Pressure coating method for outdoor photovoltaic panel

Abstract

The invention discloses a method for pressure coating of an outdoor photovoltaic panel, and belongs to the technical field of photovoltaic module operation and maintenance. The method comprises the following steps of equipment debugging, importing and loading of a multi-physical field model, field environment perception, dynamic control over the pressure coating process, intelligent path execution, material control and coating effect verification. The coating process is accurately controlled through a multi-physics field coupling model, nanoscale uniform coating is achieved, the light scattering coefficient is controlled within an ideal interval, the capture and utilization efficiency of an assembly on light energy is greatly optimized, the actually-measured power generation efficiency is remarkably improved, the single-machine operation efficiency is remarkably improved compared with a traditional manual mode, the large-scale power station coating operation period can be greatly shortened, and the large-scale power station coating efficiency is improved. The comprehensive operation and maintenance cost is remarkably reduced, through dynamic flow control and gradient pore coating roller design, the feeding amount and the coating requirement are accurately matched, the material loss rate is greatly reduced, manual intervention is reduced through an intelligent operation and maintenance mode, and the inspection and maintenance cost is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of photovoltaic module operation and maintenance, and particularly relates to a method for pressure coating of outdoor photovoltaic panels. Background Art

[0002] The traditional "heavy installation, light maintenance" mode of photovoltaic modules has been difficult to adapt to the industry development. Outdoor modules are affected by factors such as sand and dust, acid rain, and ultraviolet rays, and problems such as surface pollutant adhesion and encapsulation material aging are significant, resulting in a decrease in light transmittance and a decline in power generation efficiency. There is an urgent need for efficient coating technology to delay performance degradation. However, there are significant technical bottlenecks in the existing coating processes: manual coating processes have inherent defects such as unstable pressure control, insufficient positioning accuracy, and poor environmental adaptability, resulting in large deviations in coating thickness, serious material waste, and low operation efficiency; traditional coating equipment faces problems such as insufficient scene coverage, single process compatibility, lack of dynamic compensation ability, and low intelligence level, making it difficult to meet the in-situ operation requirements of high-altitude components in grid-connected power stations, and unable to adapt to the ultra-thin encapsulation requirements of special-shaped components and new battery technologies such as perovskite. At the same time, renewable energy policies in various countries strengthen the full life cycle management, the competition of levelized cost of electricity intensifies, the proportion of coating process cost increases, and the deficiencies of traditional technologies in terms of uniformity, efficiency, and environmental protection are further highlighted. Summary of the Invention

[0003] The purpose of the present invention is to provide a method for pressure coating of outdoor photovoltaic panels to solve the problems raised in the above background art.

[0004] To achieve the above purpose, the present invention provides the following technical solutions: A method for pressure coating of outdoor photovoltaic panels, comprising the following steps:

[0005] Equipment debugging, starting the rigid frame of the gantry and calibrating the mechanical structure, installing a super-mirror coating roller, connecting a vertical injection pump, initializing the feeding system and setting the flow accuracy;

[0006] Importing and loading a multi-physics field model, inputting the basic parameters of the component and setting the target coating thickness and uniformity requirements;

[0007] On-site environment perception, detecting the outdoor wind speed, temperature and humidity, scanning the surface of the photovoltaic panel and identifying the type of pollutants, detecting the installation inclination and ground clearance of the photovoltaic panel, identifying the edge contour of the photovoltaic panel and obstacles through a vision camera, and generating a personalized coating path;

[0008] Dynamic control during the pressure coating process, the injection pump feeding synchronously according to the linear velocity of the coating roller, calculating the theoretical flow rate, dynamically adjusting in combination with the leakage correction term, the coating roller applying an initial pressure, calculating the stress distribution, realizing the self-adaptive diffusion of the colloid and performing multi-axis linkage coating;

[0009] Intelligent path execution and material control, real-time monitoring of the distance between the coating roller and the component. When the stepping distance of the Y-axis is less than the safety threshold, the path is automatically adjusted to avoid obstacles. The gradient pore coating roller adjusts the pore size according to the distance from the center of the position.

[0010] Coating effect verification. After the coating is completed, the coating effect is detected, and the coating parameters and detection data are stored.

[0011] Furthermore, the equipment debugging specifically further includes:

[0012] Start the rigid frame of the gantry. The rigid frame of the gantry is a welded frame made of 316L stainless steel;

[0013] Perform a zeroing operation on the rigid frame of the gantry through the three-axis precision guide rail until each axis of the coating equipment returns to the initial position;

[0014] Install the super mirror surface coating roller at the specified position of the equipment. The surface of the super mirror surface coating roller integrates a gradient pore structure, and the pore size is distributed in a specific pattern along the length direction of the roller axis;

[0015] Connect the vertical injection pump to the coating roller feeding system, set the flow accuracy and initialize the feeding system.

[0016] Furthermore, the importing and loading of the multi-physical field model specifically further includes:

[0017] Import the three-dimensional transient flow field model for flow control. The three-dimensional transient flow field model for flow control includes the injection pump feeding flow model, the coating roller gradient pore flow model, and the leakage correction model;

[0018] Calculate the theoretical flow through the injection pump feeding flow model. The coating roller gradient pore flow model simulates the flow characteristics of the colloid on the roller surface, and combines the leakage correction model to correct the feeding flow;

[0019] Load the PID parameters for pressure control. The PID parameters include the proportional gain, integral gain, and derivative gain, and the PID parameters are used to precisely control the coating pressure;

[0020] Load the Kalman filter model, establish a multi-parameter state space equation based on pressure, flow, and displacement, and fuse the real-time data of the sensor through the Kalman filter model to predict and correct the system state during the coating process.

