Photovoltaic module glass plate crack early warning method and device, electronic equipment and medium

Abstract

The application provides a photovoltaic module glass plate crack early warning method and device, electronic equipment and medium, and relates to the technical field of photovoltaic modules. The method comprises the following steps: obtaining target point cloud data obtained by scanning a target glass plate by a target scanner; wherein the target glass plate is a glass plate located on the surface of a photovoltaic module, and the target point cloud data comprises color point cloud data and temperature point cloud data; the color point cloud data is composed of color data of all pixel points corresponding to the target glass plate, and the temperature point cloud data is composed of temperature data and position data of all pixel points corresponding to the target glass plate; the area value of the crack center on the target glass plate is determined according to the color point cloud data, and the shape information of the crack on the target glass plate is determined according to the temperature point cloud data; the target early warning level is determined according to the area value of the crack center and / or the shape information of the crack, and early warning is performed according to the early warning mode corresponding to the target early warning level. The above-mentioned method improves the safety of the photovoltaic module.

Description

Technical Field

[0001] This application relates to the field of photovoltaic module technology, and in particular to a method, device, electronic equipment and medium for early warning of cracks in photovoltaic module glass panels. Background Technology

[0002] Solar power generation is convenient, efficient, and saves land resources, leading to the large-scale construction of photovoltaic (PV) power plants in arid and desert regions of Northwest China. However, PV modules within these plants are susceptible to damage from harsh weather conditions such as dryness, high temperatures, low rainfall, and sandstorms. In particular, the glass panels of these modules are prone to cracking due to severe weather and the glass material itself, which can cause localized hot spots, leading to panel burnout and even fires. Therefore, the impact of severe weather and the glass material on the normal operation of PV modules is evident.

[0003] Existing methods for early warning of glass panel cracks mostly rely on manual processes. Specifically, on-site personnel inspect, record, and report any cracks on the glass panels of each photovoltaic module. However, this method is inherently subjective; different personnel may describe and classify the same crack in different ways. Furthermore, when cracks appear simultaneously on different photovoltaic module glass panels, some cracks may not be detected in a timely manner.

[0004] Because existing technologies have poor early warning capabilities, photovoltaic modules can continue to operate even when the glass panels are severely cracked, which can easily lead to fires and poses a safety hazard. Summary of the Invention

[0005] This application provides a method, device, electronic device, and medium for early warning of glass panel cracks in photovoltaic modules, in order to solve the technical problem of poor safety caused by the continued operation of photovoltaic modules even when the glass panel is severely cracked.

[0006] According to a first aspect of this application, a method for early warning of cracks in a photovoltaic module glass panel is provided, comprising:

[0007] The target point cloud data is obtained by scanning a target glass plate with a target scanner; wherein the target glass plate is a glass plate located on the surface of a photovoltaic module, and the target point cloud data includes color point cloud data and temperature point cloud data. The color point cloud data is composed of the color data of all pixels corresponding to the target glass plate, and the temperature point cloud data is composed of the temperature data and position data of all pixels corresponding to the target glass plate.

[0008] The area value of the crack center on the target glass plate is determined based on the color point cloud data, and the shape information of the crack on the target glass plate is determined based on the temperature point cloud data.

[0009] The target warning level is determined based on the area value of the crack center and / or the shape information of the crack, and a warning is issued according to the warning method corresponding to the target warning level.

[0010] Optionally, determining the area value of the crack center on the target glass plate based on the color point cloud data includes:

[0011] Determine the number of specified color data in the color point cloud data; wherein, the specified color data is a preset RGB color value;

[0012] The quantity of the specified color data is determined as the area value of the crack center.

[0013] Optionally, determining the shape information of the crack on the target glass plate based on the temperature point cloud data includes:

[0014] Determine the quantity and location of specified temperature data in the temperature point cloud data;

[0015] The area value of the crack is determined based on the quantity of the specified temperature data, and the shape type information and location information of the crack are determined based on the location data of the specified temperature data.

[0016] Optionally, determining the target warning level based on the area value of the crack center and / or the shape information of the crack includes at least one of the following:

[0017] When the area of ​​the crack reaches a first preset area threshold, or when the area of ​​the crack center reaches a second preset area threshold, a first warning level is generated.

[0018] A second warning level is generated when the area value of the crack is between a first preset area threshold and a third preset area threshold, or when the area value of the crack center is between a second preset area threshold and a fourth preset area threshold; wherein the third preset area threshold is greater than the first preset area threshold, the fourth preset area threshold is greater than the second preset area threshold, and the second warning level is higher than the first warning level.

[0019] A third warning level is generated when the area value of the crack reaches a third preset area threshold, or when the area value of the crack center reaches a fourth preset area threshold; wherein the third warning level is higher than the second warning level, and the first preset area threshold, the second preset area threshold, the third preset area threshold and the fourth preset area threshold are all determined based on the shape type information of the crack.

[0020] Optionally, the warning method corresponding to the first warning level includes a first display method; the warning method corresponding to the second warning level includes a second display method; and the warning method corresponding to the third warning level includes a third display method and a message sending method.

