油水两相流浓度电容层析成像的测量方法

以8电极油水两相流电容层析成像系统为研究对象,分析了油水两相流电容层析成像系统的测量原理,依据二重积分微元原理建立了油水两相流相浓度分布信息的数学模型,采用ART图像重建的方法完成油水两相流的浓度测量,并在重建算法中引入了阈值以提高图像重建质量和含率计算的准确性,测量误差在1%左右,较好地解决了其他测量方法速度慢,成本高,安全性差等缺陷,为油水两相流浓度的测量提供了一种新方法.     

基于鲁棒正则化极限学习机的电容层析成像图像重建

电容层析成像图像重建是一个非线性及病态性逆问题。基于此,提出了基于迭代重加权最小二乘法的鲁棒正则化极限学习机(RELM-IRLS)算法的电容层析成像图像重建方法,以油/气两相流为研究对象,通过有限元仿真构建随机分布流型,对RELM-IRLS算法完成训练,并与Landweber迭代算法及极限学习机算法进行对比,RELM-IRLS算法的测试集平均误差相比极限学习机算法减小4.6%。仿真及静态实验结果均表明, RELM-IRLS算法所得重建图像质量得到明显提升,且算法具有良好的泛化性能。     

电容成像技术及其应用

过程成像技术是近十多年来发展起来的一种新型过程检测技术，可以广泛应用于石油、化工、电力及冶金等行业中的两相流测量。本文结合清华大学自动化系过程成像小组研制的电容成像系统，介绍了电容成像技术的发展和现状，包括电容成像基本原理、微电容测量电路和图像重建算法等。论文给出了现有系统在小型流化床模拟装置上进行测量和连续图像重建的实验结果，并进行了分析。此外，论义对电容成像技术今后的发展作出了展望。     

一种电容层析成像图像重建优化算法

提出一种电学层析成像(ECT)图像重建优化算法。通过将传统正则化算法转化为最小二乘问题进行求解,结合lp范数逼近正则化最小化问题,利用重新加权的方法进行迭代计算。以油-气两相流模型进行仿真及静态实验,将所提出的优化算法与常用的LBP、Landweber迭代及Tikhonov正则化算法进行对比。结果表明,与常用算法相比,采用该优化算法对管道中心物体及多物体分布流型进行图像重建,其图像相对误差均为最低,且重建图像的形状保真度明显提高。     

Online Voidage Measurement of Two-Phase Flow Based on the Ant System Algorithm

Based on the 12-electrode electrical capacitance tomography (ECT) system and the ant system algorithm (ASA), a new method was proposed for online voidage measurement of oil-gas two-phase flow. In practical voidage measurement, based on the 66 measurement capacitances obtained from the ECT system, the real-time flow pattern of oil-gas two-phase flow was first identified. Then, according to the flow pattern identification result, an appropriate measurement model was selected, and the measurement voidage value was calculated. The measurement models related to the flow pattern were developed in advance using the ASA. Static and dynamic experimental results show that the proposed voidage measurement method is effective. Moreover, the real-time performance and measurement accuracy are satisfactory.     

两相流电容层析成像系统

本文较系统地介绍了电容层析成像系统结构原理,包括抗杂散电容影响的微小检测技术,并行数据采集与处理单元设计以及基于总变差正则化的图像重建算法.与此同时,结合研制的双截面电容成像系统进行试验研究,结果表明该系统不仅可给出实时流型识别,同时能输出表征的特征参数.     

Two Methods for Measurement of Gas-Liquid Flows in Vertical Upward Pipe Using Dual-Plane ERT System

In modern industrial processes, the accurate measurement of two-phase flow is an important task. Process tomography can provide a distribution information of a two-phase pipe flow. In order to carry out instantaneous flowrate measurements of the gas-liquid two-phase flow in a vertical upward pipe, a dual-plane electrical-resistance-tomography (ERT) system is combined with a cross-correlation technique to measure the gas-liquid two-phase flow, in which the continuous phase is a conductive liquid. A pixel correlation method and a feature-value-correlation method are applied to estimate the disperse-phase velocity. Two methods are used to estimate the local void fraction and the disperse velocity distribution by reconstructing the image pixel gray value distribution. Estimates of the mean void fraction and the disperse-phase mean velocity are obtained by extracting the feature value of the measured data at the dual-plane ERT boundary. The variation in the disperse-phase distribution with changes in time is considered, and the estimated values for both the disperse-phase void fraction and velocity have been experimentally obtained, which are used in the calculation of the instantaneous flowrate. The air-water two-phase flow experiments are designed to evaluate the validity of the two methods used in estimation. The experimental results agree with the theoretical methods for obtaining the disperse-phase velocity and instantaneous-flowrate measurement in the vertical upward pipe.     

两相流电容层析成像系统

本文较系统地介绍了电容层析成像系统结构原理,包括抗杂散电容影响的微小检测技术,并行数据采集与处理单元设计以及基于总变差正则化的图像重建算法.与此同时,结合研制的双截面电容成像系统进行试验研究,结果表明该系统不仅可给出实时流型识别,同时能输出表征的特征参数.     

基于梯度投影稀疏重建算法的电容层析成像图像重建

为解决两相流中存在中心物体、物体比较小或存在多个物体且相距较近时电容层析成像(ECT)重建图像精度较差的问题,基于稀疏分布的流型其介电常数分布满足稀疏性的先验条件,采用梯度投影稀疏重建(GPSR-BB)算法进行ECT图像重建。仿真及实验测试结果表明:GPSR-BB算法对于流体中小目标以及复杂流型的图像重建质量较好,重建图像的形状保真度高。     

基于电容层析成像系统测量信号稀疏性的两相流流型辨识

提出了基于电容层析成像(ECT)测量电容信号稀疏性的两相流流型辨识算法,该算法首先使用所有流型对应的归一化测量电容值信号构建一个过完备字典,并将待辨识样本通过该过完备字典进行稀疏表示,使其具有稀疏性并满足稀疏重构的基本要求,然后以压缩感知的正交匹配追踪(OMP)算法求取各标准样本对应于完备样本集的稀疏解,最后根据待辨识样本与标准样本稀疏解之间的线性相关程度进行流型辨识。使用该方法对5种典型的两相流流型识别进行了仿真及实验研究,结果表明:该方法的流型正确识别率均高于98%。     

Simulations for parallel processing of ultrasound reflection-mode tomography with applications to two-phase flow measurement

An evaluation of the application of a parallel-processing array to the measurement of two-phase flow, such as bubbly oil flow through a pipe, in real-time is described. Pulse-echo ultrasound tomography is used to generate a cross-sectional image of the flow that forms the basis for the deduction of flow parameters, such as the void fraction. The tomographic algorithm used is backprojection adapted for execution on an array of parallel-processing devices. It is shown that real-time reconstruction is feasible using the concepts of parallel processing. Different sensor arrangements were investigated by computer simulation. It is shown that a special multisegment sensor results in a significant improvement in signal-to-noise ratio and image quality and that the reconstructed image benefits from the concurrent activation of multiple receivers per transmitted pulse. The findings may also be useful for nondestructive testing and medical applications.     

Electrical Capacitance Volume Tomography

A dynamic volume imaging based on the principle of electrical capacitance tomography (ECT), namely, electrical capacitance volume tomography (ECVT), has been developed in this study. The technique generates, from the measured capacitance, a whole volumetric image of the region enclosed by the geometrically three-dimensional capacitance sensor. This development enables a real-time, 3-D imaging of a moving object or a real-time volume imaging (4-D) to be realized. Moreover, it allows total interrogation of the whole volume within the domain (vessel or conduit) of an arbitrary shape or geometry. The development of the ECVT imaging technique primarily encloses the 3-D capacitance sensor design and the volume image reconstruction technique. The electrical field variation in three-dimensional space forms a basis for volume imaging through different shapes and configurations of ECT sensor electrodes. The image reconstruction scheme is established by implementing the neural-network multicriterion optimization image reconstruction (NN-MOIRT), developed earlier by the authors for the 2-D ECT. The image reconstruction technique is modified by introducing into the algorithm a 3-D sensitivity matrix to replace the 2-D sensitivity matrix in conventional 2-D ECT, and providing additional network constraints including 3-to-2-D image matching function. The additional constraints further enhance the accuracy of the image reconstruction algorithm. The technique has been successfully verified over actual objects in the experimental conditions     

基于改进SR3模型算法的ECT图像重建研究

针对电容层析成像技术应用于气固两相流检测时,图像重建过程中存在的不适定性问题,提出一种稀疏松弛正则化回归模型(SR3)应用于ECT图像重建。采用软阈值迭代法和梯度下降法为SR3模型求解器,向SR3模型中加入L1、L2惩戒项,并设计滤值环节优化解向量。实验结果表明,改进SR3模型算法相比Tikhonov正则化算法、L1正则化算法及原SR3模型算法,重建图像精度明显提高,图像相对误差显著降低,有较好的成像效果。     

