Electrical Capacitance Tomography Imaging Research Articles

Study on detection of intracerebral hemorrhage based on frequency difference of permittivity

Introduction: Current detection of intracerebral hemorrhage (ICH), whether employing Electrical Capacitance Tomography (ECT) or other electrical imaging techniques, rely on time-difference measurements. The time-difference methods necessitate baseline measurements from the patient in a non-hemorrhagic state, which is impractical to obtain, rendering rapid detection of ICH unfeasible.Methods: This study introduces a novel approach that capitalizes on the distinct dispersion characteristics of the permittivity in brain tissue and the spectral variance of the permittivity between blood and other brain components. Specifically, the frequency-dependent variations in the permittivity are employed to achieve absolute detection of ICH, thereby eliminating the need for non-hemorrhagic baseline data. The methodology entails identification of two frequency points that the frequency-dependent variation in the permittivity at these two frequency points manifest the maximal difference between blood and other brain tissues. Subsequently, this permittivity differential at the two identified frequency points is utilized for hemorrhage detection. Experimental measurements were conducted using an impedance analyzer and a parallel plate capacitor to capture the capacitance in four single-component substances—distilled water, sheep blood, isolated pig fat, and isolated pig brain—as well as three mixed blood compounds—distilled water enveloping sheep blood, pig fat encapsulating sheep blood, and pig brain surrounding sheep blood—across a frequency range of 10 kHz to 20 MHz.Results: The results show that in different frequency bands, it is indeed possible to distinguish single-component substances from mixed substances by the frequency difference of capacitance variation. Comparative analysis reveals that the 1 MHz to 5 MHz frequency range is most effective for detecting blood in distilled water. For blood detection in pig fat, a 10 kHz to 1 MHz frequency range is identified as optimal, while a 10 kHz to 0.5 MHz frequency range is advantageous for blood detection in pig brain tissue.Discussion: The findings confirm that absolute detection of ICH is achievable through frequency-dependent variations in the permittivity. However, this necessitates the identification of the frequency band manifesting the largest difference of frequency-dependent variation between single-component and mixed substances. The study acknowledges limitations primarily due to the use of anticoagulant-altered sheep blood, which exhibits permittivity divergent from those of natural blood. Additionally, the in vitro pig fat and pig brain samples, having been subjected to freeze-thaw cycles, also demonstrate permittivity unrepresentative of in vivo tissue.

Microscale 3-D Capacitance Tomography with a CMOS Sensor Array.

Electrical capacitance tomography (ECT) is a non-optical imaging technique in which a map of the interior permittivity of a volume is estimated by making capacitance measurements at its boundary and solving an inverse problem. While previous ECT demonstrations have often been at centimeter scales, ECT is not limited to macroscopic systems. In this paper, we demonstrate ECT imaging of polymer microspheres and bacterial biofilms using a CMOS microelectrode array, achieving spatial resolution of 10 microns. Additionally, we propose a deep learning architecture and an improved multi-objective training scheme for reconstructing out-of-plane permittivity maps from the sensor measurements. Experimental results show that the proposed approach is able to resolve microscopic 3-D structures, achieving 91.5% prediction accuracy on the microsphere dataset and 82.7% on the biofilm dataset, including an average of 4.6% improvement over baseline computational methods.

On-line monitoring of flow process in a spout-fluid bed by combining electrical tomography and high-speed CCD camera

To investigate spouted flow characteristics in a rectangular spout-fluid bed with bafflers, a non-intrusive measurement approach, which combines electrical capacitance tomography (ECT), pressure measurements and high-speed CCD imaging technology, is proposed. The ECT sensor has 12 electrodes on the external wall and 12 electrodes inside, forming three imaging regions with 8 electrodes in each region. The flow hydrodynamic characteristics in the spouted bed e.g., pressure fluctuation, particle packing fraction and fountain form, are investigated. The frequency domain of pressure and particle packing fraction signals as well as ECT images indicate that the flow regime in the jet region transits from slugging to spouting in fountain formation process, and when the fluidization velocity in one side increases, the flow regime in the same region transits into slugging bed. The spouting pressure drop is affected by the fluidization condition in the side region, and the high characteristic frequency of pressure signal decreases when the side region condition changes from blockage to fluidization. The fountain height increases linearly with the superficial gas velocity. When the gas velocity is high, the fountain tends to be offset by the influence of the lateral airflow which is caused by the imbalance of the air pressure on two side regions.

