• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.1
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• pp.61-67
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• 2018

The effects of subsurface inhomogeneities on the detection of buried metal pipes in ground-penetrating radar(GPR) signals are investigated numerically. To model the electrical properties of the subsurface inhomogeneities, the continuous random media(CRM) generation technique is introduced. For the electromagnetic simulation of GPR signals, the finite-difference time-domain(FDTD) method is implemented. As a function of the standard deviation and the correlation length of the relative permittivity distribution for a randomly inhomogeneous ground, the GPR signals of the buried metal pipes are compared using numerical simulations. As the subsurface inhomogeneities increase, the GPR signals of the buried pipes are distorted because of the effect of the subsurface clutter.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.7
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• pp.1255-1262
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• 2009

The present study explained the phenomenon that low frequency oscillation is synchronized with discrete data obtained from a wide area system, and a sync search method. When a disturbance occurs in an power system, various controllers operate in order to maintain synchronization. If the system's damping is poor, low frequency oscillations continue for a long time and the oscillations are synchronized with one another at specific frequency. The present study estimated dominant modes, magnitude and phase of signals by applying parameter estimation methods to discrete signals obtained from an power system, and performed sync search among wide area signals by comparing the estimated data. Sync search was performed by selecting those with the same frequency and damping constant from dominant oscillation modes included in a large number of signals, and comparing their magnitude and phase. In addition, we defined sync indexes in order to indicate the degree of sync between areas in a wide area system. Furthermore, we proposed a wide area sync search method by normalizing mode magnitude in discrete data obtained from critical generator of the wide area. By applying the sync search method and sync indexes proposed in this study to two area systems, we demonstrated that sync scanning can be performed for discrete signals obtained from power systems.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.49 no.1
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• pp.44-51
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• 2000

In this paper, using a wide-band AE sensor with the frequency range from 100[kHz] to 1.5[kHz], the frequency spectra of AE signals generated from the corona discharges of the needle-plane gap and from the partial discharges of an epoxy void were analyzed to determine the proper ultrasonic sensor with optimum frequency range according to the patterns of corona discharges. We also examined the propagation characteristics of AE signals in oil and the relationship between the magnitude of corona discharge and the magnitude of AE signals in peak-to-peak value under the application of 60[Hz] ac high-voltage. From these results, the main frequency spectra of AE signals emitted from the corona discharges of the needle-plane gap were about 130[kHz] by the fast fourier transform, but the main frequency spectra appeared to be 230[kHz] in the partial discharges of an epoxy void. The magnitude of AE signals was proportional to the magnitude of corona discharge and discharge current pulse with increasing the applied voltages.

• ETRI Journal
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• v.42 no.3
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• pp.324-332
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• 2020

In this paper, a blind symbol timing offset (STO) estimation method is proposed for offset quadrature phase-shift keying (OQPSK) modulated signals, which also works for other linearly modulated signals (LMS) such as binary-PSK, QPSK, 𝜋/4-QPSK, and minimum-shift keying. There are various methods available for blind STO estimation of LMS; however, none work in the case of OQPSK modulated signals. The popular cyclic correlation method fails to estimate STO for OQPSK signals, as the offset present between the in-phase (I) and quadrature (Q) components causes the cyclic peak to disappear at the symbol rate frequency. In the proposed method, a set of close and approