Joint time-frequency domain analysis of F404 engine noise sources using event-based beamforming methods
Spatiospectral lobes are features identified in the noise fields surrounding full-scale tactical aircraft that are unseen in most lab-scale experiments. Prior studies have explored their characteristics in the frequency domain, but a joint time-frequency domain (JTFD) analysis has potential to furth...
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Veröffentlicht in: | The Journal of the Acoustical Society of America 2022-10, Vol.152 (4), p.A257-A257 |
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creator | Olaveson, Tyce Gee, Kent L. Wall, Alan T. Johnson, Jon P. |
description | Spatiospectral lobes are features identified in the noise fields surrounding full-scale tactical aircraft that are unseen in most lab-scale experiments. Prior studies have explored their characteristics in the frequency domain, but a joint time-frequency domain (JTFD) analysis has potential to further explore these phenomena and connect them to source-related events. This paper applies the event-based beamforming technique developed by Vaughn et al. [AIAA J. 2021] to acoustical data collected at a 120-microphone array near a T-7A-installed F404 engine. The algorithm correlates time-domain events between pairs of adjacent microphones to find an event propagation direction and then ray traces to the jet nozzle lipline to identify an apparent source location. In addition to the large-derivative events used previously to identify crackle-related phenomena, this paper uses a JTFD wavelet analysis to expand the possible triggers to extract physical insights into the lobes. The lobe directivities are explored and compared to frequency-domain studies. [Work supported by Grant No. N00014-21-1-2069.] |
doi_str_mv | 10.1121/10.0016198 |
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Prior studies have explored their characteristics in the frequency domain, but a joint time-frequency domain (JTFD) analysis has potential to further explore these phenomena and connect them to source-related events. This paper applies the event-based beamforming technique developed by Vaughn et al. [AIAA J. 2021] to acoustical data collected at a 120-microphone array near a T-7A-installed F404 engine. The algorithm correlates time-domain events between pairs of adjacent microphones to find an event propagation direction and then ray traces to the jet nozzle lipline to identify an apparent source location. In addition to the large-derivative events used previously to identify crackle-related phenomena, this paper uses a JTFD wavelet analysis to expand the possible triggers to extract physical insights into the lobes. The lobe directivities are explored and compared to frequency-domain studies. 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Prior studies have explored their characteristics in the frequency domain, but a joint time-frequency domain (JTFD) analysis has potential to further explore these phenomena and connect them to source-related events. This paper applies the event-based beamforming technique developed by Vaughn et al. [AIAA J. 2021] to acoustical data collected at a 120-microphone array near a T-7A-installed F404 engine. The algorithm correlates time-domain events between pairs of adjacent microphones to find an event propagation direction and then ray traces to the jet nozzle lipline to identify an apparent source location. In addition to the large-derivative events used previously to identify crackle-related phenomena, this paper uses a JTFD wavelet analysis to expand the possible triggers to extract physical insights into the lobes. The lobe directivities are explored and compared to frequency-domain studies. 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Prior studies have explored their characteristics in the frequency domain, but a joint time-frequency domain (JTFD) analysis has potential to further explore these phenomena and connect them to source-related events. This paper applies the event-based beamforming technique developed by Vaughn et al. [AIAA J. 2021] to acoustical data collected at a 120-microphone array near a T-7A-installed F404 engine. The algorithm correlates time-domain events between pairs of adjacent microphones to find an event propagation direction and then ray traces to the jet nozzle lipline to identify an apparent source location. In addition to the large-derivative events used previously to identify crackle-related phenomena, this paper uses a JTFD wavelet analysis to expand the possible triggers to extract physical insights into the lobes. The lobe directivities are explored and compared to frequency-domain studies. [Work supported by Grant No. N00014-21-1-2069.]</abstract><doi>10.1121/10.0016198</doi><tpages>1</tpages></addata></record> |
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title | Joint time-frequency domain analysis of F404 engine noise sources using event-based beamforming methods |
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