Wavelet-fused richer convolution feature for multiphase flow visual monitoring of oil and gas production processes

Multiphase flow monitoring of the oil and gas production process is of great significance to the safety of oil and gas exploitation and production. Electrical capacitance tomography (ECT) is one of the most attractive technologies in the field of multiphase flow measurement due to the advantages of its non-radioactive and non-contact properties, good visualization, and low cost. We propose a reconstruction algorithm based on wavelet and richer convolution feature (W-RCF) for solving the problem of artifacts and edge blurring in ECT imaging. In the algorithm, the two-channel source images of Tikhonov regularization and Landweber are simultaneously decomposed by a three-level wavelet. On this basis, an image fusion rule combining Bayesian decision and maximum entropy threshold is established to optimize the wavelet coefficients at each scale. The rule can reduce image artifacts and compensate for the defects in the source images. Afterward, the fused images are input to the RCF network for training and testing, and ECT reconstructed images with higher quality are obtained. Based on the simulation and experimental results, it can be seen that the image reconstruction quality of W-RCF is significantly better than that of the linear back projection, Tikhonov regularization, Landweber, and convolutional neural network algorithms. Therefore, the W-RCF algorithm has higher accuracy and stronger adaptability for multiphase flow under different flow patterns, which provides an effective method of ECT image reconstruction and is more suitable for visual monitoring of multiphase flow in the oil and gas production process.

Image Reconstruction of Electrical Capacitance Tomography Based on Adaptive Support Driven Bayesian Reweighted Algorithm

Image reconstruction of electrical capacitance tomography (ECT) is a nonlinear and ill-posed inverse problem. Therefore, how to introduce an effective algorithm to reduce the ill conditioned degree of ECT imaging, thereby improving the imaging accuracy is an important subject of ECT algorithm research. In order to further study the subject, a novel ECT image reconstruction algorithm based on an adaptive support driven Bayesian reweighted (ASDBR) algorithm was proposed in this paper. The great advantage of this algorithm is that it can accurately extract the main features of the flow pattern and remove redundant information. This algorithm transforms the original problem into a series of subproblems with iteratively reweighted weights, and solves these subproblems by the iterative shrinkage-thresholding algorithm (ISTA). Comparisons are made among the ASDBR algorithm, the Landweber iterative algorithm, the sparse Bayesian learning (SBL) algorithm, and Lasso. Both simulation and experiment results show that the proposed new method considerably enhances the quality of the reconstructed image.

CFD-DEM study of gas-solid flow regimes in a Wurster type fluidized bed with experimental validation by electrical capacitance tomography

Wurster type fluidized bed is widely used for particle coating in many industrial sectors, the gas-solid flow regimes within the fluidized bed is an important issue but rarely discussed in the literature, either numerically or experimentally. In this work, a numerical method that couples computational fluid dynamics with the discrete element method (CFD-DEM) was proposed to investigate the gas-solid flow dynamics in a Wurster type fluidized bed, with a focus on the existing gas-solid flow regimes. Two types of simulation cases, i.e., cold flow cases and the cases accounting for adhesion forces, were carried out. Experimental data by electrical capacitance tomography (ECT) imaging was employed to validate the simulation results. In cold flow cases, two fluidization regimes, including plug, and multi-bubbling were observed in the annulus region of the fluidized bed. It was found that the multi-bubbling regime can further be classified into bottom, localized and global fluidization under different air velocities, and more than 83% of the total particle mass is kept within annulus region. With increase in the inter-particle adhesion force, the flow regime in the annulus region changed from multi-bubbling to single-bubbling, followed by plug flow and eventually defluidization. The multi-bubbling, single-bubbling, and plug flows can be discriminated by cycle time ranges of 0–4, 4–15 and more than 15, respectively. Finally, it was discovered that the particle circulation times was within the ranges of 3–9 s, and the gas-solid flow regimes can be used as an indicator of the circulation time distribution. The methodology and new findings in this study complement the existing techniques and knowledge for the optimization of coating process in a Wurster type fluidized bed.

Three-dimensional electrical capacitance tomography – A tool for characterizing moisture transport properties of cement-based materials

Water often plays a major role in the degradation processes of cement-based materials and structures, and thus the durability of these structures strongly depends on their ability to impede transport of water. This paper reports the results of imaging three-dimensional (3D) unsaturated moisture flow in mortar specimens using electrical capacitance tomography (ECT) imaging, which is based on non-intrusive and contact-free capacitance surface measurements. In a series of experiments, three mortar specimens with differing moisture transport properties were imaged with ECT during a 3D ingress of water. For comparison, we also modeled the flow of moisture numerically, by Finite Element Method (FEM) approximation of the 3D equation of unsaturated moisture flow in porous media, commonly referred to as Richard's equation. The ECT reconstructions are in good agreement with the flow model for all specimens which supports the ability of ECT to image 3D water transport in cement-based materials.

