CN111986159B - Electrode defect detection method and device for solar cell and storage medium - Google Patents
Electrode defect detection method and device for solar cell and storage medium Download PDFInfo
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- 238000001514 detection method Methods 0.000 title claims abstract description 50
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- 238000003860 storage Methods 0.000 title claims abstract description 21
- 230000011218 segmentation Effects 0.000 claims abstract description 19
- 238000012946 outsourcing Methods 0.000 claims abstract description 16
- 230000000877 morphologic effect Effects 0.000 claims abstract description 8
- 230000009466 transformation Effects 0.000 claims abstract description 6
- 238000004590 computer program Methods 0.000 claims description 6
- 230000006740 morphological transformation Effects 0.000 claims description 6
- 238000012216 screening Methods 0.000 claims description 3
- 238000000034 method Methods 0.000 description 11
- 238000004519 manufacturing process Methods 0.000 description 8
- 230000003287 optical effect Effects 0.000 description 6
- 238000012545 processing Methods 0.000 description 5
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- 238000011179 visual inspection Methods 0.000 description 1
- 238000001039 wet etching Methods 0.000 description 1
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- G—PHYSICS
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
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- G06V10/267—Segmentation of patterns in the image field; Cutting or merging of image elements to establish the pattern region, e.g. clustering-based techniques; Detection of occlusion by performing operations on regions, e.g. growing, shrinking or watersheds
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- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01L—SEMICONDUCTOR DEVICES NOT COVERED BY CLASS H10
- H01L22/00—Testing or measuring during manufacture or treatment; Reliability measurements, i.e. testing of parts without further processing to modify the parts as such; Structural arrangements therefor
- H01L22/10—Measuring as part of the manufacturing process
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- H—ELECTRICITY
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- H01L—SEMICONDUCTOR DEVICES NOT COVERED BY CLASS H10
- H01L22/00—Testing or measuring during manufacture or treatment; Reliability measurements, i.e. testing of parts without further processing to modify the parts as such; Structural arrangements therefor
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Abstract
The invention discloses an electrode defect detection method, equipment and a storage medium of a solar cell. The electrode defect detection method comprises the following steps: acquiring an original image of a detected solar cell, and performing threshold segmentation on the original image to acquire a first target electrode area image; carrying out area threshold detection segmentation on the first target electrode area image to obtain a second target electrode area image; performing morphological operation on the second target electrode area image to obtain a third target electrode area image; performing region shape transformation on the third target electrode region image to obtain a minimum outsourcing rectangle; outputting parameters of the outer package rectangle to obtain a center coordinate and a lower right corner coordinate of the outer package rectangle; and sequentially performing projection operation on the third target electrode area image to obtain a column pixel coordinate gray average value. The invention aims to replace manual detection of electrode defects of solar cells.
Description
Technical Field
The invention relates to the technical field of machine vision detection, in particular to a method and equipment for detecting electrode defects of a solar cell and a storage medium.
Background
In the production process of the solar cell module, the production of the cell sheet is a core part in the whole production process of the solar cell module. The main production process of the battery piece is as follows: texturing, diffusion, wet etching, depositing thin films, printing electrodes and sintering.
Because the solar cell module has a complex production process, the surface defect of the cell sheet is inevitably caused by a machine or considered human factors, and the production process mainly depends on the human eyes in China at the present stage. Electrode overflow is a surface defect which seriously affects the quality of the solar cell. At present, the defect is identified by adopting manual visual inspection for battery plate electrode overflow detection, is greatly influenced by subjectivity of workers, can improve the cost of enterprises, reduces the production efficiency and has high error rate.
Therefore, there is a need for an electrode defect detection method for solar cells that can replace manual operation.
Disclosure of Invention
The invention provides a method, equipment and a storage medium for detecting electrode defects of a solar cell, which are used for replacing manual electrode defect detection of the solar cell.
In order to solve the technical problems, the technical scheme of the invention is as follows:
an electrode defect detection method of a solar cell, comprising:
acquiring an original image of a detected solar cell, and performing threshold segmentation on the original image to obtain a first target electrode area image;
performing area threshold detection segmentation on the first target electrode area image to obtain a second target electrode area image;
performing morphological operation on the second target electrode area image to obtain a third target electrode area image;
performing region shape transformation on the third target electrode region image to obtain a minimum outsourcing rectangle;
outputting parameters of the outsourcing rectangle to obtain a center coordinate and a lower right corner coordinate of the outsourcing rectangle;
and sequentially performing projection operation on the image of the third target electrode area to obtain a column pixel coordinate gray level average value, taking the column pixel coordinate gray level average value of a part of intervals as an overall average value, and if the column gray level average value is larger than the overall average value, regarding the image as a pixel point with electrode overflow.
