Solar panel cleaning system

Abstract

The invention provides a solar panel cleaning system. The solar panel cleaning system comprises an environment sensing module, a central control module, an execution module and a communication and feedback module. The environment sensing module is used for acquiring environment information and the state of the solar panel, capturing details on the surface of the solar panel and determining the position of the unmanned aerial vehicle; the environment sensing module transmits the collected data to the central control module to provide a decision basis for the central control module; the central control module is used for processing data collected by the environment sensing module, formulating a flight path and a cleaning strategy and controlling the flight attitude of the unmanned aerial vehicle; the communication and feedback module is used for realizing data transmission and instruction receiving between the unmanned aerial vehicle and the ground control station; and the execution module is used for executing an instruction of the central control module and completing a specific cleaning task. An innovative unmanned aerial vehicle technology is adopted, and automatic and intelligent cleaning of the solar panel is achieved.

Description

Technical Field

[0001] The invention relates to the field of solar panel cleaning, and in particular to a solar panel cleaning system. Background Art

[0002] With the large-scale application of solar panels, the demand for cleaning and maintenance is also increasing as the number of solar panels increases. Traditional solar panel cleaning methods usually rely on manual labor, which is not only inefficient, but also costly and poses safety risks. In addition, manual cleaning may not achieve the expected cleaning effect, affecting the power generation efficiency of solar panels.

[0003] At present, the traditional methods for cleaning the surface of solar panels are mainly: 1. Manual wiping. The disadvantage of this method is that it requires more manpower and material resources, and because solar panels are generally tall, there are certain safety hazards; 2. Using a water truck and a high-pressure water gun to spray and clean. The disadvantage of this method is that it wastes a lot of water resources, is inconvenient to rinse, and has a high cost; 3. Intelligent component cleaning robots. The disadvantage is that the structure and control system are complex and the cost is high.

[0004] Therefore, developing an automated and intelligent solar panel cleaning system has important practical significance and market prospects. Summary of the invention

[0005] In this context, the present invention proposes a solar panel cleaning system, which can accurately identify dust and stains on solar panels through drones equipped with high-resolution cameras, water guns, GPS positioning modules and other equipment, and automatically adjust the spray angle and pressure according to cleaning needs. In addition, the drone cleaning system also has remote monitoring and control functions. The ground control station can view the drone status and cleaning progress in real time and adjust the cleaning strategy in time. Compared with traditional manual cleaning, the present invention greatly improves the cleaning efficiency and quality, reduces labor costs and maintenance costs, and has the advantages of strong adaptability and environmental friendliness, providing strong support for the development of the solar industry.

[0006] The present invention provides a solar panel cleaning system, including an environment perception module, a central control module, an execution module, and a communication and feedback module;

[0007] The environmental perception module is used to obtain environmental information and solar panel status, capture details of the solar panel surface, determine the location of the drone, and match it with the preset cleaning area map to ensure that the drone performs its mission in the correct location, while detecting obstacles on the flight path, such as wires, trees or other aircraft, to ensure flight safety. The environmental perception module transmits the collected data to the central control module, providing it with a basis for decision-making;

[0008] The central control module is used to process the data collected by the environmental perception module, formulate the flight path and cleaning strategy, control the flight attitude of the UAV, and analyze the image data through the data processing unit to determine whether cleaning is required and how to clean and generate instructions, and send the instructions to the execution module through the communication and feedback module;

[0009] The communication and feedback module is used to realize data transmission and command reception between the UAV and the ground control station, and transmit the status and cleaning results of the UAV to the operator in real time through the feedback mechanism;

[0010] The execution module is used to execute the instructions of the central control module to complete specific cleaning tasks. It adjusts the spray angle and pressure of the water gun through the water gun control subsystem, monitors the water level of the water tank through the water supply management subsystem, and manages the output of the motor through the power energy management system.

[0011] Furthermore, in the solar panel cleaning system, the environmental perception module includes an identification module and a positioning module. The identification module captures images through the camera optical system, converts light signals into electrical signals, and then converts the electrical signals into digital image data through the image sensor, and uses computer vision algorithms, including image segmentation, feature extraction, and machine learning models, to analyze the image data to determine the contamination of the solar panel surface, while identifying and avoiding potential obstacles. The positioning module calculates the location coordinates of the drone by receiving satellite signals, and compares them with the preset map data to determine the current location of the drone. The environmental perception module transmits the collected data to the central control module.

