| Issue |
E3S Web of Conf.
Volume 389, 2023
Ural Environmental Science Forum “Sustainable Development of Industrial Region” (UESF-2023)
|
|
|---|---|---|
| Article Number | 07009 | |
| Number of page(s) | 8 | |
| Section | IT in Environmental Science | |
| DOI | https://doi.org/10.1051/e3sconf/202338907009 | |
| Published online | 31 May 2023 | |
Computer model for acquisition, processing, analysis and visualization of measurement data by electrical impedance tomography
1 Platov South-Russian State Polytechnic University (NPI), 132, str. Enlightenment, 346428, Novocherkassk, Russia
2 Le Quy Don Technical University, 463 Hoàng Quốc Việt, P, 129810, Nam Từ Liêm, Hà Nội, Viet Nam
* Corresponding author: mari.mak787@yandex.ru
In this article, a computer model for the collection, processing, analysis and visualization of measurement data by the method of electrical impedance tomography has been developed. The essence of the work performed is to build a computer model of the phantom, electrodes, conductive medium and inhomogeneities in the COMSOL Multiphysics environment to study the conductivity of objects in order to reduce the error in determining the size of the inhomogeneity in the reconstructed image. The study is performed by placing an inhomogeneity phantom in the conductive region. Based on the data obtained, a matrix of potential differences is constructed using the “near neighbor” algorithm. On its basis, in the GNU Octave environment, using the EIDORS package, a reconstruction of the conducted studies is obtained. With the help of the developed software that implements the method and algorithm for refining the boundaries, filtered images of reconstructions of the results of the studies are obtained. The use of this algorithm makes it possible to reduce the measurement error by a factor of 1.44.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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