Defect detection and classification of offshore wind turbine rotor blades

With increasing demand for electricity, wind turbines have gained significant attention from the public. Offshore wind power generation has emerged as a popular choice due to its potential to reduce power transmission losses and minimal impact on humans and organisms. However, it also presents chall...

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Veröffentlicht in:	Nondestructive testing and evaluation Jg. 39; H. 4; S. 954 - 975
Hauptverfasser:	Deng, Liwei, Liu, Shanshan, Shi, Wei, Xu, Jiazhong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Abingdon Taylor & Francis 18.05.2024 Taylor & Francis Ltd
Schlagworte:	Algorithms Classification Clustering Condition monitoring deep learning Defects Electric power demand Electricity distribution Feature extraction K-means Machine learning Offshore energy sources Particle swarm optimization PSO algorithms Rotor blades Rotor blades (turbomachinery) S-U-net Transmission loss Turbines VGG16 network Wind power generation Wind turbine rotor blades Wind turbines
ISSN:	1058-9759, 1477-2671
Online-Zugang:	Volltext
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