• Journal of Institute of Control, Robotics and Systems
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• v.9 no.1
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• pp.50-56
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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 new combined method based on genetic algorithm(GA) and modified Newton-Raphson(mNR) algorithm via two-step approach for the solution of the static EIT inverse problem. In the first step, each mesh is classified into three mesh groups: target, background, and temporary groups. The mNR algorithm can be used to determine the region of group. In the second step, the values of these resistivities are determined using genetic algorithm. Computer simulations with the 32 channels synthetic data show that the spatial resolution of reconstructed images by the proposed scheme is improved compared to that of the mNR algorithm at the expense of increased computational burden.

• Journal of Industrial Technology
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• v.27 no.B
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• pp.91-96
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• 2007

Electrical impedance tomography (EIT) is a technique for determining the electrical conductivity and permittivity distribution within the interior of a body from measurements made on its surface. One recent application area of the EIT is the detection of breast cancer by imaging the conductivity and permittivity distribution inside the breast. The present standard for breast cancer detection is X-ray mammography, and it is desirable that EIT and X-ray mammography use the same geometry. A forward model of a simplified mammography geometry for EIT imaging was proposed earlier. In this paper, we propose an iterative algorithm for computing the current pattern that will be applied to the electrodes. The current pattern applied to the electrodes influences the voltages measured on the electrodes. Since the measured voltage data is going to be used in the impedance imaging computation, it is desirable to apply currents that result in the largest possible voltage signal. We compute the eigenfunctions for a homogenous medium that will be applied as current patterns to the electrodes. The algorithm for the computation of the eigenfunctions is presented. The convergence of the algorithm is shown by computing the eigencurrent of the simplified mammography geometry.

• Journal of IKEEE
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• v.19 no.2
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• pp.219-224
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• 2015

Electrical impedance tomography is an imaging technique to reconstruct the internal conductivity distribution based on applied currents and measured voltages in a domain of interest. In this paper, a modified Gauss-Newton method is proposed for conductivity image reconstruction. In the proposed method, the dimension of the inverse term is reduced by replacing the number of elements with the number of measurement data in the conductivity updating equation of the conventional Gauss-Newton method. Therefore, the computation time is greatly reduced as compared to the conventional Gauss-Newton method. Moreover, the regularization parameter is selected by computing the minimum-maximum from the diagonal components of the Jacobian matrix at every iteration. The numerical experiments with several scenarios were carried out to evaluate the reconstruction performance of the proposed method.

• Structural Engineering and Mechanics
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• v.80 no.5
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• pp.563-583
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• 2021

Composite materials, composed of multiple constituent materials with dissimilar properties, are actively adopted in a wide range of industrial sectors due to their remarkable strength-to-weight and stiffness-to-weight ratio. Nevertheless, the failure mechanism of composite materials is highly complicated due to their sophisticated microstructure, making it much harder to predict their residual material lives in real life applications. A promising solution for this safety issue is structural damage detection. In the present paper, damage detection of composite material via electrical resistance-based technique and infrared thermography is reviewed. The operating principles of the two damage detection methodologies are introduced, and some research advances of each techniques are covered. The advancement of IR thermography-based non-destructive technique (NDT) including optical thermography, laser thermography and eddy current thermography will be reported, as well as the electrical impedance tomography (EIT) which is a technology increasingly drawing attentions in the field of electrical resistance-based damage detection. A brief comparison of the two methodologies based on each of their strengths and limitations is carried out, and a recent research update regarding the coupling of the two techniques for improved damage detection in composite materials will be discussed.

• Journal of Industrial Technology
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• v.26 no.B
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• pp.221-226
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• 2006

Electrical impedance tomography (EIT) is a technique for determining the electrical conductivity and permittivity distribution within the interior of a body from measurements made on its surface. One recent application area of the EIT is the detection of breast cancer by imaging the conductivity and permittivity distribution inside the breast. The present "gold standard" for breast cancer detection is X-ray mammography, and it is desirable that EIT and X-ray mammography use the same geometry. This paper presents a forward model of a simplified mammography geometry for EIT imaging. The mammography geometry is modeled as a rectangular box with electrode arrays on the top and bottom planes. A forward model for the electrical impedance imaging problem is derived for a homogeneous conductivity distribution and Validated by experiment using a phantom tank.

• Communications of the Korean Mathematical Society
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• v.16 no.3
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• pp.333-369
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• 2001

칼데론 문제와 유한번 측정 역전도체 문제에 대한 중요한 결과들을 설명하고, 그 응용으로서 전기임피던스 영상기법에 대하여 설명한다.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.4
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• pp.36-44
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• 2012

Electrical impedance tomography is a relatively new imaging modality in which the internal conductivity (or resistivity) distribution of a object is reconstructed based on the injected currents and measured voltages through the electrodes placed on the surface of the object. In this paper, it is assumed that the relationship between the resistivity distribution and the resistance of electrodes is linear. From this linear relation, the weighting matrix can be obtained and modified iterative Landweber method is applied to estimate the internal resistivity distribution. Additionally, to accelerate the convergence rate and improve the spatial resolution of the reconstructed image, optimal step lengths for the iterative Landweber method are computed from the objective function in the least-square sense. The numerical experiments have been performed to illustrate the superior reconstruction performance of the proposed scheme.

• Journal of Biomedical Engineering Research
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• v.28 no.1
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• pp.66-74
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• 2007

We have developed a multi-channel, multi-frequency EIT system with operating frequency of 10Hz to 500KHz. The number of digital voltmeters using phase-sensitive demodulation can be varied from 8 to 64 and we found that 16 and 32-channels are most practical. This paper describes the design, implementation, and construction of 16 and 32-channel systems. The performance of the system was thoroughly tested and we found that CMRR of the developed voltmeter is about 85dB with $100{\Omega}$ unbalancing series resistor. The SNR is greater than 99.6dB and the output impedance of the constant current source is $1{\Omega}W$ at least for all frequencies. Imaging experiments using a banana with frequency-dependent conductivity and permittivity show that frequency-difference imaging is possible using the developed system. Future works of animal and human experiments are discussed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.8
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• pp.1430-1435
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• 2016

Electrical impedance tomography (EIT) has been applied to measure the location of external disturbance using a phantom and conductive yarns. According to the test results, the addition of carbon nanotube particles into the phantom does not show remarkable improvement in location errors. On the other hand combined fabric, conductive yarns with fabric, and non-woven fabric, were added to evaluate its performance as a fabric sensor. The combined fabric resulted in a decrease of 21.5% in the circumferential location error and a decrease of 50% in the radial location error, compared to those of the yarns. Additionally, it was revealed that the measurement error is almost linearly proportional to the conductivity of the phantom liquid and resistance of the conductive yarns. The combined fabric can be a promising material for fabric sensors in sports utilities and medical devices.

• Journal of IKEEE
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• v.16 no.3
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• pp.211-216
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• 2012

In the phase boundary estimation problem, the estimation performance depends on the initial guess. However, there is no information on the number of bubbles and those positions for the initial guess in real flows. Therefore, it is very important to set appropriate initial guesses from prior information. In this paper, in order to set initial guesses for estimating the phase boundaries in two-phase flows, first, unknown resistivity distribution was estimated using the difference reconstruction method. After that, an adaptive threshold value was automatically computed using intermodes method. Based on this value, the number of bubbles and the initial position were determined. The numerical experiments have been performed to evaluate the estimation performance of the proposed method.