Electrical Capacitance Tomography System Research Articles

ECT in a large scale industrial pneumatic conveying system

The application of electrical capacitance tomography (ECT) for monitoring of industrial processes has been studied and proposed by many researchers. Examples can be found in monitoring of multiphase flows or mixing processes in reactors. Demonstrations of the functionality based on lab and test rig measurements have proven the potential of the proposed principles. This paper discusses the application of an ECT system in a heavy industries application. The harsh operating conditions in the industrial environment pose several challenges for the application of sophisticated measurement technology. This work addresses key aspects for the application of an ECT measurement system in such an environment. Specifically the electrical system design and the influence of the temperature are addressed. Relevant parameters and possible solutions are discussed. Furthermore the application of ECT as instrument for mass flow metering in pneumatic conveying processes is addressed. Supportive measurement studies from test rig experiments and comparative simulation studies are presented. Therefore, the paper provides a concise discussion on the application of ECT under harsh operating conditions, as well as the use of ECT as a measurement device for process measurement. The work concludes with a presentation of a measurement system in an industrial plant in which the proposed concepts were succesfully implemented.

ECT image reconstruction based on sensitive field expansion and optimization

Electrical capacitance tomography (ECT) is an efficient method for addressing the issue of two-phase flow monitoring. Most current methods result in low image reconstruction accuracy due to soft field issues. This paper propose an ECT image reconstruction method based on sensitive field expansion and optimization, which improve reconstruction efficiency and accuracy. Firstly, a sensitivity field optimization method based on flow pattern identification was proposed. The flow pattern recognition determines the flow pattern to which the input signal belongs and selects the sensitive field for the corresponding flow pattern. Secondly, a sensitive field expansion method based on feature extraction is proposed. The ECT image is modeled as a finite rate of innovation signal, sampled using an exponential reproducing kernel. Feature information is extracted from the input signal for data fusion, and the optimized sensitive field is expanded into a new sensitive field distribution matrix by zero-padding and random reorganization. Then, based on optimized and expanded sensitive fields, a sparse image reconstruction method is proposed. Image reconstruction by constructing comprehensive observation equation to obtain the original permittivity distribution vector of the ECT system using the sparsity of the sensitivity matrix and capacitance signal. Finally, the ECT hardware system and the upper computer measurement and imaging integration software are designed. The experimental results show that the method outperforms other existing algorithms in terms of imaging indexes, has better imaging results.

Real Time Measurement of Multiphase Flow Velocity using Electrical Capacitance Tomography

Accurate and real-time measurement of fluid flow velocity is crucial in various industrial processes, especially when dealing with multiple phase fluids. Traditional flow measurement methods often struggle to accurately quantify the velocity of complex multiphase flows within pipes. This challenge necessitates the exploration of innovative techniques capable of providing reliable measurements. This paper proposes the utilization of Electrical Capacitance Tomography (ECT) as a promising approach for measuring the velocity of multiple phase fluids in pipes. The ECT technique involves the non-intrusive imaging of the electrical capacitance distribution within the pipe. By utilizing an array of electrodes placed around the pipe circumference, the capacitance distribution can be reconstructed, offering insight into the fluid flow patterns. By analyzing the temporal changes in the capacitance distribution, the velocity of different phases within the pipe can be estimated. To achieve accurate velocity measurements, an ECT system needs to account for the complexities introduced by multiphase flows. Various image reconstruction algorithms, such as linear back-projection and iterative algorithms like Gauss-Newton and Levenberg-Marquardt, are employed to reconstruct the capacitance distribution. Additionally, advanced signal processing techniques, such as cross-correlation analysis and time-difference methods, are used to extract velocity information from the reconstructed images. This paper presents an experimental investigation of measuring the velocity of multiple-phase fluids in pipes using the ECT technique. The study aims to address the challenges associated with different flow regimes, fluid properties, and pipe geometries by exploring advancements in electrode design, system calibration, and data processing techniques to enhance the accuracy and robustness of ECT-based velocity measurements.

