Traditional solar cell surface defect detection methods contain laser scanning method [ 3 ], acoustic wave method [ 4] and Hertzian spectroscopy method [ 5 ], but the preprocessing is time-consuming and labor-intensive, and the detection accuracy is low.
The surface defects such as cracks, broken cells and unsoldered areas on the solar cell caused by manufacturing process defects or artificial operation seriously affect the efficiency of solar cell.
However, the production process of solar panels is complex and the substrate is fragile, and process defects or human errors can easily lead to subtle, hidden and hard-to-detect defects such as cracks, broken cells and unsoldered areas on the surface of solar cells [ 1 ].
The EL image can distinctly highlight barely visible defects as dark objects, but it also shows random dark regions in the background, which makes automatic inspection in EL images very difficult. A self-reference scheme based on the Fourier image reconstruction technique is proposed for defect detection of solar cells with EL images.
Some obvious defects, such as large breaks, can be directly observed from the imaged surface of a solar cell, although the random crystal grain background can camouflage the defects.
Small cracks, breaks, and finger interruptions are severe defects found in solar cells. Some of the defects, such as interior small cracks, cannot be visually observed in the image with the conventional CCD imaging system. The electroluminescence imaging technique is thus used to highlight the defects in the sensed image.