21 March 2000 Machine vision for solar cell characterization
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Proceedings Volume 3966, Machine Vision Applications in Industrial Inspection VIII; (2000); doi: 10.1117/12.380078
Event: Electronic Imaging, 2000, San Jose, CA, United States
Abstract
An in-line, non-destructive process is being developed for characterizing polycrystalline thin-film and other large area electronic devices using computer vision based imaging of the manufacturing and inspection steps during the device fabrication process. This process is being applied specifically to Cadmium Telluride/Cadmium Sulfide (CdTe/CdS) thin film, polycrystalline solar cells. Our process involves the acquisition of reflective, transmission and electroluminescence (EL) intensity images for each device. The EL intensity images have been processed by use of a modified median cut segmentation. The processed images reveal different gray level regions corresponding to different intensities of EL originating from radiative recombination events occurring within a biased solar cell. Higher efficiency devices show a more uniform intensity distribution in contrast with lower efficiency devices. The uniform intensity regions are made up of gray level intensity values found near the mean of the histogram distribution these are identified as regions of good device performance and are attributed to better material quality and processing. Low intensity regions indicate either material defects or errors in processing. This novel characterization process and analysis are providing new insights into the causes of poor performance in CdTe-based solar cells.
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Miguel Angel Ordaz, Gregory B. Lush, "Machine vision for solar cell characterization", Proc. SPIE 3966, Machine Vision Applications in Industrial Inspection VIII, (21 March 2000); doi: 10.1117/12.380078; https://doi.org/10.1117/12.380078
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KEYWORDS
Electroluminescence

Solar cells

Image segmentation

Image processing

Binary data

Cameras

Machine vision

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