Voidage measurement based on genetic algorithm and electrical capacitance tomography

A new voidage measurement method based on electrical capacitance tomography (ECT) technique, Genetic Algo- rithm (GA) and Partial Least Square (PLS) method was proposed. The voidage measurement model, linear capacitance combi- nation, was developed to measure on-line voidage. GA and PLS method were used to determine the coefficients of the voidage measurement model. GA was used to explore the optimal capacitance combination which gave significant contribution to the voidage measurement. PLS method was applied to determine the weight coefficient of the contribution of each capacitance to the voidage measurement. Flow pattern identification result was introduced to improve the voidage measurement accuracy. Experi- mental results showed that the proposed voidage measurement method is effective and that the measurement accuracy is satis- factory.

Void Fraction Measurement in Oil-Gas Transportation Pipeline Using an Improved Electrical Capacitance Tomography System

To measure the void fraction online in oil-gas pipeline, an improved electrical capacitance tomography (ECT) system has been designed. The capacitance sensor with new structure has twelve internal electrodes and overcomes the influence of the pipe wall. The data collection system is improved by using high performance IC (integrated circuit). Static tests of bubble flow, stratified flow and annular flow regime are carried out. Measurements are taken on bubble flow, stratified flow and slug flow. Results show that the new ECT system performs well on void fraction measurement of bubble flow and stratified flow, but the error of measurement for slug flow is more than 10%.

Application of Electrical Capacitance Tomography to the Concentration Measurement in a Cyclone Dipleg

Accurate solid concentration measurement plays a key role in the process industry. Measurements analyzed offline can be used to estimate process efficiencies, to identify problems in a flow, and to validate computational models. Online measurements can be used for active control. Electrical capacitance tomography （ECT） is a unique measuring technique with great potential in multiphase flow measurement. Experimental studies are carried out on a solid concentration measurement in a cyclone separator dipleg, using ECT. In this experiment eight electrodes are selected for the ECT sensor that is placed on the straight tube of the dipleg. The fluctuating characteristics according to the screw feeder and the effect of the airflow rate from the top of the cyclone are analyzed. The feasibility andreliability of the method are verified by the experimental results.

Flame Imaging in Meso-scale Porous Media Burner Using Electrical Capacitance Tomography

This study was conducted to investigate the characteristics of meso-scale combustion.The technique of electrical capacitance tomography(ECT) was used to locate flame position and monitor the effect corresponding to varied air/fuel ratio in a meso-scale combustor.Combustion phenomena including igniting,quenching and unsteady combustion have been visualized using ECT.The method of metallization protecting ECT sensor from high temperature damage and the novel calibration method adapted to ECT monitoring of unknown permittivity flame have been shown to be successful.At the same time,electrical nature of combustion and dielectric characteristics of hy-drocarbon flame were studied.The relationship between flame permittivity and state parameters of combustion gas was demonstrated preliminarily.

Reconstruction of electrical capacitance tomography images based on fast linearized alternating direction method of multipliers for two-phase flow system

Electrical capacitance tomography(ECT)has been applied to two-phase flow measurement in recent years.Image reconstruction algorithms play an important role in the successful applications of ECT.To solve the ill-posed and nonlinear inverse problem of ECT image reconstruction,a new ECT image reconstruction method based on fast linearized alternating direction method of multipliers(FLADMM)is proposed in this paper.On the basis of theoretical analysis of compressed sensing(CS),the data acquisition of ECT is regarded as a linear measurement process of permittivity distribution signal of pipe section.A new measurement matrix is designed and L1 regularization method is used to convert ECT inverse problem to a convex relaxation problem which contains prior knowledge.A new fast alternating direction method of multipliers which contained linearized idea is employed to minimize the objective function.Simulation data and experimental results indicate that compared with other methods,the quality and speed of reconstructed images are markedly improved.Also,the dynamic experimental results indicate that the proposed algorithm can ful fill the real-time requirement of ECT systems in the application.

Dynamic Visualization Approach of the Multiphase Flow Using Electrical Capacitance Tomography

Identifying the flow patterns is vital for understanding the complicated physical mechanisms in multiphase flows.For this purpose,electrical capacitance tomography(ECT) technique is considered as a promising visualization method for the flow pattern identification,in which image reconstruction algorithms play an important role.In this paper,a generalized dynamic reconstruction model,which integrates ECT measurement information and physical evolution information of the objects of interest,was presented.A generalized objective functional that simultaneously considers the spatial constraints,temporal constraints and dynamic evolution information of the objects of interest was proposed.Numerical simulations and experiments were implemented to evaluate the feasibility and efficiency of the proposed algorithm.For the cases considered in this paper,the proposed algorithm can well reconstruct the flow patterns,and the quality of the reconstructed images is improved,which indicates that the proposed algorithm is competent to reconstruct the flow patterns in the visualization of multiphase flows.

Damage Detection for CFRP Based on Planar Electrical Capacitance Tomography

Due to the widespread use of carbon fiber reinforced polymer/plastic(CFRP),the nondestructive structural health monitoring for CFRP is playing an increasingly essential role.As a nonrad iative,noninvasive and nondestructive detection technique,planar electrical capacitance tomography(PECT)electrodes array is employed in this paper to reconstruct the damage image according to the calculated dielectric constant changes.The shape and duty ratio of PECT electro-des are optimized according to the relations between sensitivity distribution and the dielectric constant of different anisotropic degrees.The sensitivity matrix of optimized PECT sensor is more uniform as the result shows,because the sensitiv-ity of insensitivity area can be increased by adding rotation of optimized electro-des.The reconstructed image qualities due to different PECT arrays and different damage locations are investigated at last.The simulation results indicate that:PECT can be used to detect the surface damage of CFRP;the sensitivity matrix of PECT for CFRP is highly relevant with the degree of anisotropic dielectric con-stant;the rotatable PECT sensor with rotation has better performance in unifor-mity of sensitivity;for different damage locations,the rotatable sensor with rotation has better image quality in most cases.

An Advanced Algorithm of Electrical Capacitance Tomography

We describe a new two phase flow electrical capacitance tomography algorithm of image reconstruction which is based on 12 electrode capacitance transducers. According to the result of computer simulation, this algorithm is able to greatly increase the imaging fidelity without decreasing the imaging velocity.

A Multiresolution Reconstructive Algorithm Based on Network Theory for Electrical Capacitance Tomography

Electrical capacitance tomography technique reconstructs dielectric constant distribution in an object by measuring the capacitances between the eletrode pairs which are mounted around this object. Because of the limitation of measurement condition, the measured data are imcomplet. This paper describes a multiresolution reconstructive algorithm which is based on network theory for electrical capacitance tomography technique. The dielectric constant distribution of flow of two components in a pipeline is reconstructed. The algorithm is as follows: Firstly, construct a rough, first level system model, and assume the dielectric constant distribution of the region to be reconstructed. After iteration, the dielectic constant of each unit can be reconstructed. Secondly, construct a finer, second level the system model and determine the initial dielectric constant of each unit in the region to be reconstructed according to related information between two levels. After iteration, the image of the pipeline's cross section can be reconstructed. The results of simulated experiments about different kinds of medium distributions show that this algorithm is effective and can converge.

Visualization detection of slurry transportation pipeline based on electrical capacitance tomography in mining filling

In the long distance transportation of slurry filled for mining filling,there exist complex variation rules of pressure and flow velocity,pipe distribution location and other influencing factors.Electrical capacitance tomography(ECT)is a technique for visualizing two-phase flow in a pipe or closed container.In this paper,a visual detection method was proposed by image reconstruction of core,laminar,bubble and annular flow based on ECT technology,which reflects distribution of slurry in deep filling pipeline and measures the degree of blockage.There is an error between the measured and the real two-phase flow distribution due to two factors,which are immature image reconstruction algorithm of ECT and difference of flow patterns leading to degrees of error.In this paper,convolutional neural networks(CNN)is used to recognize flow patterns,and then the optimal image is calculated by the improved particle swarm optimization(PSO)algorithm with weights using simulated annealing strategy,and the fitness function is improved based on the results of the shallow neural network.Finally,the reconstructed binary image is further processed to obtain the position,size and direction of the blocked pipe.The realization of this method provides technical support for pipeline detection technology.

Electrical capacitance volume tomography for measurement soil water infiltration in vessel experiments

Electrical capacitance volume tomography(ECVT) is a recently-developed technique for real-time,non-invasive 3D monitoring of processes involving materials with strong contrasts in dielectric permittivity.This work is first application of the method to visualization of water flow in soil.We describe the principles behind the method,and then demonstrate its use with a simple laboratory infiltration experiment.32 ECVT sensors were installed on the sides of an empty PVC column.Water was poured into the column at a constant rate,and ECVT data were collected every second.The column was then packed with dry sand and again supplied with water at a constant rate with data collected every second.Data were analyzed to give bulk average water contents,which proved consistent with the water supply rates.Data were also analyzed to give 3D images(216 voxels) allowing visualization of the water distribution during the experiments.Result of this work shows that water infiltration into the soil,wall flow,progress of the unstable wetting front and the final water distribution are clearly visible.

Visualization Detection of Solid-Liquid Two-Phase Flow in Filling Pipeline by Electrical Capacitance Tomography Technology

During mine filling,the caking in the pipeline and the waste rock in the filling slurry may cause serious safety accidents such as pipe blocking or explosion.Therefore,the visualization of the innermine filling of the solid-liquid two-phase flow in the pipeline is important.This paper proposes a method based on capacitance tomography for the visualization of the solid-liquid distribution on the section of a filling pipe.A feedback network is used for electrical capacitance tomography reconstruction.This reconstruction method uses radial basis function neural network fitting to determine the relationship between the capacitance vector and medium distribution error.In the reconstruction process,the error in the linear back projection is removed;thus,the reconstruction problem becomes an accurate linear problem.The simulation results showthat the reconstruction accuracy of this algorithm is better than that of many traditional algorithms;furthermore,the reconstructed image artifacts are fewer,and the phase distribution boundary is clearer.This method can help determine the location and size of the caking and waste rock in the cross section of the pipeline more accurately and has great application prospects in the visualization of filling pipelines in mines.

Modeling and Implementation of AC Electrical Capacitance Tomography

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.

Sensor monitoring and online measurement correction in electric capacitance tomography system

The recalibration of electrical capacitance tomography (ECT) system is one of the key problems in keeping the system running steadily.However, for engineering application in solids/gas transport,online calibration can not be implemented and the data from this sensor may be unreliable due to the sensor pipe interior wall abrasion during pneumatic transport,so the solids concentration calculated from the reconstructed image based on these data will be highly inaccurate.The simulations show that, the inter-electrode relative capacitance variation of electrode pair spacing 1 is the most sensitive to the abrasion of sensor pipe interior wall, so this relative capacitance variation when the sensor is filled with air can be used as an indicator demanding offline system recalibration when the wall abrasion goes significant.Furthermore, while the pipe interior wall abrasion is not very serious, online correcting measured inter-electrode capacitance with wall capacitance variation can improve the accuracy of concentration calculation.

基于有限元仿真的ECT感兴趣区域高分辨率图像重建

感兴趣区域的高分辨率图像重建是电容层析成像(electrical capacitance tomography,ECT)技术的研究热点之一。均匀电极分布的ECT模型仅在重建场域的边界位置具有较高的灵敏度系数,不适用于感兴趣区域成像。为改善感兴趣区域中的灵敏度分布,提高图像分辨率,提出了一种基于有限元仿真ECT感兴趣区域高分辨率图像重建方法,根据保角变换理论优化电极分布。进行了仿真实验,将均匀电极和优化电极分布的灵敏度矩阵代入Tikhonov算法、Landweber算法和ART算法,重建结果表明上述方法可有效提高感兴趣区域的图像重建精度。