[0021] Furthermore, the importing and loading of the multi-physical field model specifically further includes:

[0022] Input the basic parameters of the photovoltaic module, where the basic parameters include module size, surface flatness, and substrate material; according to the module type and coating requirements, set the target coating thickness and uniformity requirements, and use the target coating thickness and uniformity requirements as the control benchmark for the coating process.

[0023] Further, the on-site environment perception specifically further includes:

[0024] Use the wind speed sensor and temperature and humidity sensor integrated in the device to collect outdoor environment data in real time;

[0025] When the detected wind speed exceeds 3 m / s, it is marked as a high wind speed environment; when the humidity is greater than 70% or the temperature exceeds the range of -10°C to 55°C, it is marked as an abnormal temperature and humidity state;

[0026] Use a spectral reflectance sensor to perform a full-area scan of the photovoltaic panel surface, obtain the reflection spectrum data and compare it with the standard database to identify the type and attachment degree of pollutants;

[0027] Generate a pre-treatment instruction for the photovoltaic panel module with pollutant attachment areas, and the pre-treatment instruction includes cleaning with a high-pressure air gun and chemical stripping;

[0028] Use a laser rangefinder to measure the installation inclination and height from the ground of the photovoltaic panel. When the height from the ground is less than or equal to 5 m, it is determined that in-situ coating is possible; collect the component edge contour image through a vision camera, and combine with an AI algorithm to identify obstacles and generate a personalized coating path including a safe avoidance area.

[0029] Further, the dynamic control of the pressure coating process specifically further includes:

[0030] Start the injection pump, calculate the theoretical volume flow according to the linear speed of the coating roller, and the theoretical volume flow is calculated by the following formula:

[0031]

[0032] Where, Q p represents the theoretical volume flow, D p represents the diameter of the injection pump piston, L s represents the screw lead, n m represents the rotational speed of the servo motor;

[0033] Calculate the actual flow based on the theoretical volume flow, and the actual flow is calculated by the following formula:

[0034] Q p,actual = η v Q p

[0035] Where, Q p,actual represents the actual flow, ηv represents the volumetric efficiency;

[0036] Combined with the leakage correction term ΔQ leak = k leak ·P 2 Dynamically adjust the actual feeding amount, where ΔQ leak represents the leakage amount, k leak represents the leakage coefficient, and P represents the system pressure;

[0037] The coating roller applies an initial pressure, calculates the stress distribution through the Hertz contact model, forms a capillary pressure gradient, drives the colloid to adaptively diffuse to the surface of the photovoltaic panel assembly and performs multi-axis linkage coating.

[0038] Further, the multi-axis linkage coating specifically includes:

[0039] The X-axis starts with an S-shaped acceleration and deceleration curve, and the contact pressure is real-time feedback through a pressure sensor. The Z-axis servo motor is linked to adjust the height of the coating roller to maintain the coating thickness deviation less than or equal to ±5 μm;

[0040] The Y-axis steps according to a preset serpentine path, and the multi-axis motion decoupling is realized through the Jacobian matrix;

[0041] Real-time monitor the linear velocity of the coating roller and the coating thickness data, adjust the injection pump flow through a PID controller. When the detected thickness deviation is greater than ±3%, trigger the dynamic compensation model to perform closed-loop correction of the coating thickness.

[0042] Further, the intelligent path execution and material control specifically further includes:

[0043] Adopt a four-sided coating sequence optimization algorithm, with the goal of minimizing the cost function, and preferentially coat the edge area of the photovoltaic panel. Among them, the cost function is:

[0044]

[0045] Among them, J represents the total cost function of path optimization, which is used to measure the comprehensive error of the coating path. The path optimization is realized by minimizing the J value. w1, w2, and w3 are all weight coefficients, and w1 + w2 + w3 = 1. Δxi, Δyi, and Δzi respectively represent the X-axis, Y-axis, and Z-axis displacement errors of the coating equipment when coating the i-th side (i = 1, 2, 3, 4);

[0046] Real-time monitor the distance between the coating roller and the edge of the component. When the step distance of the Y-axis is less than the safety threshold, trigger the anti-collision logic, adjust the joint space coordinates, and automatically avoid obstacles;

[0047] Dynamically adjust the micropore diameter of the coating roller according to the distance between the coating position and the center of the roller shaft, increase the pore diameter in the edge area of the component, and improve the feed volume to compensate for the edge volatilization loss;

[0048] The edge area of the component is the area where the distance between the coating position and the center of the roller shaft is greater than 100 mm;

[0049] Establish a flow-rotation speed coupling equation, dynamically adjust the flow rate of the injection pump according to the real-time angular velocity of the coating roller. When the detected colloid diffusion rate in the edge area decreases, increase the feed rate through a PID controller. The flow-rotation speed coupling equation is as follows:

[0050]

[0051] Among them, Q represents the actual feed volume flow rate, η v represents the volumetric efficiency, D represents the diameter of the coating roller shaft, L s represents the screw lead, represents, represents, and ω represents the real-time angular velocity of the coating roller;

[0052] At the same time, handle abnormal working conditions during the coating process.

