Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | Rotating Machinery, Vibro-Acoustics and Laser Vibrometry, Proceedings of the 36th IMAC, A Conference and Exposition on Structural Dynamics 2018 |
| Herausgeber/-innen | Dario Di Maio |
| Seiten | 149-152 |
| Seitenumfang | 4 |
| Publikationsstatus | Veröffentlicht - 5 Juni 2018 |
| Veranstaltung | 36th IMAC, A Conference and Exposition on Structural Dynamics 2018 - , USA / Vereinigte Staaten Dauer: 12 Feb. 2018 → 15 Feb. 2018 |
Publikationsreihe
| Name | Conference Proceedings of the Society for Experimental Mechanics Series |
|---|---|
| ISSN (Print) | 2191-5644 |
| ISSN (elektronisch) | 2191-5652 |
Abstract
A fundamental issue during the planning of offshore wind farms is to determine representative locations for fatigue load monitoring, which can be used to reduce maintenance costs. The contribution of this work is an integrated concept based on geometry variations of the jacket substructure. A hierarchical clustering algorithm, using distance measures between these variations, aims to group turbines according to similar fatigue behavior under consideration of local environmental conditions such as wind speed, water depth, and foundation stiffness. Based on this procedure, common jacket designs for each cluster are determined. Next, one location for each cluster is identified to be most suitable for monitoring. At last, uncertainties in fatigue lifetime for other locations in the cluster are given.
ASJC Scopus Sachgebiete
- Ingenieurwesen (insg.)
- Allgemeiner Maschinenbau
- Ingenieurwesen (insg.)
- Numerische Mechanik
- Ingenieurwesen (insg.)
- Maschinenbau
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- BibTex
- RIS
Rotating Machinery, Vibro-Acoustics and Laser Vibrometry, Proceedings of the 36th IMAC, A Conference and Exposition on Structural Dynamics 2018. Hrsg. / Dario Di Maio. 2018. S. 149-152 (Conference Proceedings of the Society for Experimental Mechanics Series).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Determination of Representative Offshore Wind Turbine Locations for Fatigue Load Monitoring by Means of Hierarchical Clustering
AU - Ehrmann, Andreas
AU - Gebhardt, Cristian Guillermo
AU - Rolfes, Raimund
N1 - Funding information: We gratefully acknowledge the financial support of the German Federal Ministry for Economic Affairs and Energy (research project DEUTSCHE FORSCHUNGSPLATTFORM FÜR WINDENERGIE under FKZ 0325936E) and the Lower Saxony Ministry of Science and Culture (research project VENTUS EFFICIENS under FKZ ZN3024).
PY - 2018/6/5
Y1 - 2018/6/5
N2 - A fundamental issue during the planning of offshore wind farms is to determine representative locations for fatigue load monitoring, which can be used to reduce maintenance costs. The contribution of this work is an integrated concept based on geometry variations of the jacket substructure. A hierarchical clustering algorithm, using distance measures between these variations, aims to group turbines according to similar fatigue behavior under consideration of local environmental conditions such as wind speed, water depth, and foundation stiffness. Based on this procedure, common jacket designs for each cluster are determined. Next, one location for each cluster is identified to be most suitable for monitoring. At last, uncertainties in fatigue lifetime for other locations in the cluster are given.
AB - A fundamental issue during the planning of offshore wind farms is to determine representative locations for fatigue load monitoring, which can be used to reduce maintenance costs. The contribution of this work is an integrated concept based on geometry variations of the jacket substructure. A hierarchical clustering algorithm, using distance measures between these variations, aims to group turbines according to similar fatigue behavior under consideration of local environmental conditions such as wind speed, water depth, and foundation stiffness. Based on this procedure, common jacket designs for each cluster are determined. Next, one location for each cluster is identified to be most suitable for monitoring. At last, uncertainties in fatigue lifetime for other locations in the cluster are given.
KW - Environmental and operational conditions (EOC)
KW - Fatigue load monitoring
KW - Hierarchical cluster algorithm (HCA)
KW - Jacket substructure
KW - Offshore wind farm
UR - http://www.scopus.com/inward/record.url?scp=85060671511&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-74693-7_14
DO - 10.1007/978-3-319-74693-7_14
M3 - Conference contribution
AN - SCOPUS:85060671511
SN - 9783319746920
T3 - Conference Proceedings of the Society for Experimental Mechanics Series
SP - 149
EP - 152
BT - Rotating Machinery, Vibro-Acoustics and Laser Vibrometry, Proceedings of the 36th IMAC, A Conference and Exposition on Structural Dynamics 2018
A2 - Di Maio, Dario
T2 - 36th IMAC, A Conference and Exposition on Structural Dynamics 2018
Y2 - 12 February 2018 through 15 February 2018
ER -