Automatic detection of microphone wind noise : maximising accuracy of amplitude modulation ratings

von Hünerbein, S ORCID:, Cox, TJ ORCID:, Kendrick, P ORCID: and Bradley, S 2016, Automatic detection of microphone wind noise : maximising accuracy of amplitude modulation ratings , in: Wind Turbine Sound 2016, 17-18/11/2016, Gdansk, Poland.

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Microphone wind noise can corrupt outdoor measurements and recordings. It is a particular problem for wind turbine measurements because these cannot be carried out when the wind speed is low. Wind shields can be used, but often the sound level from the turbine is low and even the most efficient shields may not provide sufficient attenuation of the microphone wind noise. This study starts by quantifying the effect that microphone wind noise has on the accuracy of two commonly used Amplitude Modulation (AM) metrics. A wind noise simulator and synthesised wind turbine sounds based on real measurements are used. The simulations show that even relatively low wind speeds of 2.5 m/s errors of over 4 dBA can result. Microphone wind noise is intermittent, and consequently one solution is to analyse only uncorrupted parts of the recordings. This paper tests whether a single-ended wind noise detection algorithm can automatically find uncorrupted sections of the recording, and so recover the true AM metrics. Tests showed that doing this can reduce the error to ±2 dBA and ±0.5 dBA for the time and modulation-frequency domain AM metrics respectively. The paper goes on to validate the simulation approach by applying the automatic detection to near field recordings from various adjacent microphones in combination with high quality meteorological mast measurements within 40m of the microphones and wind turbines.

Item Type: Conference or Workshop Item (Speech)
Schools: Schools > School of Computing, Science and Engineering
Publisher: EWEA
Funders: Non funded research
Depositing User: Dr Sabine von Hünerbein
Date Deposited: 13 Dec 2016 13:23
Last Modified: 15 Feb 2022 21:31

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