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。     

基于两相流电容层析成像系统的正则化Landweber算法

针对电容层析成像系统的不适定性问题,提出了一种正则化Landweber阈值迭代改进算法。该算法将正则化项引入初值等式约束中,得到带约束的正则化问题,并在Landweber迭代算法的过程中设置门限阈值,在每次迭代中都自适应的调节阈值参数,最终用带约束的正则化Landweber阈值迭代算法得到最终的重建图像结果。数值仿真实验表明,正则化Landweber阈值迭代算法在改善图像重建质量和提高收敛速度方面均有明显的优势。     

基于多项式加速的电容层析成像图像重建算法

针对普通迭代方法收敛速度慢的问题,提出一种多项式加速的正则化迭代电容层析成像算法来加快其收敛速度.在介绍12电极电容层析成像系统基本原理的基础上,给出了该算法的数学模型,并利用谱分析对该算法的收敛性进行了证明.探讨了ECT应用该算法的可行性,该算法易满足收敛条件且重建图像误差小.仿真和实验结果表明,和LBP、Landweber算法相比,该算法兼备成像质量高及收敛速度快等优点,为ECT图像重建算法的研究提供了一个新的思路.     

用于电容层析成像的一步稳定图像重建算法

本文提出一种基于Landweber迭代的电容层析成像系统一步稳定图像重建算法。该算法通过构建压缩算子可以克服传统Landweber迭代方法存在的半收敛性,得到稳定的重建图像。同时该算法的矩阵算子可以预先计算,然后通过一步矩阵运算实现图像重构。实验结果表明,该算法可保证重建图像的实时性和鲁棒性。     

电容层析成像中图像重建算法评述

电容传感器具有非侵入、响应快、低成本、测量范围宽及易于安装等特点,在多相流在线检测中具有良好的发展前景。 电容层析成像中图像的重建算法与技术,是其在工业实际中得以应用的关键。近年来在图像重建方面的研究取得了较大的进 展,Tikhonov正则法,基于LBP迭代法、Landweber迭代法、同步迭代法及神经元网络法等对图像重建精度比LBP方法都有 了明显的提高,但其重建速度有待于进一步提高以适应在线应用。     

无源毫米波成像投影Landweber多重网格超分辨算法

在无源毫米波成像应用中,由于天线孔径大小的限制而导致获得的图像有可怜的分辨率,因此必须采取有效的后处理措施增强图像的分辨率。本文提出了一种针对无源毫米波成像应用的投影Landweber多重网格超分辨算法,该算法以投影Landweber算法作为主迭代过程,通过逐步频域内插避免了频谱混叠,从而实现频谱外推和超分辨。实验结果表明,该算法改善了收敛速度,增强了图像的分辨率,减少了计算量,有利于无源毫米波成像超分辨的实时实现。     

电磁层析成像图像重建中的修正共轭梯度算法

通过研究共轭梯度算法,推导出适用于电磁层析成像的修正共轭梯度算法,该方法提高了收敛速度,改善了电磁层析成像重建图像的质量。首先以共轭搜索方向充分下降为充分条件,理论推导出修正共轭梯度算法。然后从相对图像误差、相关系数和收敛曲线几个方面出发,评价了Landweber迭代法、单步Tikhonov正则化方法、共轭梯度法和修正共轭梯度法在电磁层析成像图像重建中的结果,得出结论:修正共轭梯度方法的相对图像误差最小,重建图像和原图像的相关系数最高,收敛情况优于共轭梯度算法。     

基于改进Landweber算法的两相流检测的研究

电容层析成像(ECT)具有非侵入式,响应速度快,安全等优点,是用于两相流检测非常有发展潜力的技术之一.该文在介绍了电容层析成像基本原理之后,探讨了ECT应用改进的Landweber算法的可行性,该算法收敛速度较快,且成像精度高.仿真实验表明,改进的Landweber算法同Landweber算法相比较,只需要很少的迭代次...     

改进正则化半阈值算法的 ECT 图像重建

针对电容层析成像技术应用于工业多相流管道检测时,图像重建中存在的不适定性、病态性问题,提出一种改进正则化半阈值算法。以L1/2范数为惩戒函数,改进求解L1/2范数所用的半阈值迭代算法中的阈值算子,并以加入加速项的Landweber算法解向量为修正向量,引入改进半阈值正则化模型,优化加速Landweber算法。实验的结果表明,改进正则化半阈值算法在重建图像中相关系数平均达0.91,图像误差平均降至0.21,成像速度保持0.04 s。复杂流型辨识中,改进算法比Landweber迭代算法相关系数提高21.67%,相对误差降低37.01%;比Tikhonov正则化算法相关系数提高22.61%,相对误差降低37.08%;比半阈值算法相关系数和误差分别提高14.85%和降低28.26%。结果表明改进正则化半阈值算法对ECT研究有较好应用前景。     

流场超声层析成像中图像的迭代滤波反投影重建

为提高流场超声层析成像的图像重建质量,提出了一种迭代滤波反投影图像重建算法。该算法借鉴联合迭代重建算法的原理,将滤波反投影算法引入迭代重建过程。首先,利用滤波反投影算法,通过投影数据残差重建误差图像对流场图像进行修正,实现图像的迭代重建。然后,通过优化迭代步长,使每步迭代后投影数据残差均取得极小值以便加快收敛速度。最后,基于流场连续、紧支撑分布的特点,在迭代重建过程中引入投影数据的细分内插和流场图像的圆域修正。实验表明:相比于滤波反投影算法,迭代滤波反投影算法可使理论流场重建的图像误差平均减少26%,流量误差由1.77%减小至±0.25%以内;程序运行时间为0.63s,仅为联合迭代重建算法的0.89%。该算法可实现对直管段内和单弯管下游实际流场的可靠重建,满足流场高精度实时成像的要求。     

