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Stabilization of Chaos Via Strong Nonlinearities: The Lorenz-Malkus Wheel Under Coulomb and Hystersis Frictions Read chapter Read first chapter

2021 | OriginalPaper | Chapter

Signal Analysis Through the Ensemble Empirical Mode Decomposition and Hilbert-Huang Transform-Application to Vortex Shedding

Authors : Ana Paula Ost, Alexandre Vagtinski de Paula, Sergio Viçosa Möller

Published in: Vibration Engineering and Technology of Machinery

Publisher: Springer International Publishing

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Abstract

This paper presents the application of the Hilbert-Huang transform as a tool for signal analysis. The Hilbert-Huang transform (HHT) enables the analysis of nonstationary and nonlinear data being a combination of the Empirical Mode Decomposition (EMD) and the Hilbert Spectral Analysis (HSA). A noise assisted data analysis method, called Ensemble Empirical Mode Decomposition (EEMD), based on the statistical properties of white noise, was used to overcome EMD problems like mode mixing, and successfully deal with the scale separation. The EEMD was applied to each velocity signal to obtain a collection of Intrinsic Mode Functions (IMF). Vortex shedding in turbulent flows past circular cylinders represents a canonical problem suitable for validating new approaches in experimental analysis, as it has well known features. Experimental data in form of time series from hot wire signals of the turbulent flow past circular cylinders in an aerodynamic channel are employed for the analysis. Cylinder had a diameter of 32 mm. The Reynolds numbers varied from 1.05 × 104 to 3.28 × 104. EEMD provided the localization of particular events in time-frequency space, allowing a complete physical interpretation of the dynamic processes at the corresponding flow scales. The Hilbert Spectral analysis provided an accurate representation of the amplitude-frequency-time distribution of the flow. The most energetic IMFs and the corresponding flow scales were identified from the Mean Square Energy of the IMF components. The application of HHT to the analysis of the hot wire signals obtained in the turbulent wake behind cylinders showed that it is a useful tool for the analysis of turbulent data, allowing the identification of turbulent structures and flow scales.