[0012] Furthermore, in the solar panel cleaning system, the central control module includes a flight control module and a data processing and decision-making module. The flight control module is responsible for the stable flight and precise navigation of the UAV, the flight command subsystem generates the flight path and control commands according to the decision of the central control module, and the status monitoring subsystem monitors the flight status of the UAV in real time, including speed, altitude, direction and battery power, etc., to ensure that the UAV is always in the best working state when performing tasks. The data processing and decision-making module receives the data sent back by the environmental perception module, creates an environmental map using the SLAM algorithm, analyzes the contamination of the solar panel in combination with the output of the image processing unit, and formulates a cleaning strategy based on this information, including cleaning sequence, path planning and cleaning intensity, etc., and sends the instructions to the execution module through the communication and feedback module.

[0013] Furthermore, in the solar panel cleaning system, the execution module receives instructions from the central control module, adjusts the spray pressure and flow of the water gun system, and controls the operation of the water supply system to ensure that the cleaning task can be executed according to a predetermined strategy.

[0014] Furthermore, in the solar panel cleaning system, the communication and feedback module is used to realize data exchange between the UAV and the ground control station. The image data before and after cleaning are compared, the cleaning effect is evaluated, and feedback is provided to the operator. The status feedback subsystem reports the location, battery status and cleaning progress of the UAV to the ground station in real time so that the operator can monitor the entire cleaning process and make timely adjustments.

[0015] Furthermore, in the solar panel cleaning system, the recognition module captures the details of the solar panel surface, identifies the location, size and density of dust and stains, and uses computer vision algorithms such as image segmentation, feature extraction and machine learning models to analyze the image data to determine the contamination of the solar panel surface. The following formula uses the Sobel operator and the Canny operator to extract edges from the image:

[0016]

[0017] Among them, Gx and Gy are the gradients in the horizontal and vertical directions, w ij is the weight matrix, and I(i,j) is the pixel value of the image at position (i,j).

[0018] Furthermore, in the solar panel cleaning system, the positioning module provides geographic location information of the drone for navigation and path planning. By receiving satellite signals, the location coordinates of the drone are calculated and compared with preset map data to determine the current location of the drone. The following formula uses the trilateration principle to calculate the location coordinates of the drone by receiving multiple satellite signals:

[0019]

[0020] Among them, x and y are the latitude and longitude coordinates of the drone, c is the speed of light, and t1, t2 and t3 are the time differences when the drone receives different satellite signals.

[0021] Furthermore, in the solar panel cleaning system, the data processing and decision-making module is used to process the data returned by the environment perception module, formulate a cleaning strategy, create an environmental map using the SLAM algorithm, analyze the contamination of the solar panel in combination with the output of the image processing unit, and formulate a cleaning path and intensity based on this information. The following formula is the state update formula in EKF-SLAM:

[0022] x←x+F -1 HR -1 (z-Hx)

[0023] Where x is the state vector, F is the state transfer matrix, H is the observation matrix, R is the observation noise covariance matrix, and z is the observation value.

[0024] Furthermore, in the solar panel cleaning system, the communication and feedback module evaluates the cleaning effect by comparing the image data before and after cleaning, and feeds back the evaluation result to the ground station through the data transmission unit, so that the operator can understand the cleaning effect and make corresponding adjustments. The following formula is the image contrast calculation formula:

[0025]

[0026] Where C is the contrast, I max and I min are the maximum and minimum brightness values ​​of the image respectively.

[0027] Furthermore, in the solar panel cleaning system, the communication and feedback module transmits information such as the position, battery status and cleaning progress of the drone to the ground station in real time through the data transmission unit, so that the operator can monitor the entire cleaning process and make timely adjustments. The following formula is the battery power calculation formula in drone status monitoring:

[0028]

[0029] Where SOC is the percentage of remaining battery power, Q remaining is the remaining power, Q total is the total power.

[0030] The beneficial effects of the present invention are:

[0031] The present invention realizes intelligent cleaning of solar panels through innovative drone technology and automated control system. The drone can quickly cover a large area of ​​solar panels, greatly improve cleaning efficiency, and reduce the time and manpower required for manual cleaning. Secondly, compared with manual cleaning, the drone cleaning system can reduce labor costs and maintenance costs, and the long-term operating cost is lower. In addition, the drone cleaning system avoids the risk of manual high-altitude operations and improves the safety of the cleaning process. At the same time, the drone system can adapt to different environments and terrains, expanding the application scope of solar panel cleaning. In addition, the drone cleaning system uses clean water for cleaning, which will not pollute the environment and meets the requirements of green environmental protection. With the continuous advancement of technology, the drone cleaning system can be continuously upgraded and optimized to improve the cleaning effect and intelligence level. Finally, the ground control station can monitor the status and cleaning progress of the drone in real time, adjust the cleaning strategy in time, improve the flexibility and controllability of the cleaning process, and reduce energy consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] By referring to the accompanying drawings and reading the detailed description of non-limiting embodiments, the characteristics, structure and advantages of the present invention will become clearer. In all the drawings, the same reference numerals represent the same parts. The accompanying drawings are not drawn to scale, and their main purpose is to show the core concepts of the present invention.

