• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.7
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• pp.891-897
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• 2013

The power system frequency plays an important role in monitoring and controlling the power system. The frequency can be measured through discrete Fourier transform (DFT) coefficients of its positive fundamental frequency. The accuracy of the frequency estimate is severely affected by noise in the power system signal and the leakage effect of the negative fundamental frequency in DFT. This paper proposes a DFT-based frequency estimation algorithm to cope with the noise as well as the leakage effect. In this algorithm, two suitable digital filters are introduced to reduce efficiently frequency estimate error due to the noise. These filters are designed to use a digital bandpass filter and a second-degree integrator. The effectiveness of the proposed algorithm in reduction of frequency estimate error is verified through simulations on noise, harmonics and frequency deviation.

• The Journal of the Acoustical Society of Korea
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• v.24 no.4E
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• pp.152-157
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• 2005

In this paper, a new data-aided joint phase and frequency estimator, which has very low computational complexity, is proposed and its variances of phase and frequency estimates are derived. To estimate the phase and frequency offset, first of all, the overall observation interval is divided into same length sub-intervals, and then phase estimates are independently computed based on symbols of the each sub-intervals. To be continue the sequence of computed phase estimates, proper integer multiples of $2{\pi}$ are added to (or subtracted from) the computed phase estimates, which is called linearized phase estimate. The phase offset of the proposed joint estimator is estimated by averaging the linearized phase estimates and the frequency offset by averaging the differences between consecutive linearized phase estimates. The variance of the proposed phase offset estimate is same to MCRB of phase if there is no frequency offset, but it is smaller than MCRB of phase if there is frequency offset. However, the variance of the proposed frequency offset estimate is bigger by at least 0.5 dB than MCRB of frequency with the same observation interval.

• Water for future
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• v.25 no.2
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• pp.89-97
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• 1992

This study is to verify the applicability of statistical models for predicting flood frequency at the stage gaging stations selected by considering whether the flow is natural condition in the Han River basin. From the result of verification, this statistical flood frequency models showed that is fairly reasonable to apply in practice, and also were compared with sampling variance to calibrate the statistical dfficiency of the estimate of the T year flood Q(T) by two different flood frequency models. As a result, it was showed that for return periods greater than about T=10 years the annual exceedence series estimate of Q(T) has smaller sampling variance than the annual maximum series estimate. It was showed that for the range of return periods the partial duration series estimate of Q(T) has smaller sampling varianed than the annual maximum series estimate only if the POT model contains at least 2N(N:record length)items or more in order to estimate Q(T) more efficiently than the ANNMAX model.

• The Journal of the Acoustical Society of Korea
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• v.21 no.5
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• pp.446-454
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• 2002

This paper presents the Doppler Scanning technique which enables us to detect the relative positions of moving distributed sources using Doppler frequency shift estimate when the moving source consists of distributed sources with different signature frequencies. Doppler frequency shifts of characteristic frequencies of machinery noise sources such as ship's generator and propeller, with tine along CPA (Closest Point of Approach of moving source) are unique, and can be functioned with respect to each source position. Therefore, this technique can be applied to estimate the relative geometrical positions between machinery noise sources. The Extended Kalman Filter (EKF) which has a high frequency resolution with high time resolution, is adopted for improving accuracy of Doppler frequency shift estimate geometric resolution of machinery positions since machinery noise sources show in general low frequency band characteristics with limited spacial distance. The performance of the technique is examined by the numerical simulations and is verified by the experiment using loudspeaker sources on the roof of the car.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.9
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• pp.521-530
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• 2005

In this paper, a new high resolution reflectometry scheme, time-frequency domain reflectometry(TFDR), isproposed to detect and estimate a fault in a transmission line. Traditional reflectometry methodologies have been achieved either in the time domain or in the frequency domain only. However, the TFDR can jump over the performance limits of the traditional reflectometry methodologies because the acquired signal is analyzed in time and frequency domain simultaneously. In the TFDR, the new reference signal and the novel TFDR algorithm are proposed for analyzing the acquired signal in the time-frequency domain. Because the reference signal of Gaussian envelop chirp signal is localized in the time and frequency domain simultaneously, it is suitable to the analysis in the time-frequency domain. In the proposed TFDR algorithm, the time-frequency distribution function and the normalized time-frequency cross correlation function are used to detect and estimate a fault in a transmission line. That algorithm is verified for real-world coaxial cables which are typical transmission line with different types of faults by the TFDR system composed of real instruments. The performance of the TFDR methodology is compared with that o( the commercial time domain reflectomeoy(TDR) experiments, so that concludes the TFDR methodology can detect and estimate the fault with smaller error than TDR methodology.

• Journal of Electrical Engineering and Technology
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• v.6 no.3
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• pp.319-327
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• 2011

An iterative technique based on orthogonal filters and frequency tracking is proposed to estimate harmonic components in power systems. The technique uses frequency interpolation to estimate fundamental frequency and harmonics when the nominal frequency of the signal is a non-integer value. Due to the number of computations involved during the generation of filter coefficients, an offline computation is suggested. Beneficial features of the proposed technique include fixed sampling rate and fixed data window size. The performance of the proposed technique is examined by simulating different power system operating conditions and evaluating the data from these simulations. A technique based on Fast Fourier Transform is also used to estimate the harmonic components for all the simulated signals. These estimates are compared with those obtained from the proposed technique. Results show that the proposed technique can converge to the accurate fundamental frequency and therefore, provide accurate harmonic components even when the fundamental frequency is not equal to the nominal frequency.

• 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.

• The Mathematical Education
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• v.29 no.2
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• pp.79-93
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• 1990

In this thesis the following studies have been tried: 1. To estimate reliability and validity of the items of scholastic achievment tests that had been tested by the evaluation service centers. 2. To smooth the sample frequency distribution of observed scores and to estimate the frequency distribution of observed scores approximating to the Negative Hypergeometric Distribution.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.5
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• pp.866-874
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• 2008

Motor frequency can be measured by a hall sensor. Among the many hall sensors, a linear type hall sensor is good at high accuracy frequency measuring problem. However, in general, this linear type hall sensor has DC offset which can vary along sensor's operating voltage change. Therefore, In motor frequency measurement problem using the linear hall sensor, it needs an estimator that can estimate frequency and DC offset simultaneously. In this paper, we propose the least mean square estimator to estimate motor frequency. To verify its performance, we compare the LMS estimator with a commercial analog tachometer. Experimental results shows the proposed LMS estimator works well in varying frequency and stationary DC offset.

• Structural Engineering and Mechanics
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• v.64 no.3
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• pp.279-285
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• 2017

Modal expansion technique (MET) is a method to estimate the vibration fields of flexible structures by using eigenmodes of the structure and the signals of sensors. It is the useful method to estimate the vibration fields but has the truncation error since it only uses the limit number of the eigenmodes in the frequency of interest. Even though block-wise MET performed frequency block by block with different valid eigenmodes was developed, it still has the truncation error due to the absence of other eigenmodes. Thus, this paper suggested an improved block-wise modal expansion technique. The technique recovers the truncation errors in one frequency block by utilizing other eigenmodes existed in the other frequency blocks. It was applied for estimating the vibration fields of a cylindrical shell. The estimated results were compared to the vibration fields of the forced vibration analysis by using two indices: the root mean square error and parallelism between two vectors. These indices showed that the estimated vibration fields of the improved block-wise MET more accurately than those of the established METs. Especially, this method was outstanding for frequencies near the natural frequency of the highest eigenmode of each block. In other words, the suggested technique can estimate vibration fields more accurately by recovering the truncation errors of the established METs.