Characterization of fluidized beds hydrodynamics by recurrence quantification analysis and wavelet transform

Abstract This paper reports the development of nonlinear time series analysis technique based on recurrence quantification analysis (RQA) method to characterize the hydrodynamic of gas–solid fluidized beds and a comparison with the obtained results by wavelet transform (WT) analysis method is made. An experimental work has been carried out at varying conditions, e.g. bed diameter (5, 9, 15 cm ID), particle size (150, 300 and 600 μm), bed height at aspect ratios (1, 1.5 and 2) and superficial gas velocities (ranging 0.1–1.7 m/s). Both methods show that by using larger particles and higher aspect ratios, the contribution of macro structures increases in the system. By increasing the gas velocity, finer structures in the bed first lose their contribution and after passing a transition velocity (of about 0.3, 0.5 and 0.7 m/s for sands with mean diameters of 150, 300 and 600 μm respectively) their contribution increases again. While the frequency domain analysis is not sensitive to the effect of scale; the RQA method shows an increase in meso structure contribution by increasing of the bed diameter.

[1]  Todd Pugsley,et al.  A critical evaluation of literature correlations for predicting bubble size and velocity in gas–solid fluidized beds , 2011 .

[2]  Study of transition velocity from bubbling to turbulent fluidisation by recurrence plots analysis on pressure fluctuations , 2013 .

[3]  Yongrong Yang,et al.  Multiscale resolution of fluidized‐bed pressure fluctuations , 2003 .

[4]  M. Mahjoob,et al.  Nonintrusive characterization of fluidized bed hydrodynamics using vibration signature analysis , 2009 .

[5]  Cor M. van den Bleek,et al.  Rapid detection of defluidization using the standard deviation of pressure fluctuations , 2004 .

[6]  M. Coppens,et al.  Application of chaos analysis to multiphase reactors , 2002 .

[7]  Jürgen Kurths,et al.  Recurrence plots for the analysis of complex systems , 2009 .

[8]  Liang-Shih Fan,et al.  Particle image velocimetry for characterizing the flow structure in three-dimensional gas-liquid-solid fluidized beds , 1992 .

[9]  R. O. Dendy,et al.  Recurrence plot statistics and the effect of embedding , 2005 .

[10]  T. Schildhauer,et al.  The regenerative effect of catalyst fluidization under methanation conditions , 2006 .

[11]  L. R. Glicksman,et al.  Dynamic similarity in fluidization , 1994 .

[12]  Wen-ching Yang.  Handbook of Fluidization and Fluid-Particle Systems , 2003 .

[13]  Navid Mostoufi,et al.  Characterization of various structures in gas-solid fluidized beds by recurrence quantification analysis , 2013 .

[14]  D. Ruelle,et al.  Recurrence Plots of Dynamical Systems , 1987 .

[15]  Navid Mostoufi,et al.  Determination of hydrodynamic behavior of gas–solid fluidized beds using statistical analysis of acoustic emissions , 2009 .

[16]  Martin Rüdisüli,et al.  Scale-up of bubbling fluidized bed reactors — A review , 2012 .

[17]  Filip Johnsson,et al.  Characterization of fluidization regimes by time-series analysis of pressure fluctuations , 2000 .

[18]  J. Drahoš,et al.  EVALUATION OF MINIMUM FLUIDIZING VELOCITY IN GAS FLUIDIZED BED FROM PRESSURE FLUCTUATIONS , 1985 .

[19]  Leon R. Glicksman,et al.  Simplified scaling relationships for fluidized beds , 1993 .

[20]  Navid Mostoufi,et al.  Characterization of gas-solid fluidized bed hydrodynamics by vibration signature analysis , 2011 .

[21]  Ted M. Knowlton,et al.  Scale-up of fluidized-bed hydrodynamics , 2005 .

[22]  Martin Rhodes,et al.  Introduction to Particle Technology , 1998 .

[23]  H. T. Bi.  Effects of Measurement Method on Velocities Used to Demarcate the Transition to Turbulent Fluidization , 1995 .

[24]  R. Sotudeh-Gharebagh,et al.  Monitoring of fluidized beds hydrodynamics using recurrence quantification analysis , 2013 .

[25]  F. Takens.  Detecting strange attractors in turbulence , 1981 .

[26]  M. L. Stappen.  Application of Deterministic Chaos Theory in Understanding the Fluid Dynamics Behavior of Gas-Liquid Fluidization , 1992 .

[27]  N. Mostoufi,et al.  Investigating the hydrodynamics of gas–solid bubbling fluidization using recurrence plot , 2012 .

[28]  Navid Mostoufi,et al.  Non-intrusive monitoring of bubbles in a gas-solid fluidized bed using vibration signature analysis , 2009 .

[29]  M. Llop,et al.  Characterization and classification of fluidization regimes by non-linear analysis of pressure fluctuations , 2006 .

[30]  Filip Johnsson,et al.  Characterization of fluid dynamics of fluidized beds by analysis of pressure fluctuations , 2007 .

[31]  G..  A Theory for Multiresolution Signal Decomposition : The Wavelet Representation , 2004 .

[32]  John Nijenhuis,et al.  Monitoring a lab-scale fluidized bed dryer: A comparison between pressure transducers, passive acoustic emissions and vibration measurements , 2010 .

[33]  N. Mostoufi,et al.  Conditional monitoring of moisture content in a fluidized bed dryer by the acoustic emission signature , 2012, Korean Journal of Chemical Engineering.

[34]  Tung-Yu Yang,et al.  Study of transition velocities from bubbling to turbulent fluidization by statistic and wavelet multi-resolution analysis on absolute pressure fluctuations , 2008 .

[35]  Jc Jaap Schouten,et al.  Monitoring the quality of fluidization using the short-term predictability of pressure fluctuations , 1998 .

[36]  M. Schiavetti,et al.  Quantitative estimation of bubble size in PFBC , 1994 .

[37]  Stéphane Mallat,et al.  A Theory for Multiresolution Signal Decomposition: The Wavelet Representation , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[38]  Filip Johnsson,et al.  Time-series analysis of pressure fluctuations in gas–solid fluidized beds – A review , 2011 .

[39]  Hsiaotao Bi,et al.  Effect of measurement method on the velocities used to demarcate the onset of turbulent fluidization , 1995 .

[40]  Jc Jaap Schouten,et al.  Similarity between chaos analysis and frequency analysis of pressure fluctuations in fluidized beds , 2004 .