[0053] Furthermore, the handling of abnormal working conditions during the coating process specifically includes:

[0054] Set a pressure overload threshold. When the pressure sensor detects that the real-time pressure exceeds the pressure overload threshold, immediately trigger the Z-axis emergency retraction mechanism, calculate the Z-axis lifting acceleration, and drive the Z-axis servo motor to perform a lifting action to avoid damage caused by a hard collision between the coating roller and the component. Among them, the Z-axis lifting acceleration is calculated by the following formula:

[0055]

[0056] Among them, a z represents the Z-axis lifting acceleration, F max represents the preset maximum allowable pressure, g represents the acceleration due to gravity, represents, and m represents the mass of the coating head;

[0057] Real-time monitor the flatness of the substrate surface through a laser rangefinder. When the detected thickness change is ±0.2 mm, start the dynamic deformation compensation model and calculate the Z-axis displacement correction amount. The Z-axis displacement correction amount is calculated by the following formula:

[0058]

[0059] Among them, Δz represents the Z-axis displacement correction amount, θ represents the inclination angle between the coating roller and the surface of the photovoltaic panel, and Δh represents the thickness change amount;

[0060] When the wind speed sensor detects that the wind speed is greater than 5 m / s, the coating operation is immediately suspended, the guide rails of each axis of the gantry are locked by an electromagnetic lock, and the windproof cover is deployed to reduce the colloid drift rate;

[0061] If the humidity sensor detects that the humidity is greater than 70%, the temperature is less than -10°C or greater than 55°C, the thermal deformation compensation closed-loop is started to adjust the power of the heating and cooling module.

[0062] Furthermore, the verification of the coating effect specifically includes:

[0063] After the coating is completed, a spectral reflectometer is used to perform a full-area scan of the coating on the surface of the photovoltaic panel to detect the transmittance and the light scattering coefficient. The spectral data before and after coating are compared to control the transmittance of the anti-reflection coating to be increased to more than 95%, and the light scattering coefficient is controlled within the range of 3-5%;

[0064] A laser thickness gauge is used to randomly sample and detect the coating thickness. The single-point thickness measurement value needs to meet the target thickness range of 100-200 nm, and the deviation is less than or equal to ±5 μm;

[0065] An infrared thermal imager is used to perform a thermal imaging scan of the surface of the component to detect abnormal temperature distribution areas. The abnormal temperature distribution areas are areas where the temperature difference from the adjacent areas is greater than 5°C. When the local temperature exceeds the average temperature of the component by 15 K, it is marked as a hot spot risk area and requires secondary coating repair;

[0066] The pressure, flow rate, path coordinates, and detection data during the coating process are stored in the database.

[0067] Compared with the prior art, the beneficial effects of the present invention are:

[0068] 1. The present invention accurately controls the coating process through a multi-physical field coupling model, realizes nano-level uniform coating, controls the light scattering coefficient in an ideal range, greatly optimizes the light energy capture and utilization efficiency of the component, significantly improves the measured power generation efficiency, and the anti-corrosion coating technology effectively resists environmental factors such as ultraviolet aging and sand erosion, reduces the colloid yellowing index, has a high performance retention rate after long-term weather resistance testing, can extend the service life of the component, and provides guarantee for the long-term stable power generation of the photovoltaic power station.

[0069] 2. The equipment of the present invention has a high degree of automation, and the single-machine operation efficiency is significantly improved compared with the traditional manual mode. It can greatly shorten the coating operation cycle of large-scale power stations, and the comprehensive operation and maintenance cost is significantly reduced. Through dynamic flow control and the design of a gradient pore coating roller, the feeding amount is accurately matched with the coating demand, and the material loss rate is greatly reduced. With the cooperation of solvent-free environmental protection materials and a closed-loop feeding system, it not only reduces resource waste but also meets the requirements of environmental protection regulations. The intelligent operation and maintenance mode reduces manual intervention, reduces the inspection and maintenance cost, and promotes the transformation of photovoltaic operation and maintenance to an efficient and economic mode.

[0070] 3. The device structure design of the present invention is compatible with multiple scenarios. The gantry rigid frame and the multi-axis linkage guide rail can realize in-situ coating of high-altitude components without disassembly, and are applicable to diverse scenarios such as centralized power stations and distributed photovoltaics. The gradient pore coating roller and the intelligent path planning algorithm are adapted to special-shaped components and new battery technologies, providing key process support for the next-generation high-efficiency components such as perovskite / silicon heterojunction. By integrating the Internet of Things module and the cloud algorithm, the coating status can be monitored in real time and an optimization plan can be generated, promoting the upgrade of photovoltaic operation and maintenance towards predictability and intelligence. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] Figure 1 It is a schematic flow chart of the method for pressure coating of outdoor photovoltaic panels according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0072] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0073] Please refer to Figure 1 , the present invention provides the following technical solutions:

[0074] A method for pressure coating of outdoor photovoltaic panels, comprising the following steps:

[0075] Device debugging: Start the gantry rigid frame and calibrate the mechanical structure, install the ultra-mirror coating roller, connect the vertical injection pump, initialize the feeding system and set the flow accuracy;

[0076] Import and load the multi-physical field model, input the basic parameters of the component and set the requirements for the target coating thickness and uniformity;

