Abstract
It is common to characterize fluidized bed dynamics using spectral analysis and nonlinear methods such as correlation entropy (Kolmogorov entropy). In this paper, an alternative method, the Hilbert–Huang transform (HHT), a nonlinear and nonstationary time series data analysis method, is applied to experimental data from two independent setups from the literature: circulating fluidized bed (CFB) and bubbling fluidized bed (BFB). Characterization of four representative regimes for the CFB is realized with the Hilbert spectral analysis, HSA. It is also shown in this work that an entropy based on the HHT is capable of reproducing the flow regime boundaries previously identified using other methods. Linear relationships are observed between the HHT entropy, power spectral density (PSD), and average cycle frequency. Likewise for the BFB, the HHT entropy captured the regime change from slugging to turbulent fluidization.
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