Sparse optimization for image reconstruction in Electrical Impedance Tomography

被引：5
|
作者：
Varanasi, Santhosh Kumar [1 ]
Manchikatla, Chaitanya [1 ]
Polisetty, Venkata Goutham [1 ]
Jampana, Phanindra [1 ]
机构：
[1] Indian Inst Technol Hyderabad, Dept Chem Engn, Sangareddy 502285, Telangana, India
来源：
IFAC PAPERSONLINE | 2019年 / 52卷 / 01期
关键词：
Parameter estimation; Electrical Resistance/Impedance Tomography; Sparse optimization; Orthogonal matching pursuit; REGULARIZATION; FLOW;
D O I：
10.1016/j.ifacol.2019.06.033
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Electrical Impedance Tomography (EIT) can be used to obtain phase boundaries and gas holdups in multiphase flows. The main challenge in image reconstruction using EIT is the low spatial resolution. In this paper, a reconstruction algorithm using sparse optimization techniques is presented. For multiphase flows, gradients in the conductivity vector are sparse. Therefore, the reconstruction problem is formulated as identification of this sparse vector given the current-voltage measurements. A new iterative algorithm is proposed to estimate the conductivity values. The accuracy of the proposed method is demonstrated with the help of several examples and comparison with an existing technique. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
引用
收藏
页码：34 / 39
页数：6
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