area, triggering the enhanced mode through the sensor system and starting the flight control system to adjust the flight time during the cleaning process and increase the wind blade power;

[0039] During the cleaning process, the cleaning mode is dynamically adjusted according to changes in the contamination situation in the cleaning area through the sensor system.

[0040] On the other hand, a photovoltaic panel cleaning control system based on the airflow of the wind blades of a drone is also provided, the system is used for the photovoltaic panel cleaning control method based on the airflow of the wind blades of a drone described above, the system includes a flight control system, a cleaning system and a sensor system;

[0041] The flight control system is used for path planning and attitude control of the drone, ensuring that the drone can accurately control its position and altitude during the cleaning process;

[0042] The cleaning system is used to clean dust and impurities on the surface of the photovoltaic panel using the airflow generated by the fan blades of the drone motor;

[0043] The sensor system is used to detect dirt on the surface of the photovoltaic panel and surrounding obstacles.

[0044] The embodiments of the present application belong to the field of photovoltaic cleaning technology. The photovoltaic panel cleaning control method based on the airflow of the UAV fan blades can realize an efficient and accurate automated cleaning process by integrating the flight control system, the cleaning system and the sensor system. By optimizing the flight path planning, dynamically adjusting the flight attitude, controlling the angle and power of the fan blades in real time, and combining the dirt and obstacle data provided by the sensor system, it is possible to flexibly respond to various photovoltaic panel pollution situations in different cleaning modes. This method not only improves the cleaning efficiency and avoids the inefficiency and high cost problems that may be caused by traditional manual cleaning, but also reduces energy consumption by intelligently adjusting the cleaning intensity and flight trajectory, and can effectively improve the cleaning quality and service life of the photovoltaic panel, and ultimately achieve the goal of improving the efficiency of photovoltaic power generation, with significant technical advantages and broad application prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 It is a flow chart of a photovoltaic panel cleaning control method based on UAV wind blade airflow provided by an illustrative embodiment of the present application. DETAILED DESCRIPTION

[0046] In order to make the objectives, technical solutions and advantages of the present invention more clear, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0047] The term "multiple" as used herein refers to two or more than two. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the related objects are in an "or" relationship.

[0048] Example 1

[0049] Please refer to Figure 1 , Figure 1 It is a flow chart of a photovoltaic panel cleaning control method based on UAV wind blade airflow provided by an illustrative embodiment of the present application.

[0050] The system includes a flight control system, a cleaning system and a sensor system, and the flight control system, the cleaning system and the sensor system coordinate to execute the control of the cleaning mode. The method includes:

[0051] Step 1: In the flight control system, a target cleaning path is designed based on the layout of the photovoltaic array, the size and spacing of the panels.

[0052] The target cleaning predetermined path is the shortest cleaning predetermined path, and the cleaning predetermined path adopts a serpentine or grid pattern.

[0053] In a possible implementation, step 1 includes steps S11 to S13.

[0054] Step S11, based on the distribution and size of the photovoltaic panels, a preliminary flight route is generated through a path planning algorithm.

[0055] This flight path avoids repeated cleaning areas while taking into account gaps between panels, ensuring maximum cleaning coverage.

[0056] Step S12, dynamically analyzing the photovoltaic array and adjusting the predetermined path in real time in combination with the on-site environment.

[0057] This ensures maximum path optimization and cleaning results.

[0058] Step S13, simulating and verifying the feasibility of the path planning through the flight control system.

[0059] This ensures that path planning will not interfere with other systems (such as the collection area of ​​the sensor system), and verifies the stability and efficiency of the flight through system test flights.

[0060] Step 2: In the sensor system, the dirt condition of the photovoltaic panel and the surrounding obstacle data are monitored in real time through visual sensors and lidar.

[0061] In a possible implementation, step 2 includes steps S21 to S23.

[0062] Step S21, in the sensor system, by activating the visual sensor and the lidar and performing a preliminary scan, the surface status data of the photovoltaic panel (such as dirt distribution, dust layer thickness, reflectivity, etc.) is collected.

[0063] Step S22, analyzing the type and distribution of dirt on the photovoltaic panel by image recognition technology in the sensor system to provide real-time feedback to the flight control system;

[0064] Step S23, using laser radar to detect surrounding obstacle data in real time, providing real-time obstacle avoidance information for subsequent flight path adjustment, and avoiding collisions or route obstructions during flight.

