Computational Acoustic Beamforming for Noise Source Identification for Small Wind Turbines
Author(s) -
Ping Ma,
FueSang Lien,
Eugene Yee
Publication year - 2017
Publication title -
international scholarly research notices
Language(s) - English
Resource type - Journals
ISSN - 2356-7872
DOI - 10.1155/2017/7061391
Subject(s) - nacelle , airfoil , turbine , acoustics , beamforming , noise (video) , wind power , computer science , naca airfoil , small wind turbine , aeroacoustics , marine engineering , aerospace engineering , sound pressure , meteorology , engineering , telecommunications , physics , reynolds number , turbulence , electrical engineering , artificial intelligence , image (mathematics)
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.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom