Photovoltaic cell glue path printing detection equipment and photovoltaic cell glue path printing detection method

Abstract

The invention relates to the technical field of photovoltaic cells, and discloses photovoltaic cell glue path printing detection equipment and a photovoltaic cell glue path printing detection method. In the invention, the lighting assembly comprises the first light source and the second light source of different types of light sources, so that the advantages of the different types of light sources can be combined for photographing and imaging in the imaging process, thereby improving the glue path imaging quality; the situation of glue path detection misjudgment caused by too small glue path gray scale difference value due to imaging shadow of a single-type light source is prevented; meanwhile, the optical imaging assembly is additionally provided with four cameras from a single camera, one camera corresponds to one quadrant of the battery piece, and each camera can capture more details of the battery piece in the imaging process, so that the imaging precision and effect are improved, the glue path analysis and detection precision is further improved, the misjudgment rate of battery piece printing defects is reduced, and the product quality is improved. The labor cost is saved, and the loss of cell picking during cell detection is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of photovoltaic cells, and particularly relates to a photovoltaic cell glue path printing detection device and a photovoltaic cell glue path printing detection method. Background Art

[0002] With the development of the photovoltaic industry, the requirements for product quality and efficiency are gradually increasing. Automated Optical Inspection (AOI) can, during the production process, use an optical imaging system to obtain an image of the surface of an object, and then analyze the image through image processing algorithms and pattern recognition technologies, thereby automatically detecting various defects existing on the surface of the object, with prominent technical advantages. In the photovoltaic industry, back-contact cells are widely used in various photovoltaic systems due to their unique structure and performance advantages; in the production of back-contact cells, a printing process directly affects the performance and quality of the cells. If defects such as uneven glue paths and printing offsets occur, it is easy to cause problems such as short circuits and power attenuation of the cell wafers, affecting the stability of photovoltaic modules.

[0003] However, the inventor has found that currently, for the first-pass printing detection of back-contact cells, single-camera and single-type light source imaging is mostly used. This method has obvious drawbacks. The imaging is prone to generating shadows, the gray-scale difference between the glue path and the non-printed glue area is small, and the imaging effect on transparent glue is poor, making it difficult to accurately detect defects. And printing defects will cause short circuits in the cells, threatening product quality and safety. Therefore, developing equipment and methods suitable for the first-pass printing detection of back-contact cells to eliminate imaging shadows and improve the detection effect has become an urgent task in the industry. Summary of the Invention

[0004] The purpose of the embodiments of the present invention is to provide a photovoltaic cell glue path printing detection device and a photovoltaic cell glue path printing detection method, so as to eliminate imaging shadows and improve the imaging effect during the first-pass AOI detection of back-contact cells, thereby improving the detection accuracy and efficiency.

[0005] To solve the above technical problems, the embodiments of the present invention provide a photovoltaic cell glue path printing detection device, including: an illumination component, an optical imaging component, and an image processing component; the illumination component includes a first light source and a second light source; the first light source and the second light source are light sources of different types; the first light source is disposed in close contact with the optical imaging component, and the second light source is disposed around the optical imaging component; the optical imaging component includes four cameras, and the four cameras respectively correspond to the four quadrants of the battery wafer to be measured; the optical imaging component is connected to the image processing component, and the image processing component is used to perform glue path detection and analysis on the image of the battery wafer to be measured captured by the optical imaging component.

[0006] An embodiment of the present invention further provides a method for detecting the glue path printing of a photovoltaic cell, which is applied to the above-mentioned photovoltaic cell glue path printing detection device. The method includes: after the lighting component is started, the optical imaging component takes a picture of the battery cell to be measured; the optical imaging component sends the captured image of the battery cell to be measured to the image processing component, and the image processing component performs glue path detection and analysis on the image of the battery cell to be measured.

