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.
|Number of pages||12|
|Journal||International Journal of Multiphase Flow|
|Early online date||27 Feb 2015|
|Publication status||Published - 1 Jun 2015|
- Two-phase flow imaging
- Magnetic induction tomography
- Experimental evaluation
FingerprintDive into the research topics of 'Experimental Evaluation of Conductive Flow Imaging Using Magnetic Induction Tomography'. Together they form a unique fingerprint.
- Department of Electronic & Electrical Engineering - Professor
- EPSRC Centre for Doctoral Training in Statistical Applied Mathematics (SAMBa)
- Centre for Biosensors, Bioelectronics and Biodevices (C3Bio)
- Centre for Autonomous Robotics (CENTAUR)
- Electronics Materials, Circuits & Systems Research Unit (EMaCS)
Person: Research & Teaching