A dust removal system and method for a photovoltaic panel

Abstract

The application provides a photovoltaic panel dust removal system and a dust removal method, which comprise a positioning module, a calibration group association module, a collection module, a path planning module, a dust removal task formulation module and an execution module. The system generates a task flight area through the positioning module, calibrates a cleaning starting line through the calibration group association module, encodes and associates a UAV group for a photovoltaic panel, decomposes a large-scale operation area into assignable units, replaces a single-machine mode with a multi-machine cooperation mode, and improves overall processing capacity. The collection module acquires multi-source images and determines dust accumulation areas and thicknesses, thereby providing data support for accurate operation. The path planning module plans exclusive dust removal paths for the dust accumulation areas, thereby improving operation efficiency and coverage rate of a single panel. The dust removal task formulation module accurately matches liquid spraying amount and speed under unified dust removal time, thereby realizing quantitative spraying. The execution module controls the UAV group to operate synchronously, realizes multi-machine parallel operation and partitioned cooperation, and improves resource utilization rate and overall efficiency of photovoltaic panel dust removal.

Description

Technical Field

[0001] This invention belongs to the field of photovoltaic dust removal auxiliary technology, specifically to a photovoltaic panel dust removal system and dust removal method. Background Technology

[0002] As the global energy structure shifts towards green and low-carbon development, the scale of photovoltaic power generation sites is gradually increasing. However, the power generation efficiency of large-scale photovoltaic power plants, especially photovoltaic arrays located in arid and windy areas, is greatly affected by dust accumulation on the panel surface. Dust on the photovoltaic panels can reduce the photoelectric conversion efficiency of the panels and may cause hot spot effects, shortening the equipment lifespan.

[0003] Currently, in large-scale photovoltaic power plants, drones are commonly used to clean photovoltaic panels. Drone dust removal systems typically consist of a drone platform, spraying devices, and a basic flight control system, enabling them to fly along preset routes and spray cleaning fluid. However, in the current photovoltaic panel cleaning process, dust removal is achieved by using a single drone to spray cleaning fluid in a quantitative manner. This method lacks precise sensing, meaning it cannot identify the specific dust accumulation areas and levels on each photovoltaic panel. This leads to resource waste and incomplete cleaning, such as cleaning areas where there is no dust or areas with excessive dust. Furthermore, the dust removal process with a single drone requires multiple round trips and individual cleaning of each photovoltaic panel, resulting in low dust removal efficiency. Summary of the Invention

[0004] To address the problem of low dust removal efficiency in large-scale photovoltaic power plants where a single drone is used for quantitative spraying of cleaning fluid, this invention provides a photovoltaic panel dust removal system and method.

[0005] To achieve the above objectives, the present invention provides the following technical solution: This invention proposes a dust removal system for photovoltaic panels, the system comprising: The positioning module is used to generate the mission flight area based on the arrangement area of ​​the photovoltaic array; The calibration swarm module is used to calibrate the cleaning start line in the mission flight area, encode the photovoltaic panels on the cleaning start line, and associate them with the UAV swarm. The acquisition module is used to acquire multi-source images of the encoded photovoltaic panel and determine the dust accumulation area and thickness of each photovoltaic panel based on the multi-source images. The path planning module is used to plan the dust removal path for each photovoltaic panel based on the dust accumulation area of ​​each photovoltaic panel; The dust removal task formulation module is used to determine the amount and speed of liquid spraying for each dust accumulation area on the dust removal path under the preset dust removal time of the same photovoltaic panel, and generate the dust removal task for each drone in the drone swarm at the corresponding photovoltaic panel. The execution module is used to control a swarm of drones to carry out dust removal based on the dust removal task.

[0006] Preferably, the positioning module includes a first acquisition unit and a region construction unit; The first acquisition unit is used to acquire data on the distribution area of ​​the photovoltaic panels, current environmental data, and a map of the geographical area where the photovoltaic panels are located, and to construct a photovoltaic array distribution map based on the distribution data of the photovoltaic panels. The region construction unit is communicatively connected to the first acquisition unit and is used to delineate the boundaries of the mission flight area on the geographic region map by using the distribution area data of the photovoltaic panels, thereby constructing the mission flight area.

