E3S Web Conf.
Volume 194, 20202020 5th International Conference on Advances in Energy and Environment Research (ICAEER 2020)
|Number of page(s)||6|
|Section||Power Engineering and Power Generation Technology|
|Published online||15 October 2020|
- Crabtree C.J., Feng Y, Tavner P.J.. Detecting incipient wind turbine gearbox failure: a signal analysis method for on-line condition monitoring. Proceeding of European Wind Energy Conference. C. Poland 2010:11-14. [Google Scholar]
- Lu Bin, Li Yaoyu, Wu Xin, A review of recent advance in wind turbine condition monitoring and fault diagnosis. Lincoln: Proceedings of Power Electronics and Machines in Wind Application. C. 2009:1-7. [Google Scholar]
- Hameed Z, Hong Y.S., Cho Y.M., et al. Condition monitoring and fault detection of wind turbines and related algorithm : a review. Renewable and Sustainable Energy Reviews. J. 2009, 13(1):1-39. [Google Scholar]
- Amirat Y, Benbouzid M, Al-Ahmar E, A brief status on condition monitoring and fault diagnosis in wind energy conversion systems. Renewable and Sustainable Energy Reviews. J. 2009, 13(9: 2629-2636. [Google Scholar]
- Guo Peng, David Infield, Yang Xiyun, Wind turbine gearbox condition monitoring using temperature trend analysis. Journal of Chinese Electrical Engineering Science. J. 2011, 31(32):129-136. [Google Scholar]
- Alexios Koltsidopoulos, Papatzimos, Philipp R, Thies, et al. Offshore wind turbine fault alarm prediction. Wind Energy. J. 2019:1779-1788. [Google Scholar]
- Alan Turnbull, James Carroll, Alasdair McDonald, et al. Prediction of wind turbine generator failure using two-stage cluster-classification methodology. Wind Energy. J. 2019: 1593-1602. [Google Scholar]
- Lorenzo Colone, Nikolay Dimitrov, Daniel Straub. Predictive repair scheduling of wind turbine drive-train components based on machine learning. Wind Energy. J. 2019: 1230-1242. [Google Scholar]
- James Carroll, Sofia Koukoura, Alasdair McDonald, et al. Wind turbine gearbox failure and remaining useful life prediction using machine learning techniques. Wind Energy. J. 2019: 360-375. [Google Scholar]
- Pere Marti Puig, Alejandro Blanco M, Juan José Cárdenas, et al. Feature Selection Algorithms for Wind Turbine Failure Prediction. Energies. J. 2019: 453. [Google Scholar]
- Volkan Sevinc, Omer Kucuk, Merih Goltas, A Bayesian network model for prediction and analysis of possible forest fire causes. Forest Ecology and Management. J. 2020:457. [Google Scholar]
- James Carroll, Sofia Koukoura, Alasdair Mcdonald, et al. Wind turbine gearbox failure and remaining useful life prediction using machine learning techniques. Wind Energy. J. 2019, 22(3):360-375. [Google Scholar]
- Pere Martipuig, Alejandro Blancom, J.J Cardenas, et al. Feature selection algorithms for wind turbine failure prediction. Energies. J. 2019, 12(3):453. [Google Scholar]
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