Split Bregman iteration based image reconstruction algorithm for electrical capacitance tomography

Practical applications of the electrical capacitance tomography (ECT) rely mainly on the effectiveness of reconstruction algorithms. In this paper the solution of the inverse problem with the focus on the ECT imaging is reformulated to be an optimization problem by introducing a new loss function with regularizes encoding multiple features of solution. An iterative scheme that decomposes a complex optimization problem into several simpler sub-problems is developed to solve the proposed loss function, in which the linearization approximation and the acceleration strategy are introduced to improve numerical performances. Numerical experiments validate the effectiveness of the proposed imaging method in tackling the ECT inverse problem.

Iterative reconstruction algorithm for the inverse problems in electrical capacitance tomography

The electrical capacitance tomography (ECT) technology is a promising tomography technology that can image the distribution information of permittivity in a measurement region. The imaging algorithms play crucial roles in practical ECT image reconstruction problems. Different from previous numerical methods, this study proposes a novel cost function to model the ECT inverse problem, in which the L1-norm is used as the data fidelity to weaken the influence of the outliers contained in the capacitance data, the L1 regularization is introduced to enhance the sparseness of reconstructed objects, and the second order total variation (STV) regularization is used to weaken the staircasing effects caused by the first order total variation (FTV) regularization. The split Bregman iteration (SBI) algorithm that splits a complicated ECT imaging problem into several simpler sub-problems is developed to solve the proposed cost function effectively. The numerical simulation results show that the imaging algorithm proposed in this paper can reconstruct satisfactory results.

Memetic reconstruction algorithm for the ECT

The practical performance of the electrical capacitance tomography (ECT) instrument largely relies on the accuracy and robustness of the image reconstruction algorithm. Varying from the common imaging methods, in this study, a regularisation-based loss function is proposed to transform the ECT imaging task into an optimisation problem, in which the least trimmed squares method is employed to measure the data fidelity, and the l p -norm of the variables is used as the regulariser. An efficient memetic algorithm (MA) that constitutes of the monkey king evolution algorithm and the Fletcher-Reeves conjugate gradient method is developed for solving the proposed loss function. The numerical simulations reveal that the feasibility and robustness of the proposed MA lead to a series of satisfactory results in the ECT field.

Computationally efficient image reconstruction algorithm for electrical capacitance tomography

The electrical capacitance tomography (ECT) is a visualization measurement method and can reconstruct the spatial permittivity distribution information in a measurement domain based on given capacitance values, in which the effectiveness of the image reconstruction algorithm plays a vital role in real-world engineering applications. Unlike common imaging methods, within the framework of the Tikhonov regularization methodology and the transform-domain sparsity method, a new cost function encapsulating the wavelet-based sparsity constraint is proposed to model the ECT imaging problem. An iteration scheme that integrates the superiorities of the alternating direction method of multipliers algorithm and splits a complicated optimization problem into several simpler sub-problems is developed to seek for the optimal solution of the proposed cost function. Numerical experiments validate that the proposed imaging algorithm is practicable and effective, and can improve the reconstruction accuracy and robustness.

Combination regularization reconstruction method for electrical capacitance tomography

Two-dimensional or three-dimensional images from the electrical capacitance tomography (ECT) technology provide powerful evidences for revealing complicated mechanisms behind behaviors of tomographic objects. In order to satisfy the increasing demands of dynamic measurements in real-world industrial applications, in this paper a sequential dynamic imaging model is proposed to model the inverse problem with the focus on the ECT imaging, and a new cost function that encapsulates the temporal constraint, the reweighted L1 norm based spatial constraint and the reweighted nuclear norm based low rank constraint is constructed to convert the dynamic inversion problem into a minimization problem. A new algorithm that splits an intractable optimization problem into several simpler sub-problems is developed to solve the new cost function. Comprehensive evaluations of representative imaging targets and comparisons with state-of-the-art imaging algorithms demonstrate the superiorities of the imaging technique proposed in this study on improving the imaging quality and robustness.

