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| Fault Classification of a Blade Pitch System in a Floating Wind Turbine Based on a Recurrent Neural Network |
| Seongpil Cho, Jongseo Park, Minjoo Choi |
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J. Ocean Eng. Technol.. 2021;35(4):287-295. Published online July 26, 2021 DOI: https://doi.org/10.26748/KSOE.2021.018 |
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Fault Classification of a Blade Pitch System in a Floating Wind Turbine Based on a Recurrent Neural Network Journal of Ocean Engineering and Technology. 2021;35(4):287-295  Fault detection and diagnosis of a blade pitch system in a floating wind turbine based on Kalman filters and artificial neural networks Renewable Energy. 2021;169:1-13 Model-based fault detection, fault isolation and fault-tolerant control of a blade pitch system in floating wind turbines Renewable Energy. 2018;120:306-321 Impact of a Wind Turbine Blade Pitch Rate on a Floating Wind Turbine During an Emergency Shutdown Operation Volume 9: Ocean Renewable Energy. 2020; Model-based fault detection of blade pitch system in floating wind turbines Journal of Physics: Conference Series. 2016;753:092012 Individual blade pitch control for floating wind turbine based on RBF-SMC 2019 IEEE 3rd Conference on Energy Internet and Energy System Integration (EI2). 2019; Research on Fault Early Warning of Wind Turbine Pitch System based on Long Short-Term Memory Neural Network 2021 China Automation Congress (CAC). 2021; Load response of a two‐rotor floating wind turbine undergoing blade‐pitch system faults Wind Energy. 2023;26(9):946-967 Structural Load Analysis of Floating Wind Turbines Under Blade Pitch System Faults Wind Turbine Control and Monitoring. 2014;301-334 Background of Wind Turbine Blade-Pitch Load Reduction Control Blade-Pitch Control for Wind Turbine Load Reductions. 2018;11-49 |
