基于极限学习机求解正问题的 ECT 图像重建

在电容层析成像(ECT)图像重建迭代类算法中,通常采用线性正问题求解,以加快重建速度,由此产生重建误差。针对这一问题,提出了基于极限学习机(ELM)的非线性ECT正问题求解方法,ELM网络输入为介电常数分布,其输出为预测的电容测量值。将该方法与传统的Landweber迭代算法相结合构成ELM-Landweber迭代算法进行图像重建。为使样本具有较好的代表性,物体分布位置及大小均随机生成,并计算相应的归一化电容值作为ELM网络训练及测试样本,对ELM-Landweber迭代算法进行了仿真与静态实验,并与传统Landweber迭代算法进行比较。实验结果表明,相较于传统Landweber迭代算法,采用ELM-Landweber迭代算法,其算法收敛速度显著提高,重建图像质量得到明显改善。训练样本的平均图像相对误差由0.728减小至0.504,测试样本的平均图像相对误差由0.596减小至0.475。     

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.     

Regularization parameter optimization based on the constraint of Landweber algorithm for electrical capacitance tomography

Image reconstruction algorithms play an important role in practical applications of electrical capacitance tomography. In the present paper, a combined image reconstruction method is proposed, which takes the results of Landweber algorithm as the constraint condition of Tikhonov algorithm's regularization parameter, calculates the regular parameter, inverts the inverse matrix of sensitivity matrix, and finally obtains the dielectric constant distribution; thus, reconstructed images with improved clarity were obtained. Simulation test are carried out to evaluate and analyze the proposed method from image error, correlation coefficient, image reconstruction time, and anti-noise ability. The results revealed that the Tikhonov regularization algorithm had excellent anti-noise ability; thus, it significantly improved the clarity of reconstructed images and clearly distinguished the multi-phase flow pattern and distribution.     

Tracing the motion of a large object in a fluidized bed using electrical capacitance tomography

An innovative method using electrical capacitance tomography (ECT) to trace a large object's motion on an air distributor in a fluidized bed is described here. The method fills the large object to be traced with a high permittivity material, and then a recalibration process is applied to reduce the nonlinearity caused by the large permittivity difference between the tracer particle and other fine particles in the measurement zone. The local dynamic threshold selection method is performed on the reconstructed image to locate the tracer particle's position.Static simulations and dynamic experiments testify that tracer particles with a diameter of one ninth of the measured cross-section and a fluidization velocity v/v_cr≤4.2 can be accurately located and traced. Employing this method to trace the motion of a spherical object in a bed shows that the fluidization velocity significantly influences the directional motion of a large, heavy object on an inclined air distributor.     

A novel method of plotting sensor sensitivity field and image reconstruction algorithm for electrical capacitance tomography system

Sensor sensitivity field in electrical capacitance tomography is affected by the distribution of multiphase medium, which is the peculiarity of soft field. This brings great difficulty for image reconstruction. To improve the quality of image reconstruction, it is important to analyze the distribution of the sensitivity field. In this article, using the finite element method, we expound a kind of novel plotting pattern to field, which is the distribution of sensitivity field through computer simulation. From experiments and results of sensitivity field analysis, a novel method of image reconstruction based on genetic algorithms is presented. The finite element model is correct and simulation result is fine by adopting unequal interval plotting patterns. At the same time, the result of image reconstruction has high precision. __________ Translated from Chinese Journal of Scientific Instrument, 2005, 26(3) (in Chinese)     

基于MCMC方法的电容成像图像重构算法

研究基于概率统计的电容成像图像重构算法,以马尔科夫随机场的方式给出介电常数分布的先验概率,利用电容成像(electrical capacitance tomography,ECT)线性模型得到似然函数,通过马尔科夫链蒙特卡罗(Markov chain Monte Carlo,MCMC)方法对介电常数分布的后验概率密度进行采样,马尔科夫链的转移核利用Metropolis-Hastings方法得到,结合嵌套迭代提高计算效率。仿真结果表明,嵌套迭代-MCMC方法在正则化参数设置合适的条件下,可以得到较好的图像质量,基于MCMC方法图像重构算法为解决ECT图像重构问题提供一种新思路。     

Robust dynamic inversion algorithm for the visualization in electrical capacitance tomography

Electrical capacitance tomography (ECT) is considered as a promising visualization measurement technique, in which reconstructing high-quality images is crucial for real applications. In this paper, a robust dynamic reconstruction model, which incorporates the ECT measurement information and the dynamic evolution information of a dynamic object, is presented. Under the considerations of the low rank property of an ECT image and the inaccuracies on the sensitivity matrix, the reconstruction model and the measurement data, an objective functional that fuses the ECT measurement information, the dynamic evolution information of a dynamic object, the spatial constraint, the temporal constraint and the low rank constraint is proposed. An iteration scheme that integrates the advantages of the fast composite splitting (FCS) algorithm is developed for solving the proposed objective functional. Numerical simulations are implemented to validate the feasibility of the proposed algorithm.     

