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Evaluation of Fatigue Crack Propagation of Gears Considering Uncertainties in Loading and Material Properties

Author

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  • Haileyesus B. Endeshaw

    (Department of Mechanical Engineering, University of Massachusetts Lowell, Lowell, MA 01854, USA)

  • Stephen Ekwaro-Osire

    (Department of Mechanical Engineering, Texas Tech University, Lubbock, TX 79409, USA)

  • Fisseha M. Alemayehu

    (School of Engineering, Computer Science and Mathematics, West Texas A&M University, Canyon, TX 79016, USA)

  • João Paulo Dias

    (Department of Mechanical Engineering, Texas Tech University, Lubbock, TX 79409, USA)

Abstract

Failure prediction of wind turbine gearboxes (WTGs) is especially important since the maintenance of these components is not only costly but also causes the longest downtime. One of the most common causes of the premature fault of WTGs is attributed to the fatigue fracture of gear teeth due to fluctuating and cyclic torque, resulting from stochastic wind loading, transmitted to the gearbox. Moreover, the fluctuation of the torque, as well as the inherent uncertainties of the material properties, results in uncertain life prediction for WTGs. It is therefore essential to quantify these uncertainties in the life estimation of gears. In this paper, a framework, constituted by a dynamic model of a one-stage gearbox, a finite element method, and a degradation model for the estimation of fatigue crack propagation in gear, is presented. Torque time history data of a wind turbine rotor was scaled and used to simulate the stochastic characteristic of the loading and uncertainties in the material constants of the degradation model were also quantified. It was demonstrated that uncertainty quantification of load and material constants provides a reasonable estimation of the distribution of the crack length in the gear tooth at any time step.

Suggested Citation

  • Haileyesus B. Endeshaw & Stephen Ekwaro-Osire & Fisseha M. Alemayehu & João Paulo Dias, 2017. "Evaluation of Fatigue Crack Propagation of Gears Considering Uncertainties in Loading and Material Properties," Sustainability, MDPI, vol. 9(12), pages 1-15, November.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:12:p:2200-:d:120830
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    References listed on IDEAS

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    2. Ossai, Chinedu I. & Boswell, Brian & Davies, Ian J., 2016. "A Markovian approach for modelling the effects of maintenance on downtime and failure risk of wind turbine components," Renewable Energy, Elsevier, vol. 96(PA), pages 775-783.
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