Abstract
This paper addresses the challenge of reconstructing multiphase conductivity distributions using electrical impedance tomography (EIT). The reconstruction method developed in the paper utilizes the moving morphable component (MMC) approach, where the unknown inclusion(s) to be reconstructed is (are) composed of several candidate morphable components. This work introduces a signed distance-based shape and topology description function (STDF) in lieu of the recently developed hyperelliptic STDF in the MMC approach, thereby absolving the requirement of exponent values. The MMC approach uses explicit geometric entities for the morphable components that are controlled by geometric parameters, such as varying thickness, length, and angle. The optimal inclusion shapes are found by optimizing these geometric parameters in STDFs. Numerical simulation and water tank experiments are used to demonstrate the effectiveness of the proposed method.
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The derivatives of fs with respect to shape design variables can be found using Symbolic Math Toolbox™software.
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Acknowledgements
The authors would like to thank Danny Smyl, PhD for the helpful discussions. Also, the authors would like to thank the inverse problems group at University of Eastern Finland for providing us with the experimental data.
Funding
This work was supported in part by the National Natural Science Foundation of China (Grant Nos. 61871356 and 81788101), in part by the National Key R&D Program of China (Grant No. 2018YFA0306600), in part by the Chinese Academy of Sciences (Grant Nos. XDC07040200, GJJSTD20170001, and QYZDY-SSW-SLH004), and in part by the Anhui Initiative in Quantum Information Technologies (Grant No. AHY050000).
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Liu, D., Du, J. Shape and topology optimization in electrical impedance tomography via moving morphable components method. Struct Multidisc Optim 64, 585–598 (2021). https://doi.org/10.1007/s00158-021-02970-8
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DOI: https://doi.org/10.1007/s00158-021-02970-8