Condition Assessment and Residual Life Prediction for Gearbox Bearing of Wind Turbine

doi:10.11930/j.issn.1004-9649.2017.04.141.05

Abstract

Abstract: In order to improve reliability and economy of wind turbine, a method based on Markov chain is proposed. It is used for assessing operating condition and predicting residual life of gearbox bearing of wind turbine. Firstly, the degradation process of bearing wear status is described by Gamma distribution whose parameters can be estimated by using maximum likelihood estimation method. Secondly, the wear status of gearbox bearing are divided into four levels, and the corresponding upper and lower bounds of each level are also determined. Then, state transition probabilities are calculated to construct the state transition matrix. Finally, the proposed method is applied in simulation of wind turbine gearbox bearing. The simulation result verifies the effectiveness of presented method in determining the wear state and residual life of gearbox bearing of wind turbine.

Key words: wind turbine, gearbox bearing, condition assessment, Markov chain, residual life prediction

CLC Number:

TM315

ZHAO Hongshan, ZHANG Jianping, GAO Duo, LI Lang. Condition Assessment and Residual Life Prediction for Gearbox Bearing of Wind Turbine[J]. Electric Power, 2017, 50(4): 141-145.

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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.2017.04.141.05

https://www.electricpower.com.cn/EN/Y2017/V50/I4/141

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