Infrared thermography based defect analysis of photovoltaic modules using machine learning
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2020.
Auteurs principaux: | Mobin, Ovib Hassan, Tajwar, Tahmid, Khan, Fariha Reza, Hossain, Shara Fatema |
---|---|
Autres auteurs: | Rahman, Md. Mosaddequr |
Format: | Thèse |
Langue: | en_US |
Publié: |
Brac University
2021
|
Sujets: | |
Accès en ligne: | http://hdl.handle.net/10361/14367 |
Documents similaires
-
Infrared thermography based performance analysis of photovoltaic modules
par: Amin, Moyukh, et autres
Publié: (2019) -
A comparative study and performance analysis of poly and mono Si photovoltaic modules
par: Islam, Mohaimenul
Publié: (2020) -
Autonomous fault diagnosis of commercially available PV modules using high-end deep learning frameworks
par: Tasawar, Ihtyaz Kader, et autres
Publié: (2021) -
Collision avoidance system proposed by a model using NRF24L01 and infrared sensor
par: Khan, Salsabil
Publié: (2018) -
Research on best peer finding using Q-learning using hotspot network
par: Roy, Anu Pria
Publié: (2017)