Time–Frequency Analysis Based Flow Regime Identification Methods for Airlift Reactors

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.