[0007] Preferably, the calibration group module includes a starting line calibration unit, a photovoltaic panel encoding unit, and a UAV association unit; The starting line calibration unit is communicatively connected to the region construction unit and is used to calibrate a clean starting line within the mission flight area. The photovoltaic panel encoding unit is communicatively connected to the starting line calibration unit and is used to perform sequential encoding based on the photovoltaic panels on the clean starting line; The drone association unit is communicatively connected to both the photovoltaic panel encoding unit and the drone swarm, and is used to assign the encoded photovoltaic panel cluster to the drone swarm, establishing a one-to-one task mapping relationship between the photovoltaic panel and the drone.

[0008] Preferably, the acquisition module includes a multi-source image acquisition unit, an image fusion unit, and a dust accumulation analysis unit; The multi-source image acquisition unit is communicatively connected to the photovoltaic panel encoding unit and is used to acquire multi-source images of the encoded photovoltaic panel. The image fusion unit is communicatively connected to the multi-source image acquisition unit and is used to register and fuse visible light images, multispectral images and thermal imaging images acquired on the same photovoltaic panel to generate fused image data. The dust accumulation analysis unit is communicatively connected to the image fusion unit and is used to segment the dust accumulation area based on the fused image data, and determine the dust accumulation thickness of the dust accumulation area based on the comparative analysis of multispectral or thermal features with the dust accumulation area.

[0009] Preferably, the path planning module includes a path initialization unit, a regional path generation unit, a global collision avoidance planning unit, and a path filtering unit; The path initialization unit is communicatively connected to the dust accumulation analysis unit and is used to obtain the distance value of each dust accumulation area from the cleaning start line, and to mark the dust accumulation area corresponding to the smallest distance value as the starting point of the photovoltaic panel and the dust accumulation area corresponding to the largest distance value as the ending point of the photovoltaic panel. The regional path generation unit is communicatively connected to the path initial design unit and is used to plan a preliminary dust removal path based on the starting point, the ending point, and all dust-accumulated areas covering a single photovoltaic panel. The global collision avoidance planning unit is communicatively connected to the regional path generation unit. It is used to mark obstacle areas on the side of the preliminary dust removal path, draw the UAV flight safety area at the starting point of the preliminary dust removal path, and simulate along the preliminary dust removal path, retaining the preliminary dust removal path in which the obstacle areas and the UAV flight safety area do not overlap during the simulation. The path filtering unit is communicatively connected to the global collision avoidance planning unit and is used to obtain the path lengths of all preliminary dust removal paths corresponding to the same photovoltaic panel output by the global collision avoidance planning unit, and extract the minimum path length as the dust removal path.

[0010] Preferably, the dust removal task formulation module includes a parameter calculation unit, a task allocation unit, and a task file generation unit; The parameter calculation unit is communicatively connected to the dust accumulation analysis unit and is used to determine the dust removal time of each dust accumulation area based on the same dust removal time for each photovoltaic panel, and to dynamically calculate the spray volume and spray speed of each dust accumulation area based on the dust removal time, area and thickness of the dust accumulation area. The task allocation unit is communicatively connected to the parameter calculation unit and the path filtering unit, respectively, and is used to generate an independent cleaning task for the drone associated with the photovoltaic panel based on the spray volume and spray speed on the dust removal path. The task file generation unit is communicatively connected to the task allocation unit and is used to format and generate dust removal tasks for each UAV's independent cleaning task, which can be directly read by the UAV flight control system.

[0011] Preferably, the execution module includes a simulation environment construction unit, a logic calculation unit, and a verification report generation unit; The simulation environment construction unit is communicatively connected to the region construction unit and is used to construct a virtual simulation scene in the virtual environment based on the mission flight area and the UAV model. The logic calculation unit is communicatively connected to the simulation environment construction unit and the task file generation unit, respectively, and is used to simulate the operation process of the drone swarm in the virtual simulation scenario based on the dust removal task, and generate simulation results; The verification report generation unit is communicatively connected to the logic calculation unit and is used to generate a verification report based on the simulation results.

[0012] Preferably, the execution module further includes a UAV status management unit; The drone status management unit is used to obtain the drone's real-time battery level. If the real-time battery level is less than the battery threshold, a warning signal is generated.