Identification of two-phase flow patterns based on capacitance data of electrical capacitance tomography with semi-supervised generative adversarial network.

Currently, the flow pattern identification algorithms based on ECT (electrical capacitance tomography) technology have low identification accuracy for complex flow patterns and require a large amount of label data for learning. A novel flow pattern identification method based on a semi-supervised generative adversarial network (SGAN) with capacitance data of ECT is proposed. First, the principles of the ECT technique and general GAN are briefly described, and the model parameters, loss function, and training process of the SGAN are explained in detail. Second, a capacitance data sample set of 11 400 random flow patterns is constructed by co-simulations of COMSOL and MATLAB, and then, the SGAN and BP (back propagation) and SVM (support vector machine) network models are trained and validated by the training set. Finally, static experiments are conducted on the self-developed ECT system, and the identification results of different algorithms are compared and analyzed by modifying the label sample size of the training set. The experimental results show that SGAN maintains a higher average identification accuracy under the training condition where the number of label samples of SGAN is ten times smaller than that of the other two algorithms.

Monitoring and Characterizing the Flame State of a Bluff-Body Stabilized Burner by Electrical Capacitance Tomography

Unstable combustion phenomena such as flame flashback, flame liftoff, extinction and blowout frequently take place during the operation of the bluff-body stabilized burner. Therefore, flame state monitoring is necessary for the safe operation of the bluff-body stabilized burner. In the present study, an electrical capacitance tomography (ECT) system was deployed to detect the permittivity distribution in the premixing channel and further characterize the flame states of stabilization, flashback, liftoff, extinction and blowout. A calderon-based reconstruction method was modified to reconstruct the permittivity distribution in the annular premixing channel. The detection results indicate that the permittivity in the premixing channel increases steeply when the flame flashback takes place and decreases obviously when the flame lifts off from the combustor rim. Based on the varied permittivity distribution at different flame states, a flame state index was proposed to characterize the flame state in quantification. The flame state index is 0, positive, in the range of −0.64–0, and lower than −0.64 when the flame is at the state of stable, flashback, liftoff and blowout, respectively. The flame state index at the flame state of extinction is the same as that at the flame state of liftoff. The extinction state and the blowout state can be distinguished by judging whether the flame flashback takes place before the flame is extinguished. These results reveal that the ECT system is capable of monitoring the flame state, and that the proposed flame state index can be used to characterize the flame state.

Wet fluidization characterization of potash particles in a pulsation-assisted fluidized bed

In order to improve fluidization behavior, pulsed airflow was employed to break agglomeration and eliminate channeling in a fluidized bed with wet potash particles. The effects of pulsation frequency, pulsed air to continuous flow ratio (r), and inlet relative humidity of the air on bubbling behavior were investigated via an electrical capacitance tomography system. A frequency of 1.0 Hz and an r of 0.33 with 0.1 s opening time were found to be the optimum condition, leading to the lowest minimum fluidization velocity (umf) and generation of homogeneous bubbles in size and shape. A new theoretical model was developed to predict the umf of wet particles in a fluidized bed by considering both the liquid bridge force and resonant force resulting from the pulsation. Average absolute deviation percentage values between the predicted umf and the experimental data were 13.8 and 20.7 for the dry and wet particles, respectively, indicating good agreement.

