Author:
Rahimilarki Reihane,Gao Zhiwei,Jin Nanlin,Zhang Aihua
Cited by
9 articles.
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1. Deep Learning Based Anomaly Detection Method for Wind Turbine Blades;2023 International Conference on Intelligent Management and Software Engineering (IMSE);2023-09-08
2. Ordinal few-shot learning with applications to fault diagnosis of offshore wind turbines;Renewable Energy;2023-04
3. CNN-LSTM vs. LSTM-CNN to Predict Power Flow Direction: A Case Study of the High-Voltage Subnet of Northeast Germany;Sensors;2023-01-12
4. Review of the application of deep learning for fault detection in wind turbine;2022 IEEE International Conference on Environment and Electrical Engineering and 2022 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe);2022-06-28
5. Fault Detection in Wind Turbines using Deep Learning;2022 2nd International Mobile, Intelligent, and Ubiquitous Computing Conference (MIUCC);2022-05-08