首页|Defect Detection in c-Si Photovoltaic Modules via Transient Thermography and Deconvolution Optimization

Defect Detection in c-Si Photovoltaic Modules via Transient Thermography and Deconvolution Optimization

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Defects may occur in photovoltaic(PV)modules during production and long-term use,thereby threatening the safe operation of PV power stations.Transient thermography is a promising defect detection technology;however,its detection is limited by transverse thermal diffusion.This phenomenon is particularly noteworthy in the panel glasses of PV modules.A dynamic thermography testing method via transient thermography and Wiener filtering deconvolution optimization is proposed.Based on the time-varying characteristics of the point spread function,the selection rules of the first-order difference image for deconvolution are given.Samples with a broken grid and artificial cracks were tested to validate the performance of the optimization method.Compared with the feature images generated by traditional methods,the proposed method significantly improved the visual quality.Quantitative defect size detection can be realized by combining the deconvolution optimization method with adaptive threshold segmentation.For the same batch of PV products,the detection error could be controlled to within 10%.

Photovoltaic moduletransient thermographypoint spread functiondeconvolution optimizationquantitative detection

Zekai Shen、Hanqi Dai、Hongwei Mei、Yanxin Tu、Liming Wang

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State Grid Hangzhou Power Supply Company,State Grid Zhejiang Electric Power Co.,Ltd.,Hangzhou 310000,China

Huairou Power Supply Branch,State Grid Beijing Electric Power Co.,Ltd.,Beijing 101400,China

Tsinghua Shenzhen International Graduate School,Tsinghua University,Shenzhen 518055,China

National Natural Science Foundation of China

51977117

2024

中国电气工程学报(英文)

中国电气工程学报(英文)

ISSN:
年,卷(期):2024.10(1)
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