[0065] Step 3, in response to finding that there is an area that hinders flight or requires enhanced cleaning, dynamically adjust the cleaning path through the flight control system to avoid obstacles and change the cleaning area.

[0066] In a possible implementation, step 3 includes steps S31 to S33.

[0067] Step S31, based on the feedback from the sensor system, the flight control system identifies obstacles or heavily polluted areas and updates the flight route in real time.

[0068] During this process, the flight control system evaluates multiple path options through a predictive algorithm and selects the route with the best cleaning efficiency.

[0069] Step S32, for heavily polluted areas, extend the flight time over the area and increase the airflow intensity through the flight control system, and adjust the blade angle and speed to improve the cleaning effect of the area;

[0070] Step S33, the flight control system optimizes the path planning according to different cleaning requirement priorities under multi-threading, such as coverage, cleaning intensity, etc.

[0071] Step 4: During the flight of the cleaning predetermined path, the flight attitude is adjusted through the flight control system.

[0072] In a possible implementation, step 4 includes steps S41 to S43.

[0073] During the flight of the cleaning predetermined path, the tilt angle of the drone is adjusted through the flight control system. The adjustment condition is based on whether the airflow can directly act on the dirt on the photovoltaic panel.

[0074] Coordinate the altitude sensor in the sensor system with the flight control system to control the flight altitude. The purpose of controlling the flight altitude is to control the distance between the drone and the photovoltaic panel.

[0075] A closed-loop control strategy is adopted in the flight control system and the flight attitude of the UAV is adjusted in real time.

[0076] Step 5, instruct the cleaning system to adjust the angle of the fan blades through the flight control system.

[0077] In a possible implementation, step 5 includes steps S51 to S53.

[0078] Step S51, the flight control system adjusts the inclination angle of the blades according to the real-time feedback from the sensor system to ensure that the airflow can accurately act on the most polluted areas. This step uses an algorithm to determine the optimal match between the pollution point and the airflow direction to ensure the maximum cleaning effect.

[0079] Step S52: During the cleaning process, the angle of the fan blades is fine-tuned through the flight control system according to the tilt angle of the panel to prevent the airflow from causing excessive interference or damage to the panel surface.

[0080] Step S53, according to the actual cleaning effect and panel contamination, the flight control system and the cleaning system work together to dynamically adjust the blade angle to gradually achieve the optimal cleaning solution.

[0081] Step 6: In the flight control system, the fan blade speed and the fan blade power are dynamically adjusted according to the feedback from the sensor system.

[0082] In a possible implementation, step 6 includes steps S61 to S63.

[0083] Step S61, the flight control system detects the degree of pollution in the dirt area in real time by working closely with the sensor system, and automatically adjusts the speed and power of the fan blades. In areas with heavier dirt, the fan blade power will be increased to enhance the cleaning effect of the airflow.

[0084] Step S62, according to the adjustment of the fan blade speed, the flight control system adjusts the distribution of battery power to ensure the best cleaning effect without affecting the battery life.

[0085] In step S63, the flight control system continuously optimizes the power and speed configuration of the wind blades through a feedback loop so that the airflow intensity is synchronized with the cleaning requirements of the photovoltaic panel.

[0086] In addition, cleaning modes include standard mode, enhanced mode and smart mode.

[0087] In the embodiment of the present application, the method further includes:

[0088] Detecting contamination in clean areas through a sensor system;

[0089] In response to the cleaning area being an area where dirt is evenly distributed, triggering a standard mode through a sensor system and starting the cleaning system to perform standard cleaning according to a predetermined cleaning path;

[0090] In response to the cleaning area being a severely polluted area, triggering an enhanced mode through a sensor system and activating a flight control system to adjust the flight time during the cleaning process and increase the power of the wind blades;

[0091] During the cleaning process, the cleaning mode is dynamically adjusted according to changes in the contamination situation in the cleaning area through the sensor system.

[0092] In one example, when the sensor system detects that the dirt on the photovoltaic panel is evenly distributed and the degree of contamination is light, the flight control system automatically triggers the standard mode. In this mode, the flight control system accurately performs the cleaning task according to the predetermined cleaning path. The sensor system quickly scans the contamination of each photovoltaic panel through the visual sensor, and after confirming the uniformity of the contamination distribution, it starts the standard mode to ensure that the cleaning system is executed as planned and maintains medium wind blade power for normal cleaning. In this process, the feedback from the sensor system ensures that the drone does not repeatedly clean areas that are already clean enough, thereby improving work efficiency and reducing energy consumption.

