Based on the experiences of the aforementioned researchers and the summary of existing photovoltaic module defect detection methods, this paper proposes ST-YOLO, specifically
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This paper develops a novel internal crack detection device for PV panels based on air-coupled ultrasonics and establishes a dedicated model for PV panel crack detection.
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This paper proposes a photovoltaic panel defect detection method based on an improved YOLOv11 architecture. By introducing the CFA and C2CGA modules, the YOLOv11 model is
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To address the current limitations of low precision and high image data requirements in defect detection algorithms based on visible light imaging, this paper proposes a novel visible light
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Aiming at the current PV panel defect detection methods with insufficient accuracy, few defect categories, and the problem that defect targets cannot be localized, this paper proposes a PV panel
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Several electroluminescent photovoltaic defect datasets are used to verify the effectiveness of the proposed model. The experimental results show that the map@50 and
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Based on the intrinsic connection between the surface magnetic field and the internal current of PV panels, this article proposes a current distribution reconstruction and busbar current estimation
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To address these challenges, this paper proposes the LEM-Detector, an efficient end-to-end photovoltaic panel defect detector based on the transformer architecture.
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Advancing renewable energy solutions requires efficient and durable solar Photovoltaic (PV) modules. A novel mechanism based on Deep Learning (DL) and Residual Network (ResNet) for
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A Defect detection model for PV panel electroluminescence images: We developed a defect detection model tailored to EL images of PV panels, addressing the poor detection
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