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《Chinese Journal of Scientific Instrument》 2008-05
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Identification method of gas-liquid two-phase flow regime based on empirical mode decomposition

Sun Bin,Huang Shengquan,Zhou Yunlong,Guan Yuebo(School of Energy Resources and Mechanical Engineering,Northeast Dianli university,Jilin 132012,China)  
A method of flow regime identification based on empirical mode decomposition was proposed.First of all,the collected pressure-difference fluctuation signals were decomposed into a finite number of stationary intrinsic mode function(IMFs),then a number of IMFs containing main flow regime information were selected,from which time domain feature indicator-kurtosis coefficient that serves as input parameter of LVQ neural network was extracted in order to identify the flow regimes.The successful identification of four typical flow regimes of air-water two-phase flow in horizontal pipe shows that the proposed LVQ neural network identification method based on EMD for extracting time domain features is superior to other methods and can identify flow regimes accurately and effectively.
【Fund】: 国家自然科学基金项目(50706006);; 吉林省教育厅重点项目(2006024)资助
【CateGory Index】: O359.1
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