Ect电容层析成像

… Electrical capacitance tomography (ECT) is a type of imaging technique that has been developed in industrial process tomography applications since the late 1980s and early 1990s[1]. …

For years scientists have been writing horrendously complicated programs to try to simulate on computer screens what they think goes on inside pipelines, chemical-mixing vessels and …

… Electrical capacitance tomography (ECT) is well established for 2D imaging of multiphase … In particular, we demonstrate that the changes in capacitance in a 3D sensor can be as much …

Electrical tomography techniques for process imaging are very prominent for industrial applications, such as the oil and gas industry and chemical refineries, owing to their ability to provide the flow regime of a flowing fluid within a relatively high throughput. Among the various techniques, electrical capacitance tomography (ECT) is gaining popularity due to its non-invasive nature and its capability to differentiate between different phases based on their permittivity distribution. In recent years, several hardware designs have been provided for ECT systems that have improved its resolution of measurements to be around attofarads (aF, 10 −18 F), or the number of channels, that is required to be large for some applications that require a significant amount of data. In terms of image acquisition time, some recent systems could achieve a throughput of a few hundred frames per second, while data processing time could be achieved in only a few milliseconds per frame. This paper outlines the concept and main features of the most recent front-end and back-end electronic circuits dedicated for ECT systems. In this paper, multiple-excitation capacitance polling, a front-end electronic technique, shows promising results for ECT systems to acquire fast data acquisition speeds. A highly parallel field-programmable gate array (FPGA) based architecture for a fast reconstruction algorithm is also described. This article is part of the themed issue ‘Supersensing through industrial process tomography’.

Image reconstruction of electrical capacitance tomography (ECT) is a typical inverse problem owing to non-linearity and ill-posedness. At the same time, progress towards the solution of this kind of problem has been made at good speed as a branch of mathematics in the past three decades. In this paper, most of the regularization tools developed for the inverse problem are applied to the reconstruction of various simulated images by ECT. The results show promise for ECT image reconstruction by regularization methods. The non-linearity of the sensitivity matrix seems to be the major problem.

… Due to the ‘soft-field’ nature of electrical capacitance tomography, it is necessary to employ an iterative approach for image reconstruction in order to obtain good-quality images. In an …

Based on the electrical capacitance tomography technique, a new method for the void fraction measurement of two-phase flow is proposed. A 12-electrode void fraction measurement system is established. A mathematical model of image reconstruction of electrical capacitance tomography is developed. To obtain the quantitative information of two-phase flow, combining the Tikhonov regularization principle and the algebraic reconstruction technique algorithm, a new image reconstruction algorithm is presented. The experimental results show that the accuracy of void fraction measurement is satisfactory. The proposed method is suitable for the void fraction measurement of many kinds of two-phase flow.

Due to the rapid growth of Electrical Capacitance Tomography (ECT) applications in several industrial fields, there is a crucial need for developing high quality, yet fast, methodologies of image reconstruction from raw capacitance measurements. Deep learning, as an effective non-linear mapping tool for complicated functions, has been going viral in many fields including electrical tomography. In this paper, we propose a Conditional Generative Adversarial Network (CGAN) model for reconstructing ECT images from capacitance measurements. The initial image of the CGAN model is constructed from the capacitance measurement. To our knowledge, this is the first time to represent the capacitance measurements in an image form. We have created a new massive ECT dataset of 320K synthetic image measurements pairs for training, and testing the proposed model. The feasibility and generalization ability of the proposed CGAN-ECT model are evaluated using testing dataset, contaminated data and flow patterns that are not exposed to the model during the training phase. The evaluation results prove that the proposed CGAN-ECT model can efficiently create more accurate ECT images than traditional and other deep learning-based image reconstruction algorithms. CGAN-ECT achieved an average image correlation coefficient of more than 99.3% and an average relative image error about 0.07.

… present study two modern day tomographic systems were evaluated with respect … electrical capacitance tomography (ECT) tomograph and a time-resolved X-ray tomography tomograph…

Electrical capacitance tomography exhibits great potentials in the visualization measurement of industrial processes, and high-precision images are of great significance for the reliability and usefulness of measurement results. In this paper, we propose a deep learning-based inversion method to ameliorate the reconstruction accuracy. With the aid of the deep learning methodology, the prior from the images reconstructed by a certain imaging technique to the true images is abstracted and stored in the deep extreme learning machine. A new cost function is constructed to encapsulate the prior from the proposed deep learning model and the domain expertise about imaging targets, and the split Bregman algorithm and the fast iterative shrinkage thresholding technique are combined into a new numerical method to effectively solve it to get the final reconstruction. The numerical and experimental results validate that the inversion method proposed in this paper reduces the reconstruction artifacts and deformations and leads to the much improvement in the imaging quality.