[0007] In the embodiment of the present invention, since the lighting component includes a first light source and a second light source of different types of light sources, during the imaging process, it is possible to combine the advantages of different types of light sources for taking pictures and imaging, thereby improving the quality of the glue path imaging, preventing the glue path detection misjudgment caused by too small a glue path gray difference due to the imaging shadow of a single type of light source, and there is no need to add other devices for supplementary lighting during the imaging process, improving the efficiency of the glue path detection; at the same time, the optical imaging component is increased from a single camera to four cameras, and one camera corresponds to one quadrant of the battery cell. During the imaging process, each camera can capture more details of the battery cell, thereby improving the accuracy and effect of the imaging, further improving the accuracy of the glue path analysis and detection, reducing the misjudgment rate of the printing defects of the battery cell, saving labor costs, and reducing the loss of the battery cell detection and picking.

[0008] In addition, the first light source is a coaxial light source; the second light source is a planar array light source; the number of the first light sources is the same as the number of cameras in the optical imaging component, and the lens of each camera is attached to one of the first light sources. The light emitted by each first light source and the optical axis of the attached camera are on the same axis; the four cameras in the optical imaging component are at the same horizontal height, and the four cameras simultaneously take pictures of the battery cell to be measured each time.

[0009] In addition, the pixel number of the image sensor of the camera in the optical imaging component is 20 million to 36 million.

[0010] In addition, the photovoltaic cell glue path printing detection device further includes a mechanical motion component; the mechanical motion component is provided with a placement area for the battery cell to be measured and is connected to the optical imaging component; the mechanical motion component controls the movement of the battery cell to be measured and / or the optical imaging component according to the position of the battery cell to be measured captured by the optical imaging component.

[0011] In addition, the optical imaging component sends the captured image of the battery cell to be measured to the image processing component, and the image processing component performs glue path detection and analysis on the image of the battery cell to be measured, including: the optical imaging component sends the initial images of the battery cell to be measured captured by the four cameras to the image processing component; the initial images are the original images of the battery cell to be measured captured by each camera; the image processing component receives the four initial images, splices the four initial images, and then performs glue path annotation and detection analysis on the spliced image.

[0012] In addition, the splicing process of the four initial images includes: according to the positions of the four quadrants corresponding to the four cameras, splicing the four initial images captured by the four cameras according to the corresponding positions to obtain a complete image of the battery cell to be measured.

[0013] In addition, calculate the gray value of the complete image, and mark the area in the complete image where the gray value is greater than the preset gray threshold to obtain a marked image.

[0014] In addition, the glue path annotation and detection analysis of the spliced image includes: calculating the glue path coverage rate of the marked image; when the glue path coverage rate is greater than the first preset coverage rate threshold, the detection result of the battery cell to be measured is qualified.

[0015] In addition, the glue path annotation and detection analysis of the spliced image includes: dividing the marked image into a first detection area and a second detection area according to a preset template; the first preset coverage rate threshold of the first detection area is greater than the second preset coverage rate threshold of the second detection area; calculate the glue path coverage rates of the first detection area and the second detection area in the marked image respectively; when the glue path coverage rate of the first detection area is greater than the first preset coverage rate threshold, and / or the glue path coverage rate of the second detection area is greater than the second preset coverage rate threshold, the detection result of the battery cell to be measured is qualified. Description of the Drawings

[0016] One or more embodiments are illustrated by way of example with reference to the pictures in the corresponding drawings. These exemplary illustrations do not limit the embodiments. Elements with the same reference numerals in the drawings represent similar elements, unless otherwise stated. The drawings in the figures are not drawn to scale.

[0017] Figure 1 is a schematic structural diagram of a photovoltaic cell glue path printing detection device provided by an embodiment of the present application Figure 1 ;

[0018] Figure 2 is a schematic structural diagram of a photovoltaic cell glue path printing detection device provided by an embodiment of the present applicationFigure 2 ;

[0019] Figure 3 is an image of a battery cell to be measured processed by a photovoltaic cell glue path printing detection device provided in an embodiment of the present application;

[0020] Figure 4 is the flow of a photovoltaic cell glue path printing detection method provided in an embodiment of the present application Figure 1 ;

[0021] Figure 5 is the flow of a photovoltaic cell glue path printing detection method provided in an embodiment of the present application Figure 2 ;