[0021] The provision of issuing warnings according to the warning method corresponding to the target warning level includes at least one of the following:

[0022] The location information of the crack is displayed according to the first display method;

[0023] The location information of the crack is displayed according to the second display method;

[0024] The location information of the crack is displayed according to the third display method, and the location information of the crack is sent to the terminal; wherein the output font color provided by the first display method, the output font color provided by the second display method, and the output font color provided by the third display method are all different.

[0025] Optionally, after determining the area value of the crack center on the target glass plate based on the color point cloud data and determining the shape information of the crack on the target glass plate based on the temperature point cloud data, the method further includes:

[0026] By comparing the area values ​​of the crack center at different time points, a first comparison result is obtained; by comparing the shape information of the crack at different time points, a second comparison result is obtained.

[0027] Based on the first comparison result and / or the second comparison result, the motion information of the crack is obtained.

[0028] Optionally, the photovoltaic module includes a photovoltaic panel, which is a double-glass bifacial module. The double-glass bifacial module includes a first glass plate, a first adhesive layer, a silicon crystal plate, a second adhesive layer, and a second glass plate connected sequentially from top to bottom.

[0029] The target glass plate is the first glass plate and / or the second glass plate.

[0030] According to a second aspect of this application, a photovoltaic module glass panel crack early warning device is provided, comprising:

[0031] The acquisition module is used to acquire target point cloud data obtained by the target scanner scanning the target glass plate; wherein, the target glass plate is a glass plate located on the surface of the photovoltaic module, and the target point cloud data includes color point cloud data and temperature point cloud data. The color point cloud data is composed of the color data of all pixels corresponding to the target glass plate, and the temperature point cloud data is composed of the temperature data and position data of all pixels corresponding to the target glass plate.

[0032] The determination module is used to determine the area value of the crack center on the target glass plate based on the color point cloud data, and to determine the shape information of the crack on the target glass plate based on the temperature point cloud data;

[0033] The early warning module is used to determine the target early warning level based on the area value of the crack center and / or the shape information of the crack, and to issue an early warning according to the early warning method corresponding to the target early warning level.

[0034] According to a third aspect of this application, an electronic device is provided, comprising: at least one processor and a memory;

[0035] The memory stores computer-executed instructions;

[0036] The at least one processor executes computer execution instructions stored in the memory, causing the at least one processor to perform the photovoltaic module glass plate crack early warning method as described in the first aspect above.

[0037] According to a fourth aspect of this application, a computer-readable storage medium is provided, wherein computer-executable instructions are stored therein, which, when executed by a processor, are used to implement the photovoltaic module glass panel crack early warning method as described in the first aspect above.

[0038] According to a fifth aspect of this application, a computer program product is provided, including a computer program that, when executed by a processor, implements the photovoltaic module glass panel crack early warning method described in the first aspect.

[0039] This application provides a method, device, electronic device, and medium for early warning of cracks in photovoltaic module glass panels, comprising: acquiring target point cloud data obtained by scanning a target glass panel with a target scanner; wherein the target glass panel is a glass panel located on the surface of the photovoltaic module, and the target point cloud data includes color point cloud data and temperature point cloud data; the color point cloud data consists of the color data of all pixels corresponding to the target glass panel, and the temperature point cloud data consists of the temperature data and position data of all pixels corresponding to the target glass panel; determining the area value of the crack center on the target glass panel based on the color point cloud data, and determining the shape information of the crack on the target glass panel based on the temperature point cloud data; determining the target early warning level based on the area value of the crack center and / or the shape information of the crack, and issuing an early warning according to the early warning method corresponding to the target early warning level.

[0040] The color point cloud data and temperature point cloud data used in the above methods are characterized by high precision and high resolution, which can completely reproduce the size, shape type, and shape size of cracks in photovoltaic module glass panels in real-world online scenarios. Based on this, this application uses color point cloud data to determine the area value of the crack center on the target glass panel and temperature point cloud data to determine the shape information of the crack on the target glass panel. This method enables the extraction of various information about the crack, allowing for accurate and rapid crack warning and classification, thereby ensuring the safety of photovoltaic modules.

[0041] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this application, nor is it intended to limit the scope of this application. Other features of this application will become readily apparent from the following description. Attached Figure Description

[0042] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0043] Figure 1 A schematic flowchart illustrating a method for early warning of cracks in a photovoltaic module glass panel, provided in an embodiment of this application;

[0044] Figure 2 A schematic diagram of the operation of a target scanner provided in an embodiment of this application;

[0045] Figure 3 A flowchart illustrating another method for early warning of cracks in photovoltaic module glass panels provided in this application embodiment;

[0046] Figure 4 This is a schematic diagram of the structure of a photovoltaic module glass panel crack early warning device provided in an embodiment of this application;

[0047] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0048] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0049] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application.

[0050] Existing methods for early warning of glass panel cracks mostly rely on manual processes. Specifically, on-site personnel inspect, record, and report any cracks on the glass panels of each photovoltaic module. However, this method is inherently subjective; different personnel may describe and classify the same crack in different ways. Furthermore, when cracks appear simultaneously on different photovoltaic module glass panels, some cracks may not be detected in a timely manner.

