DEFECT DETECTION OF PHOTOVOLTAIC ARRAYS BY FUSING VISIBLE AND INFRARED IMAGES

Bai Xiaojing; Xu Jiawei; Pi Yuxiao; Zhang Wenbiao; Hong Feng; Li Peizhe

doi:10.19912/j.0254-0096.tynxb.2023-2151

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Acta Energiae Solaris Sinica ›› 2025, Vol. 46 ›› Issue (4) : 313-321. DOI: 10.19912/j.0254-0096.tynxb.2023-2151

DEFECT DETECTION OF PHOTOVOLTAIC ARRAYS BY FUSING VISIBLE AND INFRARED IMAGES

Bai Xiaojing, Xu Jiawei, Pi Yuxiao, Zhang Wenbiao, Hong Feng, Li Peizhe

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Abstract

In order to ensure the efficient and safe operation of photovoltaic power generation, it is necessary to detect the operating status of photovoltaic arrays. A defect detection method of photovoltaic array based on the fusion of visible light and infrared images is proposed. CenterNet and U-Net are employed to detect solar cells in visible images and segment the high temperature region of infrared images, respectively. A region matching module is proposed to match visible and infrared images. Point of Interest （PoI） gathering module and secondary classifier are proposed to achieve the aggregation of feature vectors at key points and the classification of solar cells defects. Finally, defective solar cells are identified according to the visible and infrared image recognition results. Different networks are selected for testing. The value of AP50-95 of solar cells detected by the proposed algorithm on the relatively light CenterNet and U-Net networks reaches 84.4%, the IoU of abnormal temperature region segmentation reaches 89.7%, and the time cost of a single image is about 38ms. The results show that the proposed method can complete the detection of abnormal solar cells at a faster speed.

Key words

solar cells / PV arrays / object detection / image segmentation / infrared image / visible image

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Bai Xiaojing, Xu Jiawei, Pi Yuxiao, Zhang Wenbiao, Hong Feng, Li Peizhe. DEFECT DETECTION OF PHOTOVOLTAIC ARRAYS BY FUSING VISIBLE AND INFRARED IMAGES[J]. Acta Energiae Solaris Sinica. 2025, 46(4): 313-321 https://doi.org/10.19912/j.0254-0096.tynxb.2023-2151

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