Ensemble-Empirical-Mode-Decomposition method for instantaneous spatial-multi-scale decomposition of wall-pressure fluctuations under a turbulent flow
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This work illustrates the possibilities of the Ensemble-Empirical-Mode-Decomposition (E-EMD) technique for a detailed analysis of the time and space characteristics of the wall-pressure fluctuations under a turbulent flow. Pressure fluctuations are measured with a linear microphone array, for the cases of a turbulent boundary layer and for a diffuse airborne acoustic field. The E-EMD technique is shown to be an efficient tool for representing the spatial scales of the turbulent fluctuations at each instant. In particular, this representation is obtained without any particular assumption or a priori information on the data (e.g. temporal or spatial stationarity of the wall pressure data is not required), and acts, when applied to wide-band turbulent signals, as a wavenumber filter. Finally, it is shown how, to some extent, the E-EMD technique can separate at each instant the acoustic (propagative) from the hydrodynamic (convective) energy.
KeywordsTurbulent Boundary Layer Empirical Mode Decomposition Frequency Response Function Ensemble Empirical Mode Decomposition Intrinsic Mode Function
The authors warmly acknowledge Yves Corvez, Laurent Philippon and Pascal Biais for their technical support.
- Ai S, Li H (2008) Gear fault detection based on ensemble empirical mode decomposition and Hilbert–Huang transform. In: Proceedings of the 2008 fifth international conference on fuzzy systems and knowledge discovery, vol 3, p 173Google Scholar
- Arguillat B, Ricot D, Robert G, Bailly C (2005) Measurements of the wavenumber–frequency spectrum of wall pressure fluctuations under turbulent flows. In: Proceedings of 11th AIAA/CEAS aeroacoustics conference (26th AIAA aeroacoustics conference), Monterey, CaliforniaGoogle Scholar
- Bogey C, Bailly C (2008) Recent developments in Direct Noise Computation of turbulent flows: numerical methods and applications. In: Proceedings of 37th inter- noise congress, Shanghai, ChinaGoogle Scholar
- Corcos GM (1963) Resolution of pressure in turbulence. J Acoust Soc Am 35(2):192Google Scholar
- Debert S, Pachebat M, Valeau V, Gervais Y (2007) Experimental wave number separation of wall-pressure fluctuations beneath a turbulent boundary layer. In: Proceedings of 19th international congress of acoustics ICA2007, MadridGoogle Scholar
- Fulton M, Soraghan PJJ (2006) Ensemble Empirical Mode Decomposition applied to musical tempo estimation. In: Digital music research conference DMRN-06, Goldsmiths College, University of LondonGoogle Scholar
- Garello R (2008) Two-dimensional signal analysis. ISTE, LondonGoogle Scholar
- Hinze JO (1975) Turbulence: an introduction to its mechanism and theory, 2nd edn. McGraw-Hill Book Co., New YorkGoogle Scholar
- Huang NE, Shen SSP (2005) Hilbert–Huang transform and its applications. Interdisciplinary mathematical sciences, vol 5, World Scientific Publishing Co. Pte. Ltd, HackensackGoogle Scholar
- Huang XY, Schmitt FG, Lu ZM, Liu YL (2008) An amplitude-frequency study of turbulent scaling intermittency using Empirical Mode Decomposition and Hilbert spectral analysis. Europhys Lett 84(4)Google Scholar