Wind Turbine Blade Icing Diagnosis Using Convolutional LSTM-GRU With Improved African Vultures Optimization

Wind Turbine Blade Icing Diagnosis Using Convolutional LSTM-GRU With Improved African Vultures Optimization

Wind farms are usually located in plateau mountains and northern coastal areas, bringing a high probability of blade icing. Blade icing even leads to blade cracks and turbine collapse. Traditional methods of blade icing diagnosis increase operating costs and have the potential risk of damaging the o...

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Bibliographic Details
Main Authors: Wenhe Chen, Hanting Zhou, Longsheng Cheng, Min Xia
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Open Journal of Instrumentation and Measurement
Subjects:
Adaptive synthetic (ADASYN)
convolutional (Conv) layer
icing diagnosis
stacked long short-term memory (LSTM)-gated recursive unit (GRU)
wind turbine
Online Access:https://ieeexplore.ieee.org/document/9967763/

Internet

https://ieeexplore.ieee.org/document/9967763/

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