Spectrum Analysis Enabled Periodic Feature Reconstruction Based Automatic Defect Detection System for Electroluminescence Images of Photovoltaic Modules
Electroluminescence (EL) imaging is a widely adopted method in quality assurance of the photovoltaic (PV) manufacturing industry. With the growing demand for high-quality PV products, automatic inspection methods based on machine vision have become an emerging area concern to replace manual inspecto...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-02-01
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| Series: | Micromachines |
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| Online Access: | https://www.mdpi.com/2072-666X/13/2/332 |
| _version_ | 1797477904677863424 |
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| author | Jiachuan Yu Yuan Yang Hui Zhang Han Sun Zhisheng Zhang Zhijie Xia Jianxiong Zhu Min Dai Haiying Wen |
| author_facet | Jiachuan Yu Yuan Yang Hui Zhang Han Sun Zhisheng Zhang Zhijie Xia Jianxiong Zhu Min Dai Haiying Wen |
| author_sort | Jiachuan Yu |
| collection | DOAJ |
| description | Electroluminescence (EL) imaging is a widely adopted method in quality assurance of the photovoltaic (PV) manufacturing industry. With the growing demand for high-quality PV products, automatic inspection methods based on machine vision have become an emerging area concern to replace manual inspectors. Therefore, this paper presents an automatic defect-inspection method for multi-cell monocrystalline PV modules with EL images. A processing routine is designed to extract the defect features of the PV module, eliminating the influence of the intrinsic structural features. Spectrum domain analysis is applied to effectively reconstruct an improved PV layout from a defective one by spectrum filtering in a certain direction. The reconstructed image is used to segment the PV module into cells and slices. Based on the segmentation, defect detection is carried out on individual cells or slices to detect cracks, breaks, and speckles. Robust performance has been achieved from experiments on many samples with varying illumination conditions and defect shapes/sizes, which shows the proposed method can efficiently distinguish intrinsic structural features from the defect features, enabling precise and speedy defect detections on multi-cell PV modules. |
| first_indexed | 2024-03-09T21:24:23Z |
| format | Article |
| id | doaj.art-23b2fca47eff4636bf90cb57972e41c3 |
| institution | Directory Open Access Journal |
| issn | 2072-666X |
| language | English |
| last_indexed | 2024-03-09T21:24:23Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Micromachines |
| spelling | doaj.art-23b2fca47eff4636bf90cb57972e41c32023-11-23T21:12:14ZengMDPI AGMicromachines2072-666X2022-02-0113233210.3390/mi13020332Spectrum Analysis Enabled Periodic Feature Reconstruction Based Automatic Defect Detection System for Electroluminescence Images of Photovoltaic ModulesJiachuan Yu0Yuan Yang1Hui Zhang2Han Sun3Zhisheng Zhang4Zhijie Xia5Jianxiong Zhu6Min Dai7Haiying Wen8School of Mechanical Engineering, Southeast University, Nanjing 210096, ChinaSchool of Mechanical Engineering, Southeast University, Nanjing 210096, ChinaSchool of Mechanical Engineering, Southeast University, Nanjing 210096, ChinaSchool of Mechanical Engineering, Southeast University, Nanjing 210096, ChinaSchool of Mechanical Engineering, Southeast University, Nanjing 210096, ChinaSchool of Mechanical Engineering, Southeast University, Nanjing 210096, ChinaSchool of Mechanical Engineering, Southeast University, Nanjing 210096, ChinaSchool of Mechanical Engineering, Southeast University, Nanjing 210096, ChinaSchool of Mechanical Engineering, Southeast University, Nanjing 210096, ChinaElectroluminescence (EL) imaging is a widely adopted method in quality assurance of the photovoltaic (PV) manufacturing industry. With the growing demand for high-quality PV products, automatic inspection methods based on machine vision have become an emerging area concern to replace manual inspectors. Therefore, this paper presents an automatic defect-inspection method for multi-cell monocrystalline PV modules with EL images. A processing routine is designed to extract the defect features of the PV module, eliminating the influence of the intrinsic structural features. Spectrum domain analysis is applied to effectively reconstruct an improved PV layout from a defective one by spectrum filtering in a certain direction. The reconstructed image is used to segment the PV module into cells and slices. Based on the segmentation, defect detection is carried out on individual cells or slices to detect cracks, breaks, and speckles. Robust performance has been achieved from experiments on many samples with varying illumination conditions and defect shapes/sizes, which shows the proposed method can efficiently distinguish intrinsic structural features from the defect features, enabling precise and speedy defect detections on multi-cell PV modules.https://www.mdpi.com/2072-666X/13/2/332defect detectioncomputer visionspectrum analysisphotovoltaic moduleelectroluminescence image |
| spellingShingle | Jiachuan Yu Yuan Yang Hui Zhang Han Sun Zhisheng Zhang Zhijie Xia Jianxiong Zhu Min Dai Haiying Wen Spectrum Analysis Enabled Periodic Feature Reconstruction Based Automatic Defect Detection System for Electroluminescence Images of Photovoltaic Modules Micromachines defect detection computer vision spectrum analysis photovoltaic module electroluminescence image |
| title | Spectrum Analysis Enabled Periodic Feature Reconstruction Based Automatic Defect Detection System for Electroluminescence Images of Photovoltaic Modules |
| title_full | Spectrum Analysis Enabled Periodic Feature Reconstruction Based Automatic Defect Detection System for Electroluminescence Images of Photovoltaic Modules |
| title_fullStr | Spectrum Analysis Enabled Periodic Feature Reconstruction Based Automatic Defect Detection System for Electroluminescence Images of Photovoltaic Modules |
| title_full_unstemmed | Spectrum Analysis Enabled Periodic Feature Reconstruction Based Automatic Defect Detection System for Electroluminescence Images of Photovoltaic Modules |
| title_short | Spectrum Analysis Enabled Periodic Feature Reconstruction Based Automatic Defect Detection System for Electroluminescence Images of Photovoltaic Modules |
| title_sort | spectrum analysis enabled periodic feature reconstruction based automatic defect detection system for electroluminescence images of photovoltaic modules |
| topic | defect detection computer vision spectrum analysis photovoltaic module electroluminescence image |
| url | https://www.mdpi.com/2072-666X/13/2/332 |
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