Wavelet-based decomposition of the tonal-broadband components of propeller noise

Conference Paper (2022)
Author(s)

S. Meloni (University of Roma Tre)

E. de Paola (University of Roma Tre)

Edoardo Grande (TU Delft - Wind Energy)

D Ragni (TU Delft - Wind Energy)

L. G. Stoica (University of Roma Tre)

A. Di Marco (University of Roma Tre)

R. Camussi (University of Roma Tre)

Research Group
Wind Energy
Copyright
© 2022 S Meloni, E. de Paola, E. Grande, D. Ragni, L. G. Stoica, A. Di Marco, R. Camussi
DOI related publication
https://doi.org/10.2514/6.2022-2876
More Info
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Publication Year
2022
Language
English
Copyright
© 2022 S Meloni, E. de Paola, E. Grande, D. Ragni, L. G. Stoica, A. Di Marco, R. Camussi
Research Group
Wind Energy
ISBN (electronic)
978-1-62410-664-4
Reuse Rights

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Abstract

The present study reports a novel wavelet-based method aimed at separating the noise emitted by a single propeller into two contributions, tonal and broadband. An assessment using two different experimental investigations of propellers operating in diverse configurations is presented. The first experiment focuses upon near-field polar microphone array data of a benchmarked low-Reynolds number propeller, in hover and cruise conditions. Measurements were performed in the anechoic tunnel (A-Tunnel) at the low-speed laboratory of TU Delft. The second set of data consists of a test campaign carried out at the Pininfarina Aerodynamic and Aeroacoustic Research Center in Turin (Italy) under the EU funded project ERaCLE. The model comprises a five-bladed propeller installed close to a wing. Pressure signals were acquired using a top-mounted linear microphone array that spans different polar locations. The wavelet-based algorithm able to separate the tonal and broadband contributions through the computation of two-point statistics. The assessment of the decomposition procedure on two very different databases is presented to validate the technique with the aim to extend its range of applications.

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