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《Journal of Jilin University(Engineering and Technology Edition)》 2009-06
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Application of principal component analysis of wavelet packet on flow regime identification of gas-liquid two-phase flow

SUN Bin,LIU Tian-dong,ZHOU Yun-long(School of Energy Resources and Mechanical Engineering,Northeast Dianli University,Jilin 132012,China)  
To deal with the complex nonlinear relation between the charateristic parameters and the flow regime of the gas-liquid 2-phase flow,a flow regime identification method for this kind of flow was proposed based on the principal component analysis(PCA) of the wavelet packet and the least square support vector machine(LS-SVM).The 4-layer wavelet packet was decomposed for the acquired differential pressure fluctuation signal at 3 pressure measure intervals,and the characteristic vector matrix of the wavelet packet was formed.The input dimension of the characteristic vector matrix was reduced by the PCA.The dimension reduced vector matrix was applied to train identification of the LS-SVM.The identification results showed that the principal component features fusing the informations from 3 sensors can identify the flow regine of the gas-liquid 2-phase flow more efficient than the condition of only one sensor.
【Fund】: 国家自然科学基金项目(50706006 50976018)
【CateGory Index】: O359.1
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