Hydraulic fault detection of wind turbine generators using artificial neural networks
In the current context where fossil resources are diminishing globally, and carbon emissions are increasing daily, the importance of green energy, particularly wind energy, is growing significantly.
Tacettin Ahmet Döndüren +1 more
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NeuroVI-based wave compensation system control for offshore wind turbines. [PDF]
Ma F, Liu X, Xu Z, Ding T.
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Dynamic behaviour and power performance of a Septon semisubmersible floating wind turbine integrated with wave energy converters. [PDF]
Sebastian B, Karmakar D, Rao M.
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Hot-Pressed Multicomponent Recycled Textile Polymer Blends Reinforced with Ground GFRP from Wind Turbine Blades: Microstructure-Property Relationships. [PDF]
Wędrychowicz M +7 more
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Adaptive human-robot collaboration in wind turbine manufacturing using digital twins. [PDF]
Malik AA, Masood T.
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Wind Turbine Fault Detection Through Autoencoder-Based Neural Network and FMSA. [PDF]
Nogueira WF, Melani AHA, de Souza GFM.
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Early prediction of wind turbine anomalies using 1D-CNN and temporal feature engineering on multi-source SCADA data. [PDF]
Ata MM, Osama S, Ibraheem MR, Abas AR.
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