Study on two-phase flow regime visualization and identification using 3D electrical capacitance tomography and fuzzy-logic classification

Abstract From variety of industry-oriented imaging solutions the electrical capacitance tomography applied to the two-phase gas–liquid mixtures visualization and the phase distribution calculation is getting popular especially when flow key parameters are required. Industry demands particularly include efficient non-invasive automatic phase fraction calculation and flow structure identification in the vertical and horizontal pipelines. This can be solved by using non-deterministic fuzzy-logic based techniques for analysis of volumetric images. This paper presents a preliminary study on automated two-phase gas–liquid flow pattern identification based on a fuzzy evaluation of series of reconstructed 3D ECT volumetric images. The set of volume data is obtained by using nonlinear electrical capacitance tomography reconstruction algorithms. Finally a set of fuzzy-based features is calculated for flow substructure classification. As a result of this analysis obtained features will be used to classify given volumetric image into one of known flow regime structures.

[1]  Liang-Shih Fan,et al.  Electrical Capacitance Volume Tomography , 2007, IEEE Sensors Journal.

[2]  Manuchehr Soleimani,et al.  THREE-DIMENSIONAL NONLINEAR INVERSION OF ELECTRICAL CAPACITANCE TOMOGRAPHY DATA USING A COMPLETE SENSOR MODEL , 2010 .

[3]  G. Hewitt,et al.  Studies of Two-Phase Flow Patterns by Simultaneous X-Ray and Flash Photography , 1969 .

[4]  Robert Banasiak,et al.  Four-dimensional electrical capacitance tomography imaging using experimental data , 2009 .

[5]  Ryan M. Rifkin,et al.  In Defense of One-Vs-All Classification , 2004, J. Mach. Learn. Res..

[6]  Bin Sun,et al.  Identification Method of Gas-Liquid Two-phase Flow Regime Based on Image Multi-feature Fusion and Support Vector Machine , 2008 .

[7]  Wuqiang Yang,et al.  Image reconstruction by nonlinear Landweber iteration for complicated distributions , 2008 .

[8]  Huaxiang Wang,et al.  Identification of two-phase flow regimes based on support vector machine and electrical capacitance tomography , 2009 .

[9]  Brian S. Hoyle,et al.  Electrical capacitance tomography for flow imaging: system model for development of image reconstruction algorithms and design of primary sensors , 1992 .

[10]  J. C. Dunn,et al.  A Fuzzy Relative of the ISODATA Process and Its Use in Detecting Compact Well-Separated Clusters , 1973 .

[11]  M. Dziubiński,et al.  The flow pattern map of a two-phase non-Newtonian liquid–gas flow in the vertical pipe , 2004 .

[12]  Wuqiang Yang,et al.  A comparative study of three dimensional electrical capacitance tomography , 2007 .

[13]  Li Haiqing,et al.  Measurement and evaluation of two-phase flow parameters , 1991 .

[14]  Haiqing Li,et al.  An Online Flow Pattern Identification System for Gas–Oil Two-Phase Flow Using Electrical Capacitance Tomography , 2006, IEEE Transactions on Instrumentation and Measurement.

[15]  A. E. Dukler,et al.  Modelling flow pattern transitions for steady upward gas‐liquid flow in vertical tubes , 1980 .

[16]  Fei Wang,et al.  Electrical Capacitance Volume Tomography: Design and Applications , 2010, Sensors.

[17]  Didier Dubois,et al.  Fuzzy sets and systems ' . Theory and applications , 2007 .

[18]  M. E. Charles,et al.  Vertical two-phase flow part I. Flow pattern correlations , 1974 .

[19]  Lilian Shi,et al.  Fuzzy Recognition for Gas-liquid Two-phase Flow Pattern Based on Image Processing , 2007, 2007 IEEE International Conference on Control and Automation.

[20]  Fei Wang,et al.  Velocity Measurement of Multi-Phase flows Based on Electrical Capacitance Volume Tomography , 2007, 2007 IEEE Sensors.

[21]  Fakhri Karray,et al.  Fuzzy entropy: a brief survey , 2001, 10th IEEE International Conference on Fuzzy Systems. (Cat. No.01CH37297).

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

[23]  M. S Beck,et al.  Imaging Industrial Flows: Applications of Electrical Process Tomography , 1995 .