Preprints
https://doi.org/10.5194/wes-2021-25
https://doi.org/10.5194/wes-2021-25

  27 Apr 2021

27 Apr 2021

Review status: a revised version of this preprint was accepted for the journal WES and is expected to appear here in due course.

Identification of wind turbine main shaft torsional loads from SCADA measurements using an inverse problem approach

W. Dheelibun Remigius and Anand Natarajan W. Dheelibun Remigius and Anand Natarajan
  • Department of Wind Energy, Technical University of Denmark, Frederiksborgvej 399, 4000 Roskilde, Denmark

Abstract. To assess the structural health and remaining useful life of a wind turbine within wind farms one would require site-specific dynamic quantities such as structural response and modal parameters. In this regard, a novel inverse problem-based methodology is proposed here to identify the dynamic quantities of the drive train main shaft, i.e., torsional displacement and coupled stiffness. As a model-based approach, an inverse problem of a mathematical model concerning the coupled shaft torsional dynamics with SCADA measurements as input is solved. It involves Tikhonov regularisation to smoothen the measurement noise and irregularities on the shaft torsional displacement obtained from measured rotor and generator speed. Subsequently, the regularised torsional displacement along with necessary SCADA measurements is used as an input for the mathematical model and a model-based system identification method called the collage method is employed to estimate the coupled torsional stiffness. It is also demonstrated that the estimated shaft torsional displacement and coupled stiffness can be used to identify the site-specific main shaft torsional loads. It is shown that the torsional loads estimated by the proposed methodology is in good agreement with the aeroelastic simulations of the Vestas V52 wind turbine. Upon successful verification, the proposed methodology is applied to the V52 turbine SCADA measurements to identify the site-specific main shaft torsional loads and damage equivalent load. Since the proposed methodology does not require a design basis or additional measurement sensors, it can be directly applied to wind turbines within a wind farm irrespective of their age.

W. Dheelibun Remigius and Anand Natarajan

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on wes-2021-25', Edward Hart, 19 May 2021
    • AC1: 'Reply on RC1', W.Dheelibun Remigius, 14 Jul 2021
  • RC2: 'Comment on wes-2021-25', Anonymous Referee #2, 30 May 2021
    • AC2: 'Reply on RC2', W.Dheelibun Remigius, 14 Jul 2021

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on wes-2021-25', Edward Hart, 19 May 2021
    • AC1: 'Reply on RC1', W.Dheelibun Remigius, 14 Jul 2021
  • RC2: 'Comment on wes-2021-25', Anonymous Referee #2, 30 May 2021
    • AC2: 'Reply on RC2', W.Dheelibun Remigius, 14 Jul 2021

W. Dheelibun Remigius and Anand Natarajan

W. Dheelibun Remigius and Anand Natarajan

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Short summary
A novel inverse problem-based methodology is developed to estimate the drive train main shaft torsional stiffness and displacement only by acquisition SCADA measurements. It involves Tikhonov regularisation for regularising the measurement data and the collage method for system identification. These estimated quantities can be used to identify the site-specific torsional loads of the main shaft and to quantify the remaining useful life of the main shaft as well as other drive train components.