• 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.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2005년도 추계 학술대회논문집(수송기계편)
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• pp.118-121
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• 2005

The acoustical performance of porous materials is determined by their seven or more macroscopic physical properties. However, it is not easy to measure all these properties in many cases. Furthermore, the measurement is compels engineers to spend much times. The effect of each property on the normal incidence absorption coefficient and normalized surface impedance was studied to estimate the properties of porous materials by numerical method. According to the investigation, Properties of porous materials are divided into several groups and estimated by each group. This paper is focused on the estimation procedure of porous materials by the numerical method.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 하계학술대회 논문집 A
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• pp.156-158
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• 1993

This paper presents several techniques of power spectrum estimation for high impedance fault detection. High impedance faults are those faults with current too low to be reliably cleared by conventional overcurrent protection. So power spectrum estimation is required. AR and MA techniques require optimal order for good performance of power spectrum estimation because these techniques are unstable for order selection. ARMA and Extended techniches are stable for order selection and have very sharp response. So ARMA and Extended Prony techniques are suitable for our purpose.

• 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.

• 한국철도학회논문집
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• 제9권2호
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• pp.237-243
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• 2006

Deicing system is to melt frost or ice freezed in catenary line when the temperature is lower than $0^{\circ}C$ in winter. The principle of deicing system is to melt frost or ice by Joule heat of catenary impedance. The performance of deicing is dependant of deicing current determined by the length of deicing section, deicing impedance and current division ratio of catenary line and messenger line. So, we present technique for estimating deicing current and process for determination of deicing section in the conventional line. Deicing impedance is estimated using Carson-Pollaczek equation, and current division ratio of catenary line and messenger line is estimated using voltage drop, and deicing current is estimated using power system data of deicing system. For the determination of the final deicing section, we verified estimated value comparing with experiment value of deicing impedance and current division ratio of catenary line and messenger line using low voltage experiment. Finally, we verified the validity of estimation technique and process using a simulated test data of real deicing system operation in the Chungju Substation, Chungbuk line.

• 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.

• 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:의공학회지
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• 제26권4호
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• pp.207-214
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• 2005

Breast cancer detection using electrical impedance techniques is based on numerous experimental findings that cancerous tissues have higher electrical conductivity values than normal tissues. Lately, by taking advantage of the structure of current flows underneath a planar probe of array electrodes, a mathematical formula to find lesions from a measured trans­admittance map has been derived. In order to experimentally validate its mathematical analysis and the suggested lesion estimation algorithm, we developed a 256-channel trans-admittance scanner (TAS) for probing anomalies underneath a planar array of electrodes. In this paper, we describe the design and implementation of the TAS. Its performance together with the lesion estimation algorithm was evaluated using saline phantoms. Further studies are proposed to validate the system on human subjects.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2007년도 춘계학술대회논문집
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• pp.344-348
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• 2007

The acoustic liner has been used for the suppression of noise. The impedance characteristics of the acoustic liner are increased by the incident pressure. For the estimation of the acoustic liner on the incident acoustic pressure effect, the modified impedance model is suggested on the basis of the GE impedance prediction model. The modified impedance model is originated from the 3 parameter impedance model, and extended to the incident pressure parameter. The modified model is applied on the simple duct analysis with variant source pressure. Through the computation, it is observed that the fore directivity patterns of the duct are varied by the incident SPL level.

• 대한전기학회논문지:시스템및제어부문D
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• 제52권4호
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• pp.246-251
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• 2003

This paper proposes a new methodology for the estimation of impedance characteristics, which is one of the important issue in the power distribution network design of printed circuit boards. The modeling process of the proposed method divides the power distribution network into uniform segment, and each segment is modeled by distributed RLC transmission lines. Then, for the efficient computation of impedance characteristics in frequency domain. the proposed method uses a model-order reduction method.