• Journal of Power Electronics
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• 제16권6호
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• pp.2150-2161
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• 2016

Mechanical and electrical parameter uncertainties cause dynamic and static estimation errors of the rotor speed and position, resulting in performance deterioration of sensorless control systems. This paper applies an extended nonlinear observer to interior permanent magnet synchronous motors (IPMSM) for the simultaneous estimation of the rotor speed and position. Two compensation methods are proposed to improve the observer performance against parameter uncertainties: an on-line rotational inertia adjustment approach that employs the gradient descent algorithm to suppress dynamic estimation errors, and an equivalent flux error compensation approach to eliminate static estimation errors caused by inaccurate electrical parameters. The effectiveness of the proposed control strategy is demonstrated by experimental tests.

• Journal of Electrical Engineering and Technology
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• 제9권2호
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• pp.600-608
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• 2014

This paper presents estimation of d-axis and q-axis inductance of an interior permanent magnet synchronous motor (IPMSM) by using an extended Kalman filter (EKF). The EKF is widely used for control applications including the motor sensorless control and parameter estimation. The motor parameters can be changed by temperature and air-gap flux. In particular, the variation of the inductance affects torque characteristics like the maximum torque per ampere (MTPA) control. Therefore, by estimating the parameters, it is possible to improve the torque characteristics of the motor. The performance of the proposed estimator is verified by simulations and experimental results based on an 11kW PMSM drive system.

• Journal of Electrical Engineering and Technology
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• 제10권3호
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• pp.1144-1153
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• 2015

The resonant mechanism of reradiation interference (RRI) over 1.7MHz from power transmission lines cannot be obtained from IEEE standards, which are based on researches of field intensity. Hence, the resonance is ignored in National Standards of protecting distance between UHV power lines and radio stations in China, which would result in an excessive redundancy of protecting distance. Therefore, based on the generalized resonance theory, we proposed the idea of applying model-based parameter estimation (MBPE) to estimate the generalized resonance frequency of electrically large scattering objects. We also deduced equation expressions of the generalized resonance frequency and its quality factor Q in a lossy open electromagnetic system, i.e. an antenna-transmission line system in this paper. Taking the frequency band studied by IEEE and the frequency band over 1.7 MHz as object, we established three models of the RRI from transmission lines, namely the simplified line model, the tower line model considering cross arms and the line-surface mixed model. With the models, we calculated the scattering field of sampling points with equal intervals using method of moments, and then inferred expressions of Padé rational function. After calculating the zero-pole points of the Padé rational function, we eventually got the estimation of the RRI’s generalized resonant frequency. Our case studies indicate that the proposed estimation method is effective for predicting the generalized resonant frequency of RRI in medium frequency (MF, 0.3~3 MHz) band over 1.7 MHz, which expands the frequency band studied by IEEE.

• 한국철도학회논문집
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• 제19권3호
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• pp.314-323
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• 2016

직류 전철변전소의 가선전압은 전동차들의 회생제동 및 역행가속패턴에 따라 급격히 상승 또는 하강하는 특성을 갖는다. 가선전압 순시 변동폭을 최소로 유지함으로써, 전철변전소와 전동차들의 에너지 효율을 개선시키기 위한 다양한 연구들이 이루어지고 있다. 본 논문은 직류전철 변전소의 가선전압의 급격한 변동특성을 모델링하고 선형인공 신경망 알고리즘을 이용한 가선전압 회로모델의 파라메터 추정 방법을 제안하며, 최소자승법을 이용한 추정방법과의 비교를 통해 이 방법의 타당성을 입증한다. 가선전압 및 피더전류들의 누적 측정값을 사용하여 일괄처리 최소자승법으로 RC 병렬회로의 파라메터들을 추정한 결과를 제시하며, 실시간 가선전압 및 피더전류 측정값을 이용하여 오차역 전파방식으로 학습되는 선형인공신경망 기법 추정 결과를 분석한다.

• 대한전기학회논문지:전력기술부문A
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• 제51권4호
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• pp.163-168
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• 2002

This paper present a new verb efficient numerical algorithm for arcing faults detection and fault distance estimation in transmission line. It is based on the fundamental differential equations describing the transients on a transmission line before, during and alter the fault occurrence, and on the application of the "Least Error Squares Technique"for the unknown model parameter estimation. If the arc voltage estimated is a near zero, the fault is without arc, in other words the fault is permanent fault. If the arc voltage estimated has any high value, the faust is identified as an fault, or the transient fault. In permanent faults case, fault distance estimation is necessary. This paper uses the model of the arcing fault in transmission line using ZnO arrestor and resistance to be implemented within EMTP. One purpose of this study is to build a structure for modeling of arcing fault detection and fault distance estimation algorithm using Matlab programming. In this paper, This algorithm has been designed in Graphic user interface(GUI).

