• 전자공학회논문지
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• 제54권4호
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• pp.83-90
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• 2017

전기 임피던스 단층촬영법은 전극을 통해 주입된 전류와 측정된 전압을 기반으로, 내부 도전율 분포를 복원하는 기술로, 비교적 새로운 비파괴 영상 복원 기법이다. 본 논문에서는 이원 혼합물 유동 응용분야에서 온라인으로 적용시킬 수 있도록, 역문제의 계산시간을 줄일 뿐만 아니라 공간 해상도도 함께 향상시킬 수 있는 역문제 해법인 빠른 반복적 가우스-뉴턴 방법을 제안하였다. 제안한 방법의 영상 복원성능을 평가하기 위해 모의실험을 수행하고 그 결과를 비교분석하였다.

• 대한의용생체공학회:의공학회지
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• 제30권4호
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• pp.279-287
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• 2009

Magnetic resonance electrical impedance tomography (MREIT) is a new medical imaging modality providing cross-sectional images of a conductivity distribution inside an electrically conducting object. MREIT has rapidly progressed in its theory, algorithm and experimental technique and now reached the stage of in vivo animal and human experiments. Conductivity image reconstructions in MREIT require various steps of carefully implemented numerical computations. To facilitate MREIT research, there is a pressing need for an MREIT software package with an efficient user interface. In this paper, we present an example of such a software, called CoReHA which stands for conductivity reconstructor using harmonic algorithms. It offers various computational tools including preprocessing of MREIT data, identification of boundary geometry, electrode modeling, meshing and implementation of the finite element method. Conductivity image reconstruction methods based on the harmonic $B_z$ algorithm are used to produce cross-sectional conductivity images. After summarizing basics of MREIT theory and experimental method, we describe technical details of each data processing task for conductivity image reconstructions. We pay attention to pitfalls and cautions in their numerical implementations. The presented software will be useful to researchers in the field of MREIT for simulation as well as experimental studies.

• 전기전자학회논문지
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• 제19권3호
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• pp.407-414
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• 2015

전기 임피던스 단층촬영 기법은 대상체 표면의 전극들을 통해 주입시킨 전류 데이터와 이에 유기되는 측정 전압 데이터를 기반으로 내부의 도전율 분포를 가시화하는 기법이다. 이 논문에서는 완전전극 모델을 사용한 해석적 방법의 해법을 유도하고 전압을 계산하였다. 그리고 기존의 수치적 해법인 유한 요소법과 경계 요소법을 사용하여 전압 데이터를 또한 계산하였다. 배경이 균질한 경우와 비균질한 경우에 대해 각 정문제 해법의 해를 실험 데이터 와 비교하였다. 그리고 평균 제곱근 오차를 계산하여 정문제 해법들의 오차를 비교분석하였다.

• 전기전자학회논문지
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• 제25권4호
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• pp.650-663
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• 2021

Subsurface topology estimation is an important factor in the geophysical survey. Electrical impedance tomography is one of the popular methods used for subsurface imaging. The EIT inverse problem is highly nonlinear and ill-posed; therefore, reconstructed conductivity distribution suffers from low spatial resolution. The subsurface region can be approximated as piece-wise separate regions with constant conductivity in each region; therefore, the conductivity estimation problem is transformed to estimate the shape and location of the layer boundary interface. Each layer interface boundary is treated as an open boundary that is described using front points. The subsurface domain contains multi-layers with very complex configurations, and, in such situations, conventional methods such as the modified Newton Raphson method fail to provide the desired solution. Therefore, in this work, we have implemented a 7-layer artificial neural network (ANN) as an inverse problem algorithm to estimate the front points that describe the multi-layer interface boundaries. An ANN model consisting of input, output, and five fully connected hidden layers are trained for interlayer boundary reconstruction using training data that consists of pairs of voltage measurements of the subsurface domain with three-layer configuration and the corresponding front points of interface boundaries. The results from the proposed ANN model are compared with the gravitational search algorithm (GSA) for interlayer boundary estimation, and the results show that ANN is successful in estimating the layer boundaries with good accuracy.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1991년도 춘계학술대회
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• pp.5-7
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• 1991