Further, thresholding the image to obtain a first target electrode area image includes:
dividing the original image by adopting a preset threshold value to obtain a first target electrode area image; the preset threshold is 220 to 255.
Further, performing area threshold detection segmentation on the first target electrode area image to obtain a second target electrode area image, including:
performing area characteristic threshold detection segmentation on the first target electrode area image, and screening out areas which are not in an area interval in the first target electrode area image so as to obtain a second target electrode area image;
the selected area interval is 41000 to 700000.
Further, performing morphological operations on the second target electrode area image to obtain a third target electrode area image, including:
performing morphological transformation operation on the second target electrode area image by adopting structural elements, wherein the morphological transformation operation adopts a closed operation of expanding and then corroding to remove interference points in the second target electrode area image;
the structural elements are selected to be 50 x 50 rectangles.
Further, taking the column pixel coordinate gray scale average value of the partial section as the overall average value is:
the gray scale average value of the column pixel coordinates of 1/3 to 2/3 is taken as the overall average value.
Further, if the column gray average value is greater than the global average value, the pixel point regarded as electrode overflow includes:
setting a threshold tolerance, taking tolerance=10, and if the column gray average value is greater than the sum of the integral average value and tolerance, regarding as the pixel point coordinate of electrode overflow.
The invention also adopts the following technical scheme:
an electrode defect detection apparatus of a solar cell, the electrode defect detection apparatus comprising:
one or more processors;
a storage means for storing one or more programs;
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the electrode defect detection method as described above.
The invention also adopts the following technical scheme:
a computer readable storage medium having stored thereon a computer program, characterized in that the computer program, when executed by a processor, implements an electrode defect detection method as described above.
The invention has the following advantages:
according to the characteristic of high pixel value of electrode overflow, the invention can effectively detect the defect of electrode overflow, effectively avoid manual false detection, greatly improve the detection accuracy and adaptability, can meet the requirement of judgment accuracy, and is more suitable for industrial application.
Drawings
Fig. 1 is a flowchart of a method for detecting electrode defects of a solar cell according to an embodiment of the present invention;
fig. 2 is a schematic hardware structure of an electrode defect detecting device for a solar cell according to an embodiment of the present invention.
Detailed Description
In order that the above objects, features and advantages of the invention will be readily understood, a more particular description of the invention will be rendered by reference to the appended drawings. It should be noted that the drawings of the present invention are in simplified form and are not to scale precisely, but rather are merely intended to facilitate a clear and concise description of embodiments of the present invention.
Referring to fig. 1, fig. 1 is a flowchart of an electrode defect detection method for a solar cell according to an embodiment of the present invention, where the method may be applied to appearance detection of a surface of a cell during a production process of the solar cell to determine whether the cell has an electrode overflow defect, and the method may be performed by an electrode defect detection device and specifically includes the following steps:
s1, acquiring an original image of a detected solar cell, and performing threshold segmentation on the original image to obtain a first target electrode area image.
Alternatively, the original image may be generated by photographing the target object with a CCD imaging device.
Further, thresholding the image to obtain a first target electrode area image includes:
and segmenting the original image by adopting a preset threshold value to obtain a first target electrode area image.
Let the original image be f (x, y), the preset threshold segmentation method is as follows:
wherein: t is a set threshold value, "1" representing the target image, represented by a pixel value of 0, "0" representing the background, represented by a pixel value of 255. The g (x, y) thus obtained is a pair of binary images.
The magnitude of the preset threshold will directly affect the effectiveness of the segmentation, which in this embodiment is preferably 220 to 255.
S2, carrying out area threshold detection segmentation on the first target electrode area image so as to obtain a second target electrode area image.
Specifically, step S2 includes:
performing area characteristic threshold detection segmentation on the first target electrode area image, and screening out areas which are not in an area interval in the first target electrode area image so as to obtain a second target electrode area image; the selected area interval is 41000 to 700000.
And S3, performing morphological operation on the second target electrode area image to obtain a third target electrode area image.
Specifically, structural elements are adopted to perform morphological transformation operation on the second target electrode area image, and the morphological transformation operation adopts a closed operation of expanding and then corroding to remove interference points in the second target electrode area image.
The expansion principle means that a structural element is defined, the structural element moves in the whole image and moves to each pixel point, and if the pixel value of the structural element is equal to at least one pixel of the corresponding pixel point on the image, the value of the pixel point is reserved.
The corrosion principle is that a structural element is defined, the structural element moves in the whole image and moves to each pixel point, and only when the pixel values of the structural element and the corresponding pixel point on the image are all equal, the value of the pixel point is reserved.
In this embodiment, the structural element is selected to be a 50×50 rectangle.
S4, carrying out region shape transformation on the third target electrode region image so as to obtain the minimum outsourcing rectangle.
S5, outputting parameters of the outsourcing rectangle to obtain a center coordinate and a lower right corner coordinate of the outsourcing rectangle;
and S6, sequentially performing projection operation on the image of the third target electrode area to obtain a column pixel coordinate gray level average value, taking the column pixel coordinate gray level average value of a part of intervals as an overall average value, and if the column gray level average value is larger than the overall average value, regarding the image as a pixel point with electrode overflow.
Specifically, the projection operation is performed by the following formula:
the gray average values of the column pixel coordinates are arranged in an ascending order, 1/3 to 2/3 gray average values are taken as the whole average value, a threshold value tolerance is set, tolerance=10 is taken, and if the column gray average value is larger than the sum of the whole average value and tolerance, the pixel coordinates are regarded as pixel point coordinates with electrode overflow.
By means of the method, according to the characteristic that the electrode overflow pixel value is high, the method can effectively detect the electrode overflow defect, effectively avoid manual false detection, greatly improve detection accuracy and adaptability, meet the requirement of judgment accuracy, and is more suitable for industrial application.
As shown in fig. 2, the electrode defect detection device 12 is embodied in the form of a general purpose computing device. The components of the electrode defect detection apparatus 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, a bus 18 that connects the various system components, including the system memory 28 and the processing units 16.
Bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, and a local bus using any of a variety of bus architectures. By way of example, and not limitation, such architectures include Industry Standard Architecture (ISA) bus, micro channel architecture (MAC) bus, enhanced ISA bus, video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus.
Electrode defect detection apparatus 12 typically includes a variety of computer system readable media. Such media may be any available media that is accessible by electrode defect detection device 12 and includes both volatile and nonvolatile media, removable and non-removable media.
The system memory 28 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM) 30 and/or cache memory 32. Electrode defect detection device 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from or write to non-removable, nonvolatile magnetic media (commonly referred to as a "hard disk drive"). A magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk"), and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk such as a CD-ROM, DVD-ROM, or other optical media may be provided. In such cases, each drive may be coupled to bus 18 through one or more data medium interfaces. Memory 28 may include at least one program product having a set (e.g., at least one) of program modules configured to carry out the functions of embodiments of the invention.
A program/utility 40 having a set (at least one) of program modules 42 may be stored in, for example, memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment. Program modules 42 generally perform the functions and/or methods of the embodiments described herein.
Electrode defect detection device 12 may also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), with one or more devices that enable a user to interact with electrode defect detection device 12, and/or with any device (e.g., network card, modem, etc.) that enables electrode defect detection device 12 to communicate with one or more other computing devices. Such communication may occur through an input/output (I/O) interface 22. Also, electrode defect detection device 12 may also communicate with one or more networks, such as a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the Internet, through network adapter 20. As shown, the network adapter 20 communicates with other modules of the electrode defect inspection device 12 via the bus 18. It should be appreciated that although not shown, other hardware and/or software modules may be used in connection with electrode defect detection apparatus 12, including, but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, data backup storage systems, and the like.
