Dataset for recognition of snail trails and hot spot failures in monocrystalline Si solar panels

This article presents a dataset for thermal characterization of photovoltaic systems to identify snail trails and hot spot failures. This dataset has 277 thermographic aerial images that were acquired by a Zenmuse XT IR camera (7–13 [Formula: see text] wavelength) from a DJI Matrice 100 (1)drone (qu...

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Detalles Bibliográficos
Autores principales: Alfaro-Mejía, Estefanía, Loaiza-Correa, Humberto, Franco-Mejía, Edinson, Restrepo-Girón, Andrés David, Nope-Rodríguez, Sandra Esperanza
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Computer Science
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6811936/
https://www.ncbi.nlm.nih.gov/pubmed/31667220
http://dx.doi.org/10.1016/j.dib.2019.104441
Descripción
Sumario:This article presents a dataset for thermal characterization of photovoltaic systems to identify snail trails and hot spot failures. This dataset has 277 thermographic aerial images that were acquired by a Zenmuse XT IR camera (7–13 [Formula: see text] wavelength) from a DJI Matrice 100 (1)drone (quadcopter). Additionally, our dataset includes the next environmental measurements: temperature, wind speed, and irradiance. The experimental set up consisted in a photovoltaic array of 4 serial monocrystalline Si panels (string) and an electronic equipment emulating a real load. The conditions for images acquisition were stablished in a flight protocol in which we defined altitude, attitude, and weather conditions.

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