Adaptive automatic solar cell defect detection and classification based on absolute electroluminescence imaging

Wang, Youyang; Li, Liying; Sun, Yifan; Xu, Jinjia; Jia, Yun; Hong, Jianyu; Weng, Guoen; Luo, Xianjia; Chen, Shaoqiang; Zhu, Z. Q.; Chu, Junhao; Akiyama, Hidefumi

doi:10.1016/j.energy.2021.120606

Cited by 26 publications

(13 citation statements)

References 45 publications

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“…It can be seen that the ERE loss rate decreases rapidly under lowinjection conditions, whereas it tends to a constant and almost independent on J LED_0 under high-injection conditions. According to our previous researches, this trend of ERE loss rate links to the EL characteristics of a shunt-induced defect, [32][33][34] which is also consistent with our modified carrier-balance model in Figure 2.…”

Section: Resultssupporting

confidence: 89%

“…Ren et al 31 utilized differential EL imaging to identify ohmic and non-ohmic defects in CdTe thin-film solar cells. Our previous works [32][33][34] proposed an approach that coupled distributed equivalent circuit model with absolute EL imaging to quantitatively diagnose electrical defects of GaAs solar cells.…”

Section: Introductionmentioning

confidence: 99%

“…Ren et al 31 utilized differential EL imaging to identify ohmic and non‐ohmic defects in CdTe thin‐film solar cells. Our previous works 32–34 proposed an approach that coupled distributed equivalent circuit model with absolute EL imaging to quantitatively diagnose electrical defects of GaAs solar cells. Numerous indications indicate that defects in single‐junction solar cells affect the device performance a lot since there is no extra junction to compensate for the photon and/or electron losses.…”

Section: Introductionmentioning

confidence: 99%

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Defect‐induced current coupling in multi‐junction solar cells revealed by absolute electroluminescence imaging

Wang

Jia

et al. 2022

Progress in Photovoltaics

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An electroluminescence (EL) anomaly singular spot was observed in an industrystandard InGaP/GaAs multi-junction solar cell (MJSC). Affected by this singular spot, the spatially resolved subcell current distributions were found to exhibit unique opposite characteristics, which we call "defect-induced current coupling." Herein, we conducted systematic investigations to reveal the defect-induced current coupling phenomenon, for the first time, through the absolute EL imaging technique. Specifically, a modified carrier-balance model was first proposed to describe the subcell optoelectronic distribution around the singular spot. Then, optical and electrical properties including subcell non-radiative recombination distributions, J-V characteristics, essential photovoltaic parameters, and energy losses were quantitatively extracted for characterizing the performance inhomogeneity caused by the defect-induced coupling. Moreover, a three-dimensional distributed circuit model was established to numerically simulate the absolute EL emissions and extract local electrical parameters around the singular spot. Simulation results revealed that the defect-induced current coupling phenomenon is attributed to the deterioration of weak-diode and shunt parameters at the GaAs bottom cell, and the efficiency of the MJSC was estimated to be reduced by 0.408% compared with the defect-free MJSC model.

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Section: Resultssupporting

confidence: 89%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Defect‐induced current coupling in multi‐junction solar cells revealed by absolute electroluminescence imaging

Wang

Jia

et al. 2022

Progress in Photovoltaics

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“…Schuss et al [16] used thermographic techniques to characterize defect regions. Wang et al [17] used an image processing pipeline and adaptive thresholding using both adaptive color threshold and window size. This method works on a single PV cell that is rectangular shaped of varying sizes.…”

Section: Related Workmentioning

confidence: 99%

Spectrum Analysis Enabled Periodic Feature Reconstruction Based Automatic Defect Detection System for Electroluminescence Images of Photovoltaic Modules

Yang

Zhang

et al. 2022

Micromachines

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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.

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“…Fig.2 EL defect detection system3.2.2 Hardware systemCombining a convenient automatic detection algorithm with an effective defect diagnosis solution can reduce the sensitivity of defect detection methods to different data, and improve the calculation speed and detection accuracy[24]. Therefore, we designed a set of hand-held EL inspection devices with supporting inspection algorithms and software to make real-time defect detection and classification possible[25][26].Figure3shows the hardware system of the integrated device for EL defect detection designed by us.…”

mentioning

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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Adaptive automatic solar cell defect detection and classification based on absolute electroluminescence imaging

Cited by 26 publications

References 45 publications

Defect‐induced current coupling in multi‐junction solar cells revealed by absolute electroluminescence imaging

Defect‐induced current coupling in multi‐junction solar cells revealed by absolute electroluminescence imaging

Spectrum Analysis Enabled Periodic Feature Reconstruction Based Automatic Defect Detection System for Electroluminescence Images of Photovoltaic Modules

Design of EL defect detection system for photovoltaic power station modules

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