Dual imaging modality of granular flow based on ECT sensors

In this study, a previously developed dual modality imaging system is applied to image the flow of granular matter with different electrical properties in cylindrical vessels. The imaging system is based on both capacitance and power measurements acquired by an electrical capacitance tomography (ECT) sensor located around the vessel. The measurement data are then used to reconstruct cross-sectional images of both permittivity and conductivity distributions. A neural network multi-criterion optimization reconstruction technique (NN-MOIRT) is used for the inverse (reconstruction) problem. The contribution of this technology to the field of granular matters is explored through review of research articles that can be a direct application of this development. We discuss the capabilities of this dual-modality acquisition system using synthetic data for granular matter with different electrical properties.     

气液两相低温流体空泡率测量技术及其进展

对目前几种用于测量低温气液两相流空泡率方法的基本原理、传感器结构及国内外研究情况进行了综述,包括辐射法(射线吸收法)、微波法、射频法、电容法,分析了4种方法的优缺点,在比较4种方法的基础上,提出了目前采用电容传感器测量气液两相低温液体空泡率的优势及设计准则.     

基于SVM的ECT图像重建算法

电容层析成像（ECT）技术是基于电容敏感机理的过程层析成像技术。ECT的图像重建是一个典型的有限样本非线性映射问题。支持向量机（SVM）作为一种小样本处理方法,具有较强的泛化能力,被认为是目前针对小样本分类问题的最佳理论。提出了一种基于SVM的四层神经网络的图像重建算法,仿真结果表明,该算法用于三相流图像重建具有较强的空间分辨率和泛化能力。     

Preliminary evaluation of cryogenic two-phase flow imaging using electrical capacitance tomography

The potential application of the 2-D eight-electrode electrical capacitance tomography (ECT) to the inversion imaging of the liquid nitrogen-vaporous nitrogen (LN₂-VN₂) flow in the tube is theoretically evaluated. The phase distribution of the computational domain is obtained using the simultaneous iterative reconstruction technique with variable iterative step size. The detailed mathematical derivations for the calculations are presented. The calculated phase distribution for the two detached LN₂ column case shows the comparable results with the water-air case, regardless of the much reduced dielectric permittivity of LN₂ compared with water. The inversion images of total eight different LN₂-VN₂ flow patterns are presented and quantitatively evaluated by calculating the relative void fraction error and the correlation coefficient. The results demonstrate that the developed reconstruction technique for ECT has the capacity to reconstruct the phase distribution of the complex LN₂-VN₂ flow, while the accuracy of the inversion images is significantly influenced by the size of the discrete phase. The influence of the measurement noise on the image quality is also considered in the calculations.     

改进的共轭梯度算法的图像重建算法

针对电容层析成像图像重建问题的病态性,在Tikhonov正则化的基础上,以正则化解决方案的规模和给定数据的质量为理论依据,引入一个数学变换,提出了一种新的正则化方法,该方法克服了常规正则化方法扰乱原系统的缺陷。同时,将ECT物理模型进行规范化,并对共轭梯度算法进行改进。仿真实验表明,改进的共轭梯度算法的成像质量高于LBP算法、 Tikhonov正则化算法和共轭梯度算法,并利用相关系数进行了验证。     

数字化电容层析成像系统

基于电容敏感原理设计的数字化电容层析成像（ECT）系统,利用有限元法,分析了阵列电极结构对敏感场分布的影响,通过优化设计和仿真试验,改善了敏感场分布的均匀性;构建了以数字信号处理器（DSP）为核心、现场可编程门阵列（眦）协同工作的12电极的数字化ECT系统,提出了由离线预迭代和在线一步成像所构成的新的图像重建算法——预迭代法,其成像速度及精度均明显得到提高。     

基于深度信念网络的ECT图像重建算法

为提高图像重建质量,针对电容层析成像技术(ECT)中的电容数据复杂多样且与介电常数呈非线性关系的特点,提出一种基于深度信念网络(DBN)的重建算法,利用DBN的深层非线性网络结构来实现电容值与重建图像灰度值非线性关系.并对DBN进行了改进,将自适应步长(AS)引入到对比散度(CD)算法中,解决固定步长寻找全局最优困难的...