The detection of solar cell defects is highly important in the development, production and use of photovoltaic modules. Solar cell defects can be detected by different methods including electroluminescence, photoluminescence and thermography. In this paper, the algorithm for solar cell defect detection by digital image processing using infrared image acquired from thermal camera is proposed. The algorithm is based on comparison of infrared images of testing cell and the sample of high quality solar cell. For the algorithm realization, NI LabVIEW and NI Vision Development Module have been used. The suggested method of defects detection allows to automatically find the location of the defect with high accuracy. This is a practical example, which was tested on the production line using solar cell and thermal camera. The main idea used in the image processing part of the system is particle analysis. It’s described in the paper
oai:noad.sci.am:135814
armenpet@ipia.sci.am ; anna.l.hovhannisyan@gmail.com
Institute for Informatics and Automation Problems ; National Polytechnic University of Armenia
11th International Conference on Computer Science and Information Technologies CSIT 2017
Mar 3, 2021
Jul 17, 2020
18
https://noad.sci.am/publication/149341
Edition name | Date |
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Armen Petrosyan, Infrared Image Processing for Solar Cell Defect Detection | Mar 3, 2021 |