Beamforming of Broadband Rotor Noise
Stewart Glegg, Christopher Hickling, N. Agastya Balantrapu, Jarrod T. Banks, Humza Butt, William Nathan Alexander, William John Devenport · AIAA AVIATION 2021 FORUM · 2021
View Video Presentation: https://doi.org/10.2514/6.2021-2189.vid This paper considers the beamforming of rotor noise from a large microphone array in a wind tunnel with a high level of background noise and shows how the array measurements for a single focus point can be compared with the beamformed spectra obtained using a rotor noise prediction code. Using this approach the tunnel background noise, which was dominated by high levels of machinery noise, could be separated from the rotor noise source levels. The parameters needed to populate the prediction model are then optimized so that it is applicable at all angles and ranges from the source in spite of the poor signal to noise ratio in the test environment.