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Automatic Tracking of the Modal Parameters of an Offshore Wind Turbine Drivetrain System

Author

Listed:
  • Mahmoud El-Kafafy

    (Department of Mechanical Engineering, Vrije Universiteit Brussel, Brussels 1050-B, Belgium
    Department of Mechanical Design, Helwan University, Cairo 11975, Egypt)

  • Christof Devriendt

    (Department of Mechanical Engineering, Vrije Universiteit Brussel, Brussels 1050-B, Belgium)

  • Patrick Guillaume

    (Department of Mechanical Engineering, Vrije Universiteit Brussel, Brussels 1050-B, Belgium)

  • Jan Helsen

    (Department of Mechanical Engineering, Vrije Universiteit Brussel, Brussels 1050-B, Belgium)

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.

Suggested Citation

  • Mahmoud El-Kafafy & Christof Devriendt & Patrick Guillaume & Jan Helsen, 2017. "Automatic Tracking of the Modal Parameters of an Offshore Wind Turbine Drivetrain System," Energies, MDPI, vol. 10(4), pages 1-15, April.
  • Handle: RePEc:gam:jeners:v:10:y:2017:i:4:p:574-:d:96525
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    Citations

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    Cited by:

    1. Jijian Lian & Ou Cai & Xiaofeng Dong & Qi Jiang & Yue Zhao, 2019. "Health Monitoring and Safety Evaluation of the Offshore Wind Turbine Structure: A Review and Discussion of Future Development," Sustainability, MDPI, vol. 11(2), pages 1-29, January.
    2. Ying Wang & Wensheng Lu & Kaoshan Dai & Miaomiao Yuan & Shen-En Chen, 2018. "Dynamic Study of a Rooftop Vertical Axis Wind Turbine Tower Based on an Automated Vibration Data Processing Algorithm," Energies, MDPI, vol. 11(11), pages 1-21, November.
    3. Nicoletta Gioia & Cédric Peeters & Patrick Guillaume & Jan Helsen, 2019. "Identification of Noise, Vibration and Harshness Behavior of Wind Turbine Drivetrain under Different Operating Conditions," Energies, MDPI, vol. 12(17), pages 1-18, September.

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