IMIS | Flanders Marine Institute
 

Flanders Marine Institute

Platform for marine research

IMIS

Publications | Institutes | Persons | Datasets | Projects | Maps
[ report an error in this record ]basket (0): add | show Printer-friendly version

A modal decomposition and expansion approach for prediction of dynamic responses on a monopile offshore wind turbine using a limited number of vibration sensors
Iliopoulos, A.; Shirzadeh, R.; Weijtjens, W.; Guillaume, P.; Van Hemelrijck, D.; Devriendt, C. (2016). A modal decomposition and expansion approach for prediction of dynamic responses on a monopile offshore wind turbine using a limited number of vibration sensors. Mechanical Systems and Signal Processing 68-69: 84-104. dx.doi.org/10.1016/j.ymssp.2015.07.016
In: Mechanical Systems and Signal Processing. Elsevier: Amsterdam. ISSN 0888-3270, more
Peer reviewed article  

Available in Authors 
    VLIZ: Open Repository 292180 [ OMA ]

Keyword
    Marine
Author keywords
    Modal decomposition; Modal expansion; Response estimation; Structuralhealth Monitoring; Offshore wind turbines; Foundations

Authors  Top 
  • Iliopoulos, A., more
  • Shirzadeh, R., more
  • Weijtjens, W., more
  • Guillaume, P., more
  • Van Hemelrijck, D., more
  • Devriendt, C., more

Abstract
    Structural health monitoring of wind turbines is usually performed by collecting real-time operating data on a limited number of accessible locations using traditional sensors such as accelerometers and strain-gauges. When dealing with offshore wind turbines (OWT) though, most of the fatigue sensitive spots are inaccessible for direct measurements, e.g. at the mudline below the water level. Response estimation techniques can then be used to estimate the response at unmeasured locations from a limited set of response measurements and a Finite Element Model. In this paper the method will be validated using accelerations only. The method makes use of a modal decomposition and expansion algorithm that allows for successful response prediction. The algorithm is first validated using simulated datasets provided from HAWC2 and then using real time data obtained from a monitoring campaign on an offshore Vestas V90 3 MW wind turbine on a monopile foundation in the Belgian North Sea.

All data in IMIS is subject to the VLIZ privacy policy Top | Authors