电容层析成像系统传感器设计新方法

在电容层析成像系统中,为了提高重建图像的精度,常用的方法是提高成像传感器的极板数目,以获得较多的图像重建所需的独立电容测量值数目,但这种方法是以牺牲检测场的灵敏度为代价的。该文提出了一种在有限极板数条件下通过改变极板的组合方式成倍提高成像系统的独立电容测量值数目的方法。仿真结果表明该方法在不降低检测场灵敏度的前提下提高了电容测量值数目,从而提高了图像重建质量。     

A new hierarchical reconstruction algorithm for electrical capacitance tomography using a relaxation region-based approach

This paper presents a new two-dimensional tomography algorithm to reconstruct the internal image of a multiphase fluid passing through a section of a pipe. The embedded sensing module consists of an array of electrodes placed around the pipe to measure all possible combinations of capacitances between these electrodes. The algorithm is hierarchical and consists to confine progressively the regions of interest which hold the inhomogeneous phase by refining the finite element mesh size around their boundaries. Experimental results done on various images clearly indicate that the proposed algorithm improves the quality of the reconstructed images while keeping the computation time significantly lower than other traditional methods.     

矩形电容层析成像传感器仿真模拟和实验测量

常规电容层析成像传感器为规则对称方形或圆形结构,其测量和成像算法已相对成熟.由于受循环流化床旋风分离器入口结构段的限制,上述传感器结构已不能应用在旋风分离器入口段的测量,因此为了研究大型化循环流化床多旋风分离器并联布置入口段固体颗粒浓度分布,提出和设计了一种矩形非常规电容传感器,该传感器为12电极结构,在每个入口段的短边布置2个电极,长边布置4个电极,成像敏感场仿真计算基于Ansoft-Maxwell软件.对此传感器进行了静态仿真模拟研究和静态实验测量,对不同激励电压和频率测量结果进行分析,并对测量结果进行误差分析,得到矩形不规则电容传感器最佳测量参数(激励电压和频率),并对循环流化床分离器入口段进行了动态测量.结果表明,这种矩形非常规电容传感器可以用于循环流化床冷态试验台的旋风分离器入口段的直接测量,测量结果对改进旋风分离器的布置方式有参考意义.     

非闭合电极电容层析成像传感器在冻土测试中的应用

为了实现电容层析成像技术对冻土冻结冰峰面的在线、非侵入测试,研制出了满足冻土测试要求的非闭合电极电容层析成像传感器,并对该种传感器的电容分布特性进行了实测;确定出了适合冻土测试的的高、低介电常数的标定物质;搭建了冻土一维冻结实验系统.对含水量8%的湿土样冻结过程的冰峰面迁移进行了电容层析成像测试,并利用IMNSNOF图像重建算法重建出了冻结过程各时刻的冻结截面物质分布图像,由图像可确定出冻土中已冻土、未冻区以及冰峰面的位置.电容层析成像测试结果与温度测试结果相吻合.     

An image reconstruction algorithm based on total variation with adaptive mesh refinement for ECT

In this paper, a robust image reconstruction algorithm for electrical capacitance tomography (ECT) is proposed. The key feature of the algorithm is the use of adaptive mesh refinement based on total variation (TV) in solving the inverse problem. It keeps the edge preserving and scale-dependent properties of total variation regularization, and enhances the distinguishability by using adaptive mesh refinement. This strategy improves the spatial resolution efficiently with less calculation and is less underdetermined than uniform refinement. Simulation and experimental results show that the algorithm performs better than both standard Tikhonov regularization and the conventional total variation method.     

Dynamic imaging method using the low n-rank tensor for electrical capacitance tomography

Imaging objects in electrical capacitance tomography (ECT) measurement are often in a dynamic evolution process, and exploiting the spatial–temporal properties of the dynamic reconstruction objects is crucial for the improvement of the reconstruction quality. Based on the multiple measurement vectors, in this paper a robust dynamic reconstruction model that incorporates the ECT measurement information and the dynamic evolution information of a dynamic object, in which a series of dynamic images is cast as a third-order tensor that the first two dimensions are space and the third is time, is proposed. Under the considerations of the two-dimensional spatial structure property of a difference image and the spatial–temporal property of a third-order image tensor, a new objective functional that fuses the ECT measurement information, the dynamic evolution information, the temporal constraint, the spatial constraint, the low rank constraint of a difference image and the low n-rank constraint of a third-order tensor is proposed, where the images are reconstructed by a batching pattern. The split Bregman iteration (SBI) algorithm is developed for solving the proposed objective functional. Numerical simulations are implemented to demonstrate the advantages of the proposed algorithm on improving the reconstruction quality and the robustness.     

