Case study - Use of the Nor848A acoustic camera on wind turbines
The acoustic camera system Nor848 is a powerful tool to investigate noise sources. In realtime you listen to a beamformed audio signal so that you can hear individual sources one by one. Immediately you can identify the strongest over all noise source in a multisource environment, and you can do the same analysis for single frequencies, 1/3 or 1/1 octave bands or any given frequency range.
This study shows that in addition to document noise emission from a windturbine, the Nor848 can be a useful tool for predictive maintenance. Anomalies in noise emission from the different parts of the turbine will indicate that the given part should be further investigated to avoid later failure or breakdown.
Three different situations are investigated in this paper
1. Different sound pressure level from the different rotor blades. This can indicate damage on a rotor blade that decrease the efficiency of the turbine, and also it can generate damage from asymmetric wear and tear or even accidents if the blade or parts of the blade fall off.
2. Resonances in the tower giving low frequency noise. This is a major nuisance for neighbours as low frequency noise propagates over long distances. Also as we shall see it might be an indication of need of maintenance as it can be caused by abnormal vibration from the gearbox or the generator itself.
3. Tonal noise is another major source of complaints from neighbours of a wind turbine farm. With an acoustic camera you can locate and document the source of the tonal noise
Differences in sound pressure levels of individual rotorblades
By investigating the waterfall spectrogram differences in noise spectra between the individual blades can easily be discovered.
In this case blade one is the one with the highest level. This can be shown with the spectrogram. Therefore the virtuel microphone is set on the bladetips and the spectrogram should be switched from single (standard) to beam. By analyzing the aerodynamic sounds of the blade, we have to look on the frequencies above 1 kHz. For a better overview the time scaling should be increasd up to 10 sec.
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