Electrode configuration study for three-dimensional imaging of on-chip ECT

Conventional electrical capacitance tomography (ECT) is widely used for monitoring the fluids flow in a pipeline. As the emergence of microfluidics, the tomography system has been miniaturized and integrated into the microfludic platform for imaging purposes. The on-chip ECT is designed to monitor the permittivity distribution of the micro-platform by integrating the planar electrodes with the sensing region. However, limited research has been reported on the electrode design of on-chip ECT, especially for three-dimensional imaging. Thus, this study investigated the electrode design of an on-chip ECT that is capable for image reconstruction in three-dimensions. Four different electrode configurations with different numbers of electrode and arrangements are investigated by simulation to determine the appropriate configuration for three-dimensional imaging. The electrode dimension is optimized based on the sensitivity distribution using the sensitivity variation parameter (SVP). The simulation results shows that the electrode configuration with dual sensing planes enable three-dimensional imaging. The central electrode of each sensing plane is crucial for restoring a floating object. In experiment, the imaging object that was positioned at different vertical and horizontal locations was reconstructed successfully with an average correlation coefficient of 0.4370 using linear back projection (LBP) algorithm. This work has disclosed the appropriate electrode configuration for the three-dimensional imaging of an on-chip ECT system.

Evaluation of Image Enhancement Techniques for Electrical Capacitance Tomography Applications

The fast generation of images in Electrical Capacitance Tomography (ECT) systems is a desirable feature for many industrial applications. Non-iterative reconstruction algorithms which qualify for this requirement generate poor-quality images. The Linear Back Projection (LBP) is the fastest non-iterative reconstruction algorithm. The challenge is to find a technique to improve the quality of images from LBP at a low computational cost. Image enhancement techniques have been investigated for improving the quality of images reconstructed from the LBP algorithm. Simulated and measured static and dynamic flow data were used in the evaluation. The performance results were benchmarked with results from the Projected Land Weber (PLW) one of the accurate iterative reconstruction algorithms. The Gompertz enhancement algorithm was found to have 3.5 times more computation cost than the LBP reconstruction algorithm and the accuracy of the iterative PLW reconstruction algorithm. This is noteworthy since the algorithm does achieve a good balance between accuracy and speed. The fact that the accuracy gained satisfies the reservoir management standards in the multiphase hydrocarbon production sector is significant in this regard.
 Keywords: Electrical Capacitance tomography, Multiphase flow imaging, Maximum entropy thresholding, Gompertz distribution, Image enhancement

A pilot study on intracerebral hemorrhage imaging based on electrical capacitance tomography

Introduction: Intracerebral hemorrhage (ICH) is a devastating disease with high rates of mortality and disability. The survival rate and postoperative outcome of ICH can be greatly improved through prompt diagnosis and treatment. CT and MRI are now the gold standards for the diagnosis of ICH, but they are not practical for use in pre-hospital emergencies or at the bedside monitoring.Methods: Based on the earlier research of ICH detection with a single parallel plate electrode sensor, we developed a 16-electrode Electrical Capacitance Tomography (ECT) system for two-dimensional tomographic imaging of ICH in this study. A 5-layer spherical numerical model and an ex vivo porcine physical model of ICH were created for ECT simulation imaging and actual imaging, respectively, to assess the feasibility of this ECT for ICH imaging.Results: The bleeding circles were easily seen in the image reconstruction in numerical imaging. In ex vivo imaging, the existence of bleeding was also more clearly shown with the ECT system; however, the position of the bleeding reconstructed in the image was offset by 3 mm from the real site.Discussion: The study analyzes the causes of this discrepancy and discusses the steps that may be taken to rectify it. Overall, the simulation and ex vivo experimental trials validated the potential of ICH imaging with the ECT method; however, further work is required to increase the performance of the ECT and a more advanced imaging reconstruction algorithm is urgently needed for ICH imaging.

