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Research Papers

Imbalance Estimation Without Test Masses for Wind Turbines

[+] Author and Article Information
Ronny Ramlau

 Johannes Kepler University, Industrial Mathematics Institute, Altenbergerstrasse 69, 4040 Linz, Austriaronny.ramlau@jku.at

Jenny Niebsch

 Johann Radon Institute for Computational and Applied Mathematics (RICAM), Altenbergerstrasse 69, 4040 Linz, Austriajenny.niebsch@oeaw.ac.at

J. Sol. Energy Eng 131(1), 011010 (Jan 07, 2009) (7 pages) doi:10.1115/1.3028042 History: Received November 23, 2007; Revised June 02, 2008; Published January 07, 2009

Rotor imbalances of a wind turbine can cause severe damage of the turbine or its components and thus reduce the lifespan and security of the turbine significantly. At present, balancing of the rotor is a time consuming and expensive process due to the necessity of mounting test weights to measure a reference imbalance state. We describe a new method for the detection and reconstruction of imbalances in the rotor of a wind turbine avoiding test weight measurements. The method is based on a wind turbine model, which is derived by the finite element method. In some respect, the model information replaces the information of a reference imbalance state. A mathematical equation linking imbalances and the resulting vibrations is derived using the model. Thus the inverse problem of computing an imbalance from vibration measured at the nacelle is solvable with the usual techniques for ill-posed problems. We show that our model for a wind turbine can be used to predict the vibrations for a given imbalance distribution. In particular, it can be used to reconstruct the imbalance distribution of a wind turbine from noisy measurements in real time, which is verified both for artificial and real data. Also, an optimization strategy is presented in order to adapt the model to the wind turbine at hand. The new method requires a simple model of a wind turbine under consideration but reduces the measuring effort for the computation of balancing weights. It can be implemented into a condition monitoring system (CMS). For the first time, there can be not only an alarm generation but also the actual imbalance and balancing weights and positions can be computed directly from the observed CMS data.

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Copyright © 2009 by American Society of Mechanical Engineers
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Figures

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Figure 2

Model of a wind turbine

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Figure 3

Fourier transform of the measured data (upper image) and a zoom at the rotational frequency Ωrot=0.255Hz. Another peak appears at 3⋅Ωrot due to the movement of the blades through the slip stream of the tower.

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Figure 4

Reconstruction and balancing weights for an imbalance of 350kgm at blade B with a data noise level of 10%

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Figure 5

Vibrational data for an imbalance of 350kgm at blade B and vibrations after balancing with the computed balancing weights

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Figure 6

FFT of raw acceleration data and acceleration and displacement vibration at revolution frequency for a Vestas V80-2MW 95m wind turbine, provided by the company Deutsche WindGuard Dynamics. (a) FFT of raw acceleration data. (b) Acceleration and displacement vibration.

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