We have developed an efficient and robust image reconstruction algorithm for static impedance imaging. This improved Newton-Raphson method produced more accurate images by reducing the undesirable effects of the ill-conditioned Hessian matrix. We found that our electrical impedance tomography (EIT) system could produce two-dimensional static images from a physical phantom with 7% spatial resolution at the center and 5% at the periphery. Static EIT image reconstruction requires a large amount of computation. In order to overcome the limitations on reducing the computation time by algorithmic approaches, we implemented the improved Newton-Raphson algorithm on a parallel computer system and showed that the parallel computation could reduce the computation time from hours to minutes.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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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.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2008년도 춘계학술대회논문집
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• pp.576-579
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• 2008

Electrical impedance(EIT) for the multi-phase flow visualization is an imaging modality in which the resistivity distribution of the unknown object is estimated based on the known sets of injected currents and measured voltages on the surface of the object. In this paper, an EIT reconstruction algorithm based on the extended Kalman filter(EKF) is proposed. The EIT reconstruction problem is formulated as a dynamic model which is composed of the state equation and the observation equation, and the unknown resistivity distribution is estimated recursively with the aid of the EKF. To verify the reconstruction performance of the proposed algorithm, experiments with simulated multi-phase flow are performed.

• 대한전기학회논문지:시스템및제어부문D
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• 제52권2호
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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.

• Smart Structures and Systems
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• 제30권5호
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• pp.463-477
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• 2022

In this paper, a hybrid vibration-impedance-based damage monitoring approach is experimentally evaluated for prestressed concrete (PSC) structures with local strand breakage. Firstly, the hybrid monitoring scheme is designed to alert damage occurrence from changes in vibration characteristics and to localize strand breakage from changes in impedance signatures. Secondly, a full-scale PSC anchorage is experimented to measure global vibration responses and local impedance responses under a sequence of simulated strand-breakage events. Finally, the measured data are analyzed using the hybrid monitoring framework. The change of structural condition (i.e., damage extent) induced by the local strand breakage is estimated by changes in a few natural frequencies obtained from a few accelerometers in the structure. The damaged strand is locally identified by tomography analysis of impedance features measured via an array of PZT (lead-zirconate-titanate) sensors mounted on the anchorage. Experimental results demonstrate that the strand breakage in the PSC structure can be accurately assessed by using the combined vibration and impedance features.

• Smart Structures and Systems
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• 제8권1호
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• pp.139-155
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• 2011

Polymeric thin-film assemblies whose bulk electrical conductivity and mechanical performance have been enhanced by single-walled carbon nanotubes are proposed for measuring strain and corrosion activity in metallic structural systems. Similar to the dermatological system found in animals, the proposed self-sensing thin-film assembly supports spatial strain and pH sensing via localized changes in electrical conductivity. Specifically, electrical impedance tomography (EIT) is used to create detailed mappings of film conductivity over its complete surface area using electrical measurements taken at the film boundary. While EIT is a powerful means of mapping the sensing skin's spatial response, it requires a data acquisition system capable of taking electrical impedance measurements on a large number of electrodes. A low-cost wireless impedance analyzer is proposed to fully automate EIT data acquisition. The key attribute of the device is a flexible sinusoidal waveform generator capable of generating regulated current signals with frequencies from near-DC to 20 MHz. Furthermore, a multiplexed sensing interface offers 32 addressable channels from which voltage measurements can be made. A wireless interface is included to eliminate the cumbersome wiring often required for data acquisition in a structure. The functionality of the wireless impedance analyzer is illustrated on an experimental setup with the system used for automated acquisition of electrical impedance measurements taken on the boundary of a bio-inspired sensing skin recently proposed for structural health monitoring.