1 - Electrical Capacitance Tomography

An electrical capacitance tomography (ECT) sensor consists of a number of electrodes, which are usually mounted around the external or internal periphery of a circular insulated pipe. Therefore, the diameter of a conventional ECT sensor is fixed. This paper presents a new structure of ECT sensor, which can achieve adjustable inner diameter of the sensor within a certain range, by re-engineering the traditional structure, and therefore the electrode-to-gap ratio (EGR) of the sensor is changed. The relationship between EGR and image quality was studied by simulation. A prototype ECT sensor with variable diameter was fabricated and evaluated with an impedance-analyzer based ECT system. The experimental results show that the ECT sensor with variable diameter can provide similar reconstructed images to a conventional ECT sensor, when the sensor diameter varies in a certain range, i.e. EGR above 6:1. Therefore, this new structure can enable the ECT sensor to be adapted to the change in diameter of the measured objects.

Visualisation of gas–oil two-phase flows in pressurised pipes using electrical capacitance tomography

Multiphase flow metering is a challenging task because of the complexity of multiphase flow. In this paper, nonintrusive multiphase flow metering techniques, including machine learning (ML) / artificial intelligence models for the identification of flow regimes and estimation of flow parameters of a two-phase flow in a horizontal pipe are proposed that use data from Electrical Capacitance Tomography (ECT) and conventional measurements such as differential pressure in the pipe. The flow regimes are classified into five types, namely plug, slug, annular, wavy and stratified. Two-phase air/water flow experimental data from ECT are collected by running extensive experiments using the horizontal section of the multiphase flow rig at the University of South-Eastern Norway (USN). Exploratory data analysis (EDA) is performed on these data to extract features for use in classification and regression algorithms. Time series of normalized capacitance data from ECT sensors are used to classify flow regimes and identify flow parameters. ML techniques of Artificial Neural Network, Support Vector Machine (SVM), K-Nearest Neighbors (KNN) and Decision Tree (DT) are used to classify flow regimes by using features extracted from ECT data. The cross-correlation technique is used to estimate flow velocity using data from a twinplane ECT module. ML regression techniques are used to estimate phase fractions. Fusing data from differential pressure sensors enhances the flow regime classification. An overall system performance is given with suggestions for designing dedicated control algorithms for actuators used in multiphase flow control.

Pipelines made of dielectric materials such as Polyethylene (PE) are becoming increasingly popular. With no suitable inspection technique for dielectric pipes, there is an urgent need to develop new technology for their inspection. This paper presents a novel pipe inspection technique using Electrical Capacitance Tomography (ECT) imaging. Traditionally ECT is used for industrial process tomography as a low resolution but fast tomographic imaging technique. Typically commercial ECT can provide a resolution of approximately 10 percent of the imaging region. In this paper a limited region tomography technique is developed take into account prior knowledge about the geometry of the pipe. This has signiflcantly enhanced the imaging resolution of the ECT system, making it a viable pipe inspection solution. The experimental results in this study demonstrate an interior wall loss area as small as 0.195 percent of the ECT cross sectional imaging region is repeatable and can be reliably detected. A narrowband pass fllter method (NPFM) is used as a means to limit the region for the ECT algorithm. This results in an unprecedented resolution, making ECT a viable non-destructive evaluation (NDE) technique for plastic pipes. The NDE application of the ECT for PE pipes is demonstrated in this paper with several experimental results. A wall loss of depth of 1.5mm could be detected for an ECT sensor array of 150mm in diameter, showing a high resolution and high deflnition ECT (HD-ECT) imaging that has not been reported before.

Measurement techniques are vital for the control and operation of multiphase oil–water flow in pipes. The development of such techniques depends on laboratory experiments involving flow visualization, liquid fraction (‘hold-up’), phase slip and pressure drop measurements. They provide valuable information by revealing the physics, spatial and temporal structures of complex multiphase flow phenomena.This paper presents the hold-up measurement of oil–water flow in pipelines using gamma densitometry and electrical capacitance tomography (ECT) sensors. The experiments were carried out with different pipe inclinations from −5° to +6° for selected mixture velocities (0.2–1.5 m s−1), and at selected watercuts (0.05–0.95). Mineral oil (Exxsol D60) and water were used as test fluids. Nine flow patterns were identified including a new pattern called stratified wavy and mixed interface flow. As a third direct method, visual observations and high-speed videos were used for the flow regime and interface identification.ECT and gamma densitometry hold-up measurements show similar trends for changes in pipeline inclinations. Changing the pipe inclination affected the flow mostly at lower mixture velocities and caused a change of flow patterns, allowing the highest change of hold-up. ECT hold-up measurements overpredict the gamma densitometry measurements at higher input water cuts and underpredict at intermediate water cuts. Gamma hold-up results showed good agreement with the literature results, having a maximum deviation of 6%, while it was as high as 22% for ECT in comparison to gamma densitometry.Uncertainty analysis of the measurement techniques was carried out with single-phase oil flow. This shows that the measurement error associated with gamma densitometry is approximately 3.2%, which includes 1.3% statistical error and 2.9% error identified as electromagnetically induced noise in electronics. Thus, gamma densitometry can predict hold-up with a higher accuracy in comparison to ECT when applied to oil–water systems at minimized electromagnetic noise.