[0051] Because existing technologies have poor early warning capabilities, photovoltaic modules can continue to operate even when the glass panels are severely cracked, which can easily lead to fires and poses a safety hazard.

[0052] To address the aforementioned technical problems, the overall inventive concept of this application is to provide a method for improving the safety of photovoltaic modules.

[0053] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0054] Example 1:

[0055] Figure 1 This is a flowchart illustrating a method for early warning of cracks in a photovoltaic module glass panel, provided as an embodiment of this application. Figure 1 As shown, the method in this embodiment includes the following steps:

[0056] S10. Obtain target point cloud data obtained by scanning the target glass plate with a target scanner; wherein, the target glass plate is a glass plate located on the surface of the photovoltaic module, and the target point cloud data includes color point cloud data and temperature point cloud data. The color point cloud data consists of the color data of all pixels corresponding to the target glass plate, and the temperature point cloud data consists of the temperature data and position data of all pixels corresponding to the target glass plate.

[0057] It should be understood that target point cloud data can be interpreted as crack feature point cloud data, and photovoltaic modules can refer to the photovoltaic modules at the target observation point within the area where the photovoltaic power station is located. These photovoltaic modules can consist of helical piles, photovoltaic panels, and photovoltaic supports; therefore, the surface of the photovoltaic module can refer to the components on the surface of the photovoltaic panel. The area where the photovoltaic power station is located is also called the photovoltaic field area.

[0058] like Figure 2As shown, the target scanner 100 is a 3D laser scanner, or a monitoring device. The terminal device 200 connected to the target scanner 100 can be a computer or similar device, used to acquire target point cloud data and store and analyze that data. Power is supplied to the terminal device 200 by the power supply 300, and the terminal device 200 can also act as a power source to supply power to the target scanner 100.

[0059] Optionally, the target scanner 100 includes at least one of the following: an RGB device (or RGB camera, color camera), an infrared emitter, and a 3D depth sensor; wherein the 3D depth sensor is composed of three lenses (i.e., infrared cameras) of an infrared camera.

[0060] For example, in a photovoltaic panel, crystalline silicon cells in the silicon layer are bonded to a glass plate. The thickness of the glass plate is typically between 3.2mm and 8mm, and the thickness of the crystalline silicon cells can be between 1.5μm and 2.0μm. The glass plate can be made of a transparent material, allowing an infrared camera to pass through the glass plate and illuminate the silicon layer. Furthermore, the monitoring instrument modulates its RGB pixels to A×B and its infrared pixels to C×D, with a detection range of 0.5-5m. This embodiment does not specifically limit the values ​​of A, B, C, and D. This embodiment, by illuminating the photovoltaic panel from the side with the monitoring instrument, can measure not only the lateral development of cracks on the glass plate surface (i.e., cross-section) (e.g., width, length), but also the longitudinal development of cracks on the side of the glass plate (e.g., depth).

[0061] In this method, the hardware design of this embodiment mainly includes: photovoltaic modules, a 3D laser scanner, and a computer. The computer runs computer processing software, which can be open-source software (e.g., Visual Studio). This software calls the OpenCV library (or other libraries, which are not specifically limited in this embodiment) and sets scanning parameters to collect crack feature point cloud data at designated observation points. The collected crack feature point cloud data is then sent to third-party software for analysis to determine various crack feature data (e.g., crack size, crack shape type, length of each texture in the crack, depth of each texture in the crack, length of each texture in the crack at a future time, depth of each texture in the crack at a future time, etc.), the corresponding warning level of the crack, and the corresponding processing method, thereby improving the accuracy and comprehensiveness of the analysis.

[0062] Furthermore, this application can also increase the accuracy of crack early warning by setting the computer visualization software to display only point cloud data with crack shape features or point cloud data in white color; it can also improve the accuracy of crack early warning by using third-party software to perform hazard classification and quickly observe point cloud data.

[0063] S20. Determine the area value of the crack center on the target glass plate based on the color point cloud data, and determine the shape information of the crack on the target glass plate based on the temperature point cloud data.

[0064] It should be understood that the area value at the center of the crack and the shape information of the crack can both reflect the characteristics of the crack.

[0065] S30. Determine the target warning level based on the area value of the crack center and / or the shape information of the crack, and issue a warning according to the warning method corresponding to the target warning level.

[0066] The embodiments of this application do not specifically limit the number of target warning levels; it can be 2, 3, 4, etc.

[0067] The color point cloud data and temperature point cloud data used in the above methods are characterized by high precision and high resolution, which can completely reproduce the size, shape type, and shape size of cracks in photovoltaic module glass panels in real-world online scenarios. Based on this, the embodiments of this application determine the area value of the crack center on the target glass panel through color point cloud data and determine the shape information of the crack on the target glass panel through temperature point cloud data. This enables the extraction of various information about the crack, allowing for accurate and rapid crack warning and classification, thereby ensuring the safety of photovoltaic modules.

[0068] In one possible implementation, step S20, determining the area value of the crack center on the target glass plate based on the color point cloud data, includes the following steps:

[0069] S201. Determine the number of specified color data in the color point cloud data; wherein, the specified color data are preset RGB color values.

