Open AccessLocalization of wind turbine noise using a microphone array in wind tunnel measurements
Author(s) -
Ocker Christof,
Blumendeller Esther,
Berlinger Philipp,
Pannert Wolfram,
Clifton Andrew
Publication year - 2022
Publication title -
wind energy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.743
H-Index - 92
eISSN - 1099-1824
pISSN - 1095-4244
DOI - 10.1002/we.2665
Subject(s) - microphone array , acoustics , wind tunnel , microphone , aerodynamics , noise (video) , turbine , turbine blade , acoustic source localization , wind speed , engineering , aerospace engineering , physics , sound (geography) , sound pressure , meteorology , computer science , artificial intelligence , image (mathematics)
An experimental investigation on scaled wind turbine models in a wind tunnel with a microphone array is presented. Our study focuses on the localization and quantification of aerodynamic noise sources on rotating wind turbine blades with the aim of identifying the contributing factors that have an impact on the source spectra. Therefore, wind tunnel measurements were conducted for three different blade geometries (NACA 4412 shape, Clark‐Y shape, and sickle shape), five pitch angles between −2° and +8° and five wind velocities between 5 and 13 ms ̂−1 . For the localization of rotating sound sources with a microphone array, a rotating beamforming method based on the acoustic ray method is used. The Clean‐SC deconvolution method was used to improve the resolution of the acoustic sources, and integrated spectra were calculated for the individual blades. The sound sources were localized at the wind turbine blades and assigned to the leading edge and trailing edge subregions. The results show a high dependency on the sound source distribution and the source strength with regard to the observed one‐third octave bands, wind velocity, and blade geometry. Hence, the localization of rotating sound sources with a microphone array is a suitable method for the development of wind turbine blades that emit less noise.