Research on defect detection of photovoltaic cells based on improved mask R-CNN-attention model

Guang Yang; Jun Zhang; Haitao Li; Chenbo Bai

doi:10.1117/12.3039405

4 September 2024 Research on defect detection of photovoltaic cells based on improved mask R-CNN-attention model

Guang Yang, Jun Zhang, Haitao Li, Chenbo Bai

Proceedings Volume 13259, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2024); 132593M (2024) https://doi.org/10.1117/12.3039405
Event: Fourth International Conference on Automation Control, Algorithm, and Intelligent Bionics (ICAIB 2024), 2024, Yinchuan, China

Abstract

Photovoltaic cells play a crucial role in the field of solar power generation. However, they are often affected by defects in photovoltaic panels, which directly harm their performance. In order to solve this problem, this study proposes an improved Mask R-CNN-Attention model for defect detection of photovoltaic cell components. By introducing attention mechanism, the model can focus more accurately on key image areas, and adopts a multi-scale feature pyramid optimization to improve recognition accuracy. The experiment proves that this method has achieved significant improvement in the defect detection of photovoltaic cell components, providing an effective technical means for solving this problem. This innovative method is expected to improve the performance and maintenance efficiency of photovoltaic cell components, bring positive impact to the solar power generation industry, and provide key support for the sustainable performance and maintenance management of photovoltaic cell components.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Guang Yang, Jun Zhang, Haitao Li, and Chenbo Bai "Research on defect detection of photovoltaic cells based on improved mask R-CNN-attention model", Proc. SPIE 13259, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2024), 132593M (4 September 2024); https://doi.org/10.1117/12.3039405

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KEYWORDS

Solar cells

Object detection

Defect detection

Performance modeling

Feature extraction

Semantics

Education and training

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