Automatic detection of photovoltaic module defects in infrared images with isolated and develop-model transfer deep learning

[Display omitted] •State-of-the-art framework is proposed for automatic defect detection in PV modules.•Infrared images dataset of normal operating and defective PV modules is collected.•Isolated and develop-model transfer deep learning frameworks are proposed.•Isolated & transfer learned method...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	Solar energy Ročník 198; s. 175 - 186
Hlavní autoři:	Akram, M. Waqar, Li, Guiqiang, Jin, Yi, Chen, Xiao, Zhu, Changan, Ahmad, Ashfaq
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York Elsevier Ltd 01.03.2020 Pergamon Press Inc
Témata:	Accuracy Artificial neural networks Automatic defect detection Automation Datasets Deep learning Defects Develop-model transfer deep learning Electroluminescence Infrared imagery Infrared images Infrared imaging Inspection Isolated deep learning Labeling Machine learning Modules Monitoring methods Neural networks Performance enhancement Photovoltaic (PV) modules Photovoltaic cells Photovoltaics Solar energy Thermography Transfer learning Isolated deep learning Automatic defect detection Develop-model transfer deep learning Photovoltaic (PV) modules Infrared images Thermography
ISSN:	0038-092X, 1471-1257
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!