[0070] In this embodiment of the application, the specified color data is white, which can refer to the RGB color value (255, 225, 255), or other color values ​​that are similar to this color value. This embodiment of the application does not specifically limit the range of the color value or the number of color values.

[0071] S202. The quantity of specified color data is determined as the area value of the crack center.

[0072] It should be understood that the quantity of specified color data refers to the number of pixels possessing that specified color data. This application does not specifically limit the conversion method for transforming the number of pixels into an area value. If the glass plate cracks due to an impact, the center of the crack is referred to as the impact center.

[0073] This application embodiment can accurately identify the area value of the crack center by specifying the number of color data, providing data support for accurately determining the warning level corresponding to the crack.

[0074] In one possible implementation, step S20 involves determining the shape information of the crack on the target glass plate based on temperature point cloud data, including the following steps:

[0075] S203. Determine the quantity and location of specified temperature data in the temperature point cloud data.

[0076] S204. Determine the area value of the crack based on the quantity of specified temperature data, and determine the shape type information and location information of the crack based on the location data of the specified temperature data.

[0077] In this embodiment, the crack shape information includes: crack area value, crack shape type information, crack location information, etc. Crack shape type information includes bullseye, star, long crack, and mixed type. Bullseye cracks are mainly caused by the glass plate being struck by small stones; star cracks are mainly caused by impacts from external objects; long cracks are mainly caused spontaneously by material and environmental factors; and mixed type cracks are mainly formed because the crack continues to develop after the glass plate has been impacted.

[0078] The collected point cloud data is analyzed using third-party software. By combining infrared and color cameras, the four types of shapes mentioned above are set as point cloud recognition objects, with color values ​​of white (255, 225, 255). Since there is refraction and increased point cloud data on the cross-section when the infrared camera illuminates the crack on the glass plate, the crack is identified by the infrared camera, while the impact center is identified by the color camera.

[0079] This application embodiment can analyze temperature point cloud data to obtain information such as the area value of the crack, the shape and type of the crack, and the location information of the crack, providing data support for accurately determining the warning level corresponding to the crack.

[0080] In one possible implementation, in step S30, the target warning level is determined based on the area value of the crack center and / or the shape information of the crack, including at least one of the following:

[0081] The first item is to generate a first warning level when the area of ​​the crack reaches a first preset area threshold, or when the area of ​​the crack center reaches a second preset area threshold.

[0082] In this embodiment, the area value of the crack can be understood as crack point cloud data, and the area value of the crack center can be understood as white point cloud data. The first preset area threshold is denoted as N, and the second preset area threshold is denoted as Q. The first warning level is also referred to as the first-level warning level.

[0083] The second step involves generating a second warning level when the area of ​​the crack falls between the first and third preset area thresholds, or when the area at the crack center falls between the second and fourth preset area thresholds. Where the third preset area threshold is greater than the first, the fourth preset area threshold is greater than the second, and the second warning level is higher than the first. The third preset area threshold is denoted as M, and the fourth preset area threshold is denoted as K. The second warning level is also referred to as a level-two warning level. The N / M value is unrelated to the Q / K value.

[0084] Thirdly, a third warning level is generated when the area of ​​the crack reaches a third preset area threshold, or when the area of ​​the crack center reaches a fourth preset area threshold. The third warning level is higher than the second warning level, and may also be referred to as a level-three warning level.

[0085] For example, considering the four defined crack shapes, when the total number of crack point cloud data reaches N, or the white color value reaches Q (Q value is less than 1cm)... 2 When the number of crack point cloud data reaches the range of N to M, and the white color value reaches the range of Q to K, it indicates that the glass plate is damaged, and the adhesive layer (or film) connected to the glass plate is also damaged, and a blue warning is issued. In this embodiment, damaged components in the photovoltaic panel can be replaced in a timely manner later. When the number of crack point cloud data reaches the value M, and the area formed by the white color value reaches the value K (where K > 1 cm), it indicates that the glass plate is damaged. 2 When a red alert is triggered, it indicates that the photovoltaic module's glass panel is severely damaged, and the silicon layer is also damaged. This situation increases the risk of fire, triggering a red alert. For safety reasons, this embodiment allows for power shutdown, fire extinguishing, and timely replacement of the photovoltaic panel via smart devices.

[0086] This embodiment can pre-set the visualization software to display only the point cloud data of the crack and the white point cloud data, and pre-set four crack development shapes in the third-party software, so as to effectively identify cracks in the glass panel of the photovoltaic module in practice. The real-time observed data is compared with the threshold (e.g., N, M, Q, K values) for the occurrence of warning signals to obtain the comparison results, and then the specific level of the warning level is determined based on the comparison results.

[0087] It should be noted that the first preset area threshold, the second preset area threshold, the third preset area threshold, and the fourth preset area threshold are all determined based on the shape and type information of the crack.

[0088] For example, the preset area thresholds for the bullseye shape are N1, Q1, M1, and K1, respectively; the preset area thresholds for the star shape are N2, Q2, M2, and K2, respectively; the preset area thresholds for the long crack shape are N3, Q3, M3, and K3, respectively; and the preset area thresholds for the comprehensive shape are N4, Q4, M4, and K4, respectively.

