A Novel Method for Detection of Wind Turbine Blade Imbalance Based on Multi-Variable Spectrum Imaging and Convolutional Neural Network
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Publisher
IEEE
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http://xplorestaging.ieee.org/ielx7/8844507/8865119/08865600.pdf?arnumber=8865600
Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. LSTM Neural Networks Using the SMOTE Algorithm for Wind Turbine Fault Prediction;ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering;2024-02-01
2. Dynamic response analysis of floating wind turbine platform in local fatigue of mooring;Renewable Energy;2023-03
3. Detection of Multiple Faults in a Low-Power Wind Turbine by using Convolutional Neural Networks;2022 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC);2022-11-09
4. Learning the Aerodynamic Design of Supercritical Airfoils Through Deep Reinforcement Learning;AIAA Journal;2021-10
5. Imbalance Detection in Low Power Turbine Through Vibration Signals and Convolutional Neural Networks;2021 XVII International Engineering Congress (CONIIN);2021-06-14
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