[0022] Figure 6 is the flow of a photovoltaic cell glue path printing detection method provided in an embodiment of the present application Figure 3 ;

[0023] Figure 7 is a gray-scale comparison diagram of the glue path and the glue-deficient area in the battery cell to be measured provided in an embodiment of the present application;

[0024] Figure 8 is the flow of a photovoltaic cell glue path printing detection method provided in an embodiment of the present application Figure 4 ;

[0025] Figure 9 is a schematic diagram of the internal structure of an electronic device provided in an embodiment of the present application. Detailed implementation manners

[0026] Since single-camera and single-type light source imaging is mostly used in the first-pass printing detection of back-contact batteries, imaging is prone to generate shadows, the gray-scale difference between the glue path and the unprinted glue area is small, the imaging effect on transparent glue is poor, and it is difficult to accurately detect defects. And printing glue defects will cause battery short circuits, threatening product quality and safety. Therefore, developing equipment and methods suitable for the first-pass printing detection of back-contact batteries to eliminate imaging shadows and improve detection effects has become an urgent task in the industry.

[0027] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be described in detail below with reference to the accompanying drawings. However, those of ordinary skill in the art can understand that in the embodiments of the present invention, many technical details are provided to help readers better understand the present application. However, even without these technical details and various changes and modifications based on the following embodiments, the technical solutions claimed in the present application can still be implemented. The following division of each embodiment is for convenience of description and should not constitute any limitation to the specific implementation of the present invention. Each embodiment can be combined and cross-referenced with each other on the premise of not being contradictory. The implementation details of the photovoltaic cell glue path printing detection device according to the embodiments of the present invention will be specifically described below. The following content is only the implementation details provided for easy understanding and is not necessary for implementing the solution.

[0028] An embodiment of the present invention relates to a photovoltaic cell glue path printing detection device, which can be used to detect the glue path printing of back-contact cells. As Figure 1 and Figure 2 shown, the photovoltaic cell glue path printing detection device includes: an illumination component, an optical imaging component, and an image processing component; the illumination component includes a first light source 1 and a second light source 2; the first light source 1 and the second light source 2 are different types of light sources; the first light source 1 is attached to the optical imaging component, and the second light source 2 is arranged around the optical imaging component; the optical imaging component includes four cameras 3, and the four cameras 3 respectively correspond to the four quadrants of the battery under test; the optical imaging component is connected to the image processing component, and the image processing component is used to perform glue path detection and analysis on the image of the battery under test captured by the optical imaging component.

[0029] Specifically, in some embodiments, the four cameras in the optical imaging component are respectively a first quadrant camera corresponding to the first quadrant of the battery under test, a second quadrant camera corresponding to the second quadrant of the battery under test, a third quadrant camera corresponding to the third quadrant of the battery under test, and a fourth quadrant camera corresponding to the fourth quadrant of the battery under test. During shooting, the first quadrant camera shoots the area of the first quadrant of the battery under test; the second quadrant camera shoots the area of the second quadrant of the battery under test; the third quadrant camera shoots the area of the third quadrant of the battery under test; the fourth quadrant camera shoots the area of the fourth quadrant of the battery under test. Finally, the images of the battery under test captured by the first quadrant camera, the second quadrant camera, the third quadrant camera, and the fourth quadrant camera are stitched, integrated, and detected. The merged complete battery image is as Figure 3 shown.

[0030] In some embodiments, the first light source 1 is a coaxial light source; the second light source 2 is a surface array light source; the number of the first light sources 1 is the same as the number of cameras 3 in the optical imaging assembly, and the lens of each camera 3 is attached to one of the first light sources 1. The light emitted by each first light source 1 and the optical axis of the attached camera 3 are on the same axis; the four cameras 3 in the optical imaging assembly are at the same horizontal height, and the four cameras 3 simultaneously take pictures of the battery under test each time.

[0031] Specifically, a coaxial light source is a light source system in which the light-emitting source is coaxially installed with the optical axis of the lens. It mainly uses optical elements such as semi-transparent and semi-reflective mirrors or beam splitters. After the light emitted by the light source is reflected or refracted, it irradiates the object to be measured along the optical axis of the lens. Then, the light reflected by the object returns along the original path and enters the lens for imaging. This can ensure that the light is incident and reflected perpendicular to the surface of the object, reducing shadow and reflection interference caused by the inclination of the light. By adopting a coaxial light source in this application, imaging shadows can be eliminated and reflection can be reduced, making the edges and details of the object in the image clearer, which is beneficial to improving the contrast and quality of the image. A surface array light source is a light source that can provide uniform illumination over a large area. It is usually composed of multiple light-emitting diodes (LEDs) or other light-emitting elements arranged in a certain array pattern. By reasonably designing the optical structure and control circuit, these light-emitting elements emit light simultaneously to form a uniform surface light source, providing large-area illumination to the object to be measured. By adopting a surface array light source in this application to achieve large-area uniform illumination, it can cover a large detection area of the battery under test, ensure that the entire detection area of the battery is fully and uniformly illuminated, and increase the illumination brightness, meeting the requirements for light intensity in different areas. That is, in this application, by simultaneously setting a coaxial light source and a surface array light source in the photovoltaic cell glue path printing detection equipment to detect the battery under test, the central imaging shadow of the battery under test is reduced by the coaxial light source, and at the same time, the imaging shadow around is also reduced by the surface array light source, the brightness of the light source is made uniform, the imaging clarity of the battery under test is improved, the detection accuracy of the glue path is improved, and the misjudgment of the glue path detection is reduced.

[0032] In some embodiments, the number of pixels of the image sensor of the camera in the optical imaging assembly is 20 million to 36 million. Specifically, in one embodiment, the number of pixels of the image sensor of the camera in the optical imaging assembly is 25 million, and the pixel accuracy is 0.04 mm / pixel. It should be noted that those skilled in the art can also select different specifications for the number of pixels of the camera sensor in the optical imaging assembly according to actual detection needs, and this application does not limit it here.

[0033] In some embodiments, the photovoltaic cell glue path printing detection device further includes a mechanical motion assembly; the mechanical motion assembly is provided with an area for placing a to-be-tested cell, and is connected to the optical imaging assembly; the mechanical motion assembly controls the movement of the to-be-tested cell and / or the optical imaging assembly according to the position of the to-be-tested cell captured by the optical imaging assembly.

[0034] Specifically, in some embodiments, the mechanical motion assembly obtains in real time the image of the to-be-tested cell captured by the optical imaging assembly, determines whether the to-be-tested cell has moved to a preset position according to the position of the to-be-tested cell image. If the to-be-tested cell has moved to the preset position, the to-be-tested cell is photographed and detected; if the to-be-tested cell has not moved to the preset position, the to-be-tested cell is controlled to move to the preset position according to the distance between the current position of the to-be-tested cell and the preset position.

[0035] In the embodiments of the present invention, since the lighting assembly includes a first light source and a second light source of different types of light sources, during the imaging process, the advantages of different types of light sources can be combined for photographing and imaging, thereby improving the quality of glue path imaging, preventing the situation of misjudgment in glue path detection caused by too small a gray difference in the glue path due to imaging shadows existing in a single type of light source, and there is no need to add other devices for supplementary lighting during the imaging process, improving the efficiency of glue path detection; at the same time, the optical imaging assembly is increased from a single camera to four cameras, and one camera corresponds to one quadrant of the cell. During the imaging process, each camera can capture more details of the cell, thereby improving the accuracy and effect of imaging, further improving the accuracy of glue path analysis and detection, reducing the misjudgment rate of cell printing defects, saving labor costs, and reducing the loss of cell detection and picking.

[0036] In the description of the embodiments of the present application, technical terms such as "first" and "second" are only used to distinguish different objects, and cannot be understood as indicating or implying relative importance or implicitly indicating the quantity, specific order or primary-secondary relationship of the indicated technical features. In the description of the embodiments of the present application, the meaning of "a plurality" is more than two, unless otherwise clearly and specifically defined.