[0013] Preferably, the system further includes a storage module, which includes a timing unit and a storage unit; The storage unit is used to store the verification report and the dust removal task; The timing unit is used to record the time when the verification report and the dust removal task are stored in the storage unit, generate a timestamp, and store it in the corresponding storage unit.

[0014] This invention proposes a method for dust removal from photovoltaic panels, which utilizes the aforementioned photovoltaic panel dust removal system and includes the following steps: The positioning module generates the mission flight area based on the arrangement area of ​​the photovoltaic array; The calibration swarm module calibrates the cleaning start line in the mission flight area, encodes the photovoltaic panels on the cleaning start line, and associates them with the UAV swarm. The acquisition module obtains multi-source images of the coded photovoltaic panel and determines the dust accumulation area and thickness of each photovoltaic panel based on the multi-source images; The path planning module plans the dust removal path for each photovoltaic panel based on the dust accumulation area of ​​each panel; The dust removal task formulation module determines the amount and speed of liquid spraying for each dust accumulation area on the dust removal path under the preset dust removal time of the same photovoltaic panel, and generates the dust removal task for each drone in the drone swarm at the corresponding photovoltaic panel. The execution module controls a swarm of drones to carry out dust removal based on the dust removal task.

[0015] Compared with the prior art, the present invention has the following beneficial technical effects: This invention proposes a photovoltaic panel dust removal system. The system uses a positioning module to generate a task flight area based on the photovoltaic array layout, defining the overall operation scope. A calibration and grouping module, by calibrating the cleaning start line, encoding the photovoltaic panels, and associating them with a drone swarm, breaks down the large-scale operation area into assignable units, enabling multi-drone collaborative operation and replacing the single-drone mode, significantly improving overall processing capacity. A data acquisition module acquires multi-source images and determines the dust accumulation area and thickness, providing a data foundation for precise operation and avoiding indiscriminate spraying. A path planning module plans dedicated dust removal paths for each photovoltaic panel's dust accumulation area, improving the efficiency and coverage of individual panels. A dust removal task formulation module, under unified dust removal time constraints, precisely matches the spray volume and spray speed for each dust accumulation area, achieving quantitative and precise spraying, reducing waste and improving effectiveness. An execution module controls the drone swarm to operate synchronously according to the task, enabling multi-drone parallel and zoned collaborative operation, improving resource utilization and the overall efficiency of photovoltaic panel dust removal.

[0016] Furthermore, the positioning module of this system, through the collaboration of the first acquisition unit and the area construction unit, accurately locates the operation area of ​​a large-scale photovoltaic power station, thus defining a clear flight boundary for the operation of the drone swarm.

[0017] Furthermore, the calibration group module of this system establishes a one-to-one task mapping between drones and coded photovoltaic panels in the drone swarm through the collaborative efforts of the starting line calibration unit, photovoltaic panel coding unit and drone association unit. This enables precise task allocation and collaborative scheduling, replacing the manual allocation mode and significantly improving the standardization and efficiency of group control operations.

[0018] Furthermore, the system's acquisition module, through the collaboration of a multi-source image acquisition unit, an image fusion unit, and a dust accumulation analysis unit, achieves effective identification of dust accumulation areas and accurate quantification of dust accumulation thickness, avoiding indiscriminate spraying and improving dust removal efficiency and resource utilization.

[0019] Furthermore, the path planning module of this system, through the collaboration of the path initialization unit, the regional path generation unit, the global collision avoidance planning unit, and the path filtering unit, achieves reasonable planning of the dust removal path of the UAV and realizes safe and efficient path generation.

[0020] Furthermore, the dust removal task creation module of this system, through the collaboration of the parameter calculation unit, task allocation unit, and task file generation unit, achieves precise, standardized, and directly executable dust removal task generation, realizing accurate matching of one machine and one panel, and improving the overall efficiency of photovoltaic panel dust removal.

