Online automatic diagnosis of wind turbine bearings progressive degradations under real experimental conditions based on unsupervised machine learning

Author:

Ben Ali Jaouher,Saidi Lotfi,Harrath Salma,Bechhoefer Eric,Benbouzid Mohamed

Publisher

Elsevier BV

Subject

Acoustics and Ultrasonics

Reference54 articles.

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3. Generator bearing fault diagnosis for wind turbine via empirical wavelet transform using measured vibration signals;Chen;Renewable Energy,2016

4. “Wind Turbine Gearbox Reliability Database, Condition Monitoring, and O&M Research Update”, 19 National Renewable Energy Laboratory (NREL), NREL/PR-5000-63868;Sheng,2016

5. Application of empirical mode decomposition and artificial neural network for automatic bearing fault diagnosis based on vibration signals;Ben Ali;Appl Acoust,2015

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