Abstract:

Aimed at the nonlinear and non-Gaussian characteristics of differential pressure fluctuation signals of gas-liquid two-phase flow，a flow regime identification method based on bispectrum and kernel principal component analysis（KPCA）was proposed.The non-Gaussian characteristics of differential pressure fluctuation signals of different flow regimes were extracted by using the bispectrum method.Then the kernel principal component numerical characteristics technology based on bispectrum analysis was used to extract flow regime characteristics.At last，least square support vector machine（LS-SVM）was introduced to intelligently identify flow regimes.The test results showed that bispectrum analysis was an extremely powerful tool for the analysis of nonlinear and non-Gaussian signals，and the extracted KPCA characteristics could reflect the flow state of two-phase flow.The LS-SVM could accurately identify four typical flow regimes of gas-water two-phase flow in the horizontal pipe.The whole identification accuracy was 95% for flow regime identification by using the new effective method.