Hybrid spectrum conjugate gradient algorithm in electromagnetic tomography

IF 1.3 4区 工程技术 Q4 CHEMISTRY, ANALYTICAL
Liu Li, Y. Luo, Qian Zhao, Zhanjun Wang
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引用次数: 0

Abstract

Abstract Electromagnetic tomography is a process detection technology based upon the principles of electromagnetic induction. The forward problem model and sensitivity distribution matrix of electromagnetic tomography are introduced as the basis of the inverse problem. The search direction and iterative parameters of the conjugate gradient algorithm are modified to improve the quality and convergence of image reconstruction. A new spectral parameter conjugate gradient algorithm is described to modify the search direction, which is used to control the angle between the old and new search directions. The search direction is determined according to the iteration of each step in order to find the optimal solution. Combining the advantages of the Fletcher-Reeves and Polak-Ribiere-Polyak algorithms in the nonlinear conjugate gradient algorithm, they are mixed in a specific proportion to obtain a new hybrid conjugate gradient algorithm. In order to verify the effectiveness of the modified conjugate gradient algorithm, three physical models of electromagnetic tomography system are constructed, and the modified conjugate gradient algorithm is compared with the traditional algorithm. The experimental results show that the reconstructed image quality of the modified spectral conjugate gradient algorithm is higher and has better numerical performance. The hybrid conjugate gradient algorithm highlights the advantages of the Fletcher-Reeves and Polak-Ribiere-Polyaks algorithms. The convergence speed is faster than the Polak-Ribiere-Polyak method, and the imaging quality is higher than the other algorithms.
电磁层析成像中的混合谱共轭梯度算法
电磁层析成像是一种基于电磁感应原理的过程检测技术。引入了电磁层析成像的正演问题模型和灵敏度分布矩阵,作为反演问题的基础。改进了共轭梯度算法的搜索方向和迭代参数,提高了图像重建的质量和收敛性。提出了一种新的谱参数共轭梯度算法来修改搜索方向,用于控制新旧搜索方向之间的夹角。根据每一步的迭代确定搜索方向,以找到最优解。结合Fletcher-Reeves算法和Polak-Ribiere-Polyak算法在非线性共轭梯度算法中的优点,将它们按特定比例混合,得到一种新的混合共轭梯度算法。为了验证改进共轭梯度算法的有效性,构建了三个电磁层析成像系统的物理模型,并将改进共轭梯度算法与传统算法进行了比较。实验结果表明,改进的光谱共轭梯度算法重构图像质量更高,具有较好的数值性能。混合共轭梯度算法突出了Fletcher-Reeves算法和Polak-Ribiere-Polyaks算法的优点。收敛速度比Polak-Ribiere-Polyak方法快,成像质量高于其他算法。
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来源期刊
Instrumentation Science & Technology
Instrumentation Science & Technology 工程技术-分析化学
CiteScore
3.50
自引率
0.00%
发文量
45
审稿时长
>12 weeks
期刊介绍: Instrumentation Science & Technology is an internationally acclaimed forum for fast publication of critical, peer reviewed manuscripts dealing with innovative instrument design and applications in chemistry, physics biotechnology and environmental science. Particular attention is given to state-of-the-art developments and their rapid communication to the scientific community. Emphasis is on modern instrumental concepts, though not exclusively, including detectors, sensors, data acquisition and processing, instrument control, chromatography, electrochemistry, spectroscopy of all types, electrophoresis, radiometry, relaxation methods, thermal analysis, physical property measurements, surface physics, membrane technology, microcomputer design, chip-based processes, and more. Readership includes everyone who uses instrumental techniques to conduct their research and development. They are chemists (organic, inorganic, physical, analytical, nuclear, quality control) biochemists, biotechnologists, engineers, and physicists in all of the instrumental disciplines mentioned above, in both the laboratory and chemical production environments. The journal is an important resource of instrument design and applications data.
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