The processing unit 16 executes various functional applications and data processing by running a program stored in the system memory 28, for example, to implement an electrode defect detection method provided by an embodiment of the present invention, the method including:
acquiring an original image of a detected solar cell, and performing threshold segmentation on the original image to obtain a first target electrode area image;
performing area threshold detection segmentation on the first target electrode area image to obtain a second target electrode area image;
performing morphological operation on the second target electrode area image to obtain a third target electrode area image;
performing region shape transformation on the third target electrode region image to obtain a minimum outsourcing rectangle;
outputting parameters of the outsourcing rectangle to obtain a center coordinate and a lower right corner coordinate of the outsourcing rectangle;
and sequentially performing projection operation on the image of the third target electrode area to obtain a column pixel coordinate gray level average value, taking the column pixel coordinate gray level average value of a part of intervals as an overall average value, and if the column gray level average value is larger than the overall average value, regarding the image as a pixel point with electrode overflow.
The present embodiment also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the electrode defect detection method as provided by the embodiment of the present invention, the method comprising:
acquiring an original image of a detected solar cell, and performing threshold segmentation on the original image to obtain a first target electrode area image;
performing area threshold detection segmentation on the first target electrode area image to obtain a second target electrode area image;
performing morphological operation on the second target electrode area image to obtain a third target electrode area image;
performing region shape transformation on the third target electrode region image to obtain a minimum outsourcing rectangle;
outputting parameters of the outsourcing rectangle to obtain a center coordinate and a lower right corner coordinate of the outsourcing rectangle;
and sequentially performing projection operation on the image of the third target electrode area to obtain a column pixel coordinate gray level average value, taking the column pixel coordinate gray level average value of a part of intervals as an overall average value, and if the column gray level average value is larger than the overall average value, regarding the image as a pixel point with electrode overflow.
The computer storage media of embodiments of the invention may take the form of any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CDROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, either in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).
Note that various modifications and variations can be made to the invention by those skilled in the art without departing from the spirit and scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (6)
1. The electrode defect detection method of the solar cell is characterized by comprising the following steps of:
acquiring an original image of a detected solar cell, and performing threshold segmentation on the original image to obtain a first target electrode area image;
performing area threshold detection segmentation on the first target electrode area image to obtain a second target electrode area image;
performing morphological operation on the second target electrode area image to obtain a third target electrode area image;
performing region shape transformation on the third target electrode region image to obtain a minimum outsourcing rectangle;
outputting parameters of the outsourcing rectangle to obtain a center coordinate and a lower right corner coordinate of the outsourcing rectangle;
sequentially performing projection operation on the image of the third target electrode area to obtain a column pixel coordinate gray average value, taking the column pixel coordinate gray average value of a part of intervals as an overall average value, and if the column gray average value is larger than the overall average value, regarding the image as a pixel point with electrode overflow;
wherein:
taking the column pixel coordinate gray level average value of a part of intervals as an overall average value as follows: taking 1/3 to 2/3 of the column pixel coordinate gray scale average value as an overall average value;
if the column gray average value is greater than the overall average value, the pixel point regarded as electrode overflow includes: setting a threshold tolerance, taking tolerance=10, and if the column gray average value is greater than the sum of the integral average value and tolerance, regarding as the pixel point coordinate of electrode overflow.
2. The electrode defect detection method of claim 1, wherein thresholding the image to obtain a first target electrode area image comprises:
dividing the original image by adopting a preset threshold value to obtain a first target electrode area image; the preset threshold is 220 to 255.
3. The electrode defect detection method of claim 1, wherein performing an area threshold detection segmentation on the first target electrode region image to obtain a second target electrode region image comprises:
performing area characteristic threshold detection segmentation on the first target electrode area image, and screening out areas which are not in an area interval in the first target electrode area image so as to obtain a second target electrode area image;
the selected area interval is 41000 to 700000.
4. The electrode defect detection method of claim 1, wherein performing morphological operations on the second target electrode area image to obtain a third target electrode area image comprises:
performing morphological transformation operation on the second target electrode area image by adopting structural elements, wherein the morphological transformation operation adopts a closed operation of expanding and then corroding to remove interference points in the second target electrode area image;
the structural elements are selected to be 50 x 50 rectangles.
5. An electrode defect detecting apparatus of a solar cell, characterized in that the electrode defect detecting apparatus comprises:
one or more processors;
a storage means for storing one or more programs;
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the electrode defect detection method of any of claims 1-4.
6. A computer-readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the electrode defect detection method according to any one of claims 1-4.
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| CN114298985B (en) * | 2021-12-16 | 2023-12-22 | 苏州凌云光工业智能技术有限公司 | Defect detection method, device, equipment and storage medium |
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