• Journal of IKEEE
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• v.28 no.2
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• pp.187-198
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• 2024

Estimating the phase boundary in two-phase flow is crucial for designing and optimizing industrial processes. Electrical impedance tomography (EIT) is a promising technique for imaging phase distribution in such flows. This paper proposes using a cuckoo search (CS) optimization algorithm to estimate the phase boundary with EIT. The boundary is parameterized using the Fourier series, and the coefficients are determined by the CS algorithm. The CS algorithm iteratively seeks the phase boundary configuration by minimizing a cost function. Computer simulations and phantom experiments demonstrate the effectiveness of this method in estimating phase boundaries in two-phase flow.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1897-1902
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• 2005

The objective of this paper is to estimate the concentration distribution in flow field inside the pipeline based on electrical impedance tomography. Special emphasis is given to the development of dynamic imaging technique for two-phase field undergoing a rapid transient change. Nonlinearity-compensation extended Kalman filter is employed to cope with unexpected measurement uncertainty. The nonlinearity-compensation extended Kalman filter compensates for the influence of measurement uncertainty and solves the instability of extended Kalman filter. Extensive computer simulations are carried out to show that nonlinearity-compensation extended Kalman filter has enhanced estimation performance especially in the unexpected measurement environment.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.18 no.2
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• pp.167-180
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• 2014

In this paper we consider a novel reconstruction method in electrical impedance tomography (EIT) and its application for monitoring and detecting a hydrargyrum (mercury) polluted soil near to the surface of underground. We use electrodes placed on the surface of land to collect the data which provides the relations of voltage and current map and to produce a projected image of interior conductivity distribution onto the surface of land. Here the projected image reconstruction method is used to monitor the pollution in soil underneath the ground without any destruction and any digging into a land.

• Proceedings of the KSMRM Conference
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• 2008.04a
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• pp.82-128
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• 2008

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.2
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• pp.120-127
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• 2003

In electrical impedance tomography(EIT), various image reconstruction algorithms have been used in order to compute the internal resistivity distribution of the unknown object with its electric potential data at the boundary. Mathematically the EIT image reconstruction algorithm is a nonlinear ill-posed inverse problem. This paper presents a simulated annealing technique as a statistical reconstruction algorithm for the solution of the static EIT inverse problem. Computer simulations with the 32 channels synthetic data show that the spatial resolution of reconstructed images by the proposed scheme is improved as compared to that of the mNR algorithm or genetic algorithm at the expense of increased computational burden.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.9
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• pp.293-299
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• 2012

Electrical impedance tomography is an imaging modality for determining the electrical properties inside a domain. Small currents are injected and the resulting voltages are measured through the electrodes. The internal electrical properties are reconstructed based on these voltage and current data. In this paper, a novel on-line Landweber algorithm was developed to fast estimate the resistivity distribution in the inverse calculation. Additionally, to enhance the reconstruction performance, a step-length was computed from the eigenvalue of the weighting matrix. The numerical experiments have been performed to evaluate the reconstruction performance of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.40-45
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• 2004

This work presents a boundary estimation approach in electrical impedance imaging for binary-mixture fields based on a parallel structured multi-layer neural network. The interfacial boundaries are expressed with the truncated Fourier series and the unknown Fourier coefficients are estimated with the parallel structure of multi-layer neural network. Results from numerical experiments shows that the proposed approach is insensitive to the measurement noise and has a strong possibility in the visualization of binary mixtures for a real time monitoring.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.570-574
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• 2003

In most boundary estimation algorithms estimation in EIT (Electrical Impedance Tomography), anomaly boundaries can be expressed with Fourier series and the unknown coefficients are estimated with proper inverse algorithms. Furthermore, the number of anomalies is assumed to be available a priori. The prior knowledge on the number of anomalies may be unavailable in some cases, and we need to determine the number of anomalies with other methods. This paper presents an algorithm for the boundary estimation in EIT (Electrical Impedance Tomography) using the prior information from the conventional Newton-Raphson method. Although Newton-Raphson method generates so poor spatial resolution that the anomaly boundaries are hardly reconstructed, even after a few iterations it can give general feature of the object to be imaged such as the number of anomalies, their sizes and locations, as long as the anomalies are big enough. Some numerical experiments indicate that the Newton-Raphson method can be used as a good predictor of the unknown boundaries and the proposed boundary discrimination algorithm has a good performance.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.32-35
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• 2004

In boundary estimation in Electrical Impedance Tomography (EIT), conventional method is the modified Newton Raphson (mNR) method .The mNR is famous for good method since has good convergence and robustness against noisy data. But the mNR is low efficiency to get and update Jacobian matrix. So, the mNR become very slow algorithm. We propose the Quasi Newton (QN) method to improve efficiency which will lead to speed up in boundary estimation. The QN can improve a low efficiency by using estimated Jacobian matrix contrary to using exactly calculated Jacobian matrix, this used by the mNR. And finally, we propose the modified Quasi Newton (mQN) method because the QN has some problems such as bad early convergence rate and instability of 'divided by zero'. For the verification of the propose method, numerical experiments are conducted and the results show a good performance.

• Journal of IKEEE
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• v.19 no.3
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• pp.407-414
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• 2015

Electrical impedance tomography is an imaging technique to reconstruct the internal conductivity distribution based on applied small currents and measured voltages through an array of electrodes attached on the boundary of a domain of interest. In this paper, an analytical solver with complete electrode model is derived and the analytical voltage data are calculated. Moreover, the voltage data are also computed with existing numerical solvers such as finite element method and boundary element method. The forward solutions using homogeneous and inhomogeneous conditions are compared with phantom experiments through the root mean square errors.