A stray-immune AC capacitance measuring circuit has been developed for electrical capacitance tomography. For this application a high excitation frequency is essential to achieve high sensitivity and fast data collection rates, and also to reduce the effect of any conductive component in parallel with the measured capacitance. A high excitation frequency has been made possible by using some novel methods: (a) a high frequency digital signal generator; (b) parameter-optimised AC amplifiers and (c) a phase-sensitive demodulator utilising CMOS switches. With a 500 kHz excitation signal the circuit has good linearity and stability, and a resolution of 0.035 fF.

… the plastic pellet cooling process by using electrical capacitance tomography,” Measurement … obtained by electrical capacitance tomography,” Powder Technology, vol. 198, no. 1, pp. …

… process tomography techniques, the most conspicuous are those based on the measurement of electrical properties through the utilization of the capacitive, … , electrical tomography is …

This paper presents highly robust, novel approaches to solving the forward and inverse problems of an Electrical Capacitance Tomography (ECT) system for imaging conductive materials. ECT is one of the standard tomography techniques for industrial imaging. An ECT technique is nonintrusive and rapid and requires a low burden cost. However, the ECT system still suffers from a soft-field problem which adversely affects the quality of the reconstructed images. Although many image reconstruction algorithms have been developed, still the generated images are inaccurate and poor. In this work, the Capacitance Artificial Neural Network (CANN) system is presented as a solver for the forward problem to calculate the estimated capacitance measurements. Moreover, the Metal Filled Fuzzy System (MFFS) is proposed as a solver for the inverse problem to construct the metal images. To assess the proposed approaches, we conducted extensive experiments on image metal distributions in the lost foam casting (LFC) process to light the reliability of the system and its efficiency. The experimental results showed that the system is sensible and superior.

… Electrical capacitance tomography (ECT) is used to image cross-sections of industrial processes … JE 1993 A new reconstruction algorithm for process tomography Meas. Sci. Technol. …

… technique using Electrical Capacitance Tomography (ECT) imaging. Traditionally ECT is used for industrial process tomography as a low resolution but fast tomographic imaging …

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.

… for fast 3-D electrical capacitance tomography (ECT) of flow … and design of electrical capacitance tomography sensors,” … design of an electrical capacitance tomography sensor for use …

Three dimensional Electrical Capacitance Tomography (3D ECT) is an inexpensive tool for diagnosing non-conductive components of industrial processes. Although relatively mature, it …

… is the regularised Gauss-Newton method, which has been chosen for 3D ECT imaging in this study. To study the method in 3D ECT, the algorithm has been tested with simulated data. …

Kerja penyelidikan ini membentangkan proses pembinaan model bagi Pengesan Kapasitan Elektrik Tomografi (ECT) menggunakan Perisian Kaedah Elemen Terhingga (Finite Element method–FEM) COMSOL Multiphysics. Meskipun pengesan fizikal adalah dalam bentuk tiga dimensi (3D) tetapi secara amnya sering dimodelkan secara kepingan/ keratan rentas dalam bentuk dua dimensi (2D). Projek ini menunjukkan pendekatan model dalam bentuk geometri 3D dan 2D, linear FEM menggunakan perisian COMSOL Multiphysics dibina adalah untuk mendapatkan nilai kapasitor di antara elektrod apabila medan elektrik dikenakan dan untuk melihat bagaimana pengagihan permittivity di dalam paip yang bertutup menerusi pengesan. Bayang–bayang yang direkacipta dan nilai–nilai diukur dikemukakan dalam bentuk paip yg kosong dan aliran anulus. Model ECT adalah mewakili perkakasan yang sedia ada, ECT mudah alih yang telah dibina oleh Kumpulan Penyelidikan PROTOM UTM. Kata kunci: Pengesan; model; ECT; COMSOL multiphysics This work presents the development process for modeling an ECT (Electrical Capacitance Tomography) sensor using FEM software package COMSOL Multiphysics. The physical sensors are 3D dimensional but it has been common to model the slice or the cross–section in 2D. This project shows the modeling approach for 2D and 3D geometries, the linear Finite Element method (FEM) using COMSOL Multiphysics is developed in order to obtain the capacitance between electrodes when an electric field is applied and to obtain the permittivity distribution inside the closed pipe from the sensor. Generated phantoms and measured values are presented for empty and annular pattern. Simulation is verified using phantoms inside the 16 electrode sensor. The ECT model is representative by existing hardware, Portable ECT, PROTOM Research Group UTM. Key words: Sensor; modeling; ECT; COMSOL multiphysics

