Advanced wind turbine blade inspection with hyperspectral imaging and 3D convolutional neural networks for damage detection-Reference-Cited by-同舟云学术

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Advanced wind turbine blade inspection with hyperspectral imaging and 3D convolutional neural networks for damage detection

Published:2024-05 Issue: Volume:16 Page:100366
ISSN:2666-5468
Container-title:Energy and AI
language:en
Short-container-title:Energy and AI

Author:

Rizk Patrick,Rizk Frederic,Karganroudi Sasan Sattarpanah,Ilinca Adrian^ORCID,Younes Rafic,Khoder Jihan

Funder

NSERC

Publisher

Elsevier BV

Reference54 articles.

1. Global Wind Report 2023. 2023, GLOBAL WIND ENERGY COUNCIL (GWEC).

2. Maritime Autonomous Surface Ships: problems and Challenges Facing the Regulatory Process;Issa;Sustainability,2022

3. Chapter 14 - Reliability of wind turbines;Sheng,2023

4. Costs of repair of wind turbine blades: influence of technology aspects;Mishnaevsky Jr;Wind Energy,2020

Cited by 2 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. Research on Integrated Control Strategy for Wind Turbine Blade Life;Sensors;2024-09-03

2. Discriminative features based comprehensive detector for defective insulators;Energy and AI;2024-09

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