An Effective Measured Data Preprocessing Method in Electrical Impedance Tomography

As an advanced process detection technology, electrical impedance tomography (EIT) has widely been paid attention to and studied in the industrial fields. But the EIT techniques are greatly limited to the low spatial resolutions. This problem may result from the incorrect preprocessing of measuring...

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Main Authors: Chenglong Yu, Shihong Yue, Jianpei Wang, Huaxiang Wang
Format: Article
Language:English
Published: Hindawi Limited 2014-01-01
Series:The Scientific World Journal
Online Access:http://dx.doi.org/10.1155/2014/208765
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spelling doaj-46d2d8fee82b47ef995e228251bd96552020-11-24T21:30:37ZengHindawi LimitedThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/208765208765An Effective Measured Data Preprocessing Method in Electrical Impedance TomographyChenglong Yu0Shihong Yue1Jianpei Wang2Huaxiang Wang3School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, ChinaSchool of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, ChinaSchool of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, ChinaSchool of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, ChinaAs an advanced process detection technology, electrical impedance tomography (EIT) has widely been paid attention to and studied in the industrial fields. But the EIT techniques are greatly limited to the low spatial resolutions. This problem may result from the incorrect preprocessing of measuring data and lack of general criterion to evaluate different preprocessing processes. In this paper, an EIT data preprocessing method is proposed by all rooting measured data and evaluated by two constructed indexes based on all rooted EIT measured data. By finding the optimums of the two indexes, the proposed method can be applied to improve the EIT imaging spatial resolutions. In terms of a theoretical model, the optimal rooting times of the two indexes range in [0.23, 0.33] and in [0.22, 0.35], respectively. Moreover, these factors that affect the correctness of the proposed method are generally analyzed. The measuring data preprocessing is necessary and helpful for any imaging process. Thus, the proposed method can be generally and widely used in any imaging process. Experimental results validate the two proposed indexes.http://dx.doi.org/10.1155/2014/208765
collection DOAJ
language English
format Article
sources DOAJ
author Chenglong Yu
Shihong Yue
Jianpei Wang
Huaxiang Wang
spellingShingle Chenglong Yu
Shihong Yue
Jianpei Wang
Huaxiang Wang
An Effective Measured Data Preprocessing Method in Electrical Impedance Tomography
The Scientific World Journal
author_facet Chenglong Yu
Shihong Yue
Jianpei Wang
Huaxiang Wang
author_sort Chenglong Yu
title An Effective Measured Data Preprocessing Method in Electrical Impedance Tomography
title_short An Effective Measured Data Preprocessing Method in Electrical Impedance Tomography
title_full An Effective Measured Data Preprocessing Method in Electrical Impedance Tomography
title_fullStr An Effective Measured Data Preprocessing Method in Electrical Impedance Tomography
title_full_unstemmed An Effective Measured Data Preprocessing Method in Electrical Impedance Tomography
title_sort effective measured data preprocessing method in electrical impedance tomography
publisher Hindawi Limited
series The Scientific World Journal
issn 2356-6140
1537-744X
publishDate 2014-01-01
description As an advanced process detection technology, electrical impedance tomography (EIT) has widely been paid attention to and studied in the industrial fields. But the EIT techniques are greatly limited to the low spatial resolutions. This problem may result from the incorrect preprocessing of measuring data and lack of general criterion to evaluate different preprocessing processes. In this paper, an EIT data preprocessing method is proposed by all rooting measured data and evaluated by two constructed indexes based on all rooted EIT measured data. By finding the optimums of the two indexes, the proposed method can be applied to improve the EIT imaging spatial resolutions. In terms of a theoretical model, the optimal rooting times of the two indexes range in [0.23, 0.33] and in [0.22, 0.35], respectively. Moreover, these factors that affect the correctness of the proposed method are generally analyzed. The measuring data preprocessing is necessary and helpful for any imaging process. Thus, the proposed method can be generally and widely used in any imaging process. Experimental results validate the two proposed indexes.
url http://dx.doi.org/10.1155/2014/208765
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