[0021] Furthermore, the execution module of this system, through the collaboration of the simulation environment construction unit, logic calculation unit, and verification report generation unit, builds a solid safety and precision defense for actual operations, ensures the reliable implementation of swarm-based dust removal, and enables the swarm of drones to efficiently complete large-scale photovoltaic panel dust removal operations. Attached Figure Description

[0022] Figure 1 This invention provides a system block diagram of a photovoltaic panel dust removal system; Figure 2 This invention provides a specific system block diagram of a photovoltaic panel dust removal system; Detailed Implementation In the following description, only certain exemplary embodiments are briefly described. As those skilled in the art will recognize, the described embodiments can be modified in various ways without departing from the spirit or scope of the invention. Therefore, the drawings and description are considered to be exemplary in nature and not restrictive.

[0023] In the description of this invention, it should be understood that the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0024] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0025] This invention proposes a dust removal system for photovoltaic panels, such as... Figure 1 and Figure 2 As shown, the system includes a positioning module, a calibration group module, a data acquisition module, a path planning module, a dust removal task formulation module, and an execution module. The system comprises the following modules: a positioning module for generating a mission flight area based on the arrangement of the photovoltaic array; a calibration and grouping module for calibrating a cleaning start line within the mission flight area, encoding the photovoltaic panels on the cleaning start line, and associating them with the drone swarm; an acquisition module for acquiring multi-source images of the encoded photovoltaic panels and determining the dust accumulation area and thickness of each photovoltaic panel based on these images; a path planning module for planning a dust removal path for each photovoltaic panel based on its dust accumulation area; a dust removal task formulation module for determining the spray volume and spray speed of each dust accumulation area on the dust removal path within a preset dust removal time for the same photovoltaic panel, generating a dust removal task for each drone in the drone swarm at the corresponding photovoltaic panel; and an execution module for controlling the drone swarm to perform dust removal based on the dust removal task.

[0026] This system addresses the issues of limited coverage, excessive time consumption, and low efficiency of single-machine operations through the coordinated operation of positioning, calibration, data acquisition, path planning, dust removal task formulation, and execution modules. It achieves collaborative, precise, and efficient dust removal operations, thereby improving resource utilization and the overall efficiency of photovoltaic panel dust removal.

[0027] Furthermore, in this embodiment, the positioning module includes a first acquisition unit and a region construction unit; The first acquisition unit collects data on the distribution area of ​​photovoltaic panels, current environmental data, and a geographic map of the photovoltaic panels' location. Based on the photovoltaic panel distribution data, it constructs a photovoltaic array distribution map using GIS technology, clearly marking the boundaries of each array, the spacing between photovoltaic panels, and the location of the support structures. The photovoltaic panel distribution area data includes the spatial coordinates, dimensions, and tilt angle of the photovoltaic panels. The region construction unit, communicating with the first acquisition unit, delineates the boundaries of the mission flight area on the geographic map using the photovoltaic panel distribution area data, constructing the mission flight area, which serves as the overall mission flight area. This positioning module, through the collaboration of the first acquisition unit and the region construction unit, accurately locates the operation area of ​​a large-scale photovoltaic power station, clearly defining flight boundaries for UAV swarm operations. The first acquisition unit collects photovoltaic panel distribution, environmental, and geographic area data to construct an array distribution map, achieving accurate digital mapping of the power station's spatial layout and providing basic data for region delineation. The region construction unit delineates flight boundaries on the geographic map based on the distribution data, forming a standardized mission flight area, avoiding the subjectivity and errors of manual delineation, and ensuring a clear and controllable operational range.

[0028] Furthermore, in this embodiment, the calibration group module includes a starting line calibration unit, a photovoltaic panel encoding unit, and a UAV association unit; The system comprises several components: a starting line calibration unit, which communicates with the area construction unit, and a photovoltaic (PV) panel edge marker unit. The starting line is defined within the mission flight area, using the edge of the PV panel closest to the power station road as a reference point for dust removal operations. A PV panel coding unit, also connected to the starting line calibration unit, is used to obtain the number of PV panels on the starting line and sequentially encode them. The PV panels are coded sequentially along the starting line; for example, the PV panels in array 1 are coded as P1-01, P1-02, ..., P1-20 from west to east or north to south. The coding includes the array number and panel serial number to ensure unique identification. A drone association unit, connected to both the PV panel coding unit and the drone swarm, is used to assign the coded PV panel clusters to the drone swarm, establishing a one-to-one task mapping relationship between PV panels and drones. This calibration group module establishes a one-to-one task mapping between drones and coded photovoltaic panels within a drone swarm through the collaborative efforts of a starting line calibration unit, a photovoltaic panel coding unit, and a drone association unit. This enables precise task allocation and collaborative scheduling, replacing manual allocation and significantly improving the standardization and efficiency of swarm control operations. Specifically, the starting line calibration unit calibrates a clean starting line within the task flight area, unifying the start point of operations and preventing misalignment among multiple drones. The photovoltaic panel coding unit sequentially codes the photovoltaic panels based on the starting line, achieving orderly management of the photovoltaic array and facilitating task partitioning and traceability. The drone association unit distributes the coded photovoltaic panel clusters to the drone swarm, establishing a task mapping relationship and enabling collaborative control of multiple drones.