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제53권5호
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• pp.332-337
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• 2004

A number of techniques have been developed for estimation of speed or position in motor drives. The accuracy of these techniques is affected by the variation of motor parameters such as the stator resistance, stator inductance or torque constant. This paper is proposed a neural network based estimator for torque and stator resistance in IPMSM Drives. The neural weights are initially chosen randomly and a model reference algorithm adjusts those weights to give the optimum estimations. The neural network estimator is able to track the varying. parameters quite accurately at different speeds with consistent performance. The neural network parameter estimator has been applied to slot and flux linkage torque ripple minimization of the IPMSM. The validity of the proposed parameter estimator is confirmed by the operating characteristics controlled by neural networks control.

• 제어로봇시스템학회논문지
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• 제13권5호
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• pp.429-433
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• 2007

A number of techniques have been developed for estimation of speed or position in motor drives. The accuracy of these techniques is affected by the variation of motor parameters such as the stator resistance, stator inductance or torque constant. This paper is proposed a neural network based estimator for torque and ststor resistance in IPMSM Drives. The neural weights are initially chosen randomly and a model reference algorithm adjusts those weights to give the optimum estimations. The neural network estimator is able to track the varying parameters quite accurately at different speeds with consistent performance. The neural network parameter estimator has been applied to slot and flux linkage torque ripple minimization of the IPMSM. The validity of the proposed parameter estimator is confirmed by the operating characteristics controlled by neural networks control.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 심포지엄 논문집 정보 및 제어부문
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• pp.207-209
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• 2006

A number of techniques have been developed for estimation of speed or position in motor drives. The accuracy of these techniques is affected by the variation of motor parameters such as the stator resistance, stator inductance or torque constant. This paper is proposed a neural network based estimator for torque and ststor resistance in IPMSM Drives. The neural weights are initially chosen randomly and a model reference algorithm adjusts those weights to give the optimum estimations. The neural network estimator is able to track the varying parameters quite accurately at different speeds with consistent performance. The neural network parameter estimator has been applied to slot and flux linkage torque ripple minimization of the IPMSM. The validity of the proposed parameter estimator is confirmed by the operating characteristics controlled by neural networks control.

• 한국통신학회논문지
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• 제34권8C호
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• pp.814-821
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• 2009

초광대역 방식의 실내 무선 위치인식 추정에서 비 가시거리 환경으로 인한 불규칙한 신호 도착시간 또는 클러스터화 된 다중경로 성분들의 겹침으로 인해, 도착시간 매개변수 추정 기법들은 합리적인 도착시간 (TOA) 매개변수를 얻는데 어려움을 가진다. 이 문제를 극복하고 우수한 성능의 초광대역 실내 우선 위치인식 추정을 달성하기 위해 종래 추정 기법과 다르고 클리스터 문제에 영향을 거이 받지 않는 강인한 TOA 매개변수 추정 기법과 초광대역 신호 모형을 제안한다. 컴퓨터 모의실험을 통해 제안 모형과 추정기법의 타당성을 검증하고 추정오차의 성능도 분석한다.

• 한국정밀공학회지
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• 제16권12호
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• pp.143-151
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• 1999

The shape of surface micro-crack is very irregular due to nonhomogeneous microstructure but is very important in respect to qualitative estimation of fatigue life. Fractal geomety can quantify the shape of surface mciro-crack. Fractal dimension is measured for surface micro-cracks with coast line and box counting method and estimates cycle ration in Al 2024-T3. The average fractal dimension $D_{favg}$ of surface micro-cracks has 3-parameter weibull distribution and location parameter is nearly constant but shape parameter decreases as cycle ration increases. The fractal dimension by coast line method is measured for individual surface micro-crack but the fractal dimension by box countin method is measured for all the surface micro-cracks under sampling area. Therefore, This paper shows fractal dimension $D_{fb}$ can predict cycle ratio $N/N_f$ more convenient than fractal dimension $D_{favg}$.