CN107764829A - Solar cell open defect recognition methods - Google Patents

Solar cell open defect recognition methods Download PDF

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Publication number
CN107764829A
CN107764829A CN201610669889.1A CN201610669889A CN107764829A CN 107764829 A CN107764829 A CN 107764829A CN 201610669889 A CN201610669889 A CN 201610669889A CN 107764829 A CN107764829 A CN 107764829A
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CN
China
Prior art keywords
solar cell
image
cell piece
open defect
defects
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN201610669889.1A
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Chinese (zh)
Inventor
肖颖婕
张梦亚
赵墨
丁叶飞
朱小芳
朱旭
张雯君
陆文婷
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Shanghai Solar Energy Research Center Co Ltd
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Shanghai Solar Energy Research Center Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
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Publication date
Application filed by Shanghai Solar Energy Research Center Co Ltd filed Critical Shanghai Solar Energy Research Center Co Ltd
Priority to CN201610669889.1A priority Critical patent/CN107764829A/en
Publication of CN107764829A publication Critical patent/CN107764829A/en
Pending legal-status Critical Current

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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84Systems specially adapted for particular applications
    • G01N21/88Investigating the presence of flaws or contamination
    • G01N21/8851Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84Systems specially adapted for particular applications
    • G01N21/88Investigating the presence of flaws or contamination
    • G01N21/8851Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
    • G01N2021/8887Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges based on image processing techniques

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  • Engineering & Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Signal Processing (AREA)
  • Physics & Mathematics (AREA)
  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Chemical & Material Sciences (AREA)
  • Analytical Chemistry (AREA)
  • Biochemistry (AREA)
  • General Health & Medical Sciences (AREA)
  • General Physics & Mathematics (AREA)
  • Immunology (AREA)
  • Pathology (AREA)
  • Photovoltaic Devices (AREA)
  • Image Analysis (AREA)
  • Image Processing (AREA)

Abstract

The invention discloses a kind of solar cell open defect recognition methods, by gathering the sample image of solar cell piece and the pretreatment such as distortion correction, rotation, cutting being carried out to image, then edge detection algorithm is passed through, obtain the edge feature of cell piece, according to whether the shape of feature and location determination jagged, whether chipping and cell piece surface have the defects of slurry contamination, then judge whether battery has the defects of disconnected grid by line detection method.The inventive method is based on the principles such as NI Vision Builder for Automated Inspection, image procossing and signature analysis, substitutes manual identified method, realizes the open defect sorting of intelligent solar cell piece, is advantageous to improve the presentation quality of product, reduces cost of labor.