[0037] In the description of the embodiments of the present application, the term "and / or" is only a description of the association relationship of associated objects, indicating that three relationships can exist. For example, A and / or B can represent: the existence of A, the simultaneous existence of A and B, and the existence of B. In addition, the character " / " in this article generally represents an "or" relationship between the front and rear associated objects.

[0038] In the description of the embodiments of the present application, the term "a plurality" refers to more than two (including two). Similarly, "a plurality of groups" refers to more than two groups (including two groups), and "a plurality of pieces" refers to more than two pieces (including two pieces).

[0039] In the description of the embodiments of the present application, the orientation or positional relationship indicated by technical terms such as "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", "axial", "radial", "circumferential", etc. is based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the embodiments of the present application and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation to the embodiments of the present application.

[0040] In the description of the embodiments of the present application, unless otherwise clearly specified and limited, technical terms such as "installation", "connection", "connection", "fixation", etc. should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or integrated; it can also be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the communication inside two elements or the interaction relationship between two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the embodiments of the present application can be understood according to specific situations.

[0041] Another embodiment of the present invention relates to a method for detecting the printing of the glue path of a photovoltaic cell, which can be applied to the above-mentioned device for detecting the printing of the glue path of a photovoltaic cell. The implementation details of the method for detecting the printing of the glue path of a photovoltaic cell in the embodiments of the present invention will be specifically described below. The following content is only the implementation details provided for convenient understanding and is not necessary for implementing the solution.

[0042] As Figure 4 shown, in step 401, after the lighting component is started, the optical imaging component takes a picture of the battery cell to be tested.

[0043] In step 402, the optical imaging component sends the captured image of the battery cell to be tested to the image processing component, and the image processing component performs glue path detection and analysis on the captured image of the battery cell to be tested.

[0044] Specifically, step 402 specifically includes the following sub-steps 501 to 502, as Figure 5 shown:

[0045] In step 501, the optical imaging component sends the initial images of the battery cell to be tested captured by the four cameras to the image processing component, where the initial images are the original images of the battery cell to be tested captured by each camera.

[0046] In step 502, the image processing component receives the four initial images, splices the four initial images, and then performs glue path annotation and detection analysis on the spliced image.

[0047] Specifically, in some embodiments, the process of stitching the initial images of the four battery wafers to be tested can crop and stitch the initial image of each battery wafer to be tested according to the position of a preset template; or, according to technologies such as image recognition, extract and match the features of the initial images of each battery wafer to be tested, calculate the overlapping regions of the initial images, and stitch them after cropping the overlapping regions. It should be noted that those skilled in the art can flexibly adjust the specific recognition and stitching processing methods of the four initial images. For example, algorithms such as SIFT and SURF can be used to detect extreme points in the image, etc., to extract feature points and feature vectors with features such as scale, rotation, and illumination invariance, so as to characterize the local features of the image; or based on the extracted feature vectors, algorithms such as Knn and FLANN can be used to calculate the distance between feature vectors (such as Euclidean distance, etc.), find the nearest feature point pairs, and thus determine the corresponding relationship of feature points in different images to achieve preliminary recognition and association between images; or according to the calculated homography matrix, perform perspective transformation on the image, and transform the pictures in different quadrants to the same coordinate system according to their relative geometric relationships, so that the overlapping regions are accurately aligned in space. The present application does not limit this here.

[0048] Specifically, the time for processing and detecting the image is controlled within 200 ms to facilitate adapting to the rhythm of production detection.

[0049] In some embodiments, the stitching process of the four initial images includes: stitching the four initial images captured by the four cameras according to the positions corresponding to the four quadrants of the four cameras to obtain a complete image of the battery wafer to be tested.

[0050] After stitching the four initial images to obtain a complete image, as Figure 6 shown, the method further includes steps 601 to 603:

[0051] In step 601, calculate the gray value of the complete image to obtain the glue path information of the complete image of the battery wafer to be tested.

[0052] Specifically, since there are differences in the glue path and the color of the battery wafer, the glue path-covered area on the battery wafer to be tested can be distinguished according to the gray value by calculating the gray value of the complete image. First, perform gray value conversion on the complete image. Since the captured image is read as a color image (such as RGB format), and gray value calculation is usually based on gray images, in order to improve the efficiency and accuracy of photovoltaic battery glue path detection, the color image needs to be converted to a gray image. Secondly, after the image is converted to a gray image, each pixel point only has one gray value, and the range is usually from 0 (black) to 255 (white).

