Retrieving spectral information of individual noise sources from aircraft flyover array measurements

Abstract The normalized fan rotational speed per aircraft engine (N1%) is an essential input parameter to noise prediction models, but is often confidential and not directly accessible to researchers. The aircraft acoustic signal characteristics, and specifically the tonal component, can be used to extract this parameter. However, existing methodologies estimate N1% parameters from whole-aircraft spectra, which can lead to inaccurate estimations. This research aims at investigating the various tonal contributions by isolating and reconstructing spectrograms of individual noise sources using acoustic arrays. Using such arrays, it is possible to discriminate between the various components that contribute to the noise emitted by the aircraft, especially between the engines, but also the nose landing gear. From the resulting engine-specific spectrograms the N1% of individual engines for 24 aircraft were obtained. For the A321neo and the B737NG, it is found that, for 80% of the analyzed aircraft, additional engine tones accompany the higher harmonics of the engine blade passage frequency, with these additional tones corresponding to twice the shaft frequency. In addition, it was found that N1% differences between the two engines are reflected in the spectrograms and that a tone stemming from the nose landing gear can be present, resulting in a complex pattern of tones in the whole-aircraft spectrogram. The insights on the various tonal contributions to the received signal are of importance regarding the further development of methods that aim to extract the engine setting from aircraft noise measurements and as such for enabling more accurate noise calculations.

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Publication Details

Journal
CEAS Aeronautical Journal
Published
2026-04-10
DOI
https://doi.org/10.1007/s13272-026-00962-2
Primary Topic
Aerodynamics and Acoustics in Jet Flows
Type
article
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article

Retrieving spectral information of individual noise sources from aircraft flyover array measurements

Mirjam Snellen, Pieter Sijtsma, Irina Besnea, Irene C. Dedoussi
CEAS Aeronautical Journal
Aerodynamics and Acoustics in Jet Flows
article

Retrieving spectral information of individual noise sources from aircraft flyover array measurements

Mirjam Snellen, Pieter Sijtsma, Irina Besnea, Irene C. Dedoussi
article en

Abstract

Abstract The normalized fan rotational speed per aircraft engine (N1%) is an essential input parameter to noise prediction models, but is often confidential and not directly accessible to researchers. The aircraft acoustic signal characteristics, and specifically the tonal component, can be used to extract this parameter. However, existing methodologies estimate N1% parameters from whole-aircraft spectra, which can lead to inaccurate estimations. This research aims at investigating the various tonal contributions by isolating and reconstructing spectrograms of individual noise sources using acoustic arrays. Using such arrays, it is possible to discriminate between the various components that contribute to the noise emitted by the aircraft, especially between the engines, but also the nose landing gear. From the resulting engine-specific spectrograms the N1% of individual engines for 24 aircraft were obtained. For the A321neo and the B737NG, it is found that, for 80% of the analyzed aircraft, additional engine tones accompany the higher harmonics of the engine blade passage frequency, with these additional tones corresponding to twice the shaft frequency. In addition, it was found that N1% differences between the two engines are reflected in the spectrograms and that a tone stemming from the nose landing gear can be present, resulting in a complex pattern of tones in the whole-aircraft spectrogram. The insights on the various tonal contributions to the received signal are of importance regarding the further development of methods that aim to extract the engine setting from aircraft noise measurements and as such for enabling more accurate noise calculations.

CEAS Aeronautical Journal
University of Cambridge (GB), Scalda (NL), Delft University of Technology (NL)
Reduced inequalities, Peace, Justice and strong institutions
Openalex Percentile: Top 9%
Aerodynamics and Acoustics in Jet Flows
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