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Title: Reliability analysis for wind turbines with incomplete failure data collected from after the date of initial installation
Authors: Guo, Haitao
Watson, Simon J.
Tavner, Peter J.
Xiang, Jianping
Keywords: Reliability
Failure rate
Three-parameter Weibull model
Maximum likelihood
Least squares
Wind turbines
Issue Date: 2009
Publisher: © Elsevier
Citation: GUO, H. ... et al., 2009. Reliability analysis for wind turbines with incomplete failure data collected from after the date of initial installation. Reliability Engineering and System Safety, 94 (6), pp. 1057 - 1063
Abstract: Reliability has an impact on wind energy project costs and benefits. Both life test data and field failure data can be used for reliability analysis. In wind energy industry, wind farm operators have greater interest in recording wind turbine operating data. However, field failure data may be tainted or incomplete, and therefore it needs a more general mathematical model and algorithms to solve the model. The aim of this paper is to provide a solution to this problem. A three-parameter Weibull failure rate function is discussed for wind turbines and the parameters are estimated by maximum likelihood and least squares. Two populations of German and Danish wind turbines are analyzed. The traditional Weibull failure rate function is also employed for comparison. Analysis shows that the three-parameter Weibull function can obtain more accuracy on reliability growth of wind turbines. This work will be helpful in the understanding of the reliability growth of wind energy systems as wind energy technologies evolving. The proposed three-parameter Weibull function is also applicable to the life test of the components that have been used for a period of time, not only in wind energy but also in other industries.
Description: This article was published in the journal, Reliability Engineering & System Safety [© Elsevier]. The definitive version is available at: http://dx.doi.org/10.1016/j.ress.2008.12.004
Version: Accepted for publication
DOI: 10.1016/j.ress.2008.12.004
URI: https://dspace.lboro.ac.uk/2134/9614
Publisher Link: http://dx.doi.org/10.1016/j.ress.2008.12.004
ISSN: 0951-8320
Appears in Collections:Published Articles (Mechanical, Electrical and Manufacturing Engineering)

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