Abstract
For offshore wind farms, the costs due to operation and maintenance are large, and more optimal planning has the potential of reducing these costs. This paper presents how Bayesian networks can be used for risk-based inspection planning, where the inspection plans are updated each year through the lifetime. Two different approaches are used; one uses a threshold value of the failure probability, and one uses a Limited Memory Influence Diagram. Both methods are tested for an application example using MonteCarlo sampling, and they are both found to be efficient and equally good.
| Originalsprog | Engelsk |
|---|---|
| Titel | ICASP11 : Proceedings of the 11th International Conference on Applications of Statistics and Probability in Civil Engineering : Zurich, Switzerland, 1 - 4 August 2011 |
| Redaktører | Michael H. Faber, Koehler Jochen, Kazuyoshi Nishijima |
| Antal sider | 7 |
| Forlag | CRC Press |
| Publikationsdato | 2011 |
| Sider | 311-317 |
| ISBN (Trykt) | 978-0-415-66986-3 |
| Status | Udgivet - 2011 |
| Begivenhed | The 11th International Conference on Applications of Statistics and Probability in Civil Engineering - Zürich, Schweiz Varighed: 1 aug. 2011 → 4 aug. 2011 |
Konference
| Konference | The 11th International Conference on Applications of Statistics and Probability in Civil Engineering |
|---|---|
| Land/Område | Schweiz |
| By | Zürich |
| Periode | 01/08/2011 → 04/08/2011 |
Emneord
- Wind Farms
- Offshore Wind Farms
- Risk-Based Inspection Planning
- Bayesian Networks
- Failure Probability Value
- Limited Memory Influence Diagram
- MonteCarlo Samplings