[0033] Figure 1 It is an exemplary implementation diagram of a solar panel cleaning system of the present invention.

[0034] Reference numerals:

[0035] Environmental perception module 1, central control module 2, execution module 3, communication and feedback module 4. DETAILED DESCRIPTION

[0036] Various exemplary embodiments of the present application will now be described in detail with reference to the accompanying drawings. It should be noted that unless otherwise specifically stated, the relative arrangement of components and steps, numerical expressions and numerical values ​​set forth in these embodiments do not limit the scope of the present application.

[0037] At the same time, it should be understood that for the convenience of description, the sizes of the various parts shown in the drawings are not drawn according to the actual proportional relationship.

[0038] The following description of at least one exemplary embodiment is merely illustrative in nature and is not intended to limit the present application, its application, or uses.

[0039] Technologies, methods, and equipment known to ordinary technicians in the relevant art may not be discussed in detail, but where appropriate, the technologies, methods, and equipment should be considered as part of the specification.

[0040] It should be noted that like reference numerals and letters refer to similar items in the following figures, and therefore, once an item is defined in one figure, it need not be further discussed in subsequent figures.

[0041] In addition, the technical solutions between the various embodiments of the present application can be combined with each other, but it must be based on the fact that ordinary technicians in the field can implement it. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such combination of technical solutions does not exist and is not within the scope of protection required by this application.

[0042] It should be noted that all directional indications in the embodiments of the present application (such as up, down, left, right, front, back, etc.) are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0043] The present invention is further described in conjunction with the following examples.

[0044] See also Figure 1 , a solar panel cleaning system of the present invention comprises an environment perception module 1, a central control module 2, an execution module 3, and a communication and feedback module 4;

[0045] Specifically, the environmental perception module 1 includes an identification module and a positioning module. The identification module captures images through the camera optical system, converts light signals into electrical signals, and then converts the electrical signals into digital image data through the image sensor. Computer vision algorithms, including image segmentation, feature extraction, and machine learning models, are used to analyze the image data to determine the contamination of the surface of the solar panel, and identify and avoid potential obstacles. The positioning module calculates the position coordinates of the drone by receiving satellite signals, and compares them with the preset map data to determine the current position of the drone. The environmental perception module transmits the collected data to the central control module.

[0046] Specifically, the central control module 2 includes a flight control module and a data processing and decision-making module. The flight control module is responsible for the stable flight and precise navigation of the UAV. The flight command subsystem generates the flight path and control commands according to the decision of the central control module, while the status monitoring subsystem monitors the flight status of the UAV in real time, including speed, altitude, direction and battery power, etc., to ensure that the UAV is always in the best working state when performing tasks. The data processing and decision-making module receives the data sent back by the environmental perception module, creates an environmental map using the SLAM algorithm, analyzes the pollution of the solar panels in combination with the output of the image processing unit, and formulates a cleaning strategy based on this information, including cleaning sequence, path planning and cleaning intensity, etc., and sends the instructions to the execution module through the communication and feedback module.

[0047] Specifically, the execution module 3 receives instructions from the central control module, adjusts the spray pressure and flow of the water gun system, and controls the operation of the water supply system to ensure that the cleaning task can be executed according to the predetermined strategy.

[0048] Specifically, the communication and feedback 4 module is used to realize data exchange between the UAV and the ground control station. The image data before and after cleaning is compared, the cleaning effect is evaluated, and feedback is provided to the operator. The status feedback subsystem reports the position, battery status and cleaning progress of the UAV to the ground station in real time so that the operator can monitor the entire cleaning process and make timely adjustments.

