Segmentation and defect detection for back electrodes in solar cells

WU Yilin; XIAO Huaxi; LI Wanyi; CHEN Guoming; ZHANG Qian; LIU Yu

doi:10.13471/j.cnki.acta.snus.2021A008

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Segmentation and defect detection for back electrodes in solar cells

Research articles | 更新时间：2023-11-01

- Segmentation and defect detection for back electrodes in solar cells
- Acta Scientiarum Naturalium Universitatis Sunyatseni Vol. 61, Issue 4, Pages: 160-169(2022)
- 作者机构：
  
  1.广东第二师范学院计算机学院，广东广州 510303
  2.华南理工大学自动化科学与工程学院，广东广州 510640
  3.广州现代产业技术研究院，广东广州 511458
- 作者简介：
- 基金信息：
- DOI：10.13471/j.cnki.acta.snus.2021A008
  CLC： TP391.41
- Published：25 July 2022，
  
  Published Online：24 August 2021，
  
  Received：02 February 2021，
  
  Accepted：18 March 2021
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邬依林,萧华希,李万益等.太阳能电池背面电极的分割与缺陷检测[J].中山大学学报(自然科学版),2022,61(04):160-169.

WU Yilin,XIAO Huaxi,LI Wanyi,et al.Segmentation and defect detection for back electrodes in solar cells[J].Acta Scientiarum Naturalium Universitatis Sunyatseni,2022,61(04):160-169.
邬依林,萧华希,李万益等.太阳能电池背面电极的分割与缺陷检测[J].中山大学学报(自然科学版),2022,61(04):160-169. DOI： 10.13471/j.cnki.acta.snus.2021A008.

WU Yilin,XIAO Huaxi,LI Wanyi,et al.Segmentation and defect detection for back electrodes in solar cells[J].Acta Scientiarum Naturalium Universitatis Sunyatseni,2022,61(04):160-169. DOI： 10.13471/j.cnki.acta.snus.2021A008.

摘要

自动化质量检测系统是太阳能电池生产过程中必不可少的环节，其目的是识别潜在产品缺陷，但鲜见对太阳能电池的背面电极的检测问题的文献，针对该问题提出一种完整的背面电极分割和缺陷检测算法。首先，利用边缘强度投影和模板匹配方法依次获得电极的粗略位置和较精准位置；然后采用阈值法和种子生长法提取电极边缘点。第三，利用边缘点生成一个闭合的区域来表示电极的形状。最后，设计了一种判断电极是否存在缺陷的方法。为了验证该方法的性能，针对电极分割的精确度进行了实验。实验结果表明，提出的电极分割检测方案优于实验中四种著名的方法。

Abstract

An automatic quality inspection system， aiming to identify potential product defects， is essential for the production of solar cells. But few papers focus on the detection of back electrodes in solar cells， for which a complete algorithm is proposed to segment back electrodes and check for defects on them. Firstly， coarse and fine positions of electrodes are obtained using the edge intensity projection and template matching method. Secondly， the edge of electrodes is extracted by the threshold method and seed growing method. Thirdly， an edge-to-region method is adopted to generate a closed region with edge points. Finally， a method is designed to judge whether there are defects in electrodes or not. To verify the performance of the proposed method， an experiment is carried out. From the experiment result， the proposed segmentation method for electrodes outperforms the four famous methods implemented in the experiment.

关键词

机器视觉缺陷检测图像分割太阳能电池

Keywords

machine visiondefect detectionimage segmentationsolar cell

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