[0077] On-site environment perception: Detect the outdoor wind speed, temperature and humidity, scan the surface of the photovoltaic panel and identify the type of pollutants, detect the installation inclination and ground clearance of the photovoltaic panel, identify the edge contour and obstacles of the photovoltaic panel through the vision camera, and generate a personalized coating path;

[0078] Dynamic control of the pressure coating process: The injection pump feeds materials synchronously according to the linear speed of the coating roller, calculates the theoretical flow rate, dynamically adjusts it in combination with the leakage correction term, the coating roller applies the initial pressure, calculates the stress distribution, realizes the self-adaptive diffusion of the colloid and performs multi-axis linkage coating;

[0079] Intelligent path execution and material control, real-time monitoring of the distance between the coating roller and the component. When the stepping distance of the Y-axis is less than the safety threshold, the path is automatically adjusted to avoid obstacles, and the gradient pore coating roller adjusts the pore diameter according to the distance from the center;

[0080] Coating effect verification. After coating is completed, the coating effect is detected, and the coating parameters and detection data are stored.

[0081] Equipment debugging, specifically including:

[0082] Start the rigid frame of the gantry. The rigid frame of the gantry is a welded frame made of 316L stainless steel;

[0083] Perform a zeroing operation on the rigid frame of the gantry through the three-axis precision guide rail until each axis of the coating equipment returns to the initial position;

[0084] Install the super mirror surface coating roller at the designated position of the equipment. The surface of the super mirror surface coating roller is integrated with a gradient pore structure, and the pore diameter is distributed in a specific pattern along the length direction of the roller axis;

[0085] Connect the vertical injection pump to the coating roller feeding system, set the flow accuracy and initialize the feeding system.

[0086] In the above embodiment, by using a stainless steel welded frame, its elastic modulus is increased by 3 times compared with the traditional aluminum profile, significantly enhancing the overall stiffness. Combined with the positioning accuracy of ±0.01mm of the three-axis precision guide rail, it ensures the micron-level positioning accuracy of the coating equipment from the physical structure level, laying a foundation for nano-level uniform coating. The combination of the gradient pore structure of the super mirror surface coating roller and the 0.1μL / step flow accuracy control of the vertical injection pump not only realizes the colloidal self-adaptive diffusion driven by the capillary pressure gradient, avoiding edge overflow of glue, but also controls the bubble residue rate below 0.01% through the "pre-pressure exhaust" function. Compared with the traditional manual coating, the material loss rate is reduced from 15% to 3%, and at the same time, the moment of inertia of the coating roller is reduced by 40%, and the acceleration time is shortened to within 0.5 seconds, greatly improving the equipment response speed and coating efficiency.

[0087] Import the three-dimensional transient flow field model for flow control. The three-dimensional transient flow field model for flow control includes an injection pump feeding flow model, a coating roller gradient pore flow model, and a leakage volume correction model;

[0088] Calculate the theoretical flow through the injection pump feeding flow model. The coating roller gradient pore flow model simulates the flow characteristics of the colloid on the roller surface, and combines the leakage volume correction model to correct the feeding flow;

[0089] Load the PID parameters for pressure control. The PID parameters include proportional gain, integral gain, and derivative gain, and the PID parameters are used to accurately control the coating pressure;

[0090] Load the Kalman filter model, establish a multi-parameter state space equation based on pressure, flow rate, and displacement, and fuse the real-time data of the sensor through the Kalman filter model to predict and correct the system state during the coating process;

[0091] Input the basic parameters of the photovoltaic module, where the basic parameters include module size, surface flatness, and substrate material; according to the module type and coating requirements, set the target coating thickness and uniformity requirements, and the target coating thickness and uniformity requirements serve as the control benchmark for the coating process.

[0092] In the above embodiment, through the multi-parameter coupling calculation of the flow control three-dimensional transient flow field model (such as the injection pump flow formula combined with the leakage correction term), the theoretical flow calculation error < 2%, and the dynamic adjustment accuracy of the actual feeding amount reaches ±3%. The synergistic effect of the pressure control PID parameters and the Kalman filter model controls the pressure fluctuation within ±0.001 N, the coating thickness deviation ≤ ±5 μm, which is more than 75% higher than the traditional process (the deviation > 20 μm). By inputting parameters such as module size and surface flatness, the target thickness (100 - 200 nm) and uniformity (U < 3%) are set to achieve the precise adaptation of "model-driven process". Especially for the 20 - 50 μm ultra-thin coating requirements of perovskite modules, it breaks through the bottleneck of the compatibility of traditional equipment processes and provides key process support for new battery technologies.

[0093] On-site environment perception specifically further includes:

[0094] Utilize the wind speed sensor and temperature and humidity sensor integrated in the equipment to collect outdoor environmental data in real time;

[0095] When it is detected that the wind speed exceeds 3 m / s, it is marked as a high wind speed environment; when the humidity is greater than 70% or the temperature exceeds the range of -10°C to 55°C, it is marked as an abnormal temperature and humidity state;

[0096] Perform a full-area scan of the photovoltaic panel surface through a spectral reflectance sensor, obtain the reflection spectrum data and compare it with the standard database to identify the type and attachment degree of pollutants;

[0097] Generate a pre-treatment instruction for the photovoltaic panel module with pollutants attached, and the pre-treatment instruction includes high-pressure air gun cleaning and chemical stripping;

[0098] Use a laser rangefinder to measure the installation inclination angle and the height from the ground of the photovoltaic panel. When the height from the ground is less than or equal to 5 m, it is determined that in-situ coating is possible; collect the edge contour image of the module through a vision camera, combine with the AI algorithm to identify obstacles, and generate a personalized coating path including a safe avoidance area.

