A new method for identifying flow pattern of spouted fluidized bed by coupling Hilbert–Huang transform characteristics of differential pressure signals in different zones

Abstract

On a cold spouted fluidized bed, this study compares the characteristic differences in intrinsic mode function (IMF) energy and Hilbert–Huang spectrum between the spout zone and annulus zone under different combinations of spouted gas and fluidized gas flow rates for five typical flow patterns. The energy distribution characteristics under different flow patterns are also analyzed. The Hilbert–Huang spectrum and IMF energy of pressure difference signals exhibit distinct variations in different zones as the flow pattern changes. Moreover, there exists a correlation between the energy in the middle-frequency range and the flow pattern. Leveraging the K-means algorithm, the middle-frequency range energy of IMFs in the spout zone and annulus zone is subjected to clustering analysis, leading to the identification of partition boundaries for each flow pattern. Based on this, a flow pattern identification method of spouted fluidized bed coupled with middle-frequency range energy in spout zone and annulus zone is proposed, which has very high identification accuracy.