A new method for the on-line voidage measurement of gas-oil two-phase flow

Based on the capacitances obtained by 12-electrode ECT (electrical capacitance tomography) system and the least-squares support vector machine (LS-SVM) technique, a new method is proposed for the on-line voidage measurement of gas-oil two-phase flow. In practical voidage measurement process, the real-time flow pattern of the gas-oil two-phase flow is identified directly from 66 capacitances obtained by ECT system. Then, according to the flow pattern identification result, a suitable measurement model is selected and the voidage value is calculated. Research result shows the proposed method is effective. The voidage measurement result is flow pattern independent and the real-time performance is satisfactory. Meanwhile, compared with the conventional voidage measurement method based on ECT system, the proposed method can implement the voidage measurement without any image reconstruction process.

[1]  Hai-Feng Ji,et al.  A high-speed data acquisition system for ECT based on the differential sampling method , 2005, IEEE Sensors Journal.

[2]  Christian Igel,et al.  Evolutionary tuning of multiple SVM parameters , 2005, ESANN.

[3]  Haiqing Li,et al.  On-line Voidage Measurement of Two-phase Flow Based on Ant System Algorithm , 2006, 2006 IEEE Instrumentation and Measurement Technology Conference Proceedings.

[4]  J. Roger,et al.  Application of LS-SVM to non-linear phenomena in NIR spectroscopy: development of a robust and portable sensor for acidity prediction in grapes , 2004 .

[5]  Lijuan Cao,et al.  A comparison of PCA, KPCA and ICA for dimensionality reduction in support vector machine , 2003, Neurocomputing.

[6]  Anil K. Jain,et al.  Statistical Pattern Recognition: A Review , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  Vladimir Vapnik,et al.  Statistical learning theory , 1998 .

[8]  J. Suykens,et al.  Recurrent least squares support vector machines , 2000 .

[9]  Theodore B. Trafalis,et al.  Two-phase flow regime identification with a multiclassification support vector machine (SVM) model , 2005 .

[10]  Haiqing Li,et al.  Application of electrical capacitance tomography to the void fraction measurement of two-phase flow , 2003, IEEE Trans. Instrum. Meas..

[11]  Chih-Jen Lin,et al.  A comparison of methods for multiclass support vector machines , 2002, IEEE Trans. Neural Networks.

[12]  Lihui Peng,et al.  Image reconstruction algorithms for electrical capacitance tomography , 2003 .

[13]  Wei-Wei Wang.  Voidage Measurement of Gas-Oil Two-phase Flow , 2007 .

[14]  Clayton T. Crowe,et al.  Multiphase Flow Handbook , 2005 .

[15]  Li Xia,et al.  Application of PLSR to the Voidage Measurement of Gas-oil Two-phase Flow , 2007, 2007 8th International Conference on Electronic Measurement and Instruments.

[16]  S. Mylvaganam,et al.  Electrical Capacitance Tomography—Sensor Models, Design, Simulations, and Experimental Verification , 2006, IEEE Sensors Journal.

[17]  Johan A. K. Suykens,et al.  Least Squares Support Vector Machine Classifiers , 1999, Neural Processing Letters.