• 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.

• Proceedings of the KSEEG Conference
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• 2002.04a
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• pp.163-166
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• 2002

Initial velocity model close to real velocity structure of the subsurface governs the quality of image of prestack depth migration. Geophysicists employ velocity estimation tools such as velocity analysis (curvature method, coherency inversion), tomography and waveform inversion. We present a reflection tomography that parameterizes the subsurface into the movable blocks. By interpreting the depth-migrated section or stacked section, we can design an initial constant velocity model having only impedance boundaries. We use shooting-raytracing method that allows us to calculate the Jacobian-matrix efficiently.

• Journal of the Korean Solar Energy Society
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• v.25 no.1
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• pp.87-96
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• 2005

본 논문은 압력차로 인한 유체의 유동장에서 서스펜션의 입자 밀도를 분포 규명하기 위해 적용할 수 있는 Electric Impedance Tomography (EIT)의 새로운 기법에 대한 효율성을 다루고 있다. Regularized Newton-Raphson iterative method를 근간으로 inverse problem의 해를 구하는데, 이는 곧 목적 함수(object function)를 몇 가지의 제한조건(constraints) 하에서 최소화시키는 과정이라 할 수 있다. 한편, 관련 forward problem은 유한요소법(FEM)을 이용하여 해결하며, 기존의 연구와는 달리 선형 형상 함수(linear shape function)를 이용하여 전도도가 연속적인 물성치로 유동장에 분포되어 있는 것으로 가정하였다. 여러 경우의 test run에 대한 결과는 본 논문에서 적용한 방법론의 타당성을 보여 주고 있다. 태양에너지의 추출을 위해 직접촉식 열교환기가 종종 이용되고 있는데, 본 연구는 열교환기 내부의 분산 유체에 대한 해석에 일조를 할 수 있을 것으로 기대된다.

• 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.

• 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.

• 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 Biomedical Engineering Research
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• v.25 no.4
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• pp.269-275
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• 2004

Different biological tissues have different values of electrical resistivity. In EIT (electrical impedance tomography), we try to provide cross-sectional images of a resistivity distribution inside an electrically conducting subject such as the human body mainly for functional imaging. However, it is well known that the image reconstruction problem in EIT is ill-posed and the quality of a reconstructed image highly depends on the measurement error. This requires us to develop a high-performance EIT system. In this paper, we describe the development of a 16-channel digital EIT system including a single constant current source, 16 voltmeters, main controller, and PC. The system was designed and implemented using the FPGA-based digital technology. The current source injects 50KHz sinusoidal current with the THD (total harmonic distortion) of 0.0029% and amplitude stability of 0.022%. The single current source and switching circuit reduce the measurement error associated with imperfect matching of multiple current sources at the expense of a reduced data acquisition time. The digital voltmeter measuring the induced boundary voltage consists of a differential amplifier, ADC, and FPGA (field programmable gate array). The digital phase-sensitive demodulation technique was implemented in the voltmeter to maximize the SNR (signal-to-noise ratio). Experimental results of 16-channel digital voltmeters showed the SNR of 90dB. We used the developed EIT system to reconstruct resistivity images of a saline phantom containing banana objects. Based on the results, we suggest future improvements for a 64-channel muff-frequency EIT system for three-dimensional dynamic imaging of bio-impedance distributions inside the human body.

• Communications of the Korean Mathematical Society
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• v.16 no.3
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• pp.459-485
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• 2001

The aim of EIT (electrical impedance tomography) system is to image cross-section conductivity distribution of a human body by means of both generating and sensing electrodes attached on to the surface of the body, where currents are injected and voltages are measured. EIT has been suffered from the severe ill-posedness which is caused by the inherent low sensitivity of boundary measurements to any changes of internal tissue conductivity values. With a limited set of current-to-voltage data, figuring out full structure of the conductivity distribution could be extremely difficult at present time, so it could be worthwhile to extract some necessary partial information of the internal conductivity. We try to extract some key patterns of current-to-voltage data that furnish some core information on the conductivity distribution such s location and size. This overview provides our recent observation on the location search and the size estimation.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.12
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• pp.256-264
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• 2012

The directional algebraic reconstruction technique (DART) using the trigonometric current pattern is one of the image reconstruction algorithms in electrical impedance tomography (EIT). This method needs to compute resistances between electrode pairs as using relation between the injected currents and measured voltages for the reconstruction of the inner image. The delay time is incurred in this process. Therefore this paper proposes modified directional algebraic reconstruction technique (mDART) using the adjacent current pattern instead of the trigonometric current pattern to solve the delay time for initial resistance values. The proposed method uses measured voltages instead of computed resistances in the reconstruction algorithm. Hence this method can eliminate the delay time because it does not use the resistances. In conclusion, the proposed method improves image quality and image reconstruction time by using the adjacent current pattern. To prove performance of the proposed method, we carried on computer simulation of various cases.

• Journal of IKEEE
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• v.18 no.2
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• pp.272-281
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• 2014

In electrical impedance tomography (EIT), modified Newton Raphson (mNR) method is widely used inverse algorithm for static image reconstruction due to its convergence speed and estimation accuracy. The unknown conductivity distribution is estimated iteratively by minimizing a cost functional such that the residual error namely the difference in measured and calculated voltages is reduced. Although, mNR method has good estimation performance, EIT inverse problem still suffers from ill-conditioned and ill-posedness nature. To mitigate the ill-posedness, generally, regularization methods are adopted. The inverse solution is highly dependent on the choice of regularization parameter. In most cases, the regularization parameter has a constant value and is chosen based on experience or trail and error approach. In situations, when the internal distribution changes or with high measurement noise, the solution does not get converged with the use of constant regularization parameter. Therefore, in this paper, in order to improve the image reconstruction performance, we propose a new scheme to determine the regularization parameter. The regularization parameter is computed based on residual error and updated every iteration. The proposed scheme is tested with numerical simulations and laboratory phantom experiments. The results show an improved reconstruction performance when using the proposed regularization scheme as compared to constant regularization scheme.