Image reconstruction of electrical capacitance tomography based on non-convex and nonseparable regularization algorithm

被引：0
|
作者：
Li N. [1 ]
Zhu P. [1 ]
Zhang L. [2 ]
Lu D. [2 ]
机构：
[1] Department of Chemistry and Chemical Engineering, Chongqing Technology and Business University, Chongqing
[2] Department of Automation, North China Electric Power University, Hebei, Baoding
来源：
Huagong Xuebao/CIESC Journal | 2024年 / 75卷 / 03期
关键词：
electrical capacitance tomography; image reconstruction; non-convex and nonseparable regularization; sparse-low-rank model; two-phase mixture;
D O I：
10.11949/0438-1157.20240001
中图分类号：
学科分类号：
摘要：
Two-phase mixing in a stirrer is a common phenomenon in chemical production. Electrical capacitance tomography (ECT) technology mainly visually reconstructs the distribution of the two phases for monitoring purposes. Inspired by sparse Bayesian learning, a non-convex and nonseparable regularization (NNR) algorithm is proposed to reconstruct ECT images. The low-rank characteristics of the matrix are introduced on the basis of the sparse prior, and a new optimization problem is proposed in the latent space by using the maximum posterior estimation. Dual variables are used to map the objective function of the latent space to the original space for an iterative solution, which is used to restore the simultaneous sparse and low-rank matrices. Compared with the convex approximation L1 norm, the NNR algorithm can obtain more accurate reconstruction images, and it is easier to converge to the global optimal solution than the non-convex separable method. To verify the reconstruction effect of the NNR algorithm, the reconstruction was compared with the other five algorithms through numerical simulation and static experiments. The results show that the NNR algorithm can effectively reduce reconstruction artifacts, improve the reconstruction quality of the central object, and provide a high-quality reconstruction algorithm for the two-phase distribution in the stirrer. © 2024 Materials China. All rights reserved.
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页码：836 / 846
页数：10
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