Defect detection of solar cells in electroluminescence images using Fourier image reconstruction

• Published in: Solar energy materials and solar cells Vol. 99; pp. 250 - 262
• Main Authors: Tsai, Du-Ming, Wu, Shih-Chieh, Li, Wei-Chen
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.04.2012; Elsevier
• Subjects: Applied sciences; Defect detection; Direct energy conversion and energy accumulation; Electrical engineering. Electrical power engineering; Electrical power engineering; Energy; Exact sciences and technology; Fourier transform; Natural energy; Photoelectric conversion; Photovoltaic conversion; Solar cell; Solar cells. Photoelectrochemical cells; Solar energy; Solar thermal conversion; Solar thermal power plants; Surface inspection; Testing. Reliability. Quality control; Solar cell; Fourier transform; Surface inspection; Defect detection; CCD imaging; Fourier transformation; Electroluminescence; Experimental study; Implementation; Image reconstruction; Grain boundary; Crystalline material; Luminous intensity; Computation time; Solar power plant; Automatic measurement; Imaging; Solar energy; Silicon; Crack
• DOI: 10.1016/j.solmat.2011.12.007
• ISSN: 0927-0248

Solar power is an attractive alternative source of electricity. Solar cells, which form the basis of a solar power system, are mainly based on crystalline silicon. Many defects cannot be visually observed with the conventional CCD imaging system. This paper presents defect inspection of multicrystalline solar cells in electroluminescence (EL) images. A solar cell charged with electrical current emits infrared light, whose intensity is lower at intrinsic crystal grain boundaries and extrinsic defects of small cracks, breaks, and finger interruptions. 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. The target defects appear as line- or bar-shaped objects in the EL image. The Fourier image reconstruction process is applied to remove the possible defects by setting the frequency components associated with the line- and bar-shaped defects to zero and then back-transforming the spectral image into a spatial image. The defect region can then be easily identified by evaluating the gray-level differences between the original image and its reconstructed image. The reference image is generated from the inspection image itself and, thus, can accommodate random inhomogeneous backgrounds. Experimental results on a set of various solar cells have shown that the proposed method performs effectively for detecting small cracks, breaks, and finger interruptions. The computation time of the proposed method is also fast, making it suitable for practical implementation. It takes only 0.29s to inspect a whole solar cell image with a size of 550×550pixels. [Display omitted] ►The method can detect micro-cracks, breaks, and finger interruptions in solar cells. ► The defects are sensed and highlighted in Electroluminescence (EL) images. ► The algorithm is based on image reconstruction with Fourier transforms.