Description

Solar cell open defect recognition methods
Technical field
The present invention relates to photovoltaic technology, more particularly to a kind of solar cell open defect recognition methods.
Background technology
In process of production, for various reasons, its surface can produce some apparent defects to solar cell piece, these Defect is very big for apparent influence, influences whether the conversion efficiency of battery what is more, hides some dangers for, it is therefore desirable in battery Piece produces the later stage or component package early stage sorts to the open defect of cell piece.At present generally using artificial range estimation in industry Mode solar cell piece open defect is identified, cost of labor is high, low production efficiency, and can produce visual fatigue so as to Influence recognition effect.Therefore, there is an urgent need to a kind of quick, accurately and efficiently solar cell piece outward appearance for cell piece production enterprise Defect identification method, to improve production efficiency, reduce production cost.
The content of the invention
The purpose of the present invention, being to overcome in the presence of prior art needs manual identified solar cell piece open defect Deficiency, there is provided a kind of solar cell open defect recognition methods.
In order to achieve the above object, present invention employs following technical scheme:
A kind of solar cell open defect recognition methods, comprises the following steps:
Step 1, captured image correction template image;
Step 2, the binary image for gathering solar cell piece;
Step 3, the solar cell picture for having barrel-shaped distortion is corrected by image rectification template image, by battery picture In curve deformation be corrected to straight line;
Step 4, by Karhunen-Loeve transformation by image rotation for just;
Step 5, the solar cell picture progress edge extracting using Boundary extracting algorithm to collection, split from image Go out the only image containing cell piece;
Step 6, by edge detection algorithm, the edge feature of cell piece is obtained, according to the shape and location determination of feature Whether cell piece is jagged, chipping or the defects of slurry contamination;
Step 7, by line detection method judge whether cell piece has the defects of disconnected grid.
Described image rectification template has the chessboard grid pattern being made up of multiple lattice proper alignments, each lattice Filled respectively with black or white, and it is chequered with black and white, grid is closeer, and correction accuracy is higher.
Described edge detection algorithm, detect there are the target edges of color change in cell piece binary image, pass through The shape at these edges is for example U-shaped or V-type, and these edges where position such as battery edge or battery surface, so that it is determined that The defects of whether jagged, chipping or slurry contamination.
Compared with prior art, the beneficial effects of the invention are as follows:Using image-recognizing method, to including solar cell piece Binary image successively carries out the processing such as distortion correction, rotation, cutting, rim detection, straight-line detection and analysis, special according to edge The defects of whether shape and location determination of sign are jagged, chipping and surface size pollute, and according to the quantity for detecting straight line To judge whether battery has the defects of disconnected grid.The identification of solar cell piece open defect is carried out using the inventive method, it is only necessary to Input the binary image for including solar cell piece of collection, you can breach, chipping, slurry are carried out to the solar cell piece in image The identification of the defects of material pollution, disconnected grid, without manually being sorted by observing blocks of solar cell piece, realizes intellectuality Open defect identifies, greatly improves the recognition efficiency of open defect, reduces workload, reduces cost of labor.
Brief description of the drawings
Fig. 1 is the flow chart of solar cell open defect recognition methods of the present invention.
Embodiment
With reference to test example and embodiment, the present invention is described in further detail.But this should not be understood Following embodiment is only limitted to for the scope of the above-mentioned theme of the present invention, it is all that this is belonged to based on the technology that present invention is realized The scope of invention.
Referring to Fig. 1, solar cell open defect recognition methods provided by the invention, comprise the following steps:
Step 1:The image of captured image correction template is used for image rectification.
Step 2:The binary image of solar cell piece is gathered, and cell piece can be distinguished substantially with background in image.
Step 3:The image for the solar cell piece for having barrel-shaped distortion is corrected by the image of image rectification template, by battery Curve deformation in piece is corrected to straight line.
Step 4:By Karhunen-Loeve transformation by image rotation for just.
Step 5:Edge extracting is carried out to the solar cell picture of collection using Boundary extracting algorithm, split from image Go out the only image containing cell piece.
Step 6:By edge detection algorithm, the edge feature of cell piece is obtained, according to the shape and location determination of feature Whether whether jagged, chipping and cell piece surface have the defects of slurry contamination.
In this step, described edge detection algorithm, it is capable of detecting when there be pair of color change in cell piece bianry image As edge, pass through position such as battery edge or battery table of the shape at these edges as where U-shaped or V-type and these edges Face, the defects of so as to determine whether jagged, chipping or slurry contamination.
Step 7:Judge whether battery has the defects of disconnected grid by line detection method.

Claims (3)

1. a kind of solar cell open defect recognition methods, it is characterised in that comprise the following steps:
Step 1, captured image correction template image;
Step 2, the binary image for gathering solar cell piece;
Step 3, the solar cell picture for having barrel-shaped distortion is corrected by image rectification template image, by battery picture Curve deformation is corrected to straight line;
Step 4, by Karhunen-Loeve transformation by image rotation for just;
Step 5, the solar cell picture progress edge extracting using Boundary extracting algorithm to collection, are partitioned into only from image Image containing cell piece;
Step 6, by edge detection algorithm, the edge feature of cell piece is obtained, according to the shape of feature and location determination battery Whether piece is jagged, chipping or the defects of slurry contamination;
Step 7, by line detection method judge whether cell piece has the defects of disconnected grid.
2. solar cell open defect recognition methods as claimed in claim 1, it is characterised in that described image rectification template tool By the chessboard grid pattern being made up of multiple lattice proper alignments, each lattice is filled with black or white respectively, and black and white Alternate, grid is closeer, and correction accuracy is higher.
3. solar cell open defect recognition methods as claimed in claim 1, it is characterised in that described rim detection is calculated Method, detect there are the target edges of color change in cell piece binary image, by the way that the shape at these edges is for example U-shaped or V-type, And the position where these edges such as battery edge or battery surface, determine whether jagged, chipping or slurry contamination The defects of.
CN201610669889.1A 2016-08-15 2016-08-15 Solar cell open defect recognition methods Pending CN107764829A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201610669889.1A CN107764829A (en) 2016-08-15 2016-08-15 Solar cell open defect recognition methods