基于FCM及快速迭代收缩阈值算法的平面ECT图像重建

为提高平面阵列电容成像系统的成像精度,提出一种基于模糊C均值聚类(FCM)进行数据优化的快速迭代收缩阈值算法(FISTA)。根据平面阵列电容数据的特点,首先利用FCM算法对测量电容值进行分类,保留有效电容值,实现电容向量降维;然后利用离散小波基(DWT)对灰度值进行稀疏表示,并建立L1正则化模型,采用FISTA进行求解,以实现图像重建;最后将FCM处理后的电容值分别用于Landweber算法、Tikhonov算法进行重建对比。仿真与实验结果表明,该算法重建图像的平均相对误差约为0.0527,平均相关系数约为0.9422,均优于其它算法,且重建图像伪影较少,更接近真实情况;因此,所提算法具有更好的重建效果。。

基于多尺度自适应网络的ECT图像重建

为求解电容层析成像(ECT)中的非线性病态反问题,提出了一种多尺度自适应网络(MSANet)模型,该模型实现了更精细维度上多尺度特征的融合,且模型参数量相对较小。通过在单个残差块内构建树状结构组成多尺度特征融合模块,MSANet实现了更好的鲁棒性和更低的计算参数量;采用加入自适应空间阈值模块方式,进一步提高了图像的重建精度。实验结果表明:与线性反投影(LBP)算法、Landweber迭代算法及常用深度学习方法相比,该方法平均相对误差最小且平均相关系数最大,分别为0.181及0.967。

基于两步正则化Gauss-Newton迭代算法的ECT图像重建

电容层析成像(ECT)技术求解图像重建问题属于非线性问题,并且存在严重的不适定性。为提高图像重建精度,提出了一种基于两步正则化Gauss-Newton迭代算法的ECT图像重建方法。针对标准正则化Gauss-Newton迭代算法在图像重建中存在的不收敛问题,引入了两步迭代方法;改进了正则化矩阵,提高了解估计的精确度;考虑到Gauss-Newton算法对迭代初值的依赖性,加入了同伦算法。最后,进行仿真和静态实验,并与线性反投影(LBP)算法、Landweber算法、Tikhonov正则化算法进行对比。结果表明,该方法可有效提高图像重建精度。

基于二阶混联灵敏度矩阵的ECT图像重建

电容层析成像技术求解图像重建问题属于非线性问题。在灵敏度矩阵的推导过程中,通常只保留灵敏度系数的线性部分,但是被忽略的非线性部分同样包含重要的成像信息。为了提高图像重建精度,基于二阶灵敏度系数的数学定义,结合模糊C-均值聚类算法和电场中心线理论,建立了二阶混联灵敏度矩阵,并将矩阵引入到Landweber算法中,提出了二阶Landweber算法;最后,进行仿真和静态实验,并与传统的Tikhonov算法和一阶Landweber算法进行对比,结果表明,二阶混联灵敏度矩阵可以提高图像重建精度。

基于ECT模型修正及算法优化的超音速分离流场图像重建

超音速分离器内流场参数的准确测量对其结构与性能优化至关重要,电容层析成像(electrical capacitance tomography,ECT)能够实现非侵入式参数测量,其逆问题求解的数学模型主要通过线性化近似得到,忽略了非线性、“软场”效应等对结果的影响,使得当场域内介质分布的介电常数差异较大时,图像重建质量不高。针对上述问题,本文通过引入模型推导误差对ECT逆问题数学模型修正,在此基础上,根据目标函数的可分离特性,设计结合正则化与Split Bregman(RASB)的求解算法,分别对模型误差和待重构介质进行交叉迭代求解。最后通过仿真和实验手段对比分析了RASB算法、Tikhonov正则化算法、L1正则化算法和Landweber算法重建图像效果,结果表明所提算法RASB可以减小线性化近似产生的误差,削弱噪声对图像重建结果的影响,重构的介质分布更加准确,图像中伪影更少。RASB算法对几种模型重建图像的平均相关系数为0.8964,高于Tikhonov正则化算法的0.8353、L1正则化算法的0.8496和Landweber算法的0.8681。