Nowadays, the optimization of energy consumption and resources is one of the most urgent topics in worldwide industry. The energy consumption monitoring and control in various multiphase flow industrial applications, where a proper flow characteristic and an optimal phase mixture control is crucial, is hard to perform due to the physical and chemical complexity of the processes. The Electrical Capacitance Tomography (ECT) is one of the relatively cheap non-invasive measurement methods that can help in the monitoring and control of optimal energy and resources dozing in industrial processes. ECT diagnostics systems use unique sensors that can non-intrusively detect spatial capacitance changes caused by spatial changes in the electrical permittivity of industrial process components. One of the latest ECT extensions is a three-dimensional measurement strategy that uses a multilayer structure of the capacitance sensor. In this paper, the authors propose a novel approach to the 3D ECT sensors fabrication process that uses 3D computer modelling and 3D printing to easily get any sensor shape, electrode layout, scale and shielding strategy. This study compares the measurement abilities of a 3D ECT sensor fabricated using a traditional hand-made technique with the 3D printed device. The results have proven the potential of the new 3D print-based sensor regarding its significant fabrication time reduction as well as the improvement of the overall 3D ECT sensor measurement accuracy and stability.

Electrical capacitance tomography (ECT) has been developed successfully for industrial applications. While most ECT sensors employ a circular structure with a closed sensing area, some other structures like square and parallel are needed for some particular applications. This paper describes a parallel structure ECT sensor, which can provide incomplete measurement data only. The performance of this parallel ECT sensor is discussed based on simulation study with 2D FEM models. Images of different permittivity distributions are generated by linear back-projection (LBP) and Landweber iteration algorithms. The effect of the effective sensing area and distance of parallel plates are also discussed. Both capacitance residual and correlation coefficient are used to evaluate the image quality. The results show that (1) the width of the sensing area should be the same as the shielding layer in order to acquire high quality image and (2) the distance between two parallel plates is suggested being equal to the shielding layer to compromise the sensing space and the sensitivity of the central region.

Electrical capacitance tomography (ECT) is a non-invasive measurement technique widely used for two-phase flow imaging and parameter measurement. Image reconstruction of ECT analyzes the capacitance measurements from the ECT sensor and reconstructs the permittivity distribution in the sensing domain through certain algorithms. Due to its ill-posedness, image reconstruction has always been a hotspot and a challenge in ECT research. Over the past decade, the blooming of deep learning has introduced promising avenues for addressing this challenge. Numerous deep learning-based models and algorithms have been developed for ECT image reconstruction, and remarkable achievements have been made. This paper comprehensively summarizes the state-of-the-art deep learning approaches for ECT image reconstruction. In addition, the challenges and future directions of deep learning-based ECT image reconstruction are also discussed in perspective.

A novel method to calculate the flow velocity of solid in a solid–liquid two-phase system is induced in this paper by electrical capacitance tomography (ECT). Taking the slime settlement as an example, the concentration change of three planes in the settling tank is measured using ECT. Moreover, the settling velocity of continuous frames in different sensor planes employing the best correlation function is calculated. The results show that slime has a higher and more uniform settlement velocity in the center area of the settlement tank. A 0.02–0.04 cm/s deviation is found between the calculated velocity of clarifying interfacial layer when slime passing through the ECT sensor and the experimental data. Remarkably, the time point is in good agreement with the experimental result which is between 7 and 13 s, indicating that the method can be used to estimate the settling velocity of solid in a two-phase flow.

