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Energies 2017, 10(4), 466; doi:10.3390/en10040466

Fatigue Reliability Analysis of Wind Turbine Cast Components

1
Department of Civil Engineering, Aalborg University, 9220 Aalborg Ø, Denmark
2
Department of Wind Energy, Technical University Denmark, 4000 Roskilde, Denmark
3
Vestas Technology & Service Solutions, 8200 Aarhus, Denmark
*
Author to whom correspondence should be addressed.
Academic Editor: Simon J. Watson
Received: 14 December 2016 / Revised: 23 February 2017 / Accepted: 28 March 2017 / Published: 2 April 2017
(This article belongs to the Collection Wind Turbines)
View Full-Text   |   Download PDF [1714 KB, uploaded 2 April 2017]   |  

Abstract

The fatigue life of wind turbine cast components, such as the main shaft in a drivetrain, is generally determined by defects from the casting process. These defects may reduce the fatigue life and they are generally distributed randomly in components. The foundries, cutting facilities and test facilities can affect the verification of properties by testing. Hence, it is important to have a tool to identify which foundry, cutting and/or test facility produces components which, based on the relevant uncertainties, have the largest expected fatigue life or, alternatively, have the largest reliability to be used for decision-making if additional cost considerations are added. In this paper, a statistical approach is presented based on statistical hypothesis testing and analysis of covariance (ANCOVA) which can be applied to compare different groups (manufacturers, suppliers, test facilities, etc.) and to quantify the relevant uncertainties using available fatigue tests. Illustrative results are presented as obtained by statistical analysis of a large set of fatigue data for casted test components typically used for wind turbines. Furthermore, the SN curves (fatigue life curves based on applied stress) for fatigue assessment are estimated based on the statistical analyses and by introduction of physical, model and statistical uncertainties used for the illustration of reliability assessment. View Full-Text
Keywords: reliability; casting; fatigue; analysis of covariance (ANCOVA); wind turbines reliability; casting; fatigue; analysis of covariance (ANCOVA); wind turbines
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MDPI and ACS Style

Mirzaei Rafsanjani, H.; Sørensen, J.D.; Fæster, S.; Sturlason, A. Fatigue Reliability Analysis of Wind Turbine Cast Components. Energies 2017, 10, 466.

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