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Literature
1.
Abbate A, DeCusatis CM, Das PK (2002) Time-frequency analysis of signals. Wavelets and subbands, applied and numerical harmonic analysis. Birkhäuser, Boston, MA, pp 103–187MATH
2.
Achenbach E (1968) Distribution of local pressure and skin friction around a circular cylinder in cross-flow up to Re = 5 × 106. J Fluid Mech 34:625–639CrossRef
3.
Battista BM, Knapp C, McGee T, Goebel V (2007) Application of the empirical mode decomposition and Hilbert-Huang transform to seismic reflection data. Geophysics 72(2):H29–H37CrossRef
4.
Bearman PW (2011) Circular cylinder wakes and vortex-induced vibrations. J Fluids Struct, IUTAM symposium on bluff body wakes and vortex-induced vibrations (BBVIV-6) 27(5):648–658
5.
Bedrosian E (1963) A product theorem for Hilbert transforms. Proc IEEE 51:868–869CrossRef
6.
Bendat JS, Piersol AG (2010) Random data: analysis and measurement procedures, 4th edn. Wiley, New YorkMATHCrossRef
7.
Blevins RD (1990) Flow-induced vibration, 2a edn. Van Nostrand Reinhold, New YorkMATH
8.
Bénard H (1908a) Formation périodique de centres de giration à l’arrière d’un obstacle en mouvement. C.R. Acad Sci 147:839–842
9.
Bénard H (1908b) Etude cinématographique des ramous et des rides produits par la translation d’un obstacle, C.R. Acad. Sci. 147:970–972
10.
Capone A, Klein C, Di Felice F, Miozzi M (2016) Phenomenology of a flow around a circular cylinder at sub-critical and critical Reynolds numbers. Phys Fluids 28:074101CrossRef
11.
Catalano P, Wang M, Iaccarino G, Moin P (2003) Numerical simulation of the flow around a circular cylinder at high Reynolds numbers. Int J Heat Fluid Flow 24:463–469CrossRef
12.
Chen Z-S, Liu F-S, Wang L-P, Liu G-L (2016) Empirical modeless decomposition and modal identification method for nonstationary vibration processes. Ocean Eng 123:291–302CrossRef
13.
Coutanceau M, Defaye J-R (1991) Circular cylinder wake configurations: a flow visualization survey. Appl Mech Rev 44(6):255–305CrossRef
14.
Daubechies I (1992) Ten lectures on wavelets. SIAM – Society for Industrial and Applied Mathematics, Philadelphia
15.
Derakhshandeh JF, Alam MM (2019) A review of bluff body wakes. Ocean Eng 182:475–488CrossRef
16.
Djeridi H, Braza M, Perrin R, Harran G, Cid E, Cazin S (2003) Near-wake turbulence properties around a circular cylinder at high reynolds number. Flow Turbul Combust 71:19–34MATHCrossRef
17.
Fage A, Falkner VM (1931) Further experiments on the flow around a circular cylinder, Aero. Res. Counc. Reports and Memoranda. H.M.S.O, London
18.
19.
Feldman M (2011) Hilbert transform in vibration analysis. Mech Syst Signal Process 25(3):735–802, 1 abr
20.
Flandrin P, Rilling G, Goncalves P (2004) Empirical mode decomposition as a filter bank. IEEE Signal Process Lett 11:112–114CrossRef
21.
Foucher F, Ravier P (2010) Determination of turbulence properties by using empirical mode decomposition on periodic and random perturbed flows. Exp Fluids 49:379–390, 1 ago
22.
Franzini GR, Gonçalves RT, Pesce CP, Fujarra ALC, Mazzilli CEN, Meneghini JR, Mendes P (2015) Vortex-induced vibration experiments with a long semi-immersed flexible cylinder under tension modulation: Fourier transform and Hilbert-Huang spectral analyses. J Braz Soc Mech Sci Eng 37:589–599CrossRef
23.
Gavilán-Moreno CJ (2008) Analysis and simulation of the flow signal in the recirculation loop of a nuclear power station during a bistable flow event. Nuclear Eng Design 238(10):2754–2760, out
24.
Hahn SL (1996) Hilbert transforms in signal processing. Artech House, BostonMATH
25.
Hong J, Kim J, Ishikawa H, Ma Y (2010) Surface layer similarity in the nocturnal boundary layer: the application of Hilbert-Huang transform. Biogeosciences 7:1271–1278CrossRef
26.
Huang Y, Biferale L, Calzavarin E, Sun C, Toschi F (2013) Lagrangian single-particle turbulent statistics through the Hilbert-Huang transform. Phys Rev E 87:041003(R)CrossRef
27.
Huang NE, Shen SS (2005) Hilbert-Huang transform and its applications. World Scientific, SingaporeMATHCrossRef
28.
Huang NE, Shen Z, Long SR (1999) A new view of nonlinear water waves: the Hilbert Spectrum. Annu Rev Fluid Mech 31:417–457MathSciNetCrossRef
29.
Huang NE, Shen Z, Long SR, Wu MC, Shih HH, Zheng Q, Yen N-C, Tung CC, Liu HH (1998) The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proc R Soc Lond A: Math Phys Eng Sci 454:903–995MathSciNetMATHCrossRef
30.
Huang NE, Wu Z, Long SR, Arnold KC, Chen X, Blank K (2009) On instantaneous frequency. Adv Adapt Data Anal 01:177–229MathSciNetCrossRef
31.
Huang NE (2005) Computing instantaneous frequency by normalizing Hilbert transform. US-Patent-6,901, 353
32.
Huang NE, Wu M-LC, Long SR, Shen SSP, Qu W, Gloersen P, Fan KL (2003) A confidence limit for the empirical mode decomposition and Hilbert spectral analysis. In: proceedings of the royal society of London a: mathematical, physical and engineering sciences 459, 2317–2345
33.
34.
Indrusiak MLS, Möller SV (2011) Wavelet analysis of unsteady flows: application on the determination of the Strouhal number of the transient wake behind a single cylinder. Exp Therm Fluid Sci 35:319–327CrossRef
35.
36.
