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Keywords:

  • multiphase flow system;
  • acoustic emission;
  • structure characteristics;
  • wavelet transform;
  • rescaled range analysis;
  • particle size distribution;
  • suspension height

Abstract

This investigation was performed to study the underlying structure characteristics of acoustic emission (AE) signals, which could be helpful not only to understand a relatively complete picture of hydrodynamics in multiphase flow systems, but also to extract the most useful information from the original signals with respect to a particular measurement requirement. However, due to AE signals are made up of emission from many acoustic sources at different scales, the resolution of AE signals is often very complicated and appears to be relatively poorly researched. In this study, the structure characteristics of AE signals measured both in gas–solid fluidized bed and liquid–solid stirred tank were researched in detail by resorting to wavelet transform and rescaled range analysis. A general criterion was proposed to resolve AE signals into three physical-related characteristic scales, i.e., microscale, mesoscale, and macroscale. Multiscale resolution of AE signals implied that AE signals in microscale represented totally the dynamics of solid phase and could be applied to measure particle-related properties. Furthermore, based on the structure characteristics of AE signals, useful features related to particles motion were extracted to establish two new prediction models, one for on-line measurements of particle size distribution (PSD) and average particle size in gas–solid fluidized bed and the other for on-line measurement of the suspension height in liquid–solid stirred tank. The prediction results indicated that (1) measurements of PSD and average particle size using AE method showed a fairly good agreement with that using sieve method both for laboratory scale and plant scale fluidized beds, and (2) measurements of the suspension height using AE method showed a fairly good agreement with that using visual method. The results thus validated that the extracted features based on analyses of structure characteristics of AE signals were very useful for establishing effective on-line measurement models with respect to some particular applications. © 2009 American Institute of Chemical Engineers AIChE J, 2009