Study of granular flow in silo based on electrical capacitance tomography and optical imaging

This paper presents a comparison between optical images and two different modalities of electrical capacitance tomography (ECT), namely an off-the-shelf ECT system and a model one combining an inductance (L) - capacitance (C) - resistance (R) meter with a multiplexer. This comparison was performed to analyse the degree of measurement accuracy and to estimate the spatial resolution of the ECT systems. In this case, the detection of the position of flow boundaries during silo discharging and its translation when discharging changes from concentric to eccentric were investigated. A versatile rectangular silo model was used to generate different types of funnel flow of rice material, which was designated as the most adapted granular material to create both optical and electrical permittivity contrasts between stagnant and flowing zones. When a high temporal resolution is not requested, the model ECT system reduces the measurement error of flow boundary detection between 3% and 9% when compared with optical measurements. Moreover, the system is able to capture boundary translation of about 5% of the silo bin width, which is below the assumed spatial resolution of standard commercial ECT systems.

Hydrodynamics of inclined packed beds under flow modulation ‐ CFD simulation and experimental validation

A three‐dimensional unsteady‐state Eulerian multi‐fluid CFD model was developed to simulate the hydrodynamic behavior of inclined gas‐liquid cocurrent downflow packed beds under ON‐OFF liquid, ON‐OFF gas, and gas/liquid alternating cyclic operations. Validation of the CFD simulation results was performed with experimental data provided by electrical capacitance tomography imaging. Incorporation in the Eulerian multifluid CFD model of capillary pressure and mechanical dispersion force was essential to accurately capture the transient spatial heterogeneities arising in tilted packed beds under different cyclic modulation strategies. The applied CFD model was able to satisfactorily predict the values of liquid holdup and pressure drop as well as the morphological characteristics of the traveling waves inside the bed for the examined flow modulations. © 2017 American Institute of Chemical Engineers AIChE J, 63: 4161–4176, 2017

A Pipelined Parallel Hardware Architecture for 2-D Real-Time Electrical Capacitance Tomography Imaging Using Interframe Correlation

This paper presents a new hardware algorithm for real-time and nonlinear 2-D electrical capacitance tomography (ECT) imaging, along with its parallel hardware architecture. A potential application of this system is to reconstruct in real time cross-sectional image of a two-phase fluid with different dielectric constants when it passes through a given section of a pipeline. The proposed hardware algorithm explores the spatial correlation that may occur between one or several consecutive frames. It uses this property to reformulate the classical regularized forward and inverse problems that are indeed very time consuming, preventing them to be used for fast ECT applications. As a result, the proposed algorithm features one-single-step iteration with a substantial reduction of the size of the Jacobian matrix. In addition, the intrinsically parallel feature of the algorithm makes it suitable for parallel hardware architecture. This architecture is based on a pipeline multiprocessor architecture using advanced features of field-programmable gate array technology. It explores the variable bit-width and floating-point multipliers array available in the digital signal processor blocks, to cooperatively perform the partial matrix product with associated arithmetic and logic units, and distributed memory. The experimental results obtained on a two-phase flow loop demonstrate the capability of the system to build in real time and with good accuracy (e.g., less than 3% error) the cross-sectional image of the fluid passing through the pipeline. Around 560 frames of 4096 moving boundary pixels can be reconstructed in 1 s using IEEE754 floating-point data representation and a clock frequency of 400 MHz, for a total power consumption of less than 33 W.

Investigation of drag models for the two fluid simulation of Geldart group A powders

Electrical capacitance tomography and magnetic resonance imaging were used to investigate two drag models used when simulating Geldart group A powders with the two fluid model. Experiments were performed using cylindrical fluidised beds 50mm in diameter with a silica-alumina catalyst support particle of diameter 63μm. A dense phase, bubbling fluidised bed and a dilute phase, circulating fluidised bed were studied. Simulations were performed using the open source software MFIX. The two drag models considered were the revised Gibilaro model and the Energy Minimisation Multiscale model. Both of these models have previously been shown to be effective at describing the fluidisation of Geldart group A powders. The comparison of the simulations with experimental measurements presented here demonstrates that the revised Gibilaro model can be used to predict the voidage and particle velocity distribution in the dense fluidised bed with a high degree of accuracy, however when used to simulate the circulating fluidised bed it underestimates the solids circulation rate by approximately a factor of 4. The Energy Minimisation Multiscale drag model is able to predict the circulating fluidised bed solids circulation rate to within about 50%, however it does not predict the correct voidage distribution in the dense fluidised bed. These results indicate that neither model is able to predict the fluidisation behaviour across the entire range of fluidisation conditions.

Analysis of mutations of MDR3 exons 9 and 23 in infants with parenteral nutrition-associated cholestasis.