[0053] In step 602, the regions in the complete image with gray values greater than a preset gray threshold are marked to obtain a marked image.

[0054] Specifically, each pixel point of the gray image is traversed to obtain the gray value of each pixel point. By comparing the gray value of each pixel point with the preset gray threshold, the pixel points with gray values greater than the preset gray threshold can be regarded as the regions covered by the glue path, and the pixel points with gray values greater than the preset gray threshold are marked. It should be noted that the preset gray threshold needs to be determined according to the specific characteristics and application scenarios of the image. For example, if the image is overall brighter, the preset gray threshold can be appropriately set; if the image is darker, the preset gray threshold needs to be lowered. Those skilled in the art can adjust the specific calculation method of the gray value and the specific marking method according to actual needs, and this application does not limit it here. As Figure 7 shown, the gray value of the glue path in the battery under test is relatively high, while the glue-deficient part has a relatively low gray value. Therefore, the contrast between the glue-deficient part and the glue path part of the battery under test is obvious, which is more conducive to the subsequent calculation and judgment of the glue path coverage rate.

[0055] As Figure 6 in step 603, calculate the glue path coverage rate of the battery under test according to the glue path coverage area of the marked image.

[0056] In some embodiments, the glue path marking and detection analysis of the spliced image include: calculating the glue path coverage rate of the marked image; when the glue path coverage rate is greater than a first preset coverage rate threshold, the detection result of the battery under test is qualified.

[0057] Specifically, in some embodiments, after extracting the glue path region, calculate the coverage area of the glue path, and calculate the glue path coverage rate according to the total area of the marked image. Further, the extraction of the glue path region can be realized by means of edge detection, contour extraction, etc., and the coverage area of the glue path can be calculated according to pixel statistics and area conversion. Glue path coverage rate = glue path area / total area of the battery under test * 100%. It should be noted that those skilled in the art can calculate the glue path coverage rate according to specific detection requirements, and this application does not limit it here.

[0058] In some embodiments, before calculating the glue path coverage rate of the labeled image, the labeled image can also be preprocessed. For example, the labeled image can be binarized: the glue path part is set as the foreground (white, value 255), and the background is set as black (value 0) by methods such as the global threshold method and the Otsu algorithm. An appropriate threshold can be selected for the binarization operation according to the gray-scale characteristics of the glue path. Or methods such as filtering can be used to remove the noise in the labeled image, such as median filtering and Gaussian filtering, to avoid the influence of noise on subsequent calculations; small noise points and isolated pixels in the labeled image can also be removed by eroding first and then dilating. Binarizing or denoising the labeled image can further simplify the complexity of the coverage rate calculation, thereby improving the efficiency of image processing and detection.

[0059] In some other embodiments, as Figure 8 shown, the glue path labeling and detection analysis of the spliced image includes:

[0060] Step 801, divide the labeled image into a first detection area and a second detection area according to a preset template; the first preset coverage rate threshold of the first detection area is greater than the second preset coverage rate threshold of the second detection area; calculate the glue path coverage rates of the first detection area and the second detection area in the labeled image respectively.

[0061] Step 802, determine whether the detection result of the battery cell to be tested is qualified; when the glue path coverage rate of the first detection area is greater than the first preset coverage rate threshold, and / or the glue path coverage rate of the second detection area is greater than the second preset coverage rate threshold, the detection result of the battery cell to be tested is qualified.

[0062] Specifically, when there are multiple detection areas with different coverage rate requirements, the sizes and coverage rate thresholds of different detection areas can be set according to actual application requirements. During the actual coverage rate detection process, the glue path area of each detection area is extracted, and the covered area of the glue path is calculated. According to the area of each detection area, the glue path coverage rate in the detection area is calculated; and the detection result is judged according to whether the glue path coverage rate in the detection area is greater than the preset coverage rate threshold of the corresponding detection area. In addition, those skilled in the art can understand that the number of detection areas and the preset coverage rate thresholds of each detection area can be flexibly set according to actual application requirements, and the present application does not limit this here.

