(187d) Multiscale Dynamics System Identification of Time Series of Riser Reactor Temperature in FCC Process Based on Hilbert-Huang Transform

In this work, considering the strong nonlinear and multiscale features in FCC process, both Hilbert-Huang Transform (HHT) and phase space reconstruction techniques are applied to identify the multiscale dynamics characteristics of FCC process. Temperature in middle position of riser reactor is an indicator of reaction thermal state, so this time series data was collected from a real industrial FCC process with DCS. HHT method perform well in nonlinear and nonstationary data processing. Eleven intrinsic mode functions (IMF) which represent eleven subscale features and one residence series was decomposed by HHT from the original temperature series (OTS). Each subscale series was analyzed by phase space reconstruction, Grassberger-Procaccia (G-P) algorithm, Largest Lyapunov exponent (LLE), Kolmogorov entropy and correlation dimension (D2) algorithm. Through analyzing, the first subscale IMF(1) with highest instantaneous frequency show the noise behavior while the original temperature series and IMF(2)~IMF(9) show the chaotic behaviors. other series express steady state or period state without deterministic chaotic behaviors. These results indicate that the multiscale dynamics behaviors which caused by different temporal scales exist in the FCC process, and on the other hand, provide a multiscale way to analyze FCC process by using the industrial data.