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Automatic tracking of the modal parameters of an offshore wind turbine drivetrain system
El-Kafafy, M.; Devriendt, C.; Guillaume, P.; Helsen, J. (2017). Automatic tracking of the modal parameters of an offshore wind turbine drivetrain system. Energies (Basel) 10(4): 574. https://hdl.handle.net/10.3390/en10040574
In: Energies (Basel). Molecular Diversity Preservation International (MDPI): Basel. ISSN 1996-1073; e-ISSN 1996-1073
Peer reviewed article  

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Trefwoord
    Marien
Author keywords
    modal parameters; offshore wind turbine; drivetrain; tower modes; modetracking

Auteurs  Top 
  • El-Kafafy, M.
  • Devriendt, C.
  • Guillaume, P.
  • Helsen, J.

Abstract
    An offshore wind turbine (OWT) is a complex structure that consists of different parts (e.g., foundation, tower, drivetrain, blades, et al.). The last decade, there has been continuous trend towards larger machines with the goal of cost reduction. Modal behavior is an important design aspect. For tackling noise, vibration, and harshness (NVH) issues and validating complex simulation models, it is of high interest to continuously track the vibration levels and the evolution of the modal parameters (resonance frequencies, damping ratios, mode shapes) of the fundamental modes of the turbine. Wind turbines are multi-physical machines with significant interaction between their subcomponents. This paper will present the possibility of identifying and automatically tracking the structural vibration modes of the drivetrain system of an instrumented OWT by using signals (e.g., acceleration responses) measured on the drivetrain system. The experimental data has been obtained during a measurement campaign on an OWT in the Belgian North Sea where the OWT was in standstill condition. The drivetrain, more specifically the gearbox and generator, is instrumented with a dedicated measurement set-up consisting of 17 sensor channels with the aim to continuously track the vibration modes. The consistency of modal parameter estimates made at consequent 10-min intervals is validated, and the dominant drivetrain modal behavior is identified and automatically tracked.

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