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Energies 2017, 10(1), 32; doi:10.3390/en10010032

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

1
School of Energy, Power and Mechanical Engineering, North China Electric Power University, Beijing 102206, China
2
Key Laboratory of Condition Monitoring and Control for Power Plant Equipment of Ministry of Education, North China Electric Power University, Beijing 102206, China
3
Mechanical and Industrial Engineering, 3131 Seamans Center, The University of Iowa, Iowa City, IA 52242-1527, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Frede Blaabjerg
Received: 13 September 2016 / Revised: 5 December 2016 / Accepted: 21 December 2016 / Published: 31 December 2016
(This article belongs to the Special Issue Wind Turbine 2017)
View Full-Text   |   Download PDF [4217 KB, uploaded 31 December 2016]   |  

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. View Full-Text
Keywords: remaining useful life (RUL); prognostic; wind turbine; bearing in gearbox remaining useful life (RUL); prognostic; wind turbine; bearing in gearbox
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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.

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