An extreme learning machine combined with Landweber iteration algorithm for the inverse problem of electrical capacitance tomography

The image reconstruction of the electrical capacitance tomography (ECT) is an ill-posed and sparse problem. In order to increase the accuracy and speed of the image reconstruction, this paper proposes a new reconstruction algorithm which is based on the extreme learning machine (ELM) with the Landweber iteration method. Firstly, a nonlinear mapping model is established between the pixel gray-scale values and the interelectrode capacitances by using the ELM which has a good learning ability and high speed. Secondly, the Landweber iteration method, which has a good performance in convergence and stability, is applied to calculate the output weight matrix of ELM. Finally, a convergence and stable mapping model of ELM with the Landweber iteration algorithm (L-ELM) for ECT image reconstruction is trained on Matlab platform. Both simulation and measurement tests are carried out to evaluate and analyze the proposed method. Experimental results indicate that the proposed algorithm has good generalization ability and high image reconstruction quality which are better than those of conventional ELM algorithm.     

Preconditioned Landweber iteration algorithm for electrical capacitance tomography

Electrical capacitance tomography (ECT) has been used to obtain the cross-section images of processes with different dielectric materials inside. Image reconstruction with ECT is to retrieve the permittivity distribution of materials inside the sensor from the capacitance measurements. Algorithms for ECT image reconstruction should be both precise and fast in order to satisfy the requirements of real-time monitoring of the dynamic behavior of processes. Several algorithms have been developed for ECT image reconstruction. The Landweber iteration is the most precise one. However, the low convergence rate of the Landweber iteration limits its application for on-line imaging.This paper introduces an iterative algorithm based on the Landweber method with preconditioning for ECT image reconstruction. A preconditioner, which is equivalent to a filter, is applied to the Landweber iteration. The convergence of this algorithm is analyzed. Its performance is evaluated by using simulated and experimental data corresponding to certain typical permittivity distributions. Preliminary numerical and experimental results show that this algorithm converges more rapidly than the Landweber iteration without preconditioning. Therefore, image reconstruction iteration can be accelerated, which makes on-line quantitative image reconstruction possible.     

粒子滤波算法在ECT图像重建中的应用

针对电容层析成像技术(ECT)的图像重建质量精度较低的问题,提出了一种基于粒子滤波的ECT图像重建方法。首先,分析了ECT图像重建基本原理,以系统状态估计的方式描述了ECT图像重建最优解的搜索过程,并建立了状态空间模型。然后,以线性反投影(LBP)算法的图像重建结果作为初始状态,利用测量信息对从状态空间中获取的随机样本进行最优加权,以获得重建图像的最小方差估计。最后,对5种不同的流型进行了仿真实验。实验结果表明,利用本文方法获得的重建图像误差平均值为42.93%,相关系数平均值为0.813 9,比LBP算法、Landweber迭代算法和IMN-SNOF算法得到的相应指标要好。本文方法是一种有效、精度较高的ECT图像重建方法,为ECT图像重建技术提供了新的途径和手段。     

基于自适应模拟退火及 LM 联合反演算法的 ECT 图像重建

为解决电容层析成像技术(ECT)中图像重建的非线性和病态性问题,提出了一种自适应模拟退火-Levenberg Marquardt (ASA-LM)联合反演算法。 改进了标准模拟退火(SA)算法的新解生成策略、能量函数的定义及退火策略,并结合 LM 的直接局 部搜索方法联合反演 ECT 图像重建问题。 同时,利用 Savitzky-Golay (SG) 滤波对 ECT 图像重建所需电容数据进行平滑处理以 提高其信噪比。 最后,进行仿真及静态实验,并与线性反投影(LBP)、Landweber 迭代及标准 SA 算法进行了比较。 结果表明,与 其他 3 种算法相比,ASA-LM 算法收敛速度快、图像重建质量明显提高,边缘信息保真度高,重建图像的平均相对误差为 0. 331 1,平均相关系数为 0. 933 1。     

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.     

3D ECT reconstruction by an improved Landweber iteration algorithm

Electrical capacitance tomography (ECT) is a relatively mature non-invasive imaging technique that attempts to map dielectric permittivity of materials. Recently, 3D ECT has gained interest because of its potential to generate volumetric images. The study of a fast and accurate image reconstruction algorithm is a challenge task, especially for 3D reconstruction. In this paper, we propose an improved Landweber iteration algorithm. We incorporate an additional acceleration term into the cost function and apply an adaptive threshold operation to the image obtained in each iteration for reducing artefacts. The algorithm proposed is tested by the noise-free and noise-contaminated capacitance data. Sensitivity matrixes and capacitance data of a 3D ECT sensor are obtained by using the finite element (FE) method. Extensive simulations in 3D reconstruction are carried out. The results verify the effectiveness of these improvements. Both the reconstruction time and the artefacts in the reconstructed image are reduced obviously. The experimental results of 3D reconstruction of objects in the shape of letters U and L confirm the effectiveness of the proposed algorithm further.     

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.     

基于预优化变换的电容层析成像图像重建算法

本文提出了一种新型快速电容层析成像的图像重建算法。该方法首先将图像重建的病态问题转化为泛函极小化问题，然后采用Fletcher-Reeves算法（FR）有效地求解该泛函，并在求解的过程中引入物理意义上的约束使获得的解更符合实际情况。数值实验表明该算法的图像重建效果优于线性反投影法、Tikhonov正则法和Landweber迭代法，而且该算法具有较强的抗噪声能力。