[0029] Furthermore, in this embodiment, the acquisition module includes a multi-source image acquisition unit, an image fusion unit, and a dust accumulation analysis unit; The system includes a multi-source image acquisition unit, which communicates with the photovoltaic panel encoding unit to acquire multi-source images of the encoded photovoltaic panels. The UAV flies sequentially to a position 1.5m above the target photovoltaic panel according to the associated photovoltaic panel encoding order, and simultaneously acquires visible light images, multispectral images, and thermal images of each photovoltaic panel. During the acquisition process, the positioning module ensures that the relative positional deviation between the UAV and the photovoltaic panel is ≤0.2m. The image fusion unit, which communicates with the multi-source image acquisition unit, is used to register and fuse the visible light images, multispectral images, and thermal images acquired on the same photovoltaic panel to generate fused image data. The dust accumulation analysis unit, which communicates with the image fusion unit, is used to segment the dust accumulation area based on the fused image data and determine the dust accumulation thickness of the dust accumulation area based on the comparative analysis of multispectral or thermal features with the dust accumulation area. This acquisition module, through the collaborative efforts of a multi-source image acquisition unit, an image fusion unit, and a dust accumulation analysis unit, achieves effective identification of dust accumulation areas and accurate quantification of dust accumulation thickness, avoiding indiscriminate spraying and improving dust removal efficiency and resource utilization. Specifically, the multi-source image acquisition unit acquires multi-source images, including visible light, multispectral, and thermal imaging, of the coded photovoltaic panels to comprehensively obtain the visual, spectral, and thermal characteristics of the dust accumulation. The image fusion unit registers and fuses the multi-source images, eliminating the limitations of single-source images and improving the completeness and recognizability of dust accumulation features. The dust accumulation analysis unit segments the dust accumulation area based on the fused image and determines the dust accumulation thickness through multispectral or thermal feature comparison analysis.

[0030] Furthermore, in this embodiment, the path planning module includes a path initialization unit, a regional path generation unit, a global collision avoidance planning unit, and a path filtering unit; The system comprises the following components: a path initialization unit, which communicates with the dust accumulation analysis unit, and a path selection unit. The path initialization unit obtains the distance from each dust accumulation area to the cleaning start line, calibrating the dust accumulation area corresponding to the minimum distance as the starting point of the photovoltaic panel and the dust accumulation area corresponding to the maximum distance as the ending point of the photovoltaic panel. A region path generation unit, also communicates with the path initialization unit, plans a preliminary dust removal path based on the starting point, ending point, and all dust accumulation areas covering a single photovoltaic panel. A global collision avoidance planning unit, also communicates with the region path generation unit, marks obstacle areas on the sides of the preliminary dust removal path, draws a safe flight area for the UAV at the starting point of the preliminary dust removal path, and simulates along the preliminary dust removal path, retaining preliminary dust removal paths where the obstacle areas and the safe flight area for the UAV do not overlap during the simulation. A path selection unit, also communicates with the global collision avoidance planning unit, obtains the path lengths of all preliminary dust removal paths corresponding to the same photovoltaic panel output by the global collision avoidance planning unit, and extracts the path with the minimum path length as the dust removal path. This path planning module, through the collaborative efforts of a path initialization unit, a regional path generation unit, a global collision avoidance planning unit, and a path selection unit, achieves rational planning of the dust removal path for drones, enabling safe and efficient path generation. Specifically, the path initialization unit marks the start and end points based on the distance between the dust accumulation area and the cleaning start line, providing a clear benchmark for path planning; the regional path generation unit plans a preliminary path covering all dust accumulation areas based on the start and end points, ensuring full dust removal coverage; the global collision avoidance planning unit marks obstacles and simulates flight, eliminating paths with collision risks and improving operational safety; and the path selection unit selects the shortest effective path, reducing flight time and energy consumption, and improving the dust removal efficiency of a single photovoltaic panel.

