Computational Acoustic Beamforming for Noise Source Identification for Small Wind TurbinesReport as inadecuate




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International Scholarly Research Notices - Volume 2017 2017, Article ID 7061391, 24 pages - https:-doi.org-10.1155-2017-7061391

Research Article

Department of Mechanical and Mechatronics Engineering, University of Waterloo, Waterloo, ON, Canada N2L 3G1

Defence RandD Canada, Suffield Research Centre, Stn Main, P.O. Box 4000, Medicine Hat, AB, Canada T1A 8K6

Correspondence should be addressed to Ping Ma

Received 28 September 2016; Accepted 10 January 2017; Published 9 March 2017

Academic Editor: Francesco Zirilli

Copyright © 2017 Ping Ma et al. 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.

Abstract

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.





Author: Ping Ma, Fue-Sang Lien, and Eugene Yee

Source: https://www.hindawi.com/



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