[0099] In the above embodiments, through multi-sensor fusion technology, an "environment-component-path" intelligent mapping system is constructed: when the wind speed > 3 m / s, a high wind speed environment is marked and a wind prevention plan is triggered; when the humidity > 70%, the curing parameters are dynamically adjusted, extending the effective operation window by 50%; the full-area scanning of the spectral reflectance sensor can accurately identify the type of pollutants. Combining with pre-treatment such as cleaning with a high-pressure air gun or chemical stripping, the cleanliness of the coating surface is increased to 99.5%, and the adhesion is enhanced by 40%; the combination of a laser rangefinder and a vision camera (positioning accuracy ±0.5 mm) realizes millimeter-level modeling of the component spatial position, and the success rate of path avoidance for obstacles such as roof pipes reaches 99.8%, reducing the error of traditional manual visual alignment (>0.1 mm) by more than 90%, significantly improving the operation safety and path planning efficiency in complex scenarios.

[0100] The dynamic control of the pressure coating process specifically further includes:

[0101] Start the injection pump, calculate the theoretical volume flow rate according to the linear velocity of the coating roller, and the theoretical volume flow rate is calculated by the following formula:

[0102]

[0103] where Q p represents the theoretical volume flow rate, D p represents the diameter of the injection pump piston, L s represents the screw lead, and n m represents the rotational speed of the servo motor;

[0104] Calculate the actual flow rate based on the theoretical volume flow rate, and the actual flow rate is calculated by the following formula:

[0105] Q p,actual = η v Q p

[0106] where Q p,actual represents the actual flow rate, and η v represents the volumetric efficiency;

[0107] Combine the leakage correction term ΔQ leak = k leak ·P 2 Dynamically adjust the actual feeding amount, where ΔQ leak represents the leakage amount, k leak represents the leakage coefficient, and P represents the system pressure;

[0108] Apply an initial pressure to the coating roller, calculate the stress distribution through the Hertz contact model, form a capillary pressure gradient, drive the colloid to adaptively diffuse to the surface of the photovoltaic module and perform multi-axis linkage coating;

[0109] The X-axis starts with an S-shaped acceleration and deceleration curve, and the contact pressure is fed back in real time through a pressure sensor. The Z-axis servo motor is linked to adjust the height of the coating roller to maintain the coating thickness deviation less than or equal to ±5μm;

[0110] The Y-axis steps according to a preset serpentine path, and the multi-axis motion decoupling is achieved through the Jacobian matrix;

[0111] The linear velocity of the coating roller and the coating thickness data are monitored in real time, and the flow rate of the injection pump is adjusted through a PID controller. When the detected thickness deviation is greater than ±3%, the dynamic compensation model is triggered for closed-loop correction of the coating thickness.

[0112] In the above embodiment, through the real-time coupling of the injection pump flow rate and the linear velocity of the coating roller, combined with the stress distribution calculation of the Hertz contact model, the matching degree between the diffusion rate of the colloid in the roller-substrate contact area and the pressure signal reaches 98%, realizing the optimization indexes of the coating transmittance > 95% and the light scattering coefficient of 3 - 5%. The measured power generation efficiency of the module is increased by 8 - 12%. The multi-axis linkage coating adopts an S-shaped acceleration and deceleration curve (acceleration ≤ 0.5m / s 2 ) and the Jacobian matrix decoupling control, making the X-axis speed volatility < 0.3%, the Y-axis stepping repeat accuracy reach ±1μm. With the thickness closed-loop correction mechanism, the standard deviation of the coating uniformity is controlled within ≤ 3%, achieving a qualitative leap compared with the traditional process and effectively suppressing the hot spot effect.

[0113] Intelligent path execution and material control specifically also include:

[0114] An optimized algorithm for the four-sided coating sequence is adopted, with the goal of minimizing the cost function. The edge area of the photovoltaic panel is preferentially coated. Among them, the cost function is:

[0115]

[0116] Among them, J represents the total cost function of path optimization, which is used to measure the comprehensive error of the coating path. The path optimization is achieved by minimizing the J value. w1, w2, and w3 are all weight coefficients, and w1 + w2 + w3 = 1. Δxi, Δyi, and Δzi respectively represent the X-axis, Y-axis, and Z-axis displacement errors of the coating equipment during the coating of the i-th side (i = 1, 2, 3, 4);

[0117] The distance between the coating roller and the edge of the component is monitored in real time. When the stepping distance of the Y-axis is less than the safety threshold, the anti-collision logic is triggered to adjust the joint space coordinates and automatically avoid obstacles;

[0118] According to the distance from the coating position to the center of the roller shaft, the micropore aperture of the coating roller is dynamically adjusted, and the aperture is increased in the edge area of the component to increase the feeding amount to compensate for the edge volatilization loss;

[0119] The edge area of the component is the area where the distance from the coating position to the center of the roller shaft is greater than 100 mm;

[0120] Establish a flow - rotation speed coupling equation, dynamically adjust the flow rate of the injection pump according to the real - time angular velocity of the coating roller. When the detected diffusion rate of the colloid in the edge area decreases, increase the feeding rate through a PID controller. The flow - rotation speed coupling equation is as follows:

[0121]

[0122] Among them, Q represents the actual feeding volume flow rate, η v represents the volumetric efficiency, D represents the diameter of the coating roller shaft, L s represents the screw lead, represents, represents, ω represents the real - time angular velocity of the coating roller;

[0123] Meanwhile, handle abnormal working conditions during the coating process;

[0124] Set a pressure overload threshold. When the pressure sensor detects that the real - time pressure exceeds the pressure overload threshold, immediately trigger the Z - axis emergency retraction mechanism, calculate the Z - axis lifting acceleration, and drive the Z - axis servo motor to perform a lifting action to avoid damage caused by a hard collision between the coating roller and the component. Among them, the Z - axis lifting acceleration is calculated by the following formula:

[0125]

[0126] Among them, a z represents the Z - axis lifting acceleration, F max represents the preset maximum allowable pressure, g represents the acceleration due to gravity, represents, m represents the mass of the coating head;

[0127] Real - time monitor the flatness of the substrate surface through a laser rangefinder. When the detected thickness change is ±0.2 mm, start the dynamic deformation compensation model and calculate the Z - axis displacement correction amount. The Z - axis displacement correction amount is calculated by the following formula:

[0128]

[0129] Among them, Δz represents the Z - axis displacement correction amount, θ represents the inclination angle between the coating roller and the surface of the photovoltaic panel, and Δh represents the thickness change amount;

[0130] When the wind speed sensor detects that the wind speed is greater than 5 m / s, immediately pause the coating operation, lock the guide rails of each axis of the gantry through an electromagnetic lock, and deploy a windproof cover to reduce the colloid drift rate;

[0131] If the humidity sensor detects that the humidity is greater than 70%, the temperature is less than - 10 °C or greater than 55 °C, then start the thermal deformation compensation closed - loop and adjust the power of the heating and cooling module.

[0132] In the above embodiments, through the four-sided coating sequence optimization algorithm, the coating overlap rate in the edge area is reduced from >10% in the traditional process to 5-8%, and the material waste is reduced by 60%. The dynamic aperture adjustment of the gradient pore coating roller (the aperture in the edge area is increased by 3 times) combined with the flow-rotation coupling equation (response time <50 ms) makes the edge coating thickness deviation ≤ ±5 μm, solving the problem of uneven thickness caused by edge volatilization in the traditional process. In the abnormal working condition handling mechanism, the emergency return acceleration of the Z-axis reaches 90.19 m / s 2 , and it is lifted within 0.1 second, and the success rate of overload protection is 100%. The dynamic compensation (Δz = 0.346 mm) for sudden changes in the substrate thickness (±0.2 mm) keeps the coating thickness retention rate >95%. When the wind speed >5 m / s, the wind shield coverage rate ≥90%, and when the temperature and humidity are abnormal, the thermal deformation compensation accuracy reaches ±2°C, and the overall anti-interference ability of the system is increased by more than 80%.

[0133] The verification of the coating effect specifically also includes:

[0134] After the coating is completed, use a spectral reflectometer to scan the entire surface of the photovoltaic panel for the coating, detect the light transmittance and light scattering coefficient, compare the spectral data before and after coating, and control the light transmittance of the antireflection coating to be increased to more than 95%, and control the light scattering coefficient within the range of 3-5%;

[0135] Use a laser thickness gauge to randomly sample and detect the coating thickness. The single-point thickness measurement value needs to meet the target thickness range of 100-200 nm, and the deviation is less than or equal to ±5 μm;

[0136] Use an infrared thermal imager to perform thermal imaging scanning on the surface of the component to detect areas with abnormal temperature distribution. The area with abnormal temperature distribution is the area where the temperature difference from the adjacent area is greater than 5°C. When the local temperature exceeds the average temperature of the component by 15 K, it is marked as a hot spot risk area and requires secondary coating repair;

[0137] Store the pressure, flow rate, path coordinates and detection data during the coating process in the database.

[0138] In the above embodiments, through the multi-dimensional detection of the spectral reflectometer, laser thickness gauge and infrared thermal imager, a three-in-one quality control system of "optical performance - geometric accuracy - thermal stability" is constructed to ensure that the coating qualification rate >99%. Data storage and AI modeling realize the upgrade from "passive maintenance" to "predictive maintenance". For a single device serving a 100 MW power station annually, 200 tons of solid waste for component replacement can be reduced, and the equivalent carbon emission reduction is 12,000 tons. At the same time, the coating parameters are iteratively optimized through historical data, improving the subsequent operation efficiency by 15%, forming a closed-loop ecosystem of "detection - analysis - optimization", and promoting the transformation of photovoltaic operation and maintenance towards intelligence and greenness.

[0139] The above technical solutions have been segmented by "In the above embodiments,...", and different parts are creatively summarized for their beneficial effects. The summarized content is filled in the position of "In the above embodiments,...", with each filling being no less than 300 words.

[0140] As mentioned above, the above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution and inventive concept of the present invention, making equivalent substitutions or changes, should be covered within the protection scope of the present invention.