[0049] It can be seen from the above that the above embodiment of the present invention realizes the cleaning of solar panels through multi-module collaboration. First, the environmental perception module collects environmental information around the drone and the status information of the solar panels through high-resolution cameras, GPS positioning modules, ultrasonic sensors and other equipment. Then, the central control module uses the SLAM algorithm to create an environmental map, and analyzes the image data sent back by the environmental perception module to determine whether cleaning is needed and how to clean. Next, the execution module sprays water through the water gun system according to the instructions of the central control module, and uses the water source provided by the water supply system to clean the solar panels. At the same time, the communication and feedback module realizes data transmission and command reception between the drone and the ground control station, and transmits the status of the drone and the cleaning results to the operator in real time through the feedback mechanism. Finally, the operator monitors the entire cleaning process according to the information provided by the communication and feedback module, and makes timely adjustments.

[0050] In one embodiment, the environment perception module 1 includes a recognition module and a positioning module;

[0051] The recognition module includes a camera system, an image processing unit, and a visual obstacle avoidance system;

[0052] The camera system is used to capture high-definition images of solar panels to facilitate subsequent image processing and analysis. The camera captures images through an optical system, converts light signals into electrical signals, and then converts the electrical signals into digital image data through an image sensor (such as CMOS or CCD).

[0053] The image processing unit is used to analyze the image captured by the camera, identify the location, size and density of dust and stains, and use computer vision algorithms such as image segmentation, feature extraction and machine learning models to analyze the image data to determine the contamination of the surface of the solar panel. The following formula uses the Sobel operator and the Canny operator to extract edges from the image.

[0054]

[0055] Among them, Gx and Gy are the gradients in the horizontal and vertical directions, w ij is the weight matrix, and I(i,j) is the pixel value of the image at position (i,j).

[0056] The visual obstacle avoidance system uses a camera to capture images, identifies potential obstacles through image processing technology, and combines deep learning and image recognition technology to perform real-time analysis on the images captured by the camera to identify and avoid potential obstacles.

[0057] The positioning module includes a GPS positioning module, an ultrasonic sensor

[0058] The GPS positioning module provides the geographic location information of the drone for navigation and path planning. By receiving satellite signals, the location coordinates of the drone are calculated and compared with the preset map data to determine the current location of the drone. The following formula uses the trilateration principle to calculate the location coordinates of the drone by receiving multiple satellite signals.

[0059]

[0060] Among them, x and y are the latitude and longitude coordinates of the drone, c is the speed of light, and t1, t2 and t3 are the time differences when the drone receives different satellite signals.

[0061] The ultrasonic sensor is used to detect obstacles on the flight path, such as wires, trees or other aircraft. By emitting ultrasonic signals and receiving echoes, the distance of the obstacle is calculated to avoid collision between the drone and the obstacle. The following formula is the speed and direction calculation formula

[0062]

[0063] Where v is the velocity, Δd is the distance the ultrasonic signal travels, Δt is the time difference, θ is the angle of the flight direction, and ax and ay are the readings of the accelerometer in the horizontal and vertical directions.

[0064] In one embodiment, the central control module 2 includes a flight control module and a data processing module.

[0065] The flight control module is used to control the flight attitude and path of the UAV, receive data from the environment perception module and instructions from the communication module, adjust the attitude and speed of the UAV through the flight control board and the flight control system to achieve precise flight, and calculate the error through the following formula.

[0066] e=ry

[0067] In the formula, e is the error, r is the expected value, and y is the actual value

[0068] The data processing module is used to process the data sent back by the environment perception module, formulate a cleaning strategy, create an environmental map using the SLAM algorithm, analyze the contamination of the solar panels in combination with the output of the image processing unit, and formulate a cleaning path and intensity based on this information. The following is the state update formula in EKF-SLAM:

[0069] x←x+F -1 HR -1 (z-Hx)

[0070] Where x is the state vector, F is the state transfer matrix, H is the observation matrix, R is the observation noise covariance matrix, and z is the observation value.

[0071] In one embodiment, the central control module 2 also includes a decision support system, which generates a cleaning instruction based on the output of the data processing unit, determines the cleaning sequence, path and parameter settings of the drone according to the information provided by the environment perception module and the data processing unit, and sends the instruction to the execution module through the communication module. The following formula is the heuristic function calculation formula in the A* algorithm in path planning:

[0072] f(n)=g(n)+h(n)

[0073] Where f(n) is the total cost of node n, g(n) is the actual cost from the start node to node n, and h(n) is the estimated cost from node n to the target node.

[0074] In one embodiment, the execution module 3 includes a water gun system, a water supply system, a power and energy management system, and an execution control unit.

