DocumentCode :
27698
Title :
Comparisons of three modelling methods for the forward problem in three-dimensional electrical capacitance tomography
Author :
Hua Yan ; Yan Hui Sun ; Yi Fan Wang ; Ying Gang Zhou
Author_Institution :
Sch. of Inf. Sci. & Eng., Shenyang Univ. of Technol., Shenyang, China
Volume :
9
Issue :
5
fYear :
2015
fDate :
8 2015
Firstpage :
615
Lastpage :
620
Abstract :
Image reconstruction of electrical capacitance tomography (ECT) belongs to solving an inverse problem. The first step to solve the inverse problem is to establish a forward problem model which determines the capacitance values for known permittivity distribution. There are three main methods for ECT forward problem modelling. The first is based on the sensitivity definition. The second is based on the multiple linear regression (MLR) method. And the third is based on the electric field strength (EFS). In this study, comparisons of these three modelling methods for the forward problem in three-dimensional ECT are given in terms of modelling error, computational time and reconstruction quality. Comparison results show that the MLR method generates smallest modelling error and better reconstruction quality, especially for the very complex geometry with objects in the shape of letters H and U. However, the EFS method is significantly better than the other two methods in computational time.
Keywords :
capacitance measurement; computerised tomography; electric field measurement; electric impedance imaging; image reconstruction; inverse problems; measurement errors; permittivity; regression analysis; 3D ECT; 3D electrical capacitance tomography; EFS method; MLR method; complex geometry; electric field strength; forward problem model; image reconstruction; inverse problem; modelling error; modelling method; multiple linear regression method; permittivity distribution;
fLanguage :
English
Journal_Title :
Science, Measurement & Technology, IET
Publisher :
iet
ISSN :
1751-8822
Type :
jour
DOI :
10.1049/iet-smt.2014.0252
Filename :
7172627
Link To Document :
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