[0031] Furthermore, in this embodiment, the dust removal task formulation module includes a parameter calculation unit, a task allocation unit, and a task file generation unit; The system includes a parameter calculation unit, which is connected to the dust accumulation analysis unit. This unit determines the dust removal time for each dust accumulation area based on a preset dust removal time for each photovoltaic panel (e.g., 60s, 80s, or 120s for each panel in the same row parallel to the cleaning start line). Based on the dust removal time, area, and thickness of the dust accumulation area, it dynamically calculates the spray volume and spray speed for each area. A task allocation unit, connected to both the parameter calculation unit and the path selection unit, generates independent cleaning tasks for the drones associated with the photovoltaic panels, calibrated on the dust removal path based on the spray volume and spray speed. Finally, a task file generation unit, connected to the task allocation unit, formats each drone's independent cleaning task into a format that can be directly read by the drone's flight control system. This dust removal task creation module, through the collaboration of a parameter calculation unit, a task allocation unit, and a task file generation unit, achieves precise, standardized, and directly executable dust removal task generation. Specifically, the parameter calculation unit dynamically matches the spray volume and spray speed based on a unified dust removal time, dust accumulation area, and thickness, avoiding indiscriminate spraying and improving cleaning effectiveness and resource utilization. The task allocation unit binds parameters to the dust removal path, generating independent cleaning tasks for each drone, achieving precise correspondence between each drone and its control panel, ensuring the orderly operation of group control. The task file generation unit formats the tasks into files that the flight controller can directly read, eliminating manual conversion and significantly improving task distribution efficiency.

[0032] Furthermore, in this embodiment, the execution module includes a simulation environment construction unit, a logic calculation unit, and a verification report generation unit; The simulation environment construction unit is connected to the region construction unit and is used to construct a virtual simulation scene in the virtual environment based on the mission flight area and the UAV model. The logic calculation unit is connected to both the simulation environment construction unit and the mission file generation unit and is used to simulate the operation process of the UAV swarm in the virtual simulation scene based on the dust removal mission and generate simulation results. The verification report generation unit is connected to the logic calculation unit and is used to generate a verification report based on the simulation results. This execution module, through the collaborative efforts of a simulation environment construction unit, a logic calculation unit, and a verification report generation unit, builds a solid safety and precision defense for actual operations, ensuring the reliable implementation of swarm-based dust removal. The simulation environment construction unit builds a virtual scene based on the mission flight area and drone models, recreating the real operating environment and avoiding the costs and risks of on-site trial and error. The logic calculation unit simulates the entire process of the drone swarm performing dust removal tasks, proactively identifying potential problems such as collisions and task coordination issues. The verification report generation unit outputs a report based on the simulation results, clearly presenting the feasibility of the operation and optimization directions, facilitating advance adjustments to task parameters and paths, avoiding actual operational errors, improving operational safety and success rates, and reducing trial and error costs. It connects with the preceding task generation stage to form a closed loop, helping the drone swarm efficiently complete large-scale photovoltaic panel dust removal operations.

[0033] Furthermore, in this embodiment, the execution module also includes a UAV status management unit; The drone status management unit is used to obtain the drone's real-time battery level. If the real-time battery level is lower than the battery threshold, an alarm signal will be generated.

[0034] Furthermore, in this embodiment, the system also includes a storage module, which includes a timing unit and a storage unit; The storage unit is used to store verification reports and dust removal tasks; the time stamping unit is used to record the time when the verification reports and dust removal tasks are stored in the storage unit, generate a timestamp, and store it in the corresponding storage unit.

