Time–Frequency
Analysis Based Flow Regime Identification
Methods for Airlift Reactors
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Abstract
The flow regime transitions in an airlift reactor were
investigated
based on pressure fluctuation signals. Two time–frequency analysis
methods, i.e., Wigner–Ville distribution and wavelet transform,
were used to extract flow regime characteristics from pressure signals.
The main frequency derived from the smoothed pseudo-Wigner–Ville
distribution of the pressure signal was used to quantify flow regime
transitions in the reactor. Two flow regime transition points were
successfully detected from the evolution of main frequencies of pressure
signals. In addition, the local dynamic characteristics of the pressure
signal at different frequency bands were analyzed by use of the wavelet
transform. A new flow regime identification method based on the wavelet
entropy of the pressure signal was proposed. This method was confirmed
to be reliable and efficient to detect flow regime transitions in
the reactor