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Prognosis of the Remaining Useful Life of Bearings in a Wind Turbine Gearbox
Journal article   Open access   Peer reviewed

Prognosis of the Remaining Useful Life of Bearings in a Wind Turbine Gearbox

Wei Teng, Xiaolong Zhang, Yibing Liu, Andrew Kusiak and Zhiyong Ma
Energies (Basel), Vol.10(1), pp.32-32
12/31/2016
DOI: 10.3390/en10010032
url
https://doi.org/10.3390/en10010032View
Published (Version of record) Open Access

Abstract

Predicting 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

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