Qussai Marashdeh

Electrical Capacitance Volume Tomography

A dynamic volume imaging based on the principle of electrical capacitance tomography (ECT), namely, electrical capacitance volume tomography (ECVT), has been developed in this study. The technique generates, from the measured capacitance, a whole volumetric image of the region enclosed by the geometrically three-dimensional capacitance sensor. This development enables a real-time, 3-D imaging of a moving object or a real-time volume imaging (4-D) to be realized. Moreover, it allows total interrogation of the whole volume within the domain (vessel or conduit) of an arbitrary shape or geometry. The development of the ECVT imaging technique primarily encloses the 3-D capacitance sensor design and the volume image reconstruction technique. The electrical field variation in three-dimensional space forms a basis for volume imaging through different shapes and configurations of ECT sensor electrodes. The image reconstruction scheme is established by implementing the neural-network multicriterion optimization image reconstruction (NN-MOIRT), developed earlier by the authors for the 2-D ECT. The image reconstruction technique is modified by introducing into the algorithm a 3-D sensitivity matrix to replace the 2-D sensitivity matrix in conventional 2-D ECT, and providing additional network constraints including 3-to-2-D image matching function. The additional constraints further enhance the accuracy of the image reconstruction algorithm. The technique has been successfully verified over actual objects in the experimental conditions

Electrical Capacitance Volume Tomography: Design and Applications

This article reports recent advances and progress in the field of electrical capacitance volume tomography (ECVT). ECVT, developed from the two-dimensional electrical capacitance tomography (ECT), is a promising non-intrusive imaging technology that can provide real-time three-dimensional images of the sensing domain. Images are reconstructed from capacitance measurements acquired by electrodes placed on the outside boundary of the testing vessel. In this article, a review of progress on capacitance sensor design and applications to multi-phase flows is presented. The sensor shape, electrode configuration, and the number of electrodes that comprise three key elements of three-dimensional capacitance sensors are illustrated. The article also highlights applications of ECVT sensors on vessels of various sizes from 1 to 60 inches with complex geometries. Case studies are used to show the capability and validity of ECVT. The studies provide qualitative and quantitative real-time three-dimensional information of the measuring domain under study. Advantages of ECVT render it a favorable tool to be utilized for industrial applications and fundamental multi-phase flow research.

A nonlinear image reconstruction technique for ECT using a combined neural network approach

A combined multilayer feed-forward neural network (MLFF-NN) and analogue Hopfield network is developed for nonlinear image reconstruction of electrical capacitance tomography (ECT). The (nonlinear) forward problem in ECT is solved using the MLFF-NN trained with a set of capacitance data from measurements based on a back-propagation training algorithm with regularization. The inverse problem is solved using an analogue Hopfield network based on a neural-network multi-criteria optimization image reconstruction technique (HN-MOIRT). The nonlinear image reconstruction based on this combined MLFF-NN + HN-MOIRT approach is tested on measured capacitance data not used in training to reconstruct the permittivity distribution. The performance of the technique is compared against commonly used linear Landweber and semi-linear image reconstruction techniques, showing superiority in terms of both stability and quality of reconstructed images.

A Multimodal Tomography System Based on ECT Sensors

A new noninvasive system for multimodal electrical tomography based on electrical capacitance tomography (ECT) sensor hardware is proposed. Quasistatic electromagnetic fields are produced by ECT sensors and used for interrogating the sensing domain. The new system is noninvasive and based on capacitance measurements for permittivity and power balance measurements for conductivity (impedance) imaging. A dual sensitivity map of perturbations in permittivity and conductivity is constructed. The measured data along with the sensitivity matrix are used for the actual image reconstruction. The new multimodal tomography system has the advantage of using already established reconstruction techniques, and the potential for combination with new reconstruction techniques by taking advantage of combined conductivity/permittivity data. Moreover, it does not require direct contact between the sensor and the region of interest. The system performance has been tested on representative data, producing good results

Adaptive Electrical Capacitance Volume Tomography

Electrical capacitance volume tomography (ECVT) has shown to be an effective low-cost and high-speed imaging technique suitable for many applications, including 3-D reconstruction of multiphase flow systems. In this paper, we introduce the concept of adaptive ECVT based upon the combination of a large number of small individual sensor segments to comprise synthetic capacitance plates of different (and possibly noncontiguous) shapes while still satisfying a minimum plate area criterion set by a given SNR. The response from different segments is combined electronically in a reconfigurable fashion. The proposed adaptive concept paves the way for ECVT to be applicable in scenarios requiring higher resolution and dynamic imaging reconstruction.

Nonlinear forward problem solution for electrical capacitance tomography using feed-forward neural network

A new technique for solving the forward problem in electrical capacitance tomography sensor systems is introduced. The new technique is based on training a feed-forward neural network (NN) to predict capacitance data from permittivity distributions. The capacitance data used in training and testing the NN is obtained from preprocessed and filtered experimental measurements. The new technique has shown better results when compared to the commonly used linear forward projection (LFP) while maintaining fast prediction speed. The new technique has also been integrated into a modified iterative linear back projection (Landweber) reconstruction algorithm. Reconstruction results are found to be in favor of the NN forward solver when compared to the widely used Landweber reconstruction technique with LFP forward solver.

Sensitivity matrix calculation for fast 3-D electrical capacitance tomography (ECT) of flow systems

We discuss an improved three-dimensional sensitivity matrix calculation and measurement approach for electrical capacitance tomography of flow systems employing neural-network-based reconstruction algorithms. The experimental apparatus involved, the sensor design, and the forward and inverse numerical techniques are also discussed. Simulation results of the imaging of flow systems are provided to illustrate the capabilities of the technique.

Velocity Measurement of Multi-Phase flows Based on Electrical Capacitance Volume Tomography

In this work, a novel 3D velocimetry systems based on electrical capacitance volume tomography (ECVT) is introduced. Unlike traditional 2D velocity systems, the current system provides three dimensional velocity maps of multi-phase flows inside a conduit directly from the reconstructed image. Here, the velocity measurement process starts by acquiring capacitance data from the ECVT sensor. An image reconstruction algorithm is then used to reconstruct whole volume images directly from the three dimensional capacitance sensors. The sequence of reconstructed images from the ECVT system is used to obtain three dimensional velocity maps. Using ECVT technology for mapping velocity profiles; presented in this work; is the first to be reported.

Chapter 5 Electrical Capacitance, Electrical Resistance, and Positron Emission Tomography Techniques and Their Applications in Multi-Phase Flow Systems

Abstract This article describes the recent progress in research and development on electrical capacitance tomography (ECT), electrical resistance tomography (ERT), and positron emission tomography (PET). Specifically, the article highlights several aspects of the three technologies and illustrates their application and performance through selected demonstration cases studies. The principles and results from the methods provide quantitative and/or qualitative assessment of the significance of each technique. The measurement techniques lend themselves for widespread application in multi-phase flow imaging research and some for industrial-scale measurements due to their non-invasive nature.

Toward Multiphase Flow Decomposition Based on Electrical Capacitance Tomography Sensors

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.