[0075] The water gun system removes dust and stains on the solar panels by spraying water, and is composed of a high-pressure pump, a nozzle, a flow control valve, etc. By controlling the water pressure and flow, it ensures that the water flow can effectively clean the solar panels while avoiding damage to the solar panels.

[0076] The water supply system is used to provide a continuous water source for the water gun system, is responsible for transporting water from the ground to the drone, and ensures that the water gun system has enough water for cleaning operations.

[0077] The power and energy management system is used to provide a stable power and energy supply for the UAV.

[0078] The execution control unit is used to receive instructions from the central control module, adjust the spray pressure and flow of the water gun system, and control the operation of the water supply system to ensure that the cleaning task can be executed according to the predetermined strategy.

[0079] In one embodiment, the communication and feedback module 4 includes a data transmission unit, a signal receiving unit, a cleaning effect evaluation unit, and a state feedback unit.

[0080] The data transmission unit is used to realize data exchange between the UAV and the ground control station, using wireless communication technology (such as Wi-Fi, Bluetooth or a dedicated UAV communication protocol) to transmit the UAV status data, cleaning progress and issues that need to be decided to the ground station, and at the same time receive control instructions and feedback information from the ground station. The following formula is the bit error rate calculation formula in data transmission:

[0081]

[0082] Where BER is the bit error rate, n e is the number of error bits, nb is the total number of bits transmitted.

[0083] The signal receiving unit is used to receive instructions from the ground station, including flight commands, cleaning parameter adjustments, and emergency stop signals, etc. The data transmission unit receives the instructions from the ground station and converts them into control signals that the drone can understand, and sends them to the execution module and flight control unit. The following formula is the modulation and demodulation formula of the signal:

[0084] s(t)=A c cos(ω c t+φ)

[0085] Where s(t) is the signal, Ac is the amplitude of the carrier, ωc is the angular frequency of the carrier, and φ is the phase shift.

[0086] The cleaning effect evaluation unit is used to evaluate the cleaning effect and provide feedback to the operator. The cleaning effect is evaluated by comparing the image data before and after cleaning, and the evaluation result is fed back to the ground station through the data transmission unit so that the operator can understand the cleaning effect and make corresponding adjustments. The following formula is the image contrast calculation formula:

[0087]

[0088] Where C is the contrast, I max and I min are the maximum and minimum brightness values ​​of the image respectively.

[0089] The state feedback unit is used to report the state of the drone and the cleaning progress to the ground station in real time. The data transmission unit transmits the drone's location, battery status, cleaning progress and other information to the ground station in real time so that the operator can monitor the entire cleaning process and make timely adjustments. The following formula is the battery power calculation formula in drone state monitoring:

[0090]

[0091] Where SOC is the percentage of remaining battery power, Q remaining is the remaining power, Q total is the total power.

[0092] The embodiments of the present invention are described above. It should be understood that the present invention is not limited to the specific embodiments described, and the devices and structures not described in detail can be implemented in a manner commonly used in the art. For those skilled in the art, without departing from the scope of the technical solution of the present invention, the technical solution of the present invention can be subjected to a variety of possible changes and modifications, or equivalent changes can be made to it to achieve equivalent embodiments, which do not affect the core gist of the present invention. Therefore, any simple modification, equivalent change and modification made to the technical solution of the present invention, as long as it does not depart from the technical solution content and technical essence of the present invention, should be deemed to belong to the protection scope of the technical solution of the present invention.

Claims

1. A solar panel cleaning system, characterized in that: It includes environment perception module, central control module, execution module and communication and feedback module; The environmental perception module is used to obtain environmental information and solar panel status, capture details of the solar panel surface, determine the location of the drone, and match it with the preset cleaning area map to ensure that the drone performs the task at the correct location. At the same time, it detects obstacles on the flight path, such as wires, trees or other aircraft, to ensure flight safety. The environmental perception module transmits the collected data to the central control module, providing it with a basis for decision-making; The central control module is used to process the data collected by the environmental perception module, formulate the flight path and cleaning strategy, control the flight attitude of the UAV, and analyze the image data through the data processing unit to determine whether cleaning is required and how to clean and generate instructions, and send the instructions to the execution module through the communication and feedback module; The communication and feedback module is used to realize data transmission and command reception between the UAV and the ground control station, and transmit the status and cleaning results of the UAV to the operator in real time through the feedback mechanism; The execution module is used to execute the instructions of the central control module to complete specific cleaning tasks. It adjusts the spray angle and pressure of the water gun through the water gun control subsystem, monitors the water level of the water tank through the water supply management subsystem, and manages the output of the motor through the power energy management system.