… In this paper, the authors present their own work on 3D capacitance tomography as a … D 2001 Electrical capacitance tomography: image reconstruction along electrical field lines …

… Electrode design is investigated for electrical capacitance tomography on a 1 mm-thick 3D planar domain. Arrays of square electrodes are located on both sides of the domain, which is …

… from the earlier 2D electrical capacitance tomography (ECT) … for fast 3-D electrical capacitance tomography (ECT) of flow … Fast and robust 3D electrical capacitance tomography,” Meas…

… of using a portable 16-segmented Electrical Capacitance Tomography (ECT) sensor and a … /oil multiphase flow. The concentration profile obtained from the capacitance measurements …

Measurement of oil-gas two-phase flow parameters such as Gas Void Fraction (GVF) and phase distribution plays a vital role in oil and gas industries. To quantitatively evaluate the performance of Electrical Capacitance Tomography (ECT) for measuring the complex dynamic oil-gas two-phase flows, a three-dimensional fluid dynamics-electrostatic field coupling model (3D-FECM) is proposed in this paper. Coupling simulation are carried out with a 12-electrode ECT sensor. Utilizing the 3D-FECM, the dynamic oil-gas two-phase flows and instantaneous ECT measurements are simultaneously obtained. Two GVF measurement approaches, i.e. the capacitance-based method and the image-based method, are used to calculate GVF. The permittivity distribution is reconstructed by using Linear Back Projection (LBP) and Landweber iteration. The capacitances with signal-noise ratios (SNRs) of 40 and 60 dB are generated for comparison and verification. Evaluation results show that the structural similarity between the ground truth and the reconstructed images using noise-free data by Landweber iteration are better than 0.765, while those by LBP are higher than 0.754, the noise with SNR of 60 dB has no obvious effect on the performance of image reconstruction, and the full-scale error of the image-based GVF prediction using 60 dB noisy data is within -0.82% to +6.09%, slightly better than that of the capacitance-based GVF results (i.e. −1.16% to +7.63%).

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.

… to extend electrical capacitance tomography (ECT) to the three-dimensional (3D) mode. This technique reveals information about the entire structure of the flow that is presented as the …

Capacitive sensors are found in numerous applications, and they are capable of sensing several parameters. Multiphase flows occur in many industrial processes that require proper monitoring to improve the efficiency and safety of plants and equipment. Detailed (high-resolution) flow information is required from dedicated flow experiments at a laboratory scale to develop and validate flow modelings. In both cases, capacitive flow sensors have been applied to have a varying degree of flow detailing, e.g., from simple capacitive probes up to capacitive flow imaging and tomography. This article reviews the different capacitive sensors applied to multiphase flow measurement and imaging. Operating principles, sensor geometries, and capacitive measuring circuits are presented and discussed along with advantages and disadvantages, focusing on flow applications and possible flow parameters yielded from sensors. Some new trends in capacitive flow sensors are also presented.

… This paper investigates the identification of flow regimes for oil–gas two-phase flows using … , as the capacitance measurements (the inputs of the SVM) contain flow regime information. …

… — A portable capacitance tomography system for real-time imaging of multiphase flows is … that the Electrical Capacitance Tomography (ECT) System is applicable in flow visualization (…

… Electrical Capacitance Tomography (ECT) is well established as a tool for multiphase flow studies when permittivities of the media in the flow, are not too different, eg for oil and gas. In …

… for the Electrical Capacitance Tomography of two-phase flow … in capacitance tomography imaging of two phase flow … inverse problem of electrical capacitance tomography and its …

… ECT has been used in the past to image gas–oil flows, but only in atmospheric or low-pressure situations [5], [6]. The 12-electrode pressure-resistant capacitance tomography sensor …

This article investigates a rotational data collection strategy for planar array electrical capacitance tomography (ECT) to improve the imaging of complex-shaped objects in scenarios, where access to the object is limited. Planar array of ECT can produce 2-D and 3-D images of changes in the dielectric permittivity of the object, but detecting complex-shaped objects may require more electrodes in the array, which can decrease the quality of capacitance measurements and make it challenging to detect objects at greater depths. With the air background as calibration measurements, by rotating the sensor array or the object, more independent data can be obtained, which can enhance image quality compared to traditional planar array ECT. This article presents the experimental results of image enhancement through visual reconstruction of known-shaped dielectric test samples and quantitative analysis against the ground truth. These findings suggest that rotational data collection has the potential to improve image quality in planar array ECT for detecting complex-shaped objects.

