This paper presents an algorithm for the detection of micro-crack defects in the multicrystalline solar cells. This detection goal is very challenging due to the presence of various types of image anomalies like dislocation clusters, grain boundaries, and other artifacts due to the spurious discontinuities in the gray levels. In this work, an algorithm featuring an improved anisotropic diffusion filter and advanced image segmentation technique is proposed. The methods and procedures are assessed using 600 electroluminescence images, comprising 313 intact and 287 defected samples. Results indicate that the methods and procedures can accurately detect micro-crack in solar cells with sensitivity, specificity, and accuracy averaging at 97%, 80%, and 88%, respectively.
This paper presents a review of the machine detection systems for micro-crack inspection of solar wafers and cells. To-date, there are various methods and procedures that have been developed at various laboratories around the world to inspect solar wafers and solar cells for manufacturing defects. This paper on micro-crack detection offers a comprehensive and an up-to-date review of different detection strategies, describing the main features of each technique together with its strengths as well as weaknesses. This paper will benefit researchers and practitioners, especially those who want to develop automatic inspection systems for inspecting solar wafers or solar cells for micro-cracks.
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