Study On Application Of ARMA Model To The Measurement Of Two-Phase Flow

The two-phase flow is a complex nonlinear dynamic system. It is difficult to measure parameters of two-phase flow because there are interaction at the interface and slip between the two phases. It is significant to correctly measure parameters of two-phase flow for safety, process control, energy conservation, and quality assurance. In the parameter measurement technique of the two-phase flow, the identification of the flow regimes (patterns) is one of most important research fields. Heat transfer, mass transfer and the measurement accuracy of other flow parameters depend on the flow regimes.In this thesis, Autoregressive Moving Average (ARMA) models are applied to identify the flow regimes of two-phase flow. Experiments are carried out on the facilities include gas-solid fluidized bed and gas-liquid two-phase flow pipelines. The results show that the methods are effective. The main works as the following:R/S analysis is introduced to improve Wavelet-generalized least squares (WLS) in order to increase the estimate accuracy of the Hurst exponent. Based on wavelet analysis, WLS is the best linear unbiased estimator of regression model parameters in the context of l/f noise. Experimental results show that WLS is better than classical Autoregressive (AR) models for 0.5