Fault Identification in Solar PV Panels Using Machine Learning: GLCM, HOG, Naive-Bayes - Softcover

S. M., Renuka Devi; S., Keerthana; B., Akhila

 
9786206685517: Fault Identification in Solar PV Panels Using Machine Learning: GLCM, HOG, Naive-Bayes
Softcover
ISBN 10: 6206685519 ISBN 13: 9786206685517
Verlag: LAP LAMBERT Academic Publishing, 2023

Inhaltsangabe

Among the renewable forms of energy, Solar energy is a convincing, clean energy and acceptable worldwide. Solar photovoltaic plants, both ground mounting and the rooftop, are mushrooming throughout the world. One of the significant challenges is the fault identification of the solar photovoltaic module, since a vast power plant condition monitoring of individual panels is cumbersome.This project aims to identify the panel using a thermal imaging system and processes the thermal images using the image processing technique. Similarly, the new and aged solar photovoltaic panels were compared in the image processing technique to identify any fault in the panel. The image of the aged panels containing faults will be recorded and performance will be analyzed using MATLAB software. This book is the work of students B. Akhila, S. Keerthana, G.Meghana, K Meghana.

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Über die Autorin bzw. den Autor

Renuka Devi S M, Completed M.Tech(NITK), and Ph.D(HCU) in the area of Image processing. Published 35 international conference papers in reputed Journals and Conferences like IEEE, ACM and Springer Digital Libraries.

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Verlag
LAP LAMBERT Academic Publishing
Erscheinungsdatum
2023
Sprache
Englisch
ISBN 10 
6206685519
ISBN 13 
9786206685517
Einband
Taschenbuch
Anzahl der Seiten
68
Kontakt zum Hersteller
Nicht verfügbar
Verantwortliche Person
KreGa Onlinehandel GmbH
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info@krega-onlinehandel.de

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