Wavelet-Based Characterization of Spatiospectrotemporal Structures in F404 Engine Jet Noise

Abstract

Spatiospectral lobes are significant contributors to noise radiated from full-scale tactical aircraft. Prior studies have explored lobe frequency-domain characteristics, but a joint time–frequency domain analysis has the potential to further describe these phenomena and connect them to source-related events in the time waveform. This paper uses acoustical data collected from a 120-microphone array near a T-7A-installed F404 engine to characterize the spatiospectral lobes in combinations of the time, frequency, and spatial domains. An event-based beamforming method is used in conjunction with a wavelet transform to determine propagation angles and event source locations corresponding to each of the lobes. Temporospectral events in the wavelet transform are then analyzed using Markov chains. Finally, spatiospectral maps created from the measured data are decomposed into individual lobes using events in the wavelet transform as a guide. The spatiospectrotemporal combination of these three analyses shows that the lobes originate from multiple, overlapping regions along the jet lipline and that each lobe has its own peak radiation angle. Additionally, events corresponding to the spatiospectral lobes occur intermittently and at different times from each other, leading to bursts of acoustic energy with rapidly changing directivities.