• KIEE International Transactions on Electrophysics and Applications
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• 제4C권3호
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• pp.123-128
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• 2004

In electrical impedance tomography (EIT), the internal resistivity distribution of the unknown object is computed using the boundary voltage data induced by different current patterns using various reconstruction algorithms. This paper presents a new image reconstruction algorithm based on the genetic algorithm (GA) via a two-step approach for the solution of the EIT inverse problem, in particular for the reconstruction of "static" images. The computer simulation for the 32 channels synthetic data shows that the spatial resolution of reconstructed images in the proposed scheme is improved compared to that of the modified Newton-Raphson algorithm at the expense of an increased computational burden.rden.

• 전기전자학회논문지
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• 제24권4호
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• pp.982-990
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• 2020

Groundwater is essential source of the freshwater. Groundwater is stored in the body of the rocks or sediments, called aquifer. Finding an aquifer is a very important part of the geophysical survey. The best method to find the aquifer is to make a borehole. Single borehole is not a suitable method if the aquifer is not located in the borehole drilled area. To overcome this problem, a cross borehole method is used. Using a cross borehole method, we can estimate aquifer location more precisely. Electrical impedance tomography is use to estimate the aquifer location inside the subsurface using the cross borehole method. Electrodes are placed inside each boreholes and area between these boreholes are analysed. An aquifer is a non-uniform structure with complex shape which can represented by the truncated Fourier series. Deep neural network is evaluated as an inverse problem solver for estimating the aquifer boundary coefficients.

• 전기전자학회논문지
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• 제28권2호
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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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• 제어로봇시스템학회 2005년도 ICCAS
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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.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1998년도 제13차 학술회의논문집
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• pp.85-88
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• 1998

We have developed an eigenvalue method for impedance computed tomography to improve the ill-conditioning problem. We have compared the performance of this method and the balancing method by computer simulations. As a result, it was proved that this method is better than the balancing method very much. It was found that the initial value condition is not so severe to obtain good images.

• 한국정보기술학회논문지
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• 제16권11호
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• pp.35-41
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• 2018

전기 임피던스 단층촬영법 (EIT, electrical impedance tomography)은 비파괴검사의 일종으로 관심영역 외부에 설치된 전극에서 측정된 전압으로부터 내부의 저항률분포를 얻는 기술이다. 그러나 EIT에서 영상복원은 타고난 비선형성 (non-linearity)과 부정치성 (ill-posedness) 때문에 만족할만한 복원결과를 얻기 어렵다. 일반적으로 신경회로망은 비선형 시스템의 입력 및 출력 관계를 효율적으로 모델링 할 수 있다. 이 논문은 다층 신경회로망을 이용하여 원형인 표적의 위치(중심좌표)와 크기(반지름)를 추정하는 방법을 제안한다. 제안한 방법의 성능을 알아보기 위해, 신경회로망을 학습시키고 다양한 컴퓨터 모의실험을 수행하였고 결과로부터 제안한 방법의 만족할만한 추정성능을 확인할 수 있었다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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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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• 제어로봇시스템학회 2004년도 ICCAS
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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.

• 전자공학회논문지
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• 제49권9호
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• pp.293-299
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• 2012

전기 임피던스 단층촬영법은 대상체의 표면에 부착된 전극들을 통해 전류를 주입하고 전압을 측정함으로써, 내부의 도전율 또는 저항률 분포를 추정하고 영상으로 복원하는 비교적 새로운 영상 복원 기법이다. 이 논문에서는 on-line에서 한 번의 연산으로도 표적의 정확한 위치 정보와 복원의 정확도를 향상시킬 수 있는 새로운 역문제 알고리즘을 개발하였다. 그리고 제안한 방법의 복원 성능을 향상시키기 위해 가중 행렬의 고유치로부터 step-length를 계산하였다. 몇 가지 시나리오를 설정하고 모의실험을 통해 제안한 방법의 영상 복원의 성능을 평가하였다.

• 전자공학회논문지
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• 제54권4호
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• pp.91-98
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• 2017

전기 임피던스 단층촬영 기법은 도메인의 표면에 부착된 전극들을 통해 주입된 전류와 측정된 전압 데이터를 기반으로, 미지의 도전율 분포를 복원하는 비파괴 기술이다. 이 논문에서는 전기 임피던스 단층촬영법에서 일반적 Tikhonov 조정을 갖는 역문제를 풀고 도전율 분포를 복원하기 위해 절단된 특이값 분해 기반의 역문제 해법을 제안하였다. 역문제 계산시간을 줄이기 위해 일반 조정행렬을 역행렬 항목에서 분리시키고 절단된 특이값 분해 방법을 적용하였다. 제안한 방법의 성능을 검증하기 위해 모의실험과 팬텀실험을 수행하고 복원결과를 비교하였다.