[0063] Furthermore, when the coverage rate of each detection area reaches the preset coverage rate threshold, the detection result of the battery cell to be tested is qualified. Or, when the coverage rates of a preset number of detection areas reach the preset coverage rate threshold, the detection result of the battery cell to be tested is qualified. Those skilled in the art can understand that the situation where the detection result of the battery cell to be tested is qualified can be adjusted according to actual detection requirements, and the present application does not limit this here.

[0064] In the embodiment of the present invention, since the lighting assembly includes a first light source and a second light source of different types of light sources, during the imaging process, it is possible to combine the advantages of different types of light sources for taking pictures and imaging, thereby improving the quality of the glue path imaging, preventing the glue path detection misjudgment caused by too small a glue path gray difference due to the imaging shadow of a single type of light source, and there is no need to add other devices for supplementary lighting during the imaging process, improving the efficiency of the glue path detection; at the same time, the optical imaging assembly is increased from a single camera to four cameras, and one camera corresponds to one quadrant of the battery cell. During the imaging process, each camera can capture more details of the battery cell, thereby improving the imaging accuracy and effect, further improving the accuracy of the glue path analysis and detection, reducing the misjudgment rate of the battery cell printing defects, saving labor costs, and reducing the loss of the battery cell detection and picking.

[0065] It is not difficult to find that this embodiment is a method embodiment corresponding to the above device embodiment, and this embodiment can be implemented in cooperation with the above device embodiment. The relevant technical details mentioned in the above method embodiment are still valid in this embodiment. To avoid repetition, they will not be elaborated here. Correspondingly, the relevant technical details mentioned in this embodiment can also be applied to the above device embodiment.

[0066] The above step division of the method is only for clear description. When implemented, it can be combined into one step or some steps can be split into multiple steps. As long as the same logical relationship is included, it is within the protection scope of this patent; adding insignificant modifications to the algorithm or process or introducing insignificant designs, but not changing the core design of its algorithm and process are all within the protection scope of this patent.

[0067] In addition, the examples mentioned in the above embodiments can be freely combined, and any combination method can be understood as an embodiment. The "embodiment" or "example" mentioned at various positions in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art can understand that the embodiments described herein can be combined with other embodiments.

[0068] In summary, specific embodiments of this subject have been described. Other embodiments are within the scope of the appended claims. In some cases, the actions recited in the claims can be performed in a different order and still achieve the desired result. Additionally, the processes depicted in the figures do not necessarily require the particular order or sequential order shown to achieve the desired result.

[0069] Another embodiment of the present invention relates to an electronic device, such as Figure 9As shown, it includes at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the photovoltaic cell glue path printing detection method as described above.

[0070] Among them, the memory and the processor are connected by a bus. The bus can include any number of interconnected buses and bridges, and the bus connects various circuits of one or more processors and the memory together. The bus can also connect various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art, so they will not be further described herein. The bus interface provides an interface between the bus and the transceiver. The transceiver can be an element or multiple elements, such as multiple receivers and transmitters, providing a unit for communicating with various other devices on the transmission medium. The data processed by the processor is transmitted on the wireless medium through the antenna. Further, the antenna also receives data and transmits the data to the processor.

[0071] The processor is responsible for managing the bus and general processing, and can also provide various functions, including timing, peripheral interface, voltage regulation, power management, and other control functions. And the memory can be used to store the data used by the processor when executing operations.

[0072] Another embodiment of the present invention relates to a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the above method embodiment is implemented.

[0073] That is, those skilled in the art can understand that all or part of the steps in implementing the above method embodiments can be completed by a program instructing relevant hardware. The program is stored in a storage medium, including several instructions to enable a device (which can be a single-chip microcomputer, a chip, etc.) or a processor to execute all or part of the steps of the methods described in various embodiments of the present application. And the foregoing storage medium includes: USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs and other various media that can store program codes.

