We describe an approach, based on electrical capacitance tomography (ECT) sensors, to decompose and continuously monitor multiphase flow components (fractional areas or volumes) in mixtures containing conducting phases. The proposed approach exploits the Maxwell-Wagner-Sillars effect at distinct frequencies to reconstruct each phase of a multiphase flow and is also utilized to estimate the fractional volume of the various phases of the mixture. The approach is illustrated for a three-phase mixture composed of air, water, and oil. This approach utilizes the very same ECT measurement apparatus used for flow imaging and, as such, inherits its high speed of acquisition and suitability for real-time operation.

We compare electrical capacitance tomography (ECT) and displacement-current phase tomography (DCPT) results for non-invasive imaging of lossy media. ECT is based on mutual capacitance measurements between electrode pairs surrounding the region of interest (RoI), whereas DCPT is a relatively less mature sensing modality that utilizes the phase information inherent in the displacement current measured by such electrode pairs excited by time-harmonic voltages (in the electroquasistatic regime). DCPT and ECT can be implemented using basically the same hardware components and used alongside to provide complementary information for imaging purposes or separately to reconstruct the spatial distribution of the loss tangent or the permittivity within the RoI, respectively. We show that the (nonlinear) relationship between the measured phase in DCPT and the conductivity distribution in the RoI has a more extended linear range than the nonlinear relationship between the measured capacitances in ECT and the permittivity distribution in the RoI. Of note, DCPT does not require electrical contact with the RoI in contrast to electrical impedance tomography. To illustrate the potential of DCPT, we evaluate its performance using both numerical examples and experiment results.

Electrical Capacitance Volume Tomography (ECVT) has emerged as an attractive technology for addressing instrumentation requirements in various energy-related multiphase flow systems. ECVT can monitor multiple flow conditions and reconstruct real-time 3D images from capacitance measurements using a large set of electrode plates placed around the processes column enclosing the sensed flow system. ECVT is non-intrusive and allows the measurement of changes in mutual capacitance between all possible plate pair combinations. The objective of this paper is to provide a comprehensive review of recent advances in ECVT, enabling robust monitoring of multiphase flows, especially water-containing multiphase flows.

Electrical capacitance tomography (ECT) exhibits several attractive features that are important for industrial process tomography applications. These features include low cost, high speed, and nonintrusive nature. However, due to its soft-field character, a relatively low image resolution is an outstanding challenge for ECT. While many efforts have been made to tackle this challenge by improvements in image reconstruction algorithms, relatively less has been done to enhance the basic ECT hardware sensor configuration and data acquisition process. In this paper, a new measurement acquisition strategy is introduced to increase image resolution when using adaptive ECT (AECT). The proposed strategy is based on the manipulation of synthetic electrodes plates (``metaplates'') formed by a set of combined smaller physical electrodes (segments). The synthetic electrodes are sequentially activated with partial overlap of constituent segments to provide a fine-stepped axial and/or azimuthal electronic scan along the entire sensor. Consequently, an increased number of independent capacitance measurements are made available. Reconstruction results using the proposed measurement acquisition strategy (AECT) are shown to illustrate the enhanced resolution and stability in the imaging of objects compared to conventional ECT sensors.

We present a Relevance Vector Machine (RVM) based algorithm for electrical capacitance tomography (ECT) applications that can concurrently provide image reconstruction results and uncertainty estimates about the reconstruction. To illustrate the RVM operation in ECT, we simulate typical ECT scenarios, making explicit the connection between the reconstructed pixel values and the corresponding uncertainty estimates in each case. We compare the RVM reconstruction performance with that of the Iterative Landweber Method (ILM) and the least absolute shrinkage and selection operator (LASSO) in all the considered scenarios. The results show that, in addition to the key advantage of providing uncertainty measures, RVM can achieve similar reconstruction results with either lower or similar computational complexity.