Electrical capacitance tomography-based estimation of slug flow parameters in horizontally aligned pneumatic conveyors

Pneumatic conveying is a widely applied technique for the transportation of powders. Dense phase conveying such as slug flow is the preferable operating condition of such transport systems. Advantages are the reduced energy and conveying gas consumption and reduced material wear. The design and the operation of dense phase conveyors is a challenging task due to complex flow dynamics and the lack of reliable flow meters, which are crucial for process control. In this work the capabilities of electrical capacitance tomography (ECT) for slug flow parameter estimation are analysed. The estimation of flow parameters is addressed and demonstrated by means of laboratory experiments. Amongst other parameters it is shown that mass concentration distributions as well as particle velocity fields can be obtained from tomographic image reconstruction results, which are substantial parameters for potential mass flow metering. Additionally, the proposed estimation techniques are applied to signals provided by an ECT system, which is installed within a large-scale pneumatic conveyor of an industrial process plant. It is observed that also Geldart group A powders with Archimedes numbers in the scale of Ar≈1e0 are conveyable in slug-like structures which can be separated by stationary or non-stationary layers. Furthermore, various slug flow properties of powders with Ar>1e2 reported in literature are confirmed but also deviating properties are observed, leading to novel insights into horizontal dense phase flow processes of powders with Ar≈1e0. The results demonstrated in this work are pointing out the capabilities of ECT for flow analyses, which are enabling further insights into flow mechanisms and future developments of flow meters for dense phase flow processes.

Fluidization and bubbling behavior of potash particles in a deep fluidized bed

Most existing models for predicting bubble size and bubble frequency have been developed for freely bubbling fluidized beds. Accurate prediction of bubbling behavior in deep fluidized beds, however, has been a challenge due to the higher degree of bubble coalescence and break up, high probability of the slugging regime, partial fluidization, and chaotic behavior in the bubbling regime. In this work, the bubbling and fluidization behavior of potash particles was investigated in a deep fluidized bed employing a twin-plane electrical capacitance tomography (ECT) system. Solid volume fraction, average bubble velocity, average bubble diameter, and bubble frequency in both bubbling and slugging regimes were measured at two different bed height ratios (H/D = 3.5 and H/D = 3.78). This work is the first to illustrate a sequential view of bubbles at different superficial gas velocities in a fluidized bed. The results show that both the bubble diameter and rising velocity increased with increasing the superficial gas velocity for the two bed heights, with larger values observed in the deeper bed compared to the shallower one. Predicted values for bubble diameter, bubble rise velocity and bubble frequency from different models are compared with the experimental data obtained from the ECT system in this work. Good agreement has been achieved between the values predicted by the previous models and the experimental data for the bubble diameter and bubble rise velocity with an average absolute deviation of 16% and 15% for the bed height of 49 cm and 13% and 8% for the bed height of 53 cm, respectively.

Study on the characteristics of self-developed pulverized coal flow regulation valve for coal gasification process

Pulverized coal flow regulation valve is one of the key equipment of pulverized coal gasification process, which plays an essential role in regulating coal flow rate. However, due to complex valve flow channels and gas-solid interactions, there were few reports on the characteristics of this valve. In this paper, experiments of dense-phase pneumatic conveying were carried out with a self-developed pulverized coal flow regulation valve installed in the pipeline. Firstly, the effect of the valve opening on the pressure distribution of the conveying system was analyzed. Then, the flow patterns of gas-solid two-phase flow inside the vertical pipe and inside the horizontal pipe were investigated by the Electrical Capacitance Tomography (ECT) system, respectively. Finally, after analyzing the influence of the regulation valve on the gas-solid flow parameters and based on data regression analysis, the relationship between valve opening and solid velocity and concentration were fitted, and a semi-empirical model was established for pulverized coal flow rate prediction. The model can effectively predict the pulverized coal flow rates under different valve openings with deviations mostly less than± 10%, which is of great significance for flow rate regulation in practical applications.

A Run-Time Reconfiguration Method for an FPGA-Based Electrical Capacitance Tomography System

A desirable feature of an electrical capacitance tomography system is the adaptation possibility to any sensor configuration and measurement mode. A run-time reconfiguration of a system for electrical capacitance tomography is presented. An original mechanism is elaborated to reconfigure, on the fly, a modular EVT4 system with multiple FPGAs installed. The outlined system architecture is based on FPGA programmable logic devices (Xilinx Spartan) and PicoBlaze soft-core processors. Soft-core processors are used for communication, measurement control and data preprocessing. A novel method of FPGA partial reconfiguration is described, in which a PicoBlaze soft-core processor is used as a reconfiguration controller. Behavioral reconfiguration of the system is obtained by providing run-time access to the program code of a soft-core control processor. The tests using EVT4 hardware and different algorithms for tomographic scanning were performed. A test object was measured using 2D and 3D sensors. The time and resources required for the examined reconfiguration procedure are evaluated.