[0035] This invention proposes a method for dust removal from photovoltaic panels, which utilizes the aforementioned photovoltaic panel dust removal system and includes the following steps: The positioning module generates the mission flight area based on the arrangement area of ​​the photovoltaic array; The calibration swarm module calibrates the clean start line in the mission flight area, encodes the photovoltaic panels on the clean start line, and associates them with the drone swarm. The acquisition module obtains multi-source images of the coded photovoltaic panels and determines the dust accumulation area and thickness of each photovoltaic panel based on the multi-source images; The path planning module plans the dust removal path for each photovoltaic panel based on the dust accumulation area of ​​each panel; The dust removal task formulation module determines the amount and speed of liquid spraying for each dust accumulation area on the dust removal path under the preset dust removal time for the same photovoltaic panel, and generates the dust removal task for each drone in the drone swarm at the corresponding photovoltaic panel. The execution module controls a swarm of drones to carry out dust removal based on the dust removal task.

[0036] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered illustrative and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the scope of the invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

[0037] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can be appropriately combined to form other embodiments that can be understood by those skilled in the art. The above content is only for illustrating the technical concept of the present invention and should not be construed as limiting the scope of protection of the present invention. Any modifications made based on the technical concept proposed in this invention shall fall within the scope of protection of the claims of this invention.

Claims

1. A photovoltaic panel dust removal system, characterized in that, The system includes: The positioning module is used to generate the mission flight area based on the arrangement area of ​​the photovoltaic array; The calibration swarm module is used to calibrate the cleaning start line in the mission flight area, encode the photovoltaic panels on the cleaning start line, and associate them with the UAV swarm. The acquisition module is used to acquire multi-source images of the encoded photovoltaic panel and determine the dust accumulation area and thickness of each photovoltaic panel based on the multi-source images. The path planning module is used to plan the dust removal path for each photovoltaic panel based on the dust accumulation area of ​​each photovoltaic panel; The dust removal task formulation module is used to determine the amount and speed of liquid spraying for each dust accumulation area on the dust removal path under the preset dust removal time of the same photovoltaic panel, and generate the dust removal task for each drone in the drone swarm at the corresponding photovoltaic panel. The execution module is used to control a swarm of drones to carry out dust removal based on the dust removal task.

2. The photovoltaic panel dust removal system according to claim 1, characterized in that, The positioning module includes a first acquisition unit and a region construction unit; The first acquisition unit is used to acquire data on the distribution area of ​​the photovoltaic panels, current environmental data, and a map of the geographical area where the photovoltaic panels are located, and to construct a photovoltaic array distribution map based on the distribution data of the photovoltaic panels. The region construction unit is communicatively connected to the first acquisition unit and is used to delineate the boundaries of the mission flight area on the geographic region map by using the distribution area data of the photovoltaic panels, thereby constructing the mission flight area.

3. The photovoltaic panel dust removal system according to claim 2, characterized in that, The calibration group module includes a starting line calibration unit, a photovoltaic panel encoding unit, and a UAV association unit; The starting line calibration unit is communicatively connected to the region construction unit and is used to calibrate a clean starting line within the mission flight area. The photovoltaic panel encoding unit is communicatively connected to the starting line calibration unit and is used to perform sequential encoding based on the photovoltaic panels on the clean starting line; The drone association unit is communicatively connected to both the photovoltaic panel encoding unit and the drone swarm, and is used to assign the encoded photovoltaic panel cluster to the drone swarm, establishing a one-to-one task mapping relationship between the photovoltaic panel and the drone.

4. A photovoltaic panel dust removal system according to claim 3, characterized in that, The acquisition module includes a multi-source image acquisition unit, an image fusion unit, and a dust accumulation analysis unit; The multi-source image acquisition unit is communicatively connected to the photovoltaic panel encoding unit and is used to acquire multi-source images of the encoded photovoltaic panel. The image fusion unit is communicatively connected to the multi-source image acquisition unit and is used to register and fuse visible light images, multispectral images and thermal imaging images acquired on the same photovoltaic panel to generate fused image data. The dust accumulation analysis unit is communicatively connected to the image fusion unit and is used to segment the dust accumulation area based on the fused image data, and determine the dust accumulation thickness of the dust accumulation area based on the comparative analysis of multispectral or thermal features with the dust accumulation area.

