Speed Improvement in Electrical Capacitance Tomography Through a Multiple Excitation and Receiving Method

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.

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.

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.

This article presents investigation of 3-D electrical capacitance tomography (ECT) sensors with different excitation strategies, including dual-electrode excitation in the same plane, in adjacent plane, in planes separated by one plane or two planes, and in the adjacent position or opposite position in the same or different planes. The results show that a 3-D ECT sensor with dual-electrode excitation in the opposite position provides higher mean capacitance and lower standard deviation than in the adjacent position. Dual-electrode excitation in different planes can increase the capacitance signal and decrease the dynamic range of capacitance measurements, and thus, decrease random errors and improve the quality of 3-D reconstructed images. A 3-D ECT sensor with dual-electrode excitation in planes separated by one plane and opposite position can provide small measurement uncertainty and high image quality.

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.

Determination of bulk solid concentration changes during granular flow in a model silo with ECT sensors

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.

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.

In the design of electrical capacitance tomography (ECT) sensors, the internal wall thickness can vary with specific applications, and it is a key factor that influences the sensitivity distribution and image quality. This paper will discuss the effect of the wall thickness of ECT sensors on image quality. Three flow patterns are simulated for wall thicknesses of 2.5 mm to 15 mm on eight-electrode ECT sensors. The sensitivity distributions and potential distributions are compared for different wall thicknesses. Linear back-projection and Landweber iteration algorithms are used for image reconstruction. Relative image error and correlation coefficients are used for image evaluation using both simulation and experimental data.

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.

Electrical capacitance tomography (ECT) is a non destructive technique for obtaining the distribution of some physical quantity in a closed pipe by measuring the permittivity distribution. Several conducting plates are fixed around the circumference of the pipe so they do not disturb the flow or movement of materials. The imaging quality of an electrical capacitance tomography system depends upon many co-influential parameters such as number of electrodes, length and width of electrodes, axial guard electrodes, radial guard electrodes, and screen guard. Optimum selection of these variables coupled with advancements in sensing electronics and imaging algorithm provides the best inside view of a closed vessel/pipe. This, in turn, provides better process information for control. This article is intended to summarize such design rules for ECT electrodes and sensors. Numerical simulations were performed using commercially available finite element method (FEM) software to help verify the optimality of the design parameters chosen. Experimental verification was conducted using a fabricated capacitance sensing circuit that could measure capacitance in the range of 1 fF to 7999 femtofarads with a root means square noise level of 0.07 fF. Some parameters such as the thickness of the pipe are chosen as demanded by the process. This article will be useful for researchers to design the ECT Sensors with ease.

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.

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.

Electrical capacitance tomography (ECT) technique has been developed due to its inherent simplicity and low cost. The tomographic images are obtained based on the permittivity differences between the investigated materials and background material (air, in most cases). The dynamic range of capacitance measurements in ECT could be 40 dB or higher. Simultaneously, the changes in the measured capacitances take up only 5% of the full measurement range. Therefore, the capacitance measuring circuit should be of high dynamic range as well as high precision, which constitutes one of the greatest challenges in ECT system design. The standing capacitances in ECT measurements may be canceled by differential measurement. In this paper, a recently developed differential ECT scheme has been presented. An active screen is employed as the differential electrode in the sensor, which is placed between the measuring electrode array and outer screen. Accordingly, a transmitter channel is implemented to accommodate the active screen, which enables the active screen to deliver multi-level AC signal. Simulation and experimental results show that the differential ECT system has a signal-to-noise ratio of 16 dB higher than the previous design, i.e. the non-differential system.

Two means can be used to improve the data acquisition rate of the electrical capacitance tomography (ECT) system with a fixed excitation frequency, i.e., improving the capacitance measurement speed or changing the capacitance measurement mode from serial to parallel. This paper presents a newly developed high-speed ECT system by combing digital recursive demodulation and parallel-mode capacitance measurement methods. By using the digital recursive demodulator, the time-cost for one time of capacitance measurement can be one period of the excitation sinusoid or less. By using the parallel-mode capacitance measuring unit, capacitances between the exciting electrode and all other measuring electrodes can be measured simultaneously. The data acquisition rate of the parallel-mode ECT system with a sensor of N electrodes is N-1 times of a traditional serial-mode ECT system with the same excitation frequency. When the excitation frequency is 100 kHz and 0.6 periods of data are used for signal demodulation, the data acquisition rate can reach up to 15 150 frames/s. The developed system together with a heat-resisting circular ECT sensor with 12 electrodes was used to monitor the ignition process of a cylindrical flame generated by a Bunsen burner. Experimental results show that the ECT system can locate the position and capture the dynamic process of the flame with a high temporal resolution.