2. A solar panel cleaning system according to claim 1, characterized in that: The environmental perception module includes an identification module and a positioning module; the identification module captures images through the camera optical system, converts light signals into electrical signals, and then converts the electrical signals into digital image data through the image sensor, and uses computer vision algorithms, including image segmentation, feature extraction and machine learning models, to analyze the image data to determine the pollution status of the solar panel surface, and identify and avoid potential obstacles; the positioning module calculates the position coordinates of the drone by receiving satellite signals, and compares it with the preset map data to determine the current position of the drone, and the environmental perception module transmits the collected data to the central control module.

3. A solar panel cleaning system according to claim 2, characterized in that: The central control module includes a flight control module and a data processing and decision-making module. The flight control module is responsible for the stable flight and precise navigation of the UAV; the flight command subsystem generates a flight path and control commands according to the decision of the central control module, and the status monitoring subsystem monitors the flight status of the UAV in real time, including speed, altitude, direction and battery power, to ensure that the UAV is always in the best working condition when performing tasks; the data processing and decision-making module receives data sent back by the environmental perception module, creates an environmental map using the SLAM algorithm, analyzes the contamination of the solar panels in combination with the output of the image processing unit, and formulates a cleaning strategy based on this information, including cleaning sequence, path planning and cleaning intensity, and sends instructions to the execution module through the communication and feedback module.

4. A solar panel cleaning system according to claim 3, characterized in that: The execution module receives instructions from the central control module, adjusts the spray pressure and flow of the water gun system, and controls the operation of the water supply system to ensure that the cleaning task can be executed according to the predetermined strategy.

5. A solar panel cleaning system according to claim 3, characterized in that: The communication and feedback module is used to realize data exchange between the UAV and the ground control station, compare the image data before and after cleaning, evaluate the cleaning effect, and provide feedback to the operator; The status feedback subsystem reports the drone's location, battery status, and cleaning progress to the ground station in real time so that the operator can monitor the entire cleaning process and make timely adjustments.

6. A solar panel cleaning system according to claim 2, characterized in that: The recognition module captures the details of the solar panel surface, identifies the location, size and density of dust and stains, and uses computer vision algorithms such as image segmentation, feature extraction and machine learning models to analyze the image data to determine the contamination of the solar panel surface. The following formula uses the Sobel operator and the Canny operator to extract edges from the image: Among them, Gx and Gy are the gradients in the horizontal and vertical directions, w ij is the weight matrix, and I(i,j) is the pixel value of the image at position (i,j).

7. A solar panel cleaning system according to claim 2, characterized in that: The positioning module provides the geographic location information of the drone for navigation and path planning. By receiving satellite signals, the location coordinates of the drone are calculated and compared with the preset map data to determine the current location of the drone. The following formula uses the trilateration principle to calculate the location coordinates of the drone by receiving multiple satellite signals: Among them, x and y are the latitude and longitude coordinates of the drone, c is the speed of light, and t1, t2 and t3 are the time differences when the drone receives different satellite signals.

8. A solar panel cleaning system according to claim 3, characterized in that: The data processing and decision-making module is used to process the data sent back by the environmental perception module, formulate a cleaning strategy, create an environmental map using the SLAM algorithm, analyze the contamination of the solar panels in combination with the output of the image processing unit, and formulate a cleaning path and intensity based on this information. The following is the state update formula in EKF-SLAM: x←x+F -1 HR -1 (z-Hx) Where x is the state vector, F is the state transfer matrix, H is the observation matrix, R is the observation noise covariance matrix, and z is the observation value.

9. A solar panel cleaning system according to claim 5, characterized in that: The communication and feedback module evaluates the cleaning effect by comparing the image data before and after cleaning, and feeds back the evaluation result to the ground station through the data transmission unit so that the operator can understand the cleaning effect and make corresponding adjustments. The following formula is the image contrast calculation formula: Where C is the contrast, I max and I min are the maximum and minimum brightness values ​​of the image respectively.

10. A solar panel cleaning system according to claim 5, characterized in that: The communication and feedback module transmits the position, battery status, cleaning progress and other information of the drone to the ground station in real time through the data transmission unit, so that the operator can monitor the entire cleaning process and make timely adjustments. The following formula is the battery power calculation formula in drone status monitoring: Where SOC is the percentage of remaining battery power, Q remaining is the remaining power, Q total is the total power.

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