Table of Contents
International Scholarly Research Notices
Volume 2017, Article ID 7061391, 24 pages
https://doi.org/10.1155/2017/7061391
Research Article

Computational Acoustic Beamforming for Noise Source Identification for Small Wind Turbines

1Department of Mechanical and Mechatronics Engineering, University of Waterloo, Waterloo, ON, Canada N2L 3G1
2Defence R&D Canada, Suffield Research Centre, Stn Main, P.O. Box 4000, Medicine Hat, AB, Canada T1A 8K6

Correspondence should be addressed to Ping Ma; moc.liamg@gnipamylno

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.