Method for minor defect detection in electroluminescent solar cells based on CSR-YOLOv5s

Abstract

The increasing production of solar cells, resulting from the rapid development of new energy sources, necessitates their inspection during both solar cell production and photovoltaic power plant inspection. Target detection algorithms are widely utilized for defect detection in solar cells. To achieve more accurate detection of minor defects in electroluminescent solar cells, an improved algorithm called CSR-YOLOv5s is proposed in this paper. The CSR-YOLOv5s combines Decoupled Head and CSRBlock with the YOLOv5s baseline model. The CSR-Y OLOv5s demonstrates a 1.1% increase in accuracy and a 2.1% increase in F1-score compared to the YOLOv5s baseline model, resulting in improved accuracy and recall. The algorithm effectively identifies minor defects in electroluminescent solar cells.