[0093] The implementation principle is that the visual sensor in the sensor system scans the entire photovoltaic panel and uses image processing technology to analyze the dirt distribution. When the dirt is uniform and the degree of contamination is light, the sensor system will feed back the data to the flight control system.

[0094] Based on the data provided by the sensors, the flight control system confirms the layout, panel size and spacing of the photovoltaic array, automatically designs the target cleaning path, and starts the cleaning system. During this process, the cleaning system maintains the blade power at a medium level to ensure a stable and effective cleaning process.

[0095] The flight control system guides the drone to fly along the shortest path based on the cleaning path, and automatically adjusts the flight speed based on sensor feedback to ensure cleaning efficiency.

[0096] In one example, when the sensor system detects that there is severe dirt or dust accumulation in certain areas of the photovoltaic panel, the system will automatically switch to enhanced mode. In this mode, the flight control system will adjust the flight time according to the degree of pollution and extend the drone's stay in the area to ensure thorough cleaning. At the same time, the flight control system will instruct the cleaning system to increase the power of the wind blades, increase the airflow intensity, and enhance the cleaning effect. When planning the flight path, the flight control system will give priority to those areas with severe dirt, and adjust the flight route and cleaning intensity in real time through the feedback data from the sensor system to ensure that these areas are fully cleaned.

[0097] The implementation principle is that the sensor system continuously monitors the contamination of the photovoltaic panels, obtains image information of the dirt through the visual sensor, and uses the image recognition algorithm to determine the contaminated area. If it detects that a certain area is seriously contaminated, the sensor system immediately feeds back to the flight control system to trigger the enhanced mode.

[0098] The flight control system will extend the flight time of the drone in the enhanced mode to ensure that the dirt is thoroughly cleaned. This process monitors the cleaning progress of the photovoltaic panel surface in real time to determine whether the cleaning time needs to be further extended.

[0099] The flight control system issues instructions to adjust the speed and angle of the fan blades to increase the intensity of the airflow. Specifically, when the dirt in the cleaning area is serious, the system will adjust the angle of the fan blades to enhance the concentration of the airflow, thereby improving the cleaning effect.

[0100] In one example, when there is uneven distribution of pollution on the photovoltaic panel, the sensor system uses image recognition technology to analyze the distribution of dirt on the panel in real time, and automatically switches to intelligent mode when it finds that the local pollution is heavy. In intelligent mode, the flight control system is linked with the cleaning system to dynamically adjust the flight path and cleaning intensity. The sensor system continuously monitors the changes in pollution of the photovoltaic panel, intelligently judges the cleaning effect, and decides whether to switch the cleaning mode. For example, when the sensor recognizes that an area has been cleaned, the flight control system will automatically adjust the flight path to the uncleaned area to further optimize the cleaning efficiency. This mode can make the most reasonable judgment based on the environment and dirt conditions, greatly improving the intelligence and adaptability of cleaning.

[0101] The implementation principle is that the visual sensors and lidar sensors in the sensor system are not only used to monitor the distribution of dirt in real time, but also to analyze historical cleaning data through machine learning algorithms to predict future pollution trends. Based on this data, the system can predict the degree of pollution in a specific area and plan the cleaning path in advance.

[0102] When the sensor system detects that the pollution in a local area is more serious, the intelligent mode will automatically switch to the enhanced mode to increase the cleaning intensity; in the cleaner area, it will automatically switch back to the standard mode.

[0103] The flight control system optimizes the flight path based on sensor feedback and dynamically adjusts the power of the fan blades. In areas with lower cleaning intensity, the power of the fan blades is reduced to save energy, and in areas with more pollution, the airflow intensity and flight time are increased to ensure the cleaning effect.

[0104] In one example, in order to improve the real-time adaptability during the cleaning process, the sensor system continuously monitors changes in dirt during the cleaning process. If the pollution condition of a cleaning area changes (such as local dirt reduction or increase), the system will dynamically adjust the cleaning mode. For example, when using the enhanced mode in the early stage, some areas are found to be less polluted after cleaning, and the system will automatically switch to the standard mode. When new polluted areas are found, it will switch to the enhanced mode again. At the same time, the flight control system will adjust the flight time, flight altitude and wind blade power according to the changing pollution conditions to ensure that each area is cleaned in the optimal mode.

