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Machine Learning based Identification and Classification of Field-Operation caused Solar Panel Failures observed in Electroluminescence Images

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posted on 23.09.2021, 06:58 by Stefan BordihnStefan Bordihn
Failure or degradation effects lead to power losses in solar panels during their field operation and are identified commonly by electroluminescence imaging. Failures like potential induced degradation and light and enhanced temperature induced degradation require an identification of the electroluminescence pattern over the entire solar panel. As the manual process of analysing patterns is prone to error, we seek for an automatic detection of these failure types. We predict automatically the failure types potential induced degradation and light and enhanced temperature induced degradation by adopting the principle component analysis method in combination with a k-nearest neighbour classifier.

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Email Address of Submitting Author

bordihn@isfh.de

ORCID of Submitting Author

https://orcid.org/0000-0001-7077-7905

Submitting Author's Institution

Institute for Solar Energy Research, Emmerthal, Germany

Submitting Author's Country

Germany

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