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

Wei Teng, Xiaolong Zhang, Yibing Liu, Andrew Kusiak and Zhiyong Ma
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Wei Teng: School of Energy, Power and Mechanical Engineering, North China Electric Power University, Beijing 102206, China
Xiaolong Zhang: School of Energy, Power and Mechanical Engineering, North China Electric Power University, Beijing 102206, China
Yibing Liu: School of Energy, Power and Mechanical Engineering, North China Electric Power University, Beijing 102206, China
Andrew Kusiak: Mechanical and Industrial Engineering, 3131 Seamans Center, The University of Iowa, Iowa City, IA 52242-1527, USA
Zhiyong Ma: School of Energy, Power and Mechanical Engineering, North China Electric Power University, Beijing 102206, China

Energies, 2016, vol. 10, issue 1, 1-16

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.

Keywords: remaining useful life (RUL); prognostic; wind turbine; bearing in gearbox (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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