Process tomography techniques play an important role in visualizing and monitoring industrial processes, which help to produce high quality product without affecting the work flow in plants. The industrial process tomography techniques, i.e., electrical tomography and computerized tomography, have been widely applied. Such tomographic tools can be used to investigate various types of multi-phase flows, in which the components may differentiate in density, conductivity, and permittivity. In a gas-liquid-solid flow, however, it is usually difficult for the existing tomographic tools to visualize the distributions of all three phases. In addition, it is necessary to assume some simplifications, i.e., by viewing two disperse phases as one unified phase. The objective of this research is to provide a dual-modality imaging tool by combining electrical capacitance tomography (ECT) and electromagnetic tomography (EMT). First, an integrated dual-modality sensor was designed and implemented on the same cross-section of the process vessel. Subsequently, dual-modality tomographic measurements were collected by a custom-built multi-channel impedance measurement system. The performance of the dual-modality sensor was verified by numerical simulations and experimental tests, showing that it can produce reliable ECT and EMT measurements at a satisfying signal-to-noise ratio. The complementary tomographic images can be obtained from ECT and EMT, and the distributions of two disperse phases, i.e., gas and solid phases, can be observed. The preliminary image fusion results were also given by combining the information from both the ECT and EMT images.

… finite element, a model of Electrical Capacitance Tomography electrodes array was constructed. Based on the model, the sensitivity matrix of the sensor was calculated and sensitivity …

… electrical capacitance tomography (ECT) with focus on illuminating the design criteria involved in the radial and axial dimensions of different electrodes used in ECT sensors. After …

Planar electrical capacitance tomography (PECT) is sensitive to the dielectric changes in its proximity; therefore, it has an attractive prospect in the non-destructive evaluation for the non-metallic composite materials. Currently, the planar ECT employs the static image method for the defect detection, which uses an individual frame of measurements for image reconstruction. The use of static image methods for defect detection depends greatly on the spatial resolution of image reconstruction algorithms. However, the ECT static images are usually of low spatial resolution, primarily due to the ill-posedness in solving its inverse problem. In this article, a dynamic imaging method has been proposed, aiming to detect the small defects from the temporally consecutive images. The Tikhonov regularization method is first employed for achieving the static image reconstructions. In addition, the level set method has been utilized for the image segmentation to distinguish between the defect and background materials. Subsequently, the dynamic imaging method that based on the frame-difference methods has been used for calculating the contour of target defects. The numerical simulations and experiments showed that the defect of different sizes and shapes could be figured out using the dynamic imaging method. It also can be shown that the dynamic imaging method offers more possibilities and ways in detecting the defects.

… a meaningful reconstruction result. In this paper, an image reconstruction algorithm for ECT is … The image reconstruction problem is transformed into an optimization problem and the …

PurposeElectrical capacitance tomography (ECT) and electrical resistance tomography (ERT) are promising techniques for multiphase flow measurement due to their high speed, low cost, non-invasive and visualization features. There are two major difficulties in image reconstruction for ECT and ERT: the “soft-field”effect, and the ill-posedness of the inverse problem, which includes two problems: under-determined problem and the solution is not stable, i.e. is very sensitive to measurement errors and noise. This paper aims to summarize and evaluate various reconstruction algorithms which have been studied and developed in the word for many years and to provide reference for further research and application.Design/methodology/approachIn the past 10 years, various image reconstruction algorithms have been developed to deal with these problems, including in the field of industrial multi-phase flow measurement and biological medical diagnosis.FindingsThis paper reviews existing image reconstruction algorithms and the new algorithms proposed by the authors for electrical capacitance tomography and electrical resistance tomography in multi-phase flow measurement and biological medical diagnosis.Originality/valueThe authors systematically summarize and evaluate various reconstruction algorithms which have been studied and developed in the word for many years and to provide valuable reference for practical applications.

Electrical Capacitance Tomography (ECT) image reconstruction has been largely applied for industrial applications. However, there is still a crucial need to develop a new framework to enhance the quality of reconstructed images and make it faster. Deep learning has recently boomed and applied in many fields since it is good at mapping complicated nonlinear functions based on series of artificial neural networks. In this paper, a novel image reconstruction method based on a deep neural network is proposed. The proposed image reconstruction algorithm mainly uses Long Short-Term Memory (LSTM) deep neural network, which is abbreviated as LSTM-IR algorithm. A big simulation dataset containing 160k pairs of instances is created to train and test the performance of the proposed LSTM-IR algorithm. Each pair of the sample has a predefined permittivity distribution vector and corresponding capacitance vector. The generalization ability and feasibility of the LSTM-IR network are measured using contaminated data, data not included in the training dataset, and experimental data. The preliminary results show that the proposed LSTM-IR method can create fast and more accurate ECT images than traditional and deep learning image reconstruction algorithms.

