• Proceedings of the Korean Society of Marine Engineers Conference
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• 2005.11a
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• pp.45-46
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• 2005

In this paper, a passive telemetry sensor system using Unscented Kalman Filter(UKF) is proposed. Specially, to show the effective tracking performance of the UKF, we compared with the tracking performance of Recursive Least Square Estimation (RLSE) using linearization.

• KIEE International Transactions on Power Engineering
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• v.5A no.4
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• pp.350-356
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• 2005

Earth equipments are essential to protect humans and other types of equipment from abnormal conditions. Earth resistance and potential must be restricted within a low value. An estimation algorithm of earth parameters and equivalent resistivity is introduced to calculate reliable earth resistance in this research. The proposed algorithm is based on the relationship between apparent resistances and earth parameters. The proposed algorithm, which approximates the non-linear characteristics of earth by using the Artificial Neural Network (ANN), estimates the earth parameters and equivalent resistivity. The effectiveness of the proposed method is verified with case studies.

• Proceedings of the KIEE Conference
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• 2007.04c
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• pp.29-33
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• 2007

In this paper, time-varying parameter of passive telemetry RF sensor system is estimated using RLS(Rescursive $\leq$* Square) algorithm. In order to overcome the problems such as power limits and complication that general RF sensor system including IC chip has, the principle of inductive coupling is applied to model sensor system The model parameter is rearranged for applying RLS algorithm based on mathematical model to the derived model using inductive coupling principle. Time variant parameter of rearranged model is estimated using forgetting factor, and in case measured data is contaminated by noise and modelling error, the performance of RLS algorithm characterized by the convergence of squared error sum is verified by simulation.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.4
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• pp.232-239
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• 1988

The approximate overdetermined method is proposed for high resolution spectral estimation in case of short data record length or narrow band signal. And a new recursive AR parameter estimation is derived in the form of fast algorithm. For ARMA spectral estimation, two stage procedure is used in estimating ARMA parameters. First AR parameters are estimated by using the modified Yule-Walker equations, and then MA parameters are implicitly estimated by estimating numerator spectral(NS) coefficients.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.10
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• pp.1822-1828
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• 2008

This paper presents design parameter calculation methodology and its realization to construction for the 10/350${\mu}s$ lightning impulse current generator(ICG) modelled as double exponential function waveform with characteristic parameters ${\alpha},{\beta}$. Matlab internal function, "fzero" was applied to find ${\lambda}={\alpha}/{\beta}$ which is solution of nonlinear equation linearly related with two wave parameter $T_1$ and $T_2$. The calculation results for 10/350${\mu}s$ lightning impulse current show very good accuracy with error less 0.03%. Two type of 10/350${\mu}s$ ICGs based on the calculated design circuit parameters were fabricated by considering the load variation. One is applicable to the MOV based Surge protective device(SPD) for less 15 kA and the other is to test small resistive devices such as spark gap arrester and bonding device with maximum current capability 30 kA. The tested waveforms show error within 10% in comparison with the designed estimation and the waveform tolerance recommended in the IEC 61643-1 and IEC 60060-1.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.7
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• pp.265-272
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• 2006

This paper describes a method of parameter estimation of time series data using discrete Fourier transform(DFT). DFT have been mainly used to precisely and rapidly obtain the frequency of a signal. In a dynamic system, a real part of a mode used to learn damping characteristics is a more important factor than the frequency of the mode. The parameter estimation method of this paper can directly estimate modes and parameters, indicating the characteristics of a dynamic system, on the basis of the Fourier transform of the time series data. Real part of a mode estimates by subtracting a frequency of the Fourier spectrum corresponding to 0.707 of a magnitude of the peak spectrum from a peak frequency, or subtracting a frequency of the power spectrum corresponding to 0.5 of the peak power spectrum from a peak frequency, or comparing the Fourier(power) spectrum ratio. Also, the residue and phase of time signal calculate by simple equation with the real part of the mode and the power spectrum that have been calculated. Accordingly, the proposed algorithm is advantageous in that it can estimate parameters of the system through a single DFT without repeatedly calculating a DFT, thus shortening the time required to estimate the parameters.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.691-694
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• 1991

In a discrete parameter estimation system, the standard least squares method shows slow convergence. On the other hand, the weighted least squares method has relatively fast convergence. However, if the input is not sufficiently rich, then gain matrix grows unboundedly. In order to solve these problems, this paper proposes a modified least squares algorithm which prevents gain matrix from growing unboundedly and has fast convergence.

• The Journal of the Acoustical Society of Korea
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• v.18 no.1E
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• pp.3-6
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• 1999

In digital mobile communication system, the transmission errors affect the quality of output speech seriously. There are many error concealment techniques using a posteriori probability which provides information about any transmitted parameter. They need knowledge about channel transition probability as well as the 1st order Markov transition probability of codec parameters for estimation of transmitted parameters. However, in applications of mobile communication systems, the channel transition probability varies depending on nonstationary channel characteristics. The mismatch of designed channel transition probability of the estimator to actual channel transition probability degrades the performance of the estimator. In this paper, we proposed a new parameter estimator which adapts to the channel characteristics using short time average of maximum a posteriori probabilities(MAPs). The proposed scheme, when applied to the LSP parameter estimation, performed better than the conventional estimator which do not adapt to the channel characteristics.

• Journal of Electrical Engineering and Technology
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• v.7 no.3
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• pp.304-311
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• 2012

So far, the importance for an accurate load model has been constantly raised and its necessity would be further more emphasized. Currently used load model for analysis of power system in Korea was developed 10 years ago, which is aggregated by applying the statistically estimated load compositions to load models based on individual appliances. As modern appliances have diversified and rapidly changed, the existing load model is no longer compatible with current loads in the Korean power system. Therefore, a measurement based load model is more suitable for modern power system analysis because it can accurately include the load characteristics by directly measuring target load. This paper proposes a ZIP model employing a Kalman-filter as the estimation algorithm for the model parameters. The Kamlan-filter based parameter identification offers an advantage of fast parameter determination by removing iterative calculation. To verify the proposed load model, the four-second-interval real data from the Korea Energy Management System (K-EMS) is used.

• The Transactions of the Korean Institute of Power Electronics
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• v.18 no.3
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• pp.289-295
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• 2013

It is important to know exact values of Interior Permanent Magnet Synchronous Motors(IPMSM)' parameters such as stator resistance and inductance in order to have their high performance. This paper proposes a novel motor parameter(stator resistance, d&q axis inductance) estimation algorithm for IPMSM. The proposed estimation method utilizes back-EMF equations and model reference adaptive system(MRAS). The algorithm using back-EMF estimates d and q axis inductances in the constant torque region, and the stator resistance is estimated by using MRAS with the estimated inductance regardless of speed regions. The validity of the proposed algorithm is verified by simulations and experiments.