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Iterative computational imaging method for flow pattern reconstruction based on electrical capacitance tomography

期刊

CHEMICAL ENGINEERING SCIENCE
卷 214, 期 -, 页码 -

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ces.2019.115432

关键词

Flow pattern imaging; Image reconstruction; Split Bregman algorithm; Regularization method; Electrical capacitance tomography

资金

  1. Fundamental Research Funds for the Central Universities [JB2019117, 2017MS012, 2017MS073]
  2. National Natural Science Foundation of China [61871181, 61571189]
  3. National Key Research and Development Program of China [2017YFB0903601]
  4. State Administration of Foreign Experts Affairs [B13009]

向作者/读者索取更多资源

The electrical capacitance tomography (ECT) is a promising measurement technique, which tries to reconstruct the permittivity distribution in a measurement domain by solving an inverse problem. Low quality images narrow the applicability of the technique. To address the challenge, a new cost function, which considers model deviation and measurement noises, is devised to model the ECT reconstruction problem. The soft thresholding method and the fast-iterative shrinkage thresholding technique (FIST) are embedded into the iterative split Bregman (ISB) method to solve the devised objective functional. The numerical and experimental results indicate that the proposed ECT imaging technique not only mitigates the ill-posed nature, but also improves the reconstruction quality. (C) 2019 Elsevier Ltd. All rights reserved.

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