Legua M, Sánchez-Ruiz LM (2017) Cauchy principal value contour integral with applications. Entropy 19:215CrossRef
37.
Mazellier N, Loyer S, Kourta A (2013) Investigation of the turbulent near-wake square cylinder by means of the empirical mode decomposition. In: Proceedings of the international symposium on turbulence and shear flow (TSFP-8), P30, Poitiers, FR
38.
Medina OD, Schmitt FG, Calif R (2015) Multi-scale correlations between synchronized power and wind measurements: a way to characterize turbulent effect in a scale invariant way. In: presented at the European wind energy association, Paris, p 3
39.
Meng H, Liu Z, Yu Y, Wu J (2012) Time-frequency analysis of Hilbert spectrum of pressure fluctuation time series in a Kenics Static Mixer based on empirical mode decomposition. Braz J Chem Eng 29:167–182CrossRef
40.
Miau JJ, Hu CC, Tu JK (2007) Hilbert and Wavelet analyses of unsteady, three-dimensional characteristics of vortex shedding from a circular cylinder. J Chin Soc Mech Eng 28(1):99–109
41.
Miau JJ, Tu JK, Liao TW (2009) Insights into vortex shedding with data analysis. J Fluid Sci Technol 4(2):415–429CrossRef
42.
Mironov, D. S., Lebiga, V. A., Miau, J. J., Pak, A. Yu., and Zinoviev, V. N., 2017, Application of Hilbert-Huang transform for analyzing non-stationary fluctuations of flow characteristics, AIP Conference Proceedings 1893, 030021; https://​doi.​org/​10.​1063/​1.​5007479
43.
Moffat RJ (1988) Describing the uncertainties in experimental results. Exp Thermal Fluid Sci 1:3–17CrossRef
44.
Möller SV, Silveira RS, de Paula AV, Indrusiak MLS, Olinto CR (2015) Some features of the flow on cylinders in aerodynamic channels and considerations about the effect of the blockage ratio - Part 1: single cylinder. ERCOFTAC Bull 104:24–29
45.
Niemann H-J, Hölscher N (1990) A review of recent experiments on the flow past circular cylinders. J Wind Eng Ind Aerodyn 33(1):197–209CrossRef
46.
Ong L, Wallace J (1996) The velocity field of the turbulent very near wake of a circular cylinder. Exp Fluids 20:441–453CrossRef
47.
48.
Parnadeau P, Carlier J, Heitz D, Lamballais E (2008) Experimental and numerical studies of the flow over a circular cylinder at reynolds number 3900. Phys Fluids 20:085101MATHCrossRef
49.
Phillips SC, Gledhill RJ, Essex JW (2003) Application of the Hilbert-Huang transform to the analysis of molecular dynamics simulations. J Phys Chem A 107(24):4869–4876CrossRef
50.
Rinoshika A, Zhou Y (2005) Orthogonal wavelet multi-resolution analysis of a turbulent cylinder wake. J Fluid Mech 524:229–248MATHCrossRef
51.
Roshko A (1961) Experiments on the flow past a circular cylinder at very high Reynolds number. J Fluid Mech 10(3):345–356MATHCrossRef
52.
Silveira RS, Möller SV (2012) Hilbert-Huang transform: a comparison with fourier and wavelet transform for the analysis of the shedding process. In: Proceedings of the 10th international conference on flow-induced vibration (& Flow-Induced Noise), Dublin
53.
Strouhal V (1878) Über eine besondere Art der Tonerregung. Ann Phys Chem 5:216–251. New Series
54.
Townsend AA (1956) The structure of turbulent shear flow. Cambridge University Press, LondonMATH
55.
Tsai F-F, Fan S-Z, Lin Y-S, Huang NE, Yeh J-R (2016) Investigating power density and the degree of nonlinearity in intrinsic components of Anesthesia EEG by the Hilbert-Huang transform: an example using Ketamine and Alfentanil. PLoS ONE 11(12)
56.
Veltcheva A, Guedes Soares C (2016) Nonlinearity of abnormal waves by the Hilbert–Huang Transform method. Ocean Eng [s. l.] 115:30–38
57.
Wieselsberger C (1922) New data on the laws of fluid resistance, National Advisory Committee for Aeronautics. Technical Note ; National Advisory Committee for Aeronautics, Washington DC
58.
Wu Z, Huang NE (2004) A study of the characteristics of white noise using the empirical mode decomposition method. Proc R Soc Lond A: Math Phys Eng Sci 460:1597–1611MATHCrossRef
59.
Wu Z, Huang NE (2009) Ensemble empirical mode decomposition: a noise-assisted data analysis method. Adv Adapt Data Anal 01:1–41CrossRef
60.
Yang JN, Lei Y, Huang N (2004) Hilbert-Huang based approach for structural damage detection. J Eng Mech 130(1):85–95
61.
Zdravkovich MM (1990) Conceptual overview of laminar and turbulent flows past smooth and rough circular cylinders. J Wind Eng Ind Aerodyn 33(1):53–62CrossRef
62.
Zdravkovich MM (1997) Flow around circular cylinders: Volume I: Fundamentals. OUP, Oxford
63.
Zhu L, Qiu X, Luo J, Liu Y (2016) Scale properties of turbulent transport and coherent structure in stably stratified flows. Appl Math Mech 37:443–458MathSciNetCrossRef
64.
Ziada S, Oengören A (1992) Vorticity shedding and acoustic resonance in an in-line tube bundle part I: Vorticity shedding. J Fluids Struct 6:271–292CrossRef
Metadata
Title
Signal Analysis Through the Ensemble Empirical Mode Decomposition and Hilbert-Huang Transform-Application to Vortex Shedding
Authors
Ana Paula Ost
Alexandre Vagtinski de Paula
Sergio Viçosa Möller
Copyright Year
2021
Book
Vibration Engineering and Technology of Machinery

Print ISBN: 978-3-030-60693-0

Electronic ISBN: 978-3-030-60694-7

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-3-030-60694-7_6

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