Prognosis of the Remaining Useful Life of Bearings in a Wind Turbine Gearbox
AbstractPredicting the remaining useful life (RUL) of critical subassemblies can provide an advanced maintenance strategy for wind turbines installed in remote regions. This paper proposes a novel prognostic approach to predict the RUL of bearings in a wind turbine gearbox. An artificial neural network (NN) is used to train data-driven models and to predict short-term tendencies of feature series. By combining the predicted and training features, a polynomial curve reflecting the long-term degradation process of bearings is fitted. Through solving the intersection between the fitted curve and the pre-defined threshold, the RUL can be deduced. The presented approach is validated by an operating wind turbine with a faulty bearing in the gearbox. View Full-Text
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Teng, W.; Zhang, X.; Liu, Y.; Kusiak, A.; Ma, Z. Prognosis of the Remaining Useful Life of Bearings in a Wind Turbine Gearbox. Energies 2017, 10, 32.
Teng W, Zhang X, Liu Y, Kusiak A, Ma Z. Prognosis of the Remaining Useful Life of Bearings in a Wind Turbine Gearbox. Energies. 2017; 10(1):32.Chicago/Turabian Style
Teng, Wei; Zhang, Xiaolong; Liu, Yibing; Kusiak, Andrew; Ma, Zhiyong. 2017. "Prognosis of the Remaining Useful Life of Bearings in a Wind Turbine Gearbox." Energies 10, no. 1: 32.
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