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Operational Modal Analysis for Assessing the Dynamic Behaviour of Wind Turbines
Figure 3: A Wind Turbine in Operation
or modal parameters, are the parameters of the modal model. Hence,
we needed to identify them experimentally. To identify these
parameters from the measured time series, we used ARTeMIS Extractor
software. We applied a frequency–domain technique (enhanced FDD
[EFDD]) for a preliminary analysis and a time–domain technique (SSI) for
detailed analysis.
Starting the assessment by applying EFDD, we first determined the
power spectral density (PSD) matrix from the measured time series.
Next, we performed a singular value decomposition (SVD) of the PSD
matrix. Modal parameters can be identified easily since the singular
values near the resonant frequency are proportional to the PSD of a
single degree of freedom (SDOF) system. In Figure 4, the curve
progression near 3Hz is highlighted, characterising an identified SDOF
system. All other identified modes for the frequency range up to 12Hz
are also highlighted (red boxes). Because of the spectral characteristics
of ambient wind loading, the lower-frequency modes of the turbine
structure in particular were highly excited. Hence, the singular values
are clearly evident on the left side of Figure 4.
In a detailed analysis, we took advantage of the more sophisticated SSI
techniques in order to improve the parameter identification in the less
excited higher-frequency range and the identification of ‘nearby’
modes. These techniques, working in the time domain, rely on linear
least squares estimation of the underlying parametric model using the
raw measured time series.
Exciting Experimental Results
Looking at Figure 4, it should be noted that all of the dominant peaks
(highlighted by red boxes) display the resonances of the complete wind
turbine; even so, we only measured the responses of the carrier
structure. Using the identification methods described above, we quite
available through companies such as Structural Vibration Solutions A/S. effortlessly extracted all modes of interest of the carrier structure (or,
In order to analyse the recorded data, two main groups of modal more precisely, modes with a dominant carrier structure contribution)
identification methods are available: non-parametric methods, primarily from the measured data. Figure 5 shows two of the carrier’s
developed in the frequency domain (frequency–domain decomposition fundamental mode shapes.
technique [FDD]), and parametric time–domain methods (stochastic
subspace identification technique [SSI]). We refer the interested reader Surprisingly, in combination with the FE model of the complete wind
to the literature for more details of these techniques. turbine (including, besides the finely modelled carrier, at least a mass
and stiffness representation of all other components), we were also
able to obtain nearly all global mode shapes for the entire windOur Practical Experiences
We performed OMA on a 2.5MW wind turbine with a rotor diameter of turbine. We achieved this by using the experimental data for the
100m and a hub height of 98m. This wind turbine type was designed carrier structure and performing a computerised modal correlation
by W2E Wind to Energy GmbH (see advertisement on page 59) and is (utilising the Modal Assurance Criterion [MAC]) with the wind turbine
manufactured by Fuhrländer AG with the type designation FL2500-100. FE model. Again, it took relatively little effort to obtain such
We recorded data both during operation and with the wind turbine spectacular, all-encompassing results, which are usually obtained only
stopped (rotor idling). The wind speed during the tests reached a by expansive experimental investigations. We collected data for just
maximum at about 5m/s; higher wind speeds may improve upon the one hour with all transducers conveniently located inside the machine
results presented here. The insert in cabin (nacelle). Additionally, we were able to verify the industry-wideFigure 2 displays the measurement
model and transducer locations. multibody-based load simulation software Flex5 for its accuracy inFigure 3 shows the wind turbine in
operation, producing power. We recorded vibration responses at the computing all of the wind turbine’s global resonant frequencies and
desired positions over a 60-minute period and sampled with a frequency mode shapes.
of 128Hz. For data acquisition, we utilised a top-class A/D converter
with a high dynamic range in combination with seismic accelerometers. In the case of the carrier structure, we intend to use the evaluated carrier
FE model as a flexible body within a Flexible Multibody Analysis for
advanced load and stress simulations of our wind turbine components.The Identification Procedure
The reader will recall that resonant frequency, modal damping and the To this end we utilised the MSC software ADAMS/ADWIMO. In order to
corresponding mode shape, which together are referred to as ‘modes’ evaluate the carrier FE model, we conducted a correlation between
MODERN ENERGY REVIEW VOLUME 2 ISSUE 1
60
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