Experimental evaluation of conductive flow imaging using magnetic induction tomography

Abstract Multi-phase flow imaging is a challenging topic in industrial process tomography. In this paper, we present a non-invasive imaging technique for the electrically conductive phase of a multi-phase flow problem. Magnetic induction tomography (MIT) is sensitive to the conductivity of the target, and as such has the potential to be used as an imaging technique to visualise the conductive components in a multi-phase flow application. A 16 channel MIT system is used for this study, among which eight excitation coils are supplied with a 15 V peak, 13 MHz sinusoidal signal in sequence from a signal generator, while the remaining eight coils are floated as receivers. The imaging region of this MIT system has an inner and outer diameter of 190 mm and 200 mm respectively. Static fluid distribution patterns are produced using several fluids with different conductivities and placed inside the imaging region to form conductivity phase contrasts. Experimental results show within our hardware and software capability, a conductivity contrast of 0.06 S/m for an inclusion that occupies 8.69% of the imaging region can be imaged. An in-depth experimental evaluation of the system response towards various fluid measurements is shown for the first time, as are results for quasi-static fluid experiments showing that a non-homogenous flow of gas bubbles can be imaged in various conductive backgrounds. In sum, the analyses presented investigate the feasibility and capability of MIT for this application, while also reporting some of the first flow rig tests in this field.

[1]  M. Vauhkonen,et al.  Imagereconstruction approaches for Philips magnetic induction tomograph , 2007 .

[2]  Min Han,et al.  Magnetic Induction Tomography , 2015 .

[3]  Lu Ma,et al.  Electromagnetic imaging for internal and external inspection of metallic pipes , 2012 .

[4]  A new imaging approach for in situ and ex situ inspections of conductive fiber–reinforced composites by magnetic induction tomography , 2014 .

[5]  O Dössel,et al.  Design and performance of a planar-array MIT system with normal sensor alignment. , 2005, Physiological measurement.

[6]  Ze Liu,et al.  Simulation study of the sensing field in electromagnetic tomography for two-phase flow measurement , 2005 .

[7]  Nevzat G. Gencer,et al.  Electrical conductivity imaging via contactless measurements: an experimental study , 2003, IEEE Transactions on Medical Imaging.

[8]  Abelardo Ramirez,et al.  Environmental process tomography in the United States , 1995 .

[9]  H. Lackner,et al.  Magnetic induction tomography: hardware for multi-frequency measurements in biological tissues. , 2001, Physiological measurement.

[10]  Manuchehr Soleimani,et al.  Sensitivity maps in three-dimensional magnetic induction tomography , 2006 .

[11]  B. T. Hjertaker,et al.  Three-phase flow measurement in the petroleum industry , 2012 .

[12]  Anthony J. Peyton,et al.  Addressing the difficulties in using inductive methods to evaluating human body composition. , 2003 .

[13]  Jiangtao Sun,et al.  Fringe effect of electrical capacitance and resistance tomography sensors , 2013 .

[14]  Zhongying,et al.  MULTI-PARAMETER TIKHONOV REGULARIZATION FOR LINEAR ILL-POSED OPERATOR EQUATIONS , 2008 .

[15]  Wuqiang Yang,et al.  A hybrid reconstruction algorithm for electrical impedance tomography , 2007 .

[16]  Xiandong Ma,et al.  Development of multiple frequency electromagnetic induction systems for steel flow visualization , 2008 .

[17]  Manuchehr Soleimani,et al.  Two-phase low conductivity flow imaging using magnetic induction tomography , 2012 .

[18]  Jian Guo Zhang,et al.  Application of Electrical Resistance Tomography to Ice-Water Two-Phase Flow Parameters Measurement , 2013 .

[19]  H Griffiths,et al.  Magnetic Induction Tomography: A Measuring System for Biological Tissues , 1999, Annals of the New York Academy of Sciences.

[20]  U. TAUTENHAHN,et al.  Dual Regularized Total Least Squares And Multi-Parameter Regularization , 2008 .

[21]  Wang Bao-shou Research on void fraction of gas-liquid two-phase flow based on COMSOL , 2013 .

[22]  Xiandong Ma,et al.  Hardware and software design for an electromagnetic induction tomography (EMT) system for high contrast metal process applications , 2005 .

[23]  O. Bíró Edge element formulations of eddy current problems , 1999 .

[24]  H Griffiths,et al.  A magnetic induction tomography system for samples with conductivities below 10 S m−1 , 2008 .

[25]  N Terzija,et al.  Use of electromagnetic induction tomography for monitoring liquid metal/gas flow regimes on a model of an industrial steel caster , 2010 .

[27]  O. Scherzer,et al.  Hybrid tomography for conductivity imaging , 2011, 1112.2958.

[28]  N. H. Saunders,et al.  A feasibility study of in vivo electromagnetic imaging. , 1993, Physics in medicine and biology.

[29]  Maomao Zhang,et al.  Magnetic induction tomography guided electrical capacitance tomography imaging with grounded conductors , 2014 .

[30]  H Scharfetter,et al.  A multifrequency magnetic induction tomography system using planar gradiometers: data collection and calibration. , 2006, Physiological measurement.

[31]  Manuchehr Soleimani,et al.  Hardware and software design for a National Instrument-based magnetic induction tomography system for prospective biomedical applications. , 2012, Physiological measurement.

[32]  Manuchehr Soleimani,et al.  Absolute Conductivity Reconstruction in Magnetic Induction Tomography Using a Nonlinear Method , 2006, IEEE Transactions on Medical Imaging.

[33]  Wuliang Yin,et al.  A planar EMT system for the detection of faults on thin metallic plates , 2006 .