The aim of this study was to investigate mutations of multidrug resistance 3 (MDR3) exons 9 and 23 in infants with parenteral nutrition-associated cholestasis (PNAC). A total of 41 infants with PNAC were enrolled in the study. Genomic DNA was extracted from the peripheral venous blood leukocytes of each patient and MDR3 exons 9 and 23 were amplified by polymerase chain reaction. One patient was identified who carried a frameshift mutation in MDR3 exon 23 (C.2793) that was caused by the insertion of a single adenine residue, while mutations were not found in MDR3 exon 23 in the other 40 patients. The clinical features of the patient with the MDR3 exon 23 frameshift mutation included high serum γ-glutamyl transferase levels, the absence of biliary dilatation and deformity in magnetic resonance cholangiopancreatography, and abnormal electrical capacitance tomography imaging of the liver. No mutations in MDR3 exon 9 were identified in any of the patients. All 41 PNAC patients recovered following oral ursodeoxycholic acid treatment. The C.2793 frameshift mutation in MDR3 exon 23 is potentially associated with the development of PNAC in infants.

Imaging floating metals and dielectric objects using electrical capacitance tomography

Electrical capacitance tomography (ECT) is a well-established industrial process tomography technique. The application of ECT is generally limited to imaging insulating objects with permittivity contrast. Although ECT imaging for grounded conductors are studied earlier, there is not a systematic study of imaging floating metals using ECT. To broaden the application of the ECT, imaging of suspended metallic samples is studied in this paper. Placing a metallic conductor between electrodes has an effect of shortening the spacing between the electrodes, thus the capacitances are increased. This increment in capacitances can be regarded as placing a dielectric sample with higher permittivity than the reference data. An ECT image of the floating metallic samples can be reconstructed using traditional sensitivity based image reconstruction, which is in the same way as imaging dielectric permittivity. In this paper, both metallic and dielectric samples are tested, and the results show the feasibility of ECT imaging for floating metals.

Dynamic reconstruction algorithm for electrical capacitance tomography based on the proper orthogonal decomposition

Due to the vivid visualizations obtained of the spatial material distributions of inaccessible objects, electrical capacitance tomography (ECT) is considered to be a promising method for the monitoring and control of various industrial processes in which image reconstruction algorithms play important roles in practical applications. In this study, the proper orthogonal decomposition (POD) method is used to derive a low-dimensional model for ECT imaging problems. We propose a POD-based dimensionality reduction dynamic imaging model, which incorporates the time-varying properties of dynamic imaging objects and prior knowledge obtained from previous measurements, other sensors, or numerical simulation results to simultaneously improve the accuracy and speed of image reconstruction. In the framework of this POD-based low-dimensional imaging model, we propose a new objective functional that integrates additional prior information related to imaging objects to convert the ECT image reconstruction task into an optimization problem. The split Bregman iteration (SBI) method is employed to search for the optimal solution to the proposed objective functional. Unlike standard pixel-based imaging methods, the proposed low-dimensional imaging model is obtained by projecting the original unknown variables onto subspaces spanned by a set of orthogonal basis vectors, where the unknown images are reconstructed indirectly by estimating a low-dimensional coefficient vector. Our theoretical study and numerical simulation results validate the superior performance of the proposed imaging method in alleviating the ill-posedness of the ECT image reconstruction problem, as well as increasing the imaging quality, decreasing the computational cost, improving the reconstruction speed, and enhancing robustness.

Magnetic induction tomography guided electrical capacitance tomography imaging with grounded conductors

Electrical capacitance tomography (ECT) is an imaging technique commonly used for imaging dielectric permittivity of insulating objects. In applications such industrial process tomography and non-destructive testing (NDT), the objects under test may exhibit variations in both dielectric permittivity and electrical conductivity. In particular, a sample that includes high conductivity, such as metal, can cause a large change in electrical field in ECT. The metal sample in imaging area will cause a large change in the sensitivity map of ECT compared to free space, which will make the ECT image reconstruction inaccurate. This effect is more severe in grounded conductor than floating conductors, so this paper focuses on grounded conductor. In order to update the sensitivity map, one needs to gain information about the conductivity distribution in ECT problem. Magnetic induction tomography (MIT) is sensitive to electrical conductivity and not sensitive to permittivity variations; therefore, it can be used to visualize the conductivity distribution of the target under test. In this paper, a dual-modality MIT and ECT system is proposed to image a medium including conductors and dielectrics. Both simulated and experimental results are presented, which demonstrate the feasibility of the proposed method.