Prototype Portable Electrical Resistance Tomography

Tomography is a way to describe something non-destructively. Some types of Tomography are Electrical Resistance Tomography (ERT), Electrical Impedance Tomography (EIT), and Electrical Capacitance Tomography (ECT). This study aims to combine the ECT and ERT systems. The combination uses the ERT technique (Borehole method) and develops until it can be used like ECT. This research conducts three significant stages (design making, designed realization, and examination). The examination is carried out by simulation and experimental measurement. The simulation result is compared to the result of the experimental measurement. The result shows that both have the same patterns, but it has the amplitude of voltage difference pattern. It is because the resistivity result affects the measured voltage difference result. The higher the resistivity result of the medium, the smaller the measured voltage difference.Tomography is a way to describe something non-destructively. Some types of Tomography are Electrical Resistance Tomography (ERT), Electrical Impedance Tomography (EIT), and Electrical Capacitance Tomography (ECT). This study aims to combine the ECT and ERT systems. The combination uses the ERT technique (Borehole method) and develops until it can be used like ECT. This research conducts three significant stages (design making, designed realization, and examination). The examination is carried out by simulation and experimental measurement. The simulation result is compared to the result of the experimental measurement. The result shows that both have the same patterns, but it has the amplitude of voltage difference pattern. It is because the resistivity result affects the measured voltage difference result. The higher the resistivity result of the medium, the smaller the measured voltage difference.

Image Reconstruction Algorithm Based on Total Least Squares Target Correction for ECT.

In the image reconstruction of the electrical capacitance tomography (ECT) system, the application of the total least squares theory transforms the ill-posed problem into a nonlinear unconstrained minimization problem, which avoids calculating the matrix inversion. But in the iterative process of the coefficient matrix, the ill-posed problem is also produced. For the effect on the final image reconstruction accuracy of this problem, combined with the principle of the ECT system, the coefficient matrix is targeted and updated in the overall least squares iteration process. The new coefficient matrix is calculated, and then, the regularization matrix is corrected according to the adaptive targeting singular value, which can reduce the ill-posed effect. In this study, the total least squares iterative method is improved by introducing the mathematical model of EIV to deal with the errors in the measured capacitance data and coefficient matrix. The effect of noise interference on the measurement capacitance data is reduced, and finally, the high-quality reconstructed images are calculated iteratively.

Design and Simulation of an 8-Lead Electrical Capacitance Tomographic System for Flow Imaging

Electrical Capacitance Tomography (ECT) is a method for determining the dielectric permittivity distribution inside an object from measurements of external capacitance. The technique differs from conventional tomographic methods in which high-resolution images are formed from slices of the material. The measuring electrodes, which are metal plates, must be large enough to give a measurable change in capacitance. The main objective of this paper is the implementation and simulation of 8 external electrode ECT systems in order to increase the quality of reconstructed permittivity images while preserving the simplicity of design and fulfilling the demand for real-time process tomography. A complete sensor model was developed to improve the accuracy of the forward validation, especially the validation of measured data from neighboring electrodes. A prototype ECT sensor with high sensitivity was designed that can be applied to all materials which have low electrical conductivity. The capacitance between different electrode pairs is calculated for some typical permittivity distributions based on LabVIEW and MATLAB. The obtained capacitance data can be used to reconstruct images. The sensitivity distributions for the ECT sensors with different numbers of electrodes were analyzed. Preliminary tests were performed and the developed prototype showed good performance. The developed concept contributes to the study and comprehension of the ECT systems that can be used for the monitoring of oil-gas flow.