[0089] In this application embodiment, the first warning level is used to indicate that the glass plate is damaged, but the adhesive layer is not damaged; the second warning level is used to indicate that the adhesive layer is damaged; and the third warning level is used to indicate that the silicon layer is damaged.

[0090] In the embodiments of this application, the setting of different warning levels can quickly identify the damage caused by glass plate cracks, thereby providing targeted treatment methods and ultimately improving the safety of safety components.

[0091] In one possible implementation, the warning method corresponding to the first warning level includes a first display method; the warning method corresponding to the second warning level includes a second display method; and the warning method corresponding to the third warning level includes a third display method and a message sending method.

[0092] In step S30, an early warning is issued according to the warning method corresponding to the target warning level, including at least one of the following:

[0093] The first item is to display the location information of the crack according to the first display method.

[0094] The second item is to display the location information of the crack according to the second display method.

[0095] The third item is to display the location information of the crack according to the third display method and send the location information of the crack to the terminal; wherein the output font colors provided by the first display method, the second display method, and the third display method are all different.

[0096] Specifically, this embodiment pre-sets the warning levels to include: Level 1, Level 2, and Level 3. Level 1 corresponds to a yellow warning, Level 2 to a blue warning, and Level 3 to a red warning. Different color warnings can be used to set the font color of the crack location information, the background color of the corresponding icon for the photovoltaic module, or the light color of the indicator light for the corresponding photovoltaic module.

[0097] For example, a yellow warning signal is issued when the number of cracked point cloud data reaches N or the number of white point cloud data reaches Q; a blue warning signal is issued when the number of cracked point cloud data is between N and M or the number of white point cloud data is between Q and K; and a red warning signal is issued when the number of cracked point cloud data reaches M and the number of white point cloud data reaches K.

[0098] For example, if the number of crack point cloud data is within the value N, it indicates that the glass plate is damaged, and the corresponding warning level for the glass plate is a Level 1 warning. If the number of crack point cloud data is between N and M, it indicates that the glass plate and film are damaged, and the corresponding warning level for the glass plate is a Level 2 warning. When the number of crack point cloud data reaches the value M, it indicates that the silicon wafer is damaged, and the corresponding warning level for the glass plate is a Level 3 warning.

[0099] When a computer monitors cracks in the glass panels of multiple photovoltaic modules, this embodiment can display warnings for all cracks using a scroll bar when issuing warnings for different cracks. Alternatively, it can display multiple cracks simultaneously on a single interface by flashing the corresponding icons for each photovoltaic module. This embodiment can be customized according to actual needs, and this embodiment does not impose any specific limitations on it.

[0100] Before sending the location information of the crack to the terminal, this embodiment of the application can bind the name, location, and other information of the photovoltaic module with the mobile phone number of the corresponding maintenance personnel to obtain a corresponding relationship table. The mobile phone number of the maintenance personnel can be found through the corresponding relationship table. Then, when the crack of the photovoltaic module glass panel reaches the level three warning, the computer can automatically send a text message to the corresponding mobile phone number through software. The text message content can include the location information of the photovoltaic module, various information about the crack of the photovoltaic module glass panel, images, etc. This embodiment of the application does not specifically limit the content of the text message.

[0101] This application embodiment can quickly and accurately determine the warning level corresponding to the crack through different warning signals, and then provide corresponding solutions. This can ensure the safety of photovoltaic modules and avoid safety hazards caused by the continued operation of photovoltaic modules in cases of poor safety. After the operation and maintenance personnel resolve the safety hazards, the photovoltaic power station can be effectively maintained in a stable operating state for a long time.

[0102] In one possible implementation, after determining the area value of the crack center on the target glass plate based on color point cloud data and determining the shape information of the crack on the target glass plate based on temperature point cloud data, the method further includes the following steps:

[0103] S40. Compare the area values ​​of the crack center at different time points to obtain the first comparison result. Compare the shape information of the crack at different time points to obtain the second comparison result.

[0104] S50. Based on the first comparison result and / or the second comparison result, obtain the motion information of the crack.

[0105] In this embodiment, the crack motion information can refer to changes in crack length, changes in crack depth, etc. Since the crack contains multiple textures, the crack length change can refer to changes in texture length, and the crack depth change can refer to changes in texture depth. This crack motion information is used to predict the future moment when the photovoltaic module glass panel will shatter, and then to replace the photovoltaic module glass panel before that future moment.

[0106] The photovoltaic module glass panel crack early warning method provided in this application studies a quantitative method for early warning of photovoltaic module glass panel explosion caused by severe weather and glass material. This method is economical, convenient and efficient, which can greatly improve the measurement efficiency and accuracy of predicting photovoltaic module glass panel explosion, effectively avoid fire accidents in photovoltaic fields, and provide technical support for future monitoring of photovoltaic module glass panel explosion early warning methods.

[0107] In one possible implementation, the photovoltaic module includes a photovoltaic panel, which is a double-glass bifacial module. The double-glass bifacial module includes a first glass plate, a first adhesive layer, a silicon crystal plate, a second adhesive layer, and a second glass plate connected sequentially from top to bottom; the target glass plate is the first glass plate and / or the second glass plate.