5. A photovoltaic panel dust removal system according to claim 4, characterized in that, The path planning module includes a path initialization unit, a regional path generation unit, a global collision avoidance planning unit, and a path filtering unit. The path initialization unit is communicatively connected to the dust accumulation analysis unit and is used to obtain the distance value of each dust accumulation area from the cleaning start line, and to mark the dust accumulation area corresponding to the smallest distance value as the starting point of the photovoltaic panel and the dust accumulation area corresponding to the largest distance value as the ending point of the photovoltaic panel. The regional path generation unit is communicatively connected to the path initial design unit and is used to plan a preliminary dust removal path based on the starting point, the ending point, and all dust-accumulated areas covering a single photovoltaic panel. The global collision avoidance planning unit is communicatively connected to the regional path generation unit. It is used to mark obstacle areas on the side of the preliminary dust removal path, draw the UAV flight safety area at the starting point of the preliminary dust removal path, and simulate along the preliminary dust removal path, retaining the preliminary dust removal path in which the obstacle areas and the UAV flight safety area do not overlap during the simulation. The path filtering unit is communicatively connected to the global collision avoidance planning unit and is used to obtain the path lengths of all preliminary dust removal paths corresponding to the same photovoltaic panel output by the global collision avoidance planning unit, and extract the minimum path length as the dust removal path.

6. A photovoltaic panel dust removal system according to claim 5, characterized in that, The dust removal task formulation module includes a parameter calculation unit, a task allocation unit, and a task file generation unit; The parameter calculation unit is communicatively connected to the dust accumulation analysis unit and is used to determine the dust removal time of each dust accumulation area based on the same dust removal time for each photovoltaic panel, and to dynamically calculate the spray volume and spray speed of each dust accumulation area based on the dust removal time, area and thickness of the dust accumulation area. The task allocation unit is communicatively connected to the parameter calculation unit and the path filtering unit, respectively, and is used to generate an independent cleaning task for the drone associated with the photovoltaic panel based on the spray volume and spray speed on the dust removal path. The task file generation unit is communicatively connected to the task allocation unit and is used to format and generate dust removal tasks for each UAV's independent cleaning task, which can be directly read by the UAV flight control system.

7. A photovoltaic panel dust removal system according to claim 6, characterized in that, The execution module includes a simulation environment construction unit, a logic calculation unit, and a verification report generation unit; The simulation environment construction unit is communicatively connected to the region construction unit and is used to construct a virtual simulation scene in the virtual environment based on the mission flight area and the UAV model. The logic calculation unit is communicatively connected to the simulation environment construction unit and the task file generation unit, respectively, and is used to simulate the operation process of the drone swarm in the virtual simulation scenario based on the dust removal task, and generate simulation results; The verification report generation unit is communicatively connected to the logic calculation unit and is used to generate a verification report based on the simulation results.

8. A photovoltaic panel dust removal system according to claim 7, characterized in that, The execution module also includes a UAV status management unit; The drone status management unit is used to obtain the drone's real-time battery level. If the real-time battery level is less than the battery threshold, a warning signal is generated.

9. A photovoltaic panel dust removal system according to claim 7, characterized in that, The system also includes a storage module, which comprises a timing unit and a storage unit; The storage unit is used to store the verification report and the dust removal task; The timing unit is used to record the time when the verification report and the dust removal task are stored in the storage unit, generate a timestamp, and store it in the corresponding storage unit.

10. A method for dust removal from photovoltaic panels, using a photovoltaic panel dust removal system according to any one of claims 1 to 9, characterized in that, Includes the following steps: The positioning module generates the mission flight area based on the arrangement area of ​​the photovoltaic array; The calibration swarm module calibrates the cleaning start line in the mission flight area, encodes the photovoltaic panels on the cleaning start line, and associates them with the UAV swarm. The acquisition module obtains multi-source images of the coded photovoltaic panel and determines the dust accumulation area and thickness of each photovoltaic panel based on the multi-source images; The path planning module plans the dust removal path for each photovoltaic panel based on the dust accumulation area of ​​each panel; The dust removal task formulation module determines the amount and speed of liquid spraying for each dust accumulation area on the dust removal path under the preset dust removal time of the same photovoltaic panel, and generates the dust removal task for each drone in the drone swarm at the corresponding photovoltaic panel. The execution module controls a swarm of drones to carry out dust removal based on the dust removal task.

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