循环流化床上ECT传感器灵敏场的有限元分析

电容层析成像传感器的敏感场受多相流介质分布的影响,软场特性给图像重建带来很大困难,为了提高重建图像质量,对敏感场分布进行分析是非常必要的.该文以12电极方形电容传感器为基础,对电容层析成像技术应用于循环流化床研究做了简单阐述,着重研究了用有限元法对方形电容传感器敏感场分布的计算机仿真,讨论了负敏感场的处理方法.     

A non-convex regularization method combined with Landweber method for image reconstruction in electrical resistance tomography

Electrical resistance tomography (ERT) is a promising technique with which the conductivity distribution in the detected region can be visualized. Mathematically, the reconstruction of conductivity distribution is a seriously ill-posed inverse problem which poses a great challenge for the ERT sensing technique. The regularization method has been found to be an effective approach in coping with the inverse problem. In this work, a novel reconstruction strategy which combines the non-convex regularization method with Landweber method is proposed for the image reconstruction in ERT. At each iteration, the non-convex regularization is used to constrain the conductivity calculated with the Landweber method. A simple and efficient generalized iterated shrinkage algorithm is developed to solve the proposed method. To validate the performance of the proposed method, a series of numerical simulation is conducted and comparative analysis with other methods is performed. From the results, it can be observed that images with high quality are obtained when reconstructing with the proposed method. The impact of noise on the reconstruction is also investigated which shows that the images reconstructed by the proposed method are the least sensitive to the noise. The performance of the proposed method in the image reconstruction is also verified by experimental data. The results demonstrate that the inclusion is accurately reconstructed and the background is clear when the proposed method is adopted for the image reconstruction.     

基于加权奇异值分解截断共轭梯度的电容层析图像重建

针对电容层析成像技术(ECT)中的软场效应和病态问题,提出了一种基于加权奇异值分解(SVD)截断共轭梯度的电容层析(ECT)图像重建算法。阐述了电容层析成像工作原理,提出了12电极ECT系统的测量方法。在分析灵敏度矩阵的奇异值分解理论的基础上,推导出了加权SVD截断共轭梯度的数学模型,并利用Tikhonov方法进行正则化加权处理。最后,分析了算法的收敛性,并将其应用于电容层析成像系统的图像重建中。实验结果表明,对于层流,截断共轭梯度算法的平均误差能达到27.54%,全部流型平均迭代步数达到13步,与LBP、Landweber和CG算法比较,该算法具有成像效果好,成像速度快,易于实现等特点。     

基于双截面ECT的气/固两相流参数检测系统

为了实现多相流的流动过程在线监测和多参数测量,设计并研发了一套应用于气/固两相流检测的双截面8电极电容层析成像系统.采用交流法电容检测原理实现具有16个独立电容检测通道的电容测量电路,实测系统的成像速度为590帧/秒.将双截面电容层析成像系统用于气/固两相流的实时检测,并将两层截面的图像作相关计算,获取成像截面的固相速度分布.由固相速度和浓度最终算出气/固两相流的固相质量流量,从而实现气/固两相流浓度、速度、流量等多参数的综合检测.将双截面ECT传感器算得的质量流量与发料罐重力传感器获取的质量流量作对比发现,两者具有较好的一致性,流量测量误差小于8％.     

Image reconstruction of electrical capacitance tomography based on optimal simulated annealing algorithm using orthogonal test method

Electrical capacitance tomography (ECT) is a visualization measurement method for two-phase flow. Imaging permittivity distributions using electrical capacitance tomography has always been one of the most significant issues studied by scholars, and the algorithm will have a great impact on the accuracy of image reconstruction result. This paper applies simulated annealing (SA) algorithm to image reconstruction in ECT. However, some parameters of SA algorithm need to be optimized in order to obtain better reconstructed images in ECT. The influence of different parameter values in SA algorithm for image reconstruction in ECT is studied, and a set of optimal parameters of the SA algorithm is obtained based on the orthogonal experimental design method in this paper. At the same time, simulation and static experiments are conducted. Reconstructed images by SA algorithm with optimized parameter are compared with the linear back projection (LBP) and Landweber iterative algorithms. The results show that better images can be obtained for typical oil-gas two-phase flow using SA algorithm. The quality and shape fidelity of reconstructed image for the central object are obviously improved.     

基于小波包和极限学习机的汽车发动机失火故障识别

针对缸盖振动信号的非平稳特性,提出了基于小波包相关系数和极限学习机的汽车发动机失火故障诊断系统.首先,对原始信号进行小波包分解,然后计算得到每个样本的能量熵和每个样本各子频带重构信号与原始信号的相关性系数.分别利用相关系数法和能量熵融合峭度的方法建立特征向量,随后输入到BP神经网络和极限学习机中进行训练和测试.实验结果表明,该方法可以有效地反映故障产生的差异并准确地识别单缸失火故障,具有精度高、训练时间短的优点.