[0105] The implementation principle is that the sensor system monitors the real-time changes of dirt on the photovoltaic panels and triggers mode switching according to the changes in pollution in different areas. For example, during the cleaning process, if the sensor system detects that the dirt in a certain area is gradually decreasing, the flight control system will automatically switch to the standard mode; while in the area where the dirt increases, the system will switch to the enhanced mode.

[0106] The flight control system adjusts the flight path in real time based on sensor feedback. When the system identifies that there is a lot of dirt in a certain area, the flight control system will automatically extend the flight time and increase the power of the wind blades to ensure the cleaning effect; when there is less dirt, the flight time will be automatically shortened and the power will be reduced to save energy.

[0107] The flight control system adjusts the flight attitude according to the changes in dirt, such as adjusting the tilt angle of the drone and optimizing the direction of the airflow to ensure that the airflow can accurately act on the dirt in the contaminated area.

[0108] The flight control system, cleaning system, and sensor system work together to achieve precise cleaning of photovoltaic panels. In specific implementation, it can be automatically executed through the algorithm embedded in the control system to ensure the efficiency, intelligence, and adaptability of each process.

[0109] In summary, the photovoltaic panel cleaning control method based on the airflow of drone blades can realize an efficient and accurate automated cleaning process by integrating the flight control system, cleaning system and sensor system. By optimizing flight path planning, dynamically adjusting flight attitude, controlling the angle and power of the blades in real time, and combining the dirt and obstacle data provided by the sensor system, it can flexibly respond to various photovoltaic panel pollution situations in different cleaning modes. This method not only improves the cleaning efficiency and avoids the inefficiency and high cost problems that may be caused by traditional manual cleaning, but also reduces energy consumption by intelligently adjusting the cleaning intensity and flight trajectory, and can effectively improve the cleaning quality and service life of photovoltaic panels, ultimately achieving the goal of improving photovoltaic power generation efficiency, with significant technical advantages and broad application prospects.

[0110] Example 2

[0111] On the other hand, a photovoltaic panel cleaning control system based on drone fan blade airflow is also provided, characterized in that the system is used for the above-mentioned photovoltaic panel cleaning control method based on drone fan blade airflow, and the system includes a flight control system, a cleaning system and a sensor system.

[0112] The flight control system is used for the path planning and attitude control of the drone, ensuring that the drone can accurately control its position and altitude during the cleaning process. The cleaning system is used to use the airflow generated by the fan blades of the drone's motor to clean dust and impurities on the surface of the photovoltaic panel. The sensor system is used to detect dirt on the surface of the photovoltaic panel and surrounding obstacles.

[0113] The present application provides a photovoltaic panel cleaning control system based on drone fan blade airflow, which can support the operation of the photovoltaic panel cleaning control method of the drone fan blade airflow in the above-mentioned embodiment, so as to optimize the flight path planning, dynamically adjust the flight attitude, and control the fan blade angle and power in real time, and combine the dirt and obstacle data provided by the sensor system. It can flexibly respond to various photovoltaic panel pollution conditions in different cleaning modes, which not only improves the cleaning efficiency and avoids the inefficiency and high cost problems that may be caused by traditional manual cleaning, but also reduces energy consumption by intelligently adjusting the cleaning intensity and flight trajectory, and can effectively improve the cleaning quality and service life of the photovoltaic panel, and ultimately achieve the goal of improving the efficiency of photovoltaic power generation. It has significant technical advantages and broad application prospects.

[0114] An embodiment of the present application also provides a computer-readable medium storing at least one instruction, and the at least one instruction is loaded and executed by a processor to implement the photovoltaic panel cleaning control method based on drone wind blade airflow as described in the above embodiments.

[0115] The above description is only an optional embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A photovoltaic panel cleaning control method based on the airflow of UAV blades, characterized in that: The system includes a flight control system, a cleaning system and a sensor system, and the method includes: In the flight control system, a predetermined path for target cleaning is designed based on the layout of the photovoltaic array, the size and spacing of the panels; In the sensor system, the dirt condition of the photovoltaic panel and the surrounding obstacle data are monitored in real time by visual sensors and laser radars; In response to finding that there is an area that hinders flight or requires enhanced cleaning, dynamically adjusting the predetermined cleaning path through the flight control system to avoid obstacles and change the cleaning area; During the cleaning predetermined path flight process, adjusting the flight attitude through the flight control system; Instructing the cleaning system to adjust the angle of the fan blades through the flight control system; In the flight control system, the fan blade speed and the fan blade power are dynamically adjusted according to the feedback of the sensor system; The flight control system, the cleaning system and the sensor system coordinate to execute the control of the cleaning mode.