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201610669889.1A CN107764829A (en) 2016-08-15 2016-08-15 Solar cell open defect recognition methods

Publications (1)

Publication Number Publication Date
CN107764829A true CN107764829A (en) 2018-03-06

Family

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Family Applications (1)

Application Number Title Priority Date Filing Date
CN201610669889.1A Pending CN107764829A (en) 2016-08-15 2016-08-15 Solar cell open defect recognition methods

Country Status (1)

Country Link
CN (1) CN107764829A (en)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111229648A (en) * 2020-01-19 2020-06-05 青岛滨海学院 Solar cell panel flaw detection system and detection method based on machine vision
CN118279887A (en) * 2024-05-27 2024-07-02 佛山隆深机器人有限公司 Retired battery sorting method and system applied to battery disassembly production line

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1830002A (en) * 2003-07-28 2006-09-06 奥林巴斯株式会社 Image processing apparatus, image processing method, and distortion correcting method
CN102519365A (en) * 2011-12-06 2012-06-27 桂林电子科技大学 Detector of properties of gate line of solar cell piece
CN103033517A (en) * 2011-07-15 2013-04-10 株式会社Npc Defect inspection device for solar cells and inspection method
CN103116878A (en) * 2013-02-25 2013-05-22 徐渊 Method and device for correcting image barrel distortion and image processing device
CN103489254A (en) * 2012-06-11 2014-01-01 深圳信息职业技术学院 Lottery recognition method and lottery recognition system
CN103872983A (en) * 2014-04-04 2014-06-18 天津市鑫鼎源科技发展有限公司 Device and method for detecting defects on surface of solar cell
CN104713883A (en) * 2013-12-11 2015-06-17 上海空间电源研究所 Rapid detection and automatic identification method for large-area space solar battery array defects

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1830002A (en) * 2003-07-28 2006-09-06 奥林巴斯株式会社 Image processing apparatus, image processing method, and distortion correcting method
CN103033517A (en) * 2011-07-15 2013-04-10 株式会社Npc Defect inspection device for solar cells and inspection method
CN102519365A (en) * 2011-12-06 2012-06-27 桂林电子科技大学 Detector of properties of gate line of solar cell piece
CN103489254A (en) * 2012-06-11 2014-01-01 深圳信息职业技术学院 Lottery recognition method and lottery recognition system
CN103116878A (en) * 2013-02-25 2013-05-22 徐渊 Method and device for correcting image barrel distortion and image processing device
CN104713883A (en) * 2013-12-11 2015-06-17 上海空间电源研究所 Rapid detection and automatic identification method for large-area space solar battery array defects
CN103872983A (en) * 2014-04-04 2014-06-18 天津市鑫鼎源科技发展有限公司 Device and method for detecting defects on surface of solar cell

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
中华人民共和国工业信息化部: "《中华人民共和国电子行业标准 SJ/T 11631-2016 太阳能电池用硅片外观缺陷测试方法》", 5 April 2016 *
李久芳: "基于标准棋盘格的图像校准方法", 《电子工业专用设备》 *
黄远民 等: "基于Halcon的太阳能硅片缺陷检测", 《机械工程与技术》 *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111229648A (en) * 2020-01-19 2020-06-05 青岛滨海学院 Solar cell panel flaw detection system and detection method based on machine vision
CN118279887A (en) * 2024-05-27 2024-07-02 佛山隆深机器人有限公司 Retired battery sorting method and system applied to battery disassembly production line

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Application publication date: 20180306

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