In this paper, the closed-loop control strategy was facilitated to iteratively reconstruct images of high quality for electrical capacitance tomography (ECT). The classical direct reconstruction algorithm, e.g., Calderon’s method, was first used to roughly estimate the permittivity distributions. The yielded distributions were subsequently utilized to generate the mutual capacitances between different electrodes. A fast capacitance extraction method with constraints of equal potential on all nodes in each electrode was also introduced for the first time to calculate the mutual capacitances in terms of the discretized Dirichlet-to-Neumann map. In the method, only the stiffness matrix in the finite-element model was involved to calculate the capacitances between electrodes regarded as floating potentials, and the consumption time can be dramatically reduced. The calculated capacitances from the reconstructed distributions were then compared with the measured data from the ECT sensor. The deviations were used to correct the reconstructed distributions. A proportional-integral-derivative controller was introduced to perform a closed-loop control strategy for image correction. Similar to the classical feedback control systems, Calderon’s method was treated as the control object to generate an output. The output of the retrieved distributions passes the capacitance calculation and the capacitances are used as the negative feedback. In addition, the invariant property of the conformal transformation was strictly proved for the first time for the ECT sensor with a cross-section of any simply-connected region. As a result, the proposed iterative reconstruction algorithm can be promoted to the cases of any non-circular ECT sensors, e.g., square sensor. Simulated data contaminated with and without noises and real data from the experiments were used to demonstrate the feasibility and effectiveness of the proposed iterative reconstruction algorithm for ECT.

… The electrical capacitance tomography (ECT) is a visualization measurement method and can reconstruct … based on given capacitance values, in which the effectiveness of the image …

… as a promising process tomography (PT) … image reconstruction algorithms. In this paper, based on the wavelet multi-scale analysis method, an efficient image reconstruction algorithm is …

Electrical Capacitance Tomography (ECT) is a well-established industrial process tomography technique. Image reconstruction for the ECT is a nonlinear problem, and the inverse problem is usually ill-posed and ill-conditioned. Hence, the solutions for the ECT are not unique and highly sensitive to the measurement noise. In this paper, a novel tuned fuzzy algorithm is proposed for reconstructing accurate images to monitor the distribution of the multi-phase flow in the industrial process. The proposed algorithm utilizes a Tuned Fuzzy Inference System (TFIS) to overcome the nonlinear characteristics of the ECT system. The optimal parameters of the fuzzy membership functions are obtained using the Particle Swarm Optimization (PSO) technique. In the past few decades, the naturally inspired intelligent swarm algorithms got more attention due to their wide spectrum of research for real-world complex problems optimization. The proposed PSO-tuned fuzzy algorithm is fast since it does not require solving the forward problem to update the sensitivity matrix. Comparing the results with traditional reconstruction algorithms, the proposed algorithm performs better in visual effects and imaging quality, since the image edges and details are better preserved.

Image reconstruction is the main research problem of electrical capacitance tomography (ECT). In this article, a novel ECT image reconstruction algorithm based on an efficient sparse Bayesian learning (ESBL) algorithm is presented. This algorithm takes the Gaussian-scale mixture model as the prior distribution of the parameters to increase the flexibility of the model. Then, a surrogate function is used to replace the Gaussian likelihood function to reduce the computational complexity of the algorithm. Finally, the original cost function is equivalently converted into a concave–convex optimization problem through logarithm, and the block coordinate descent (BCD) method is used to solve the problem under the majorization–minimization (MM) framework. In order to verify the effectiveness of this algorithm, the Laplace distribution and the Student’s T distribution are used as the prior distribution of the parameters to achieve two specific implementations of this algorithm, and simulation and experiments are carried out. Compared with the sparse Bayesian learning (SBL) algorithm, the Laplace prior-based Bayesian compress sensing (LPBCS) algorithm, the total variation (TV) algorithm, and the Landweber algorithm, the presented EBSL algorithm with the Laplace prior distribution has better image quality and fairly good real-time performance.

… a new image reconstruction algorithm with sparse representation. To evaluate the performance of the proposed algorithm comprehensively, an iterative thresholding algorithm with a …

… capacitance and changes in permittivity distribution complicates reconstruction algorithms and … -field effect in ECT image reconstruction, developing algorithms for providing high-quality …