Homotopy Extension and Selfscaling Metric Image Reconstruction Algorithm for Electrical Capacitance Tomography System

In order to solve the “soft field” and uncertainty problems in electrical capacitance tomography, a homotopy extension regularization and selfscaling metric image reconstruction algorithm for electrical capacitance tomography is presentedOn the basis of ECT theory, the algorithm combines homotopy co...

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Bibliographic Details
Main Authors: CHEN Yu, ZHANG Jiangtao, XIA Zongji
Format: Article
Language:zho
Published: Harbin University of Science and Technology Publications 2020-10-01
Series:Journal of Harbin University of Science and Technology
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Online Access:https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=1868
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Summary:In order to solve the “soft field” and uncertainty problems in electrical capacitance tomography, a homotopy extension regularization and selfscaling metric image reconstruction algorithm for electrical capacitance tomography is presentedOn the basis of ECT theory, the algorithm combines homotopy continuation with regularization method, and derives the corresponding correction formula combined with selftuning ratio Finally, the mathematical model of inverse problem of ECT Image reconstruction is derived.The algorithm is used in digital simulation experiment to verify its effectiveness The simulation results are compared with the classical Landweber algorithm, SD algorithm and other imaging algorithms The results show that the algorithm has the advantages of high image quality, fast convergence speed and less iteration times in ECT Image reconstruction It is an effective algorithm to solve ECT imaging problems
ISSN:1007-2683