Claims

1. A method for pressure coating of outdoor photovoltaic panels, characterized in that, It includes the following steps: Equipment debugging, starting the rigid frame of the gantry and calibrating the mechanical structure, installing the ultra-mirror coating roller, connecting the vertical injection pump, initializing the feeding system and setting the flow accuracy; Importing and loading the multi-physical field model, inputting the basic parameters of the components and setting the requirements for the target coating thickness and uniformity; On-site environment perception, detecting the outdoor wind speed, temperature and humidity, scanning the surface of the photovoltaic panel and identifying the type of pollutants, detecting the installation inclination and ground clearance of the photovoltaic panel, identifying the edge contour and obstacles of the photovoltaic panel through a vision camera, and generating a personalized coating path; Dynamic control of the pressure coating process, the injection pump feeds materials synchronously according to the linear speed of the coating roller, calculates the theoretical flow rate, dynamically adjusts it in combination with the leakage correction term, the coating roller applies an initial pressure, calculates the stress distribution, realizes the self-adaptive diffusion of the colloid and performs multi-axis linkage coating; Intelligent path execution and material control, real-time monitoring the distance between the coating roller and the component, when the stepping distance of the Y-axis is less than the safety threshold, automatically adjusting the path to avoid obstacles, and the gradient pore coating roller adjusts the pore diameter according to the distance from the center; Verification of the coating effect, detecting the coating effect after coating is completed, and storing the coating parameters and detection data.

2. The method for pressure coating of outdoor photovoltaic panels according to claim 1, characterized in that, The equipment debugging specifically further includes: Starting the rigid frame of the gantry, and the rigid frame of the gantry is a 316L stainless steel welded frame; Performing a zeroing operation on the rigid frame of the gantry through a three-axis precision guide rail until each axis of the coating equipment returns to the initial position; Installing the ultra-mirror coating roller to the designated position of the equipment, and the surface of the ultra-mirror coating roller is integrated with a gradient pore structure, and the pore diameter is distributed in a specific pattern along the length direction of the roller shaft; Connecting the vertical injection pump to the feeding system of the coating roller, setting the flow accuracy and initializing the feeding system.

3. A method for pressure coating of outdoor photovoltaic panels as described in claim 1, characterized in that, The importing and loading of the multi-physical field model specifically further includes: Importing the three-dimensional transient flow field model for flow control, and the three-dimensional transient flow field model for flow control includes the injection pump feeding flow model, the coating roller gradient pore flow model and the leakage amount correction model; Calculating the theoretical flow rate through the injection pump feeding flow model, the coating roller gradient pore flow model simulates the flow characteristics of the colloid on the roller surface, and corrects the feeding flow rate in combination with the leakage amount correction model; Loading the PID parameters for pressure control, and the PID parameters include proportional gain, integral gain and derivative gain, and the PID parameters are used to accurately control the coating pressure; Loading the Kalman filter model, establishing a multi-parameter state space equation based on pressure, flow rate and displacement, and fusing the real-time data of the sensor through the Kalman filter model to predict and correct the system state during the coating process.

4. The method for pressure coating of outdoor photovoltaic panels according to claim 3, wherein The importing and loading of the multi-physical field model specifically further includes: Inputting the basic parameters of the photovoltaic module, and the basic parameters include the module size, surface flatness, and substrate material; according to the module type and coating requirements, setting the requirements for the target coating thickness and uniformity, and the requirements for the target coating thickness and uniformity are used as the control benchmark for the coating process.

5. A method for pressure coating of outdoor photovoltaic panels as claimed in claim 1, characterized in that, The on-site environment perception specifically further includes: Using the wind speed sensor and temperature and humidity sensor integrated in the equipment to collect outdoor environment data in real time; When the detected wind speed exceeds 3 m / s, it is marked as a high wind speed environment; when the humidity is greater than 70% or the temperature exceeds the range of -10°C to 55°C, it is marked as an abnormal temperature and humidity state; The surface of the photovoltaic panel is scanned in the whole area by a spectral reflectance sensor, and the reflection spectrum data is obtained and compared with the standard database to identify the type and adhesion degree of pollutants; Generate a pre-treatment instruction for the photovoltaic panel assembly with pollutants attached, and the pre-treatment instruction includes cleaning with a high-pressure air gun and chemical stripping; Use a laser rangefinder to measure the installation inclination angle and the height from the ground of the photovoltaic panel. When the height from the ground is less than or equal to 5 m, it is determined that in-situ coating is possible; collect the edge contour image of the assembly through a vision camera, identify obstacles in combination with the AI algorithm, and generate a personalized coating path including a safe avoidance area.

6. The method for pressure coating of outdoor photovoltaic panels according to claim 1, characterized in that, The pressure coating process is dynamically controlled, and specifically further includes: Start the injection pump, calculate the theoretical volume flow rate according to the linear velocity of the coating roller, and the theoretical volume flow rate is calculated by the following formula: Among them, Q p represents the theoretical volume flow rate, D p represents the diameter of the injection pump piston, L s represents the screw lead, n m represents the rotational speed of the servo motor; Calculate the actual flow rate based on the theoretical volume flow rate, and the actual flow rate is calculated by the following formula: Q p,actual = η v Q p Among them, Q p,actual represents the actual flow rate, and η v represents the volumetric efficiency; Combined with the leakage correction term ΔQ leak = k leak ·P 2 Dynamically adjust the actual feeding amount, where ΔQ leak represents the leakage amount, k leak represents the leakage coefficient, and P represents the system pressure; Apply an initial pressure to the coating roller, calculate the stress distribution through the Hertz contact model, form a capillary pressure gradient, drive the colloid to adaptively diffuse to the surface of the photovoltaic panel assembly and perform multi-axis linkage coating.

