In-line photoluminescence imaging of crystalline silicon solar cells for micro-crack detection

Teo, Teow Wee; Abdullah, Mohd Zaid

doi:10.1109/ist.2016.7738199

Cited by 8 publications

(5 citation statements)

References 9 publications

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“…However, after the experimental research of related companies, it is known that when the ultrasonic probe is translated on the module, although the signal change can tell whether there are micro-cracks, the gap between the cells will also cause signal change, which cannot be applied to the detection of the entire module. The second is the PL detection scheme, which uses a customized light source to illuminate the silicon wafer, generates excitation and causes luminescence, and collects corresponding images for detection [13] [14]. However, the cost of this scheme is high, and it is generally used for the quality control of silicon wafers before leaving the factory.…”

Section: Related Workmentioning

confidence: 99%

Design of EL defect detection system for photovoltaic power station modules

Fan

Yan

et al. 2022

J. Phys.: Conf. Ser.

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In recent years, the photovoltaic power generation industry has been vigorously promoted and developed, while the solar cell as its core component may have micro-crack defects, which directly affect the power generation efficiency and stability of the photovoltaic system. Therefore, it is necessary to adopt a low-cost, efficient and flexible method to detect defects in solar cells. At present, most of the existing micro-cracks detection is carried out in the laboratory, and there is no EL micro-cracks detection in the actual photovoltaic power station. The main purpose of this paper is to design a set of EL defect detection system that can be used for actual photovoltaic power station modules, which is different from the traditional laboratory-level or module-level defect detection, and to carry the designed detection algorithm to the integrated device to operate. Experiments have shown that the system can perform real-time detection of photovoltaic module defects based on the string level, which improves the detection efficiency while saving time and cost, and shows good performance.

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Section: Related Workmentioning

confidence: 99%

Design of EL defect detection system for photovoltaic power station modules

Fan

Yan

et al. 2022

J. Phys.: Conf. Ser.

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“…To minimise exposure from external light sources, the entire PL imaging set-up would be enclosed in a dark box. A detailed design for a practical in-line PL imaging set-up was proposed in our previous study [8].…”

Section: A Hardware Overviewmentioning

confidence: 99%

Solar Cell Micro-Crack Detection Using Localised Texture Analysis

Teo¹,

Abdullah²

2018

JOIG

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A novel method to classify micro-cracks in Photoluminescence (PL) images of polycrystalline solar cells is proposed. Micro-cracks in PL images are difficult distinguish as they're easily confused with noises that are present which may share the same size and shape features. Instead of relying on shape analysis to classify micro-cracks, the proposed method takes advantage of the patterns that are present at the end points of micro-cracks. Textural features are extracted via grey level co-occurrence matrix at the end points and then used as feature vectors in a SVM classifier. The proposed method is compared against existing shape analysis method and a preliminary experimental result has shown a significant improvement in sensitivity, specificity and accuracy.  Index Terms-solar cell, photoluminescence, micro-crack Teow Wee Teo graduated from University of Bradford, UK with a first-class honours B.Sc. degree from the Department of Computing and Mathematics in 2007 before joining TTVision Technologies Sdn. Bhd. as a R&D Engineer. His research focuses on machine vision applications in the photovoltaic industry with particular interests on machine learning, infrared imaging and luminescence technologies. As present, he is also a Ph.D. candidate under the supervision of Professor Dr Mohd Zaid Bin Abdullah at Universiti Sains Malaysia. Mohd Zaid graduated from Universiti Sains Malaysia (USM) with a B. App. Sc. degree in Electronic in 1986 before joining Hitachi Semiconductor (Malaysia) as a Test Engineer. In 1989 he commenced an M.Sc. in

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“…Various defects of solar cell surface may appear during the production of solar cells due to some uncontrollable factors, such as: manual errors, mechanical pressure caused by the machine breakdown, etc. [29,37]. The typical solar cell surface defects and their causes are shown in Table 1.…”

Section: Typical Defects Of Solar Cells Surfacementioning

confidence: 99%

Solar Cell Surface Defects Detection based on Computer Vision

Qian¹

2017

IJPE

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Various types of defects exist in the solar cell surface because of some uncontrollable factors during the process of production. The solar cell surface defects detection is indispensable for the production of solar cell. The automatic defects detection methods based on computer vision have been widely used because of its convenience, real time and low cost. The state-of-the-art methods of solar cell surface defects detection based on computer vision are reviewed in this paper. Firstly, the typical defects of solar cell surface are summarized. Secondly, the state-of-the-art methods are classified into three categories: local scheme, global scheme and local-global scheme based methods, and separately introduced. Thirdly, the qualitative and exact evaluations of state-of-the-art methods are presented. The main contents of this paper and future development trends are summarized in the end.

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In-line photoluminescence imaging of crystalline silicon solar cells for micro-crack detection

Cited by 8 publications

References 9 publications

Design of EL defect detection system for photovoltaic power station modules

Design of EL defect detection system for photovoltaic power station modules

Solar Cell Micro-Crack Detection Using Localised Texture Analysis

Solar Cell Surface Defects Detection based on Computer Vision

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