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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Fault Identification in Solar PV Panels Using Machine Learning
Verlag:
LAP LAMBERT Academic Publishing Nov 2023, 2023
ISBN 10: 6206685519
ISBN 13: 9786206685517
Neu
Taschenbuch
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. Neuware -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.Books on Demand GmbH, Überseering 33, 22297 Hamburg 68 pp. Englisch. Artikel-Nr. 9786206685517
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Fault Identification in Solar PV Panels Using Machine Learning | GLCM, HOG, Naive-Bayes
Verlag:
LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6206685519
ISBN 13: 9786206685517
Neu
Taschenbuch
Anbieter: preigu, Osnabrück, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. 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. Artikel-Nr. 128050324
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