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Bayesian Estimation of Remaining Useful Life for Wind Turbine Blades.
- Source :
-
Energies (19961073) . May2017, Vol. 10 Issue 5, p664. 13p. 1 Diagram, 6 Charts, 4 Graphs. - Publication Year :
- 2017
-
Abstract
- To optimally plan maintenance of wind turbine blades, knowledge of the degradation processes and the remaining useful life is essential. In this paper, a method is proposed for calibration of a Markov deterioration model based on past inspection data for a range of blades, and updating of the model for a specific wind turbine blade, whenever information is available from inspections and/or condition monitoring. Dynamic Bayesian networks are used to obtain probabilities of inspection outcomes for a maximum likelihood estimation of the transition probabilities in the Markov model, and are used again when updating the model for a specific blade using observations. The method is illustrated using indicative data from a database containing data from inspections of wind turbine blades. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 19961073
- Volume :
- 10
- Issue :
- 5
- Database :
- Academic Search Index
- Journal :
- Energies (19961073)
- Publication Type :
- Academic Journal
- Accession number :
- 123267168
- Full Text :
- https://doi.org/10.3390/en10050664