Autonomous fault diagnosis of commercially available PV modules using high-end deep learning frameworks
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2021.
Asıl Yazarlar: | Tasawar, Ihtyaz Kader, Tanzeem, Abyaz Kader, Ahmed, Tahmid, Zarin, Shah Faiza |
---|---|
Diğer Yazarlar: | Rahman, Md. Mosaddequr |
Materyal Türü: | Tez |
Dil: | English |
Baskı/Yayın Bilgisi: |
Brac University
2021
|
Konular: | |
Online Erişim: | http://hdl.handle.net/10361/15153 |
Benzer Materyaller
-
Infrared thermography based defect analysis of photovoltaic modules using machine learning
Yazar:: Mobin, Ovib Hassan, ve diğerleri
Baskı/Yayın Bilgisi: (2021) -
Infrared thermography based performance analysis of photovoltaic modules
Yazar:: Amin, Moyukh, ve diğerleri
Baskı/Yayın Bilgisi: (2019) -
A two-dimensional fault diagnosis model of induction motors using a gabor filter on segmented images
Yazar:: Uddin, Jia, ve diğerleri
Baskı/Yayın Bilgisi: (2016) -
Fault analysis in solar photovoltaic arrays
Yazar:: Nunneh, Bill N.
Baskı/Yayın Bilgisi: (2023) -
Deep learning based early Glaucoma detection
Yazar:: Islam, Aabrar, ve diğerleri
Baskı/Yayın Bilgisi: (2024)