A wavelet-based separation method for tonal and broadband components of low Reynolds-number propeller noise

Abstract

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.

A multivariate statistical analysis of the noise emitted by an installed propeller

“…Specifically, the PSD was calculated using a Hanning window with 50% of overlap. Considering a sampling frequency of f s = 2 16 Hz and a windowing of win = 2 14 samples, the frequency bandwidth has been set at ∆f = 4 Hz. It is worth noting that in all the three polar angles reported in figure 2, the BPF and the first two harmonics are clearly visible at the lower frequencies resulting in slightly amplified with the ingestion of the boundary layer.…”

“…To further investigate the haystacking behaviour, the second part of the analysis has been performed in the wavelet domain. Unlike the Fourier transform, the wavelet decomposition is a useful tool when it comes to analysing a temporal signal in terms of the time shift (t) and the resolution time scale (s) [13,14]. The formal definition is reported as follows:…”

Interactions of Propellers in Edgewise Flight with Turbulence

“…The broadband noise content observed in Fig. 5 is non-deterministic in nature and will have a substantial contribution from trailing-edge scattering of the blade [40]. Since the propeller is hovering in static conditions, turbulence impingement noise at the leading edge of the propeller blades will contribute to the stochastic noise [12,41].…”

Low-Frequency Intensity Modulation of High-Frequency Rotor Noise

“…In this regard, cyclo-stationary spectral analysis [34] or wavelet-based methods [35] can be considered, but these are beyond the scope of the current paper. It is important to realize that BPFM does not affect an ensemble-averaged spectrum (or any other second-order statistics).…”

“…An in-depth route to separate tonal and broadband components is also useful to explore (particularly when harmonics appear at very high frequencies). In this regard, cyclo-stationary spectral analysis [34] or wavelet-based methods [35] can be considered, but these are beyond the scope of the current paper.…”