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

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

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

Synopsis

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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Éditeur
LAP LAMBERT Academic Publishing
Date d'édition
2023
Langue
anglais
ISBN 10 
6206685519
ISBN 13 
9786206685517
Reliure
Broché
Nombre de pages
68
Coordonnées du fabricant
non disponible
Personne responsable
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