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Fatigue assessment of offshore wind turbines on monopile foundations using multi-band modal expansion
Iliopoulos, A.; Weijtjens, W.; Van Hemelrijck, D.; Devriendt, C. (2017). Fatigue assessment of offshore wind turbines on monopile foundations using multi-band modal expansion. Wind Energ. 20(8): 1463-1479.
In: Wind Energy. Wiley: Chichester. ISSN 1095-4244; e-ISSN 1099-1824, meer
Peer reviewed article  

Beschikbaar in  Auteurs 

Author keywords
    virtual sensing; offshore wind turbines; fatigue assessment; structuralhealth monitoring

Auteurs  Top 
  • Iliopoulos, A., meer
  • Weijtjens, W., meer
  • Van Hemelrijck, D., meer
  • Devriendt, C., meer

    Offshore wind turbines (OWTs) are subjected to both quasi-static loads originating from variations in the thrust force and dynamic loads linked to turbulence, waves and turbine dynamics. Both types of loads contribute to fatigue life progression and thus define the turbine's age. As a structural health monitoring solution, one could thus directly measure the stress history at fatigue critical locations. However, for OWTs on monopile foundations some fatigue critical locations are located below the seabed. Installing strain sensors at these hotspots is therefore impossible for existing wind turbines. This measurement restriction is overcome by reconstructing the full-field response of the structure based on the limited number of accelerometers and strain sensors (installed at a few easily accessible locations) and a calibrated finite element model of the system. The system model uses a multi-band modal expansion approach constituted of the quasi-static and dynamic contributions. These contributions are superimposed to reconstruct the stress history at all degrees of freedom of the finite element model, and the subsequent assess fatigue life consumption at all fatigue hot spots of the OWT. In this paper, the proposed virtual sensing technique is validated by predicting the stresses in the transition piece with 12 days of consecutive measurements from an operational OWT. The data set contains both variations in environmental and operating conditions as well as extreme events. Finally, a full-field strain assessment in the tower and foundation system of the OWT is demonstrated.

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