2. The method according to claim 1, characterized in that In the flight control system, a target cleaning predetermined path is designed according to the layout of the photovoltaic array, the size and spacing of the panels, including: Based on the distribution and size of the photovoltaic panels, a preliminary flight route is generated through a path planning algorithm; Dynamically analyze the photovoltaic array and adjust the planned path in real time based on the on-site environment; The feasibility of the path planning is simulated and verified through the flight control system.

3. The method according to claim 1, characterized in that In the sensor system, the dirt condition of the photovoltaic panel and the surrounding obstacle data are monitored in real time by visual sensors and laser radars, including: In the sensor system, surface condition data of the photovoltaic panel is collected by activating the visual sensor and the laser radar and performing a preliminary scan; In the sensor system, the type and distribution of dirt on the photovoltaic panel are analyzed by image recognition technology to provide real-time feedback to the flight control system; The laser radar detects surrounding obstacle data in real time, provides real-time obstacle avoidance information for subsequent flight path adjustment, and avoids collisions or route obstructions during flight.

4. The method according to claim 1, characterized in that: In response to finding that there is an area that hinders flight or requires enhanced cleaning, dynamically adjusting the predetermined cleaning path through the flight control system includes: Based on the feedback from the sensor system, obstacles or heavily polluted areas are identified through the flight control system, and the flight route is updated in real time; For heavily polluted areas, the flight control system is used to extend the flight time over the area and increase the airflow intensity, and to adjust the angle and speed of the wind blades to improve the cleaning effect of the area; The flight control system optimizes path planning according to different cleaning demand priorities under multi-threading.

5. The method according to claim 2, characterized in that: During the cleaning predetermined path flight process, adjusting the flight attitude through the flight control system includes: During the cleaning flight along the predetermined path, the tilt angle of the drone is adjusted by the flight control system, and the adjustment condition is based on whether the airflow can directly act on the dirt on the photovoltaic panel; Coordinate the altitude sensor in the sensor system with the flight control system to control the flight altitude, wherein the purpose of controlling the flight altitude is to control the distance between the UAV and the photovoltaic panel; A closed-loop control strategy is adopted in the flight control system and the flight attitude of the UAV is adjusted in real time.

6. The method according to claim 1, characterized in that The step of instructing the cleaning system to adjust the blade angle by the flight control system includes: adjusting the inclination angle of the wind blades according to the real-time feedback of the sensor system through the flight control system; During the cleaning process, the angle of the fan blades is fine-tuned by the flight control system according to the tilt angle of the panel; According to the actual cleaning effect and panel contamination, the fan blade angle is dynamically adjusted through the cooperation of the flight control system and the cleaning system.

7. The method according to any one of claims 1 to 6, characterized in that: The predetermined cleaning path adopts a serpentine or grid pattern.

8. The method according to any one of claims 1 to 6, characterized in that: The cleaning modes include standard mode, enhanced mode and smart mode; The method further comprises: detecting the contamination condition of the cleaning area by means of the sensor system; In response to the cleaning area being an area where dirt is evenly distributed, triggering the standard mode through the sensor system and starting the cleaning system to perform standard cleaning according to the predetermined cleaning path; In response to the cleaning area being a severely polluted area, triggering the enhanced mode through the sensor system and starting the flight control system to adjust the flight time during the cleaning process and increase the wind blade power; During the cleaning process, the cleaning mode is dynamically adjusted according to changes in the contamination situation in the cleaning area through the sensor system.

9. A photovoltaic panel cleaning control system based on the airflow of UAV blades, characterized in that: The system is used for the photovoltaic panel cleaning control method based on the airflow of the UAV blades as described in any one of claims 1 to 8 above, and the system includes a flight control system, a cleaning system and a sensor system; The flight control system is used for path planning and attitude control of the drone, ensuring that the drone can accurately control its position and altitude during the cleaning process; The cleaning system is used to clean dust and impurities on the surface of the photovoltaic panel using the airflow generated by the fan blades of the drone motor; The sensor system is used to detect dirt on the surface of the photovoltaic panel and surrounding obstacles.

Images