[0074] Those of ordinary skill in the art can understand that the above embodiments are specific embodiments for implementing the present invention, and in practical applications, various changes can be made in form and details without departing from the spirit and scope of the present invention.

Claims

1. A photovoltaic cell glue path printing detection device, characterized in that: include: Illumination components, optical imaging components, and image processing components; The lighting assembly includes a first light source and a second light source; the first light source and the second light source are light sources of different types; the first light source is arranged in close contact with the optical imaging assembly, and the second light source is arranged around the optical imaging assembly; The optical imaging assembly includes four cameras, and the four cameras correspond to four quadrants of the battery cell to be tested respectively; The optical imaging component is connected to the image processing component, and the image processing component is used to perform glue path detection and analysis on the image of the battery cell to be tested captured by the optical imaging component.

2. The photovoltaic cell glue path printing detection equipment according to claim 1, characterized in that: The first light source is a coaxial light source; the second light source is an array light source; The number of the first light sources is the same as the number of cameras in the optical imaging assembly, and the lens of each camera is arranged in close contact with one of the first light sources, and the light emitted by each of the first light sources is located on the same axis as the optical axis of the camera to which it is attached; The four cameras in the optical imaging assembly are located at the same horizontal height, and the four cameras synchronously shoot the battery cell to be tested each time.

3. The photovoltaic cell glue path printing detection equipment according to claim 1, characterized in that: The number of pixels of the image sensor of the camera in the optical imaging component is 20 million to 36 million.

4. The photovoltaic cell glue path printing detection equipment according to claim 1, characterized in that: The photovoltaic cell glue path printing detection equipment also includes a mechanical motion component; The mechanical motion component is provided with a placement area for the battery cell to be tested and is connected to the optical imaging component; The mechanical motion component controls the movement of the battery cell to be tested and / or the optical imaging component according to the position of the battery cell to be tested captured by the optical imaging component.

5. A photovoltaic cell glue path printing detection method, characterized in that: Applied to the photovoltaic cell glue path printing detection device according to any one of claims 1 to 4, the method comprising: After the lighting component is started, the optical imaging component takes a picture of the battery cell to be tested; The optical imaging component sends the captured image of the battery cell to be tested to the image processing component, and the image processing component performs glue path detection and analysis on the image of the battery cell to be tested.

6. The method for detecting glue path printing according to claim 5, characterized in that: The optical imaging component sends the captured image of the cell to be tested to the image processing component, and the image processing component performs glue path detection and analysis on the image of the cell to be tested, including: The optical imaging component sends the initial images of the battery cell to be tested captured by the four cameras to the image processing component; the initial images are original images of the battery cell to be tested captured by each camera; The image processing component receives the four initial images, splices the four initial images, and then performs glue path marking, detection and analysis on the spliced ​​images.

7. The method for detecting glue path printing according to claim 6, characterized in that: The stitching process of the four initial images comprises: According to the positions of the four quadrants corresponding to the four cameras, the four initial images captured by the four cameras are spliced ​​according to the corresponding positions to obtain a complete image of the battery cell to be tested.

8. The method for detecting glue path printing according to claim 7, characterized in that: Grayscale values ​​of the complete image are calculated, and regions in the complete image whose grayscale values ​​are greater than a preset grayscale threshold are marked to obtain a marked image.

9. The method for detecting glue path printing according to claim 8, characterized in that: The step of marking and detecting the glue path of the spliced ​​image includes: calculating the glue path coverage of the marked image; When the glue path coverage is greater than the first preset coverage threshold, the detection result of the battery cell to be tested is qualified.

10. The method for detecting glue path printing according to claim 8, characterized in that: The glue path marking and detection analysis of the stitched image includes: dividing the marked image into a first detection area and a second detection area according to a preset template; a first preset coverage rate threshold of the first detection area is greater than a second preset coverage rate threshold of the second detection area; Calculate the glue path coverage of the first detection area and the second detection area in the annotated image respectively; When the glue path coverage of the first detection area is greater than the first preset coverage threshold, and / or the glue path coverage of the second detection area is greater than the second preset coverage threshold, the detection result of the battery cell to be tested is qualified.

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