Analysis and Performance Evaluation of Entropic Thresholding Image Processing Techniques for Electrical Capacitance Tomography Measurement System

To improve image quality generated from the electrical capacitance tomography measurement system, the use of entropic thresholding techniques is investigated in this article. Based on the analysis of the principle of Electrical Capacitance Tomography (ECT) image reconstruction and entropic thresholding, various algorithms have been proposed for easy extraction of quantitative information from tomograms generated from the ECT system. Experiments indicate that proposed algorithms can provide high-quality images at no or minimum computational cost. It is easier to implement and integrate with classical algorithms such as Linear Back Projection, Singular value decomposition, Tikhonov regularization, and Landweber. Entropic thresholding techniques present a feasible and effective way toward the industrial utilization of ECT measurement systems.
 Keywords: Electrical Capacitance Tomography; Inverse Problem; Image Reconstruction; Entropic Thresholding

Study on the spatial and temporal distribution of the bed density in an air dense medium fluidized bed (ADMFB) based on the electrical capacitance tomography (ECT) measurement system

In this study, the ECT system was used to study the temporal and spatial distribution characteristics of bed density in an ADMFB under the influence of superficial gas velocity and static bed height. The results show that, In the axial distribution, the closer to the top of the bed at low gas velocity(<11.5 cm/s), the higher the density, and the closer to the top at high gas velocity (> 13 cm/s), the lower the density. In the radial distribution, the closer to the central axis, the lower the density. With the decrease of static bed height, the radial uniformity becomes worse. The optimal gas velocity is 12.5 cm/s, under which the bed spatial distribution is the most uniform, and the ecart probable moyen of spherical particles is 0.06. The separation density is smaller than the bed density and is close to the central axis density.

The capacitance tomography image reconstruction algorithm based on sensitivity field sensitivity matrix

Successful applications of ECT technology depend on the speed and precision of the image reconstruction algorithms. The image reconstruction for electrical capacitance tomography (ECT) is an inherently nonlinear and ill-posed inverse problem. To solve the problems, in this paper 12-electrode ECT system was set up to acquire real measurement capacitances under capacitance tomography that based on sensitivity field sensitivity matrix, which is T-LBP. In this paper four typical flow patterns are simulated, such as laminar flow, core flow, annular flow and bubbly flow, which in a circular section pipe. The simulation data indicate that the quality and the error, which was obtained in this paper, of the reconstructed images were better than the corresponding images obtained by the LBP and the Landweber algorithm. This new algorithm presents a feasible and effective way to research on image reconstruction algorithm for the industrial applications of Electrical Capacitance Tomography System.

Image Reconstruction for High-Performance Electrical Capacitance Tomography System Using Deep Learning

For great achievements in recent decades, image reconstruction for electrical capacitance tomography (ECT) has been considered in this study. ECT has demonstrated impressive potentials in multiprocess measurement, and the obtained images are of high resolution, which are suitable for advanced procedures in industrial and medical applications and across different tasks and domains. But the ECT system still requires improvements in the quality of image reconstruction given its importance of great significance to obtain the reliability and usefulness of measurement results. The deep neural network is used in this study to extract new features and to update the number of nodes and hidden layers in the system. Recently, deep learning exhibits suitable solutions in many flourishing fields based on different series of artificial neural networks for mapping nonlinear functions. To address the obstacles, this paper proposes an imaging method using an optimizer reconstruction model. An optimization model for imaging is generated as a powerful optimizer for building a computational model to ameliorate the reconstruction accuracy. Based on the deep learning methodology, the previous images reconstructed by using one of the imaging techniques to the required images are abstracted and stored in the deep learning machine, resulting in an error rate of 8.9%, and this is considered good on ECT. Therefore, an artificial neural network of the capacitance (ANNoC) system is introduced to estimate capacitance measurements.