Wavelet transform has become a common tool for processing non-stationary signals in many different fields. The present paper reports a review of some applications of wavelet in aeroacoustics with a special emphasis on the analysis of experimental data taken in compressible jets. The focus is on three classes of wavelet-based signal processing procedures: (i) conditional statistics; (ii) acoustic and hydrodynamic pressure separation; (iii) stochastic modeling. The three approaches are applied to an experimental database consisting of pressure time series measured in the near field of a turbulent jet. Future developments and possible generalization to other applications, e.g., airframe or propeller noise, are also discussed.

Experiments were conducted to assess the aeroacoustic characteristics of a 30P30N three-element high-lift airfoil fitted with two different types of slat cove fillers in the Aeroacoustic Facility at the University of Bristol. The results are presented for the angle of attack α = 18° at a free-stream velocity of U_∞ = 30 m/s, which corresponds to a chord-based Reynolds number of Re_c = 7 × 10⁵. Simultaneous measurements of the unsteady surface pressure were carried out at several locations in the vicinity of the slat cove and at the far-field location to gain a deeper understanding of the slat noise generation mechanism. The results were analyzed using a higher-order statistical approach to determine the nature of the broadband hump seen at low frequencies for the 30P30N high-lift airfoil observed in recent studies and also to further understand the tone generation mechanism within the slat cavity. Intermittent events induced by the resonant mechanism between the slat and its trailing edge were investigated in detail. A series of correlation and coherence analysis of the unsteady surface pressure measurements was carried out to identify and isolate the low-frequency hump. A wavelet analysis was performed to investigate the nature of the slat-wing resonant intermittent events in both time and frequency domains. Novel approaches, dynamic mode decomposition, and multi-resolution dynamic mode decomposition were applied to the wavelet coefficient moduli to determine the nature of the noise.

Propeller noise generally exhibits a rich mixture of tonal and broadband components related to different physical mechanisms. Specifically, the tones are characterized by having deterministic and persistent characteristics, while the broadband counterpart has random behaviour. The separation is essential for the experimenters as they provide information on the different noise sources. In this framework, the study presents a novel wavelet-based method able to separate the noise emitted by a low Reynolds number propeller into its tonal and broadband components. The technique is applied to an isolated rotor operating under different loading configurations, including hover and cruise conditions. The acoustic pressure data are obtained in the anechoic tunnel (A-tunnel) of the TU Delft low-speed laboratory with a near-field polar and azimuthal distribution of microphones. The method is based upon a threshold varying procedure that separates the tonal and broadband components through the computation of two-point statistics. Advantages and drawbacks with respect to other methodologies already known from the literature are discussed. The application of the method provides the spectral content of the tonal and broadband components as well as the different polar and azimuthal directivity. Specifically, the observed dipole-like shape directivity for the tonal part and flatter broadband OASPL, confirm that the method can provide quite a good separation. Furthermore, the overall flow behaviour is inferred from the decomposition and validated through benchmarked flow visualizations.

Wall-pressure fluctuations induced by a subsonic jet over a wing/flap scaled model have been experimentally investigated in a large-scale wind-tunnel facility. The pressure field on the wing was me...