| Gas-solid fluidized beds have been assumed as important equipment in the production process in chemical and energy industry. Information of flow regimes and their transition is needed in the model building, design, research and development due to the importance of improving the performance of fluidized beds and increasing the heat transfer rate and mass transfer rate. The detection or identification of the parameters characterizing different flow regimes has long been a significant topic in the parameter measurement of two-phase system.Pressure fluctuation time series in gas-solid fluidized beds contain a lot of dynamic information, such as the information of flow regimes and transition states. Since gas-solid fluidized beds are a complex nonlinear time-varying system under wide operation, nonlinear theory is adopted and implemented to extract the characters of pressure fluctuation time series in gas-solid fluidized beds and find the new way to flow regime identification. Some new technologies and new ideas about the flow regime identification are discussed in this paper so as to cognize the fluidization from a new viewpoint in depth.Based on a large amount of experimental data, nonlinear analysis, such as Hilbert-Huang Transform (HTT), mutual information and fuzzy information fusion theory, are used in the time series analysis of pressure fluctuation in gas-solid fluidized beds for the first time. Application of nonlinear theory to the flow regime identification is discussed systematically from the aspects of theory and experiment. Finally, three kinds of regime-identification methods are proposed and proved to be suitable for using in practical industrial fields and experimental studies.In this study for the first time, the Hilbert-Huang Transform (HHT) is applied to analysis of the pressure-fluctuation in gas-fluidized beds. By using this new nonlinear and non-stationary signal-processing method, the Intrinsic Mode Functions (IMFs) are extracted from the pressure fluctuation signals and the time-frequency-energy distribution called Hilbert spectrum is established. From the spectrum the relationship between the flow transition and the energy distribution can be found. With the following study, the corresponding relations of the energy-transmission between different orders of Intrinsic Mode Functions (IMFs) under different flow states are obtained. Based on it, a new method, with which the energy-transmission between IMFs of pressure fluctuations andthe energy distribution in different IMFs can be used to detect the flow regime identification, is formed in this study. Because of the speed of analyzing by the new method, the prospect of its application to engineering will be fine.After the discussion of phased-space reconstruct technology, complexity parameter algorithm and mutual information theory, the mutual information of different time serials from different sensors at different regimes in gas-solid fluidized beds are calculated. The fluctuate complexity of those mutual time information are got, and then the Information Transform Matrix (ITM) is obtained. Further more, the Mean of ITM (MITM) is applied to defining the identification of different fluidized regimes.According to the previous study, transition states between different flow regimes in gas-solid fluidized beds show with obvious fuzzy characteristics. In this paper, fuzzy theory is implemented to identify the transition states in gas-solid fluidized beds. Membership functions are established to represent the membership grade of transition states for deterministic flow regimes. Transition states are quantified with fuzzy language and applying the fuzzy information fusion theory, multi parameters delivered from separated sensors are fused at characteristic level and multi decisions of each sensor are fused at the decision level. The experimental results indicate that the identification rate of flow regimes is improved. The fuzzy information fusion technology provides a new way to identify the transition states.Finally, for ap...
|
PDF Full Text Request