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Experimental dynamic identification of modeshape driving wind turbine grid loss event on nacelle testrig

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Listed:
  • Helsen, J.
  • Devriendt, C.
  • Weijtjens, W.
  • Guillaume, P.

Abstract

This paper experimentally investigates a grid loss event on the Gearbox Reliability Collaborative drivetrain mounted on the NREL nacelle testrig. It is shown that during the grid loss event the system vibration is driven by a counter phase rotation of the rotor and generator rotor about the drivetrain flexibility. This behavior results in significant torque oscillations with significant negative torque periods. This work shows that at each zero-crossing the teeth disengage contact, go through the backlash and re-engage at the other flank by means of strain gauge measurements at the HSS pinion teeth. The driving torsional resonance is identified by means of a pLSCF modal identification estimator. Challenges for accurate modal parameter estimation related to harmonic excitation are elaborated and tackled. Finally the dominating eigenfrequency, corresponding modeshape and damping value are determined.

Suggested Citation

  • Helsen, J. & Devriendt, C. & Weijtjens, W. & Guillaume, P., 2016. "Experimental dynamic identification of modeshape driving wind turbine grid loss event on nacelle testrig," Renewable Energy, Elsevier, vol. 85(C), pages 259-272.
    • Handle: RePEc:eee:renene:v:85:y:2016:i:c:p:259-272
    DOI: 10.1016/j.renene.2015.06.046
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    References listed on IDEAS

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    1. Helsen, Jan & Peeters, Pepijn & Vanslambrouck, Klaas & Vanhollebeke, Frederik & Desmet, Wim, 2014. "The dynamic behavior induced by different wind turbine gearbox suspension methods assessed by means of the flexible multibody technique," Renewable Energy, Elsevier, vol. 69(C), pages 336-346.
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    Cited by:

    1. Liu, Fushun & Yang, Qi & Li, Huajun & Li, Wei & Wang, Bin, 2016. "Discrepancy study of modal parameters of a scale jacket-type supporting structure of 3.0-MW offshore wind turbine in water and in air," Renewable Energy, Elsevier, vol. 89(C), pages 60-70.
    2. Verstraeten, Timothy & Nowé, Ann & Keller, Jonathan & Guo, Yi & Sheng, Shuangwen & Helsen, Jan, 2019. "Fleetwide data-enabled reliability improvement of wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 109(C), pages 428-437.
    3. Jamil, Faras & Verstraeten, Timothy & Nowé, Ann & Peeters, Cédric & Helsen, Jan, 2022. "A deep boosted transfer learning method for wind turbine gearbox fault detection," Renewable Energy, Elsevier, vol. 197(C), pages 331-341.

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