Enhancing the Reliability and Efficiency of Solar Systems Through Fault Detection in Solar Cells Using Electroluminescence (EL) Images and YOLO Version 5.0 Algorithm-Reference-Cited by-同舟云学术

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Enhancing the Reliability and Efficiency of Solar Systems Through Fault Detection in Solar Cells Using Electroluminescence (EL) Images and YOLO Version 5.0 Algorithm

Published:2024 Issue: Volume: Page:35-43
ISSN:2199-7373
Container-title:World Sustainability Series
language:en
Short-container-title:

Author:

El yanboiy Naima,Khala Mohamed,Elabbassi Ismail,Elhajrat Nourddine,Eloutassi Omar,El hassouani Youssef,Messaoudi Choukri,Omari Alaoui Ali

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-52419-6_4

Reference15 articles.

1. Abbas MN, Zhang D (2021) A smart fault detection approach for PV modules using adaptive neuro-fuzzy inference framework. Energy Rep

2. Açikgöz H, Korkmaz D (2022) Automatic classification of defective photovoltaic module cells in electroluminescence images. Fırat Üniversitesi Mühendislik Bilimleri Dergisi

3. Aghaei M et al (2022) Review of degradation and failure phenomena in photovoltaic modules. Renew Sustain Energy Rev

4. Chen Z et al (2017) Intelligent fault diagnosis of photovoltaic arrays based on optimized kernel extreme learning machine and I–V characteristics. Appl Energy

5. Chen Z et al (2018) Random forest based intelligent fault diagnosis for PV arrays using array voltage and string currents. Energy Conv Manag

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A PV cell defect detector combined with transformer and attention mechanism;Scientific Reports;2024-09-05

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