Identificaton Of Two-Phase Regime And Measurement Of Flow Rate Based On Data Fusion

Two-phase flow widely exists in processes such as power, chemical, petrol, metallurgy, pipeline transport, medical and refrigeration industries. Researching of the hydrodynamics mechanisms and precisely detection of parameters in two-phase flow are very important for the development of modern industrial equipment. This dissertation focuses on the application of data fusion in two-phase flow regime identification. Following is the main contribution of the dissertation.1)Based on quartile and first order differential, a new outlier detection algorithm is presented, Experiments show that the method combining with low pass filter can remove gross error and unwanted frequency components. The method has been applied successfully in two phase flow pressure signal processing.2)Entropy is a measure of information in signals. Based on the conception of entropy, two new features-Shannon entropy and Threshold entropy are proposed in flow regime identification. Experiments show that the features can effectively discriminate flow regimes.3)Data fusion is proposed in flow regime identification researches. Some problems such as fusion level and architecture of applying data fusion in flow regime research are studied. A Fl (Fuzzy Integral) fusion regime identification algorithm is implemented on horizontal gas-liquid two-phase flow. Inputs of the Fl algorithm are three features extracted from differential pressure signal. The experiment is done on pipes of diameter 20mm and 25mm, and pressure sample distance of 155mm and 1000mm. Three typical flow regime, bubble, slug and annularIIIABSTRACTflow are considered. Results proved that the Fl fusion method outperforms any individual sensors. The results also show that no significant different exist between pressure sample distance of 155mm and 1000mm. Pressure signal from the two distances can all identify flow regime effectively.4)Relations between differential pressure signal and two-phase flow parameters are studied in the dissertation. Factors that affect two-phase flow pressure drop are discussed in details at first. Polynomial is used to fit the relation between property of differential pressure signal and Lockhart- Martinelli parameter X. Based on the relation, a dual- parameter identification scheme using only differential pressure signal is given. The experiment data from horizontal gas-liquid flow on 20mm and 25mm diameter pipes proved that separate phase flow-rate can be measured from differential pressure signal.