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Computational Acoustic Beamforming for Noise Source Identification for Small Wind Turbines
This paper develops a computational acoustic beamforming (CAB) methodology for identification of sources of small wind turbine noise. This methodology is validated using the case of the NACA 0012 airfoil trailing edge noise. For this validation case, the predicted acoustic maps were in excellent con...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5362733/ https://www.ncbi.nlm.nih.gov/pubmed/28378012 http://dx.doi.org/10.1155/2017/7061391 |
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author | Ma, Ping Lien, Fue-Sang Yee, Eugene |
author_facet | Ma, Ping Lien, Fue-Sang Yee, Eugene |
author_sort | Ma, Ping |
collection | PubMed |
description | This paper develops a computational acoustic beamforming (CAB) methodology for identification of sources of small wind turbine noise. This methodology is validated using the case of the NACA 0012 airfoil trailing edge noise. For this validation case, the predicted acoustic maps were in excellent conformance with the results of the measurements obtained from the acoustic beamforming experiment. Following this validation study, the CAB methodology was applied to the identification of noise sources generated by a commercial small wind turbine. The simulated acoustic maps revealed that the blade tower interaction and the wind turbine nacelle were the two primary mechanisms for sound generation for this small wind turbine at frequencies between 100 and 630 Hz. |
format | Online Article Text |
id | pubmed-5362733 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-53627332017-04-04 Computational Acoustic Beamforming for Noise Source Identification for Small Wind Turbines Ma, Ping Lien, Fue-Sang Yee, Eugene Int Sch Res Notices Research Article This paper develops a computational acoustic beamforming (CAB) methodology for identification of sources of small wind turbine noise. This methodology is validated using the case of the NACA 0012 airfoil trailing edge noise. For this validation case, the predicted acoustic maps were in excellent conformance with the results of the measurements obtained from the acoustic beamforming experiment. Following this validation study, the CAB methodology was applied to the identification of noise sources generated by a commercial small wind turbine. The simulated acoustic maps revealed that the blade tower interaction and the wind turbine nacelle were the two primary mechanisms for sound generation for this small wind turbine at frequencies between 100 and 630 Hz. Hindawi 2017-03-09 /pmc/articles/PMC5362733/ /pubmed/28378012 http://dx.doi.org/10.1155/2017/7061391 Text en Copyright © 2017 Ping Ma et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Ma, Ping Lien, Fue-Sang Yee, Eugene Computational Acoustic Beamforming for Noise Source Identification for Small Wind Turbines |
title | Computational Acoustic Beamforming for Noise Source Identification for Small Wind Turbines |
title_full | Computational Acoustic Beamforming for Noise Source Identification for Small Wind Turbines |
title_fullStr | Computational Acoustic Beamforming for Noise Source Identification for Small Wind Turbines |
title_full_unstemmed | Computational Acoustic Beamforming for Noise Source Identification for Small Wind Turbines |
title_short | Computational Acoustic Beamforming for Noise Source Identification for Small Wind Turbines |
title_sort | computational acoustic beamforming for noise source identification for small wind turbines |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5362733/ https://www.ncbi.nlm.nih.gov/pubmed/28378012 http://dx.doi.org/10.1155/2017/7061391 |
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