Wind turbine blade bearing fault detection with Bayesian and Adaptive Kalman Augmented Lagrangian Algorithm
Author:
Funder
Research Councils UK
UKRI
Publisher
Elsevier BV
Subject
Renewable Energy, Sustainability and the Environment
Reference28 articles.
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2. G.W.E. Council, Global Wind Report 2016–Annual Market Update, Global Wind Energy Council, Brussels, Belgium.
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5. Simultaneous bearing fault recognition and remaining useful life prediction using joint-loss convolutional neural network;Liu;IEEE Trans. Ind. Inf.,2019
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