Using blind signal processing algorithms to remove wind noise from environmental noise assessments : a wind turbine amplitude modulation case study

Kendrick, P; von Hünerbein, S; Cox, TJ

Abstract

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 synthesized wind turbine sounds based on real measurements are used. The simulations show that even relatively low wind speeds of 3 m/s can cause large errors in the AM metrics. Microphone
wind noise is intermittent, and consequently, one solution is to analyze 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.

Citation

Kendrick, P., von Hünerbein, S., & Cox, T. Using blind signal processing algorithms to remove wind noise from environmental noise assessments : a wind turbine amplitude modulation case study. ˜The œJournal of the Acoustical Society of America (Online), 138(3), 1731-1732. https://doi.org/10.1121/1.4933451

• Journal Article Type: Article
• Deposit Date: Jun 28, 2016
• Journal: The Journal of the Acoustical Society of America (JASA)
• Print ISSN: 0001-4966
• Volume: 138
• Issue: 3
• Pages: 1731-1732
• DOI: https://doi.org/10.1121/1.4933451
• Publisher URL: http://dx.doi.org/10.1121/1.4933451
• Related Public URLs: http://scitation.aip.org/JASA