Gearboxes have been prone to early failure rather than any mechanical part of modern wind turbines, much earlier than their predicted design life. Some studies indicated that gearboxes of wind turbines fail during the first 3 to 5 years of operation of the system as opposed to the total design life of the wind turbine, which usually is 20 years. Consequently, such failures cause the highest down time and extremely expensive replacement activities. Gearboxes are subjected to torsional, bending and axial wind loads which are yet not fully defined. The uncertainty in loading conditions and system design parameters has brought about the importance of considering probabilistic design and modeling approach than the traditional deterministic approach. Accordingly, the motivation of this study is to improve the reliability of gearboxes for wind turbine applications. A probabilistic multibody dynamic modeling of the gearbox, that fully integrates uncertainties in wind loading and design parameters, is sought. This paper presents previous studies and finally proposes the above mentioned approach as a potential way of improving, in general, the reliability of wind energy and, in particular, the gearboxes in wind turbines.
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ASME 2011 International Mechanical Engineering Congress and Exposition
November 11–17, 2011
Denver, Colorado, USA
Conference Sponsors:
- ASME
ISBN:
978-0-7918-5493-8
PROCEEDINGS PAPER
Probabilistic Multibody Modeling of Gearboxes for Wind Turbines
Fisseha M. Alemayehu,
Fisseha M. Alemayehu
Texas Tech University, Lubbock, TX
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Stephen Ekwaro-Osire
Stephen Ekwaro-Osire
Texas Tech University, Lubbock, TX
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Fisseha M. Alemayehu
Texas Tech University, Lubbock, TX
Stephen Ekwaro-Osire
Texas Tech University, Lubbock, TX
Paper No:
IMECE2011-64639, pp. 793-804; 12 pages
Published Online:
August 1, 2012
Citation
Alemayehu, FM, & Ekwaro-Osire, S. "Probabilistic Multibody Modeling of Gearboxes for Wind Turbines." Proceedings of the ASME 2011 International Mechanical Engineering Congress and Exposition. Volume 7: Dynamic Systems and Control; Mechatronics and Intelligent Machines, Parts A and B. Denver, Colorado, USA. November 11–17, 2011. pp. 793-804. ASME. https://doi.org/10.1115/IMECE2011-64639
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