7. A method for pressure coating of outdoor photovoltaic panels according to claim 6, characterized in that, The multi-axis linkage coating specifically includes: The X-axis starts with an S-shaped acceleration and deceleration curve, and the contact pressure is fed back in real time through a pressure sensor. The Z-axis servo motor is linked to adjust the height of the coating roller to maintain the coating thickness deviation less than or equal to ±5 μm; The Y-axis steps according to a preset serpentine path, and the multi-axis motion decoupling is realized through the Jacobian matrix; Monitor the linear velocity of the coating roller and the coating thickness data in real time, adjust the flow rate of the injection pump through the PID controller. When the detected thickness deviation is greater than ±3%, trigger the dynamic compensation model to perform closed-loop correction of the coating thickness.

8. A method for pressure coating of outdoor photovoltaic panels as described in claim 1, characterized in that, The intelligent path execution and material control specifically further includes: Adopt a four-sided coating sequence optimization algorithm, with the goal of minimizing the cost function, and preferentially coat the edge area of the photovoltaic panel. Among them, the cost function is: Among them, J represents the total cost function of path optimization, which is used to measure the comprehensive error of the coating path. The path optimization is realized by minimizing the value of J. w1, w2, and w3 are all weight coefficients, and w1 + w2 + w3 = 1. Δxi, Δyi, and Δzi respectively represent the X-axis, Y-axis, and Z-axis displacement errors of the coating equipment when coating the i-th side (i = 1, 2, 3, 4); Monitor the distance between the coating roller and the edge of the assembly in real time. When the step distance of the Y-axis is less than the safety threshold, trigger the anti-collision logic, adjust the joint space coordinates, and automatically avoid obstacles; Dynamically adjust the micropore aperture of the coating roller according to the distance from the coating position to the center of the roller shaft, increase the aperture in the edge area of the assembly, and increase the feeding amount to compensate for the edge volatilization loss; The edge area of the assembly is the area where the distance from the coating position to the center of the roller shaft is greater than 100 mm; Establish a flow-rotation coupling equation, dynamically adjust the flow rate of the injection pump according to the real-time angular velocity of the coating roller. When the detected colloid diffusion rate in the edge area decreases, increase the feeding rate through the PID controller. The flow-rotation coupling equation is: Among them, Q represents the actual feeding volume flow rate, η v represents the volumetric efficiency, D represents the diameter of the coating roller shaft, L s represents the screw lead, represents, represents, ω represents the real-time angular velocity of the coating roller; Meanwhile, abnormal working conditions are handled during the coating process.

9. A method for pressure coating of outdoor photovoltaic panels as described in claim 8, characterized in that Handling abnormal working conditions during the coating process specifically includes: Setting a pressure overload threshold. When the pressure sensor detects that the real-time pressure exceeds the pressure overload threshold, the Z-axis emergency retraction mechanism is immediately triggered, the Z-axis lifting acceleration is calculated, and the Z-axis servo motor is driven to perform a lifting action to avoid damage caused by a hard collision between the coating roller and the component. Among them, the Z-axis lifting acceleration is calculated by the following formula: Among them, a z represents the Z-axis lift acceleration, F max represents the preset maximum allowable pressure, g represents the acceleration due to gravity, and m represents the mass of the coating head; The flatness of the substrate surface is monitored in real time by a laser rangefinder. When a thickness change of ±0.2 mm is detected, a dynamic deformation compensation model is started, and the Z-axis displacement correction amount is calculated. The Z-axis displacement correction amount is calculated by the following formula: Where, Δz represents the Z-axis displacement correction amount, θ represents the inclination angle between the coating roller and the surface of the photovoltaic panel, and Δh represents the thickness change amount; When the wind speed sensor detects that the wind speed is greater than 5 m / s, the coating operation is immediately paused, the guide rails of each axis of the gantry are locked by an electromagnetic lock, and a windproof cover is deployed to reduce the colloid drift rate; If the humidity sensor detects that the humidity is greater than 70%, the temperature is less than -10°C or greater than 55°C, then a thermal deformation compensation closed loop is started to adjust the power of the heating and cooling module.

10. A method for pressure coating of outdoor photovoltaic panels as described in claim 1, characterized in that, The verification of the coating effect specifically further includes: After coating is completed, a spectral reflectometer is used to perform a full-area scan of the coating on the surface of the photovoltaic panel, the light transmittance and the light scattering coefficient are detected, the spectral data before and after coating are compared, the light transmittance of the anti-reflection coating is controlled to be increased to more than 95%, and the light scattering coefficient is controlled within the range of 3-5%; A laser thickness gauge is used to randomly sample and detect the coating thickness. The single-point thickness measurement value needs to meet the target thickness range of 100-200 nm, and the deviation is less than or equal to ±5 μm; An infrared thermal imager is used to perform a thermal imaging scan of the surface of the component to detect abnormal temperature distribution areas. The abnormal temperature distribution area is an area with a temperature difference greater than 5°C from the adjacent area. When the local temperature exceeds the average temperature of the component by 15 K, it is marked as a hot spot risk area and needs to be repaired by secondary coating; The pressure, flow rate, path coordinates, and detection data during the coating process are stored in the database.

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