Fluid flow signals processing based on fractional Fourier transform in a stirred tank reactor

The analysis of fluid flow signals and the characterization of fluid flow behavior are of great importance for two-phase flow studies. In this work, the fractional Fourier transform (FRFT), which was based on the optimum order calculated by stepping search method, was proposed to extract the characteristics of fluid flow signals. Meanwhile, the largest Lyapunov exponent (LLE), which is an indication of the chaotic degree of mixing process, was adopted to quantify fluid flow behavior. The maximum amplitude (MA) and LLE value were taken together to inquire into the relationship between the characteristics of fluid flow signals and the characterization of fluid flow behavior. In addition, differences between the two adjacent values (AD) and the maximum differences (MD) are employed to further analyze the differences in behavioral characterization with MA and LLE. The results show that the MA value performs the same increasing trend as the LLE value when the gas flow rate and agitation speed increase. AD and MD values of the MA are one to two orders of magnitude greater than those of the LLE. The eigenvalues (MA) solved by the FRFT method is facilitates capturing small changes owing to changes in external conditions. These findings can provide new ideas for the extraction and characterization of fluid flow behavior.