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

Renuka Devi S. M. (u. a.)

ISBN 10: 6206685519 / ISBN 13: 9786206685517

Published by LAP LAMBERT Academic Publishing, 2023

About this Item

Fault Identification in Solar PV Panels Using Machine Learning | GLCM, HOG, Naive-Bayes | Renuka Devi S. M. (u. a.) | Taschenbuch | Englisch | 2023 | LAP LAMBERT Academic Publishing | EAN 9786206685517 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Seller Inventory # 128050324

Bibliographic Details

• Title: Fault Identification in Solar PV Panels Using Machine Learning | GLCM, HOG, Naive-Bayes
• Publisher: LAP LAMBERT Academic Publishing
• Publication Date: 2023
• Language: English
• ISBN 10: 6206685519
• ISBN 13: 9786206685517
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 5D millimeters 220 millimeters width by 150 millimeters height by 5 millimeters depth
• Weight: 119 grams
• Seller catalogs:
  • Bücher

About this title

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.