[0108] It should be understood that the double-glass bifacial module is a monocrystalline silicon P-type double-glass module. This double-glass module includes: a first glass plate, the bottom of which is fixedly connected to the top of a first adhesive layer; the bottom of the first adhesive layer is fixedly connected to the top of a silicon crystal plate; the bottom of the silicon crystal plate is fixedly connected to the top of a second adhesive layer; and the bottom of the second adhesive layer is fixedly connected to the top of a second glass plate.

[0109] The photovoltaic field can use monocrystalline silicon P-type double-sided double-glass modules. The structure of this module is 5 layers: the two outermost layers are glass plates, the two innermost layers are films, and the middle layer is a silicon wafer. Since glass plate breakage can easily lead to cross-sectional damage and also to depth damage, based on the glass plate thickness of 3mm-8mm, when the monitoring instrument observes crack point cloud data in the film area, a red warning is immediately issued. It can be seen that the embodiments of this application can effectively identify the depth of cracks.

[0110] This application provides a method for early warning of cracks in photovoltaic module glass panels. Using a 3D laser scanner, the method sets the crack shape parameters of the photovoltaic module glass panel via a computer program. Then, it collects point cloud data of the crack on the surface of the photovoltaic module glass panel and point cloud data of the crack on the thickness surface of the photovoltaic module glass panel. The entire data is transmitted to third-party software. Based on the point cloud data reflecting the crack size set in the program, the crack is classified into different hazard levels. When the developing crack causes localized hot spots on the photovoltaic module, a red warning signal is immediately issued on the page through the third-party software. Simultaneously, a message sending mechanism can be set in the third-party software to send a warning SMS to the mobile phone number of on-duty personnel. This method requires simple hardware, is easy to use, and can accurately measure the development trend of cracks on the photovoltaic module glass panel and predict the moment when a fire may occur. Therefore, the photovoltaic module can be replaced before the expected fire time, effectively preventing fires and improving the safety of the photovoltaic module.

[0111] Based on the above embodiments, the technical solution of this application will be described in more detail below with reference to several specific embodiments.

[0112] Figure 3 This is a schematic flowchart illustrating another method for early warning of cracks in photovoltaic module glass panels provided in an embodiment of this application. Figure 3 As shown, the method in this embodiment includes the following steps:

[0113] S31. Debug the equipment.

[0114] S32. Monitor photovoltaic modules.

[0115] S33. Save the monitoring data.

[0116] S34. Analyze and monitor data through third-party clients / mobile devices.

[0117] S35. Implement hazard factor classification.

[0118] S36. Send a warning signal.

[0119] As described in steps S31 to S36, the working process of this embodiment is as follows: First, the scanner and computer are debugged. With power on, the OpenCV library in open-source software (e.g., Visual Studio software) is called to execute the program. According to the size of the photovoltaic panel in the photovoltaic module, the scanning range (x, y, z) is set by the computer program to control the scanner to start, collect, and save point cloud data. After the data is obtained, a third-party software is used to perform hazard classification analysis and display it in real time in the third-party software. That is, when the area value of the crack reaches the threshold of a certain warning level and / or the area value of the crack center reaches the threshold of a certain warning level, the software automatically issues a warning signal corresponding to the warning level.

[0120] To improve the effectiveness of the data, the point cloud data obtained by the monitoring instrument in this embodiment can be preprocessed in third-party software (the preprocessing includes filtering and noise reduction to remove irrelevant noise in the point cloud data). After the preprocessing is completed, the glass plate surface observation and depth observation are performed. The warning level corresponding to the crack is determined in the glass plate surface observation, and the crack depth development and specific damaged components are determined through depth observation.

[0121] This application provides the following two extensions:

[0122] I. This method has the advantage of providing early warning of fires caused by cracks in the glass panels of photovoltaic modules. The imaging data is relatively accurate. In order to expand the scanning range, this embodiment can set up multiple observation points and use multiple scanners to observe at multiple observation points to achieve the effect of moving from point to area. This enables real-time monitoring of the photovoltaic field, allowing for early detection of cracks and focused observation, thereby achieving the effect of fire prevention.

[0123] Second, this embodiment can also achieve a larger scanning range of three-dimensional laser scanning by controlling drones. By controlling the drone to fly at low altitudes to scan, the point cloud data of cracks in the photovoltaic module glass panel can be saved. The collected data can be processed and controlled by a computer, which can achieve economic, convenient and efficient results.

[0124] In the above method, the three-dimensional point cloud data of the crack shape obtained by the infrared and depth cameras is added to the point cloud data by the color lens on the monitoring instrument that integrates infrared, color and depth cameras. Therefore, in this embodiment, the monitoring instrument can obtain a set of spatial three-dimensional color point cloud data that is the same as the physical object of the crack.

[0125] Example 3:

[0126] Figure 4This is a schematic diagram of a photovoltaic module glass panel crack early warning device provided in an embodiment of this application. The device in this embodiment can be in the form of software and / or hardware. Figure 4 As shown, the photovoltaic module glass panel crack early warning device provided in this embodiment includes: an acquisition module 41, a determination module 42, and an early warning module 43. Wherein:

[0127] The acquisition module 41 is used to acquire target point cloud data obtained by the target scanner scanning the target glass plate; wherein, the target glass plate is a glass plate located on the surface of the photovoltaic module, and the target point cloud data includes color point cloud data and temperature point cloud data. The color point cloud data consists of the color data of all pixels corresponding to the target glass plate, and the temperature point cloud data consists of the temperature data and position data of all pixels corresponding to the target glass plate.

[0128] The determination module 42 is used to determine the area value of the crack center on the target glass plate based on the color point cloud data, and to determine the shape information of the crack on the target glass plate based on the temperature point cloud data.

[0129] The early warning module 43 is used to determine the target early warning level based on the area value of the crack center and / or the shape information of the crack, and to issue an early warning according to the early warning method corresponding to the target early warning level.

[0130] In one possible implementation, the determining module 42 is further used for:

[0131] Determine the number of specified color data in the color point cloud data; where the specified color data are preset RGB color values.

[0132] The quantity of specified color data is determined as the area value at the center of the crack.

[0133] In one possible implementation, the determining module 42 is further used for:

[0134] Determine the quantity and location of specified temperature data in the temperature point cloud data.

[0135] The area value of the crack is determined based on the quantity of specified temperature data, and the shape type and location information of the crack are determined based on the location data of the specified temperature data.

[0136] In one possible implementation, the early warning module 43 is also used for:

[0137] A first warning level is generated when the area of ​​the crack reaches a first preset area threshold, or when the area of ​​the crack center reaches a second preset area threshold.

[0138] A second warning level is generated when the area value of the crack is between the first preset area threshold and the third preset area threshold, or when the area value of the crack center is between the second preset area threshold and the fourth preset area threshold; wherein, the third preset area threshold is greater than the first preset area threshold, the fourth preset area threshold is greater than the second preset area threshold, and the second warning level is higher than the first warning level.

[0139] A third warning level is generated when the area of ​​the crack reaches the third preset area threshold, or when the area of ​​the crack center reaches the fourth preset area threshold; wherein the third warning level is higher than the second warning level, and the first preset area threshold, the second preset area threshold, the third preset area threshold and the fourth preset area threshold are all determined according to the shape and type information of the crack.

[0140] In one possible implementation, the warning method corresponding to the first warning level includes a first display method; the warning method corresponding to the second warning level includes a second display method; and the warning method corresponding to the third warning level includes a third display method and a message sending method. The warning module 43 is also used for:

[0141] The location information of the crack is displayed according to the first display method.

[0142] The location information of the crack is displayed according to the second display method.

[0143] The location information of the crack is displayed according to the third display method, and the location information of the crack is sent to the terminal; wherein, the output font color provided by the first display method, the output font color provided by the second display method, and the output font color provided by the third display method are all different.

[0144] In one possible implementation, after determining the area of ​​the crack center on the target glass plate based on color point cloud data and determining the shape information of the crack on the target glass plate based on temperature point cloud data, the photovoltaic module glass plate crack early warning device is further used for:

[0145] By comparing the area values ​​of the crack center at different time points, a first comparison result is obtained; by comparing the shape information of the crack at different time points, a second comparison result is obtained.

[0146] Based on the first comparison result and / or the second comparison result, the motion information of the crack is obtained.

[0147] In one possible implementation, the photovoltaic module includes a photovoltaic panel, which is a double-glass bifacial module. The double-glass bifacial module includes a first glass plate, a first adhesive layer, a silicon crystal plate, a second adhesive layer, and a second glass plate connected sequentially from top to bottom; the target glass plate is the first glass plate and / or the second glass plate.

[0148] The photovoltaic module glass plate crack early warning device provided in this embodiment can be used to execute the photovoltaic module glass plate crack early warning method provided in any of the above method embodiments. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0149] It should be noted that the user information and data involved in this application (including but not limited to data used for analysis, stored data, and displayed data) are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use, and processing of the relevant data must comply with the relevant laws, regulations, and standards of the relevant countries and regions, and corresponding operation portals are provided for users to choose to authorize or refuse.

[0150] In other words, the collection, storage, use, processing, transmission, provision, and disclosure of user personal information involved in the technical solution of this application all comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0151] According to embodiments of this application, this application also provides an electronic device and a readable storage medium.

[0152] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device includes a receiver 50, a transmitter 51, at least one processor 52, and a memory 53. The electronic device composed of the above components can be used to implement the above-described specific embodiments of this application, which will not be described in detail here.

[0153] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the methods described above.

[0154] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the various steps in the methods described above.

[0155] Various embodiments of the systems and technologies described above in this application can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include: implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0156] The program code used to implement the methods of this application may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing device, such that when executed by the processor or controller, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or electronic device.

[0157] In the context of this application, a computer-readable storage medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium can be a machine-readable signal medium or a machine-readable storage medium. A computer-readable storage medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of computer-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0158] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0159] The systems and technologies described herein can be implemented in computing systems that include back-end components (e.g., as data electronic devices), or computing systems that include middleware components (e.g., application electronic devices), or computing systems that include front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and technologies described herein), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0160] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this application can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this application can be achieved, and this is not limited herein.

[0161] The specific embodiments described above do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the principles of this application should be included within the scope of protection of this application.

Claims

1. A method for early warning of glass panel cracks of a photovoltaic module, characterized in that, include: The target point cloud data is obtained by scanning a target glass plate with a target scanner; wherein the target glass plate is a glass plate located on the surface of a photovoltaic module, and the target point cloud data includes color point cloud data and temperature point cloud data. The color point cloud data is composed of the color data of all pixels corresponding to the target glass plate, and the temperature point cloud data is composed of the temperature data and position data of all pixels corresponding to the target glass plate. Determining the area value of the crack center on the target glass plate based on the color point cloud data includes: determining the number of specified color data in the color point cloud data; wherein the specified color data is a preset RGB color value; and determining the number of specified color data as the area value of the crack center; determining the shape information of the crack on the target glass plate based on the temperature point cloud data includes: determining the number and location data of specified temperature data in the temperature point cloud data; determining the area value of the crack based on the number of specified temperature data, and determining the shape type information and location information of the crack based on the location data of the specified temperature data; The target warning level is determined based on the area value of the crack center and / or the shape information of the crack, and a warning is issued according to the warning method corresponding to the target warning level.

2. The method according to claim 1, characterized in that, Determining the target warning level based on the area value of the crack center and / or the shape information of the crack includes at least one of the following: When the area of ​​the crack reaches a first preset area threshold, or when the area of ​​the crack center reaches a second preset area threshold, a first warning level is generated. A second warning level is generated when the area value of the crack is between a first preset area threshold and a third preset area threshold, or when the area value of the crack center is between a second preset area threshold and a fourth preset area threshold; wherein the third preset area threshold is greater than the first preset area threshold, the fourth preset area threshold is greater than the second preset area threshold, and the second warning level is higher than the first warning level. A third warning level is generated when the area value of the crack reaches a third preset area threshold, or when the area value of the crack center reaches a fourth preset area threshold; wherein the third warning level is higher than the second warning level, and the first preset area threshold, the second preset area threshold, the third preset area threshold and the fourth preset area threshold are all determined based on the shape type information of the crack.

3. The method according to claim 2, characterized in that, The warning method corresponding to the first warning level includes a first display method; the warning method corresponding to the second warning level includes a second display method; the warning method corresponding to the third warning level includes a third display method and a message sending method. The provision of issuing warnings according to the warning method corresponding to the target warning level includes at least one of the following: The location information of the crack is displayed according to the first display method; The location information of the crack is displayed according to the second display method; The location information of the crack is displayed according to the third display method, and the location information of the crack is sent to the terminal; wherein the output font color provided by the first display method, the output font color provided by the second display method, and the output font color provided by the third display method are all different.

4. The method according to claim 1, characterized in that, After determining the area value of the crack center on the target glass plate based on the color point cloud data, and determining the shape information of the crack on the target glass plate based on the temperature point cloud data, the method further includes: By comparing the area values ​​of the crack center at different time points, a first comparison result is obtained; by comparing the shape information of the crack at different time points, a second comparison result is obtained. Based on the first comparison result and / or the second comparison result, the motion information of the crack is obtained.

5. The method according to claim 1, characterized in that, The photovoltaic module includes a photovoltaic panel, and the photovoltaic panel is a double-glass bifacial module. The double-glass bifacial module includes a first glass plate, a first adhesive layer, a silicon crystal plate, a second adhesive layer, and a second glass plate connected in sequence from top to bottom. The target glass plate is the first glass plate and / or the second glass plate.

6. A photovoltaic module glass panel crack early warning device, characterized in that, include: The acquisition module is used to acquire target point cloud data obtained by the target scanner scanning the target glass plate; wherein, the target glass plate is a glass plate located on the surface of the photovoltaic module, and the target point cloud data includes color point cloud data and temperature point cloud data. The color point cloud data is composed of the color data of all pixels corresponding to the target glass plate, and the temperature point cloud data is composed of the temperature data and position data of all pixels corresponding to the target glass plate. The determination module is used to determine the area value of the crack center on the target glass plate based on the color point cloud data, and to determine the shape information of the crack on the target glass plate based on the temperature point cloud data; The early warning module is used to determine the target early warning level based on the area value of the crack center and / or the shape information of the crack, and to issue an early warning according to the early warning method corresponding to the target early warning level; The determining module is specifically used to determine the quantity of specified color data in the color point cloud data; wherein the specified color data is a preset RGB color value; the quantity of the specified color data is determined as the area value of the crack center; it is also specifically used to determine the quantity and location data of specified temperature data in the temperature point cloud data; the area value of the crack is determined according to the quantity of the specified temperature data, and the shape type information and location information of the crack are determined according to the location data of the specified temperature data.

7. An electronic device, characterized in that, include: At least one processor and memory; The memory stores computer-executed instructions; The at least one processor executes computer execution instructions stored in the memory, causing the at least one processor to perform the photovoltaic module glass plate crack early warning method as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the photovoltaic module glass plate crack early warning method as described in any one of claims 1 to 5.

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