Abstract
This paper concerns the development of a probabilistic model for riskbased maintenance planning for offshore wind turbines. A prior damage model can be combined with data to give an updated estimate of the probability of failure. For indicators, an indicator model is needed, and this paper presents how Bayesian networks can be used to learn such a model when past data is available.
Original language | English |
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Journal | Proceedings of the International Offshore and Polar Engineering Conference |
Pages (from-to) | 451-457 |
Number of pages | 7 |
ISSN | 1098-6189 |
Publication status | Published - 2011 |
Event | The Twenty-first (2011) International Offshore and Polar Engineering Conference (ISOPE) - Maui, Hawaii, United States Duration: 19 Jun 2011 → 24 Jun 2011 |
Conference
Conference | The Twenty-first (2011) International Offshore and Polar Engineering Conference (ISOPE) |
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Country/Territory | United States |
City | Maui, Hawaii |
Period | 19/06/2011 → 24/06/2011 |
Keywords
- Risk-Based Planning
- Maintenance
- Bayesian Networks
- Indicators