This article describes the recent progress in research and development on electrical capacitance tomography (ECT). Specifically, the article highlights several aspects of ECT including the electrical capacitance volume tomography (ECVT), 3D sensor design, 3D neural network multicriterion image reconstruction technique (3D-NN-MOIRT), multimodal imaging based on ECT and ECVT sensors, static-charge effects and the scheme of their elimination in the ECT image reconstruction, and multiphase flow imaging applications. The multimodal capability that enables permittivity and conductivity imaging to be simultaneously conducted is illustrated. The simulation and experimental results are presented to provide quantitative and/or qualitative assessment of the significance of various ECT techniques. The employment of ECVT in conjunction with using electrical capacitance based imaging sensors is shown to represent a favorable tool for industrial multiphase flow imaging.

The usage of Electrical Capacitance Tomography (ECT) is not limited to the imaging of mixtures in process equipment, it also can be used to measure the concentration profiles of component, and in certain case ECT is being used to investigate the boundaries and phase sizes within vessels and pipelines. There are quite a number of type of ECT sensors such as circular structure, square structure, concentric -annulus and parallel structure which are used for particular applications. In this paper, a study was carried out in order to investigate the behavior of electric field on the miniature parallel ECT. Simulations using COMSOL Multiphysics are being done to study the effect of increasing the size of the test object and the effect of increasing the permittivity of the test object. The results show that (1) the electric field lines relatively follow the phantom shape corresponding to the increasing of the size of the phantom and (2) the electrical field lines seems to bend more around the when the permittivity increases. Presented simulations establish first step of investigation, however already proved its usefulness for ECT performance model validation.

Electrical Capacitance Tomography (ECT) determines the dielectric permittivity of the interior object depending on the measurements of exterior capacitance. Generally, the electrodes are placed outside the PVC cylinder where the medium to be imaged is present; but in ECT using inter-electrode capacitance measurements can be achieved by placing inside of the dielectric medium. In the proposed ECT system, the ECT sensor is modeled using ANSYS software and the model is implemented in real ECT system. For each step of measurement, a stable AC signal is applied to a pair of electrodes that form a capacitor. The novel system is to measure the capacitance range variation in picofarad and the corresponding voltage ranges from 1 volt to 4 volts. The switching speed of all combinational electrodes is implemented using embedded system to achieve higher speed performance of AC ECT system which eliminates the drift and stray capacitance error. This is yielding the original image of unknown multiphase medium inside the electrodes using Lab VIEW. This paper investigates several advantages such as improved overall system performance; simple structure, avoids stray capacitance effect, reduces the drift problem and achieves high signal to noise ratio.

As a powerful visualization tomography technique, electrical capacitance tomography (ECT) method, which reconstructs the permittivity distribution in a sensing domain according to the measured capacitance data, has been widely used in different industry scenarios. However, the image reconstruction in ECT is an ill-posed problem, and its application is plagued by low-quality reconstructions, and seeking for a robust algorithm to reduce reconstruction errors and artifacts is crucial. To increase the reconstruction quality, a novel cost function is built for imaging, in which the $L_{1-2}$ norm is designed as a regularizer for encoding the sparsity prior of imaging objects. The ant lion optimizer (ALO) algorithm and the alternating direction method of multipliers (ADMMs) with the Douglas–Rachford splitting (DRS) method and the soft thresholding algorithm as powerful optimizers for minimizing the subproblems are combined into a novel solver for solving the built cost function more effectively. Simulation and experimental results indicate that the proposed imaging technique can improve the quality of reconstructed images.

Visualization of flow pattern in thermosyphon by ECT

This research work is mainly focused on modeling and simulation of Electrical Capacitance Tomography (ECT) sensor which comprises of 12 electrodes that are fabricated externally. The arrangement of electrodes is in the form of multi-plane (i.e. single and twin-plane electrodes). The Finite Element Method (FEM) can be utilized to simulate and compute capacitance values. This simulation method can provide sensitivity distribution and also helpful in obtaining the permittivity distribution for multi-phase flow. This paper focuses on the need for field simulation in the design and analysis of multi-electrode capacitance sensors for tomographic flow imaging. However, the real sensors are 3D but mostly a cross-section is modeled in 2D. The governing equations and the modeling approach for 2D single- and twin-plane ECT sensor using Electromagnetic Module of COMSOL Multiphysics are discussed in this manuscript. The single- and twin-plane simulation has been done for velocity and volume measurement respectively. An image reconstruction algorithm for ECT have presented in this work is based on the FEM. Simulation results are duly verified by an experimental data that has been obtained from the calculation of gas-oil two-phase flow.