• Journal of Electrical Engineering and Technology
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• v.6 no.5
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• pp.658-665
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• 2011

In the present paper, a novel fast peak detector for single- or three-phase unsymmetrical voltage sags is proposed. The proposed detector is modified from a single-phase digital phase-locked loop based on a d-q transformation using an all-pass filter (APF). APF generates a virtual phase with $90^{\circ}$ phase delay. However, this virtual phase cannot reflect a sudden change of the grid voltage in the moment of voltage sag, which causes a peak value to be significantly distorted and to settle down slowly. Specifically, the settling time of the peak value is too long when voltage sag occurs around a zero crossing, such as phase $0^{\circ}$ and $180^{\circ}$. This paper describes the operating principle of the APF problem and proposes a modified all-pass filter (MAPF) to mitigate the inherent APF problem. In addition, a new fast peak detector using MAPF is proposed. The proposed detector is able to calculate a peak value within 0.5 ms, even when voltage sag occurs around zero crossing. The proposed fast peak detector is compared with the conventional detector using APF. Results show that the proposed detector has faster detection time in the whole phase range. Furthermore, the proposed fast peak detector can be effectively applied to unsymmetrical three-phase voltage sags. Simulation and experimental results verify the advantages of the proposed detector and MAPF.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.2199-2200
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• 2006

Reliable frequency estimation is important for active power control, load shedding and generator protection. Thereby, frequency estimation is researched and some algorithms is proposed. This paper analyzed strength and weakness of each algorithms through comparative analysis of frequency estimation. Used algorithms are Zero Crossing detection, Discrete Fourier Transformation, Least Error Squares.

• Proceedings of the KIEE Conference
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• 2006.07a
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• pp.567-568
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• 2006

Reliable frequency estimation is important for active power control, load shedding and generator protection. Thereby, frequency estimation is researched and some algorithms is proposed. This paper analyzed strength and weakness of each algorithms through comparative analysis of frequency estimation. Used algorithms are Zero Crossing detection, Discrete Fourier Transformation, Least Error Squares.

• Journal of information and communication convergence engineering
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• v.7 no.4
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• pp.545-550
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• 2009

A method fully utilizing multiscale line filter responses is presented to estimate the point spread function(PSF) of a CT scanner and diameters of small tubular structures based on the PSF. The estimation problem is formulated as a least square fitting of a sequence of multiscale responses obtained at each medical axis point to the precomputed multiscale response curve for the ideal line model. The method was validated through phantom experiments and demonstrated through phantom experiments and demonstrated to accurately measure small-diameter structures which are significantly overestimated by conventional methods based on the full width half maximum(FWHM) and zero-crossing edge detection.

• Proceedings of the KIEE Conference
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• 2006.07b
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• pp.1233-1234
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• 2006

Reliable frequency estimation is important for active power control, load shedding and generator protection. Thereby, frequency estimation is researched and some algorithms is proposed. This paper analyzed strength and weakness of each algorithms through comparative analysis of frequency estimation. Used algorithms are Zero Crossing detection, Discrete Fourier Transformation, Least Error Squares.

• Proceedings of the KIEE Conference
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• 2006.07c
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• pp.1693-1694
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• 2006

Reliable frequency estimation is important for active power control, load shedding and generator protection. Thereby, frequency estimation is researched and some algorithms is proposed. This paper analyzed strength and weakness of each algorithms through comparative analysis of frequency estimation. Used algorithms are Zero Crossing detection, Discrete Fourier Transformation, Least Error Squares.

• The Transactions of the Korea Information Processing Society
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• v.7 no.7
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• pp.2238-2245
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• 2000

In this papr, eatue parameters, extracted using Wavelet transform for Korean isolated worked speech, are sued for speech detection and recognition feature. As a result of the speech detection, it is shown that it produces more exact detection result than eh method of using energy and zero-crossing rate on speech boundary. Also, as a result of the method with which the feature parameter of MFCC, which is applied to he recognition, it is shown that the result is equal to the result of the feature parameter of MFCC using FFT in speech recognition. So, it has been verified the usefulness of feature parameters using Wavelet transform for speech analysis and recognition.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1360-1363
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• 1996

EPD(End Point Detection) is used to decide etching degree of layer which must be removed at wafer etching process in plasma etching process which is one of the most important process in semiconductor manufacturing. In this thesis, the method which detects malfunction of etching process in real-time will be discussed. Several EPD signal traces are collected in normal plasma etching condition and used as reference EPD signal traces. Critical points can be detected by applying differentiation and zero-crossing techniques to reference EPD signal. Mean and standard deviation of critical parameters which is memorized from reference EPD signal are calculated and these determine the lower and higher limit of control chart. And by applying statical control chart to EPD signals which are collected in real etching process malfunctions of process are detected in real-time. By means of applying this method to the real etching process we prove our method can accurately detect the malfunction of etching process and can compensate disadvantage of current industrial method.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.10
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• pp.910-916
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• 2015

A sensorless motor control scheme with conventional back-Electro Motive Force (EMF) sensing based on zero crossing point (ZCP) detection has been widely used in various applications. However, there are several problems with the conventional method for effectively driving sensorless brushless motors. For example, a phase mismatch of 30 degrees occurs between the ZCP and commutation time. Additionally, most of the motor speed/current controls are achieved based on a pulse width modulation (PWM) method, which generates significant noise that distracts the back-EMF sensing. Due to the PWM switching, the ZCP is not deterministic, and thus the efficiency of the motor is reduced because the phase transition points become uncertain. Moreover, the motor driving performance is degraded at a low speed range due to the effect of PWM noise. To solve these problems, an improved back-EMF detection method based on a differential line method is proposed in this paper. In addition, the proposed sensorless BLDC driver addresses the problems by using a variable voltage driver generated from a buck converter. The variable voltage driver does not generate the PWM switching noise. Consequently, the proposed sensorless motor driver improves 1) the signal-to-noise ratio of back-EMF, 2) the operation range of a BLDC motor, and 3) the torque characteristics. The proposed sensorless motor driver is verified through simulations and experiments.

• The Journal of the Acoustical Society of Korea
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• v.36 no.1
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• pp.30-38
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• 2017

In this paper, we propose an underwater acoustic sensor fault detection method for passive sonar systems. In general, a passive sonar system displays processed results of array signals obtained from tens of the acoustic sensors as a two-dimensional image such as displays for broadband or narrowband analysis. Since detection result display in the operation software is to display the accumulated result through the array signal processing, it is difficult to determine the possibility where signal may be contaminated by the fault or failure of a single channel sensor. In this paper, accordingly, we propose a detection method based on the analysis of RMSCR (Root Mean Square Crossing-Rate), and the processing techniques for the faulty sensors are analyzed. In order to evaluate the performance of the proposed method, the precision of detecting fault sensors is measured by using signals acquired from real array being operated in several coastal areas. Besides, we compare performance of fault processing techniques. From the experiments, it is shown that the proposed method works well in underwater environments with high average RMS, and mute (set to zero) shows the best performance with regard to fault processing techniques.