A novel stochastic process diffusion model for wind turbines condition monitoring and fault identification with multi-parameter information fusion
Author:
Funder
Natural Science Foundation of Hebei Province
Hebei Province Graduate Innovation Funding Project
National Natural Science Foundation of China
Publisher
Elsevier BV
Reference51 articles.
1. Deep discriminative representation learning for nonlinear process fault detection;Jiang;IEEE Trans. Autom. Sci. Eng.,2020
2. Trends in non-stationary signal processing techniques applied to vibration analysis of wind turbine drive train – a contemporary survey;Uma Maheswari;Mech. Syst. Signal Proc.,2017
3. A novel wind turbine data imputation method with multiple optimizations based on gans;Qu;Mech. Syst. Signal Proc.,2020
4. An online technique for condition monitoring the induction generators used in wind and marine turbines;Yang;Mech. Syst. Signal Proc.,2013
5. Maximum power point tracking strategy for large-scale wind generation systems considering wind turbine dynamics;Huang;IEEE Trans. Ind. Electron.,2015
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