A modal decomposition and expansion approach for prediction of dynamic responses on a monopile offshore wind turbine using a limited number of vibration sensors. (February 2016)

• Record Type: Journal Article
• Authors: Iliopoulos, Alexandros; Shirzadeh, Rasoul; Weijtjens, Wout; Guillaume, Patrick; Hemelrijck, Danny Van; Devriendt, Christof
• Is Part Of: Mechanical systems and signal processing. Volume 68/69(2016)
• Page Start: 84
• Page End: 104
• Publication Date: 2016-02
• Subjects: Modal decomposition -- Modal expansion -- Response estimation -- Structural health Monitoring -- Offshore wind turbines -- Foundations; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2015.07.016
• Languages: English
• ISSNs: 0888-3270

Abstract

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. Highlights: A dynamic response prediction method is applied on an offshore wind turbine. The proposed method is fast, easy to implement, reliable and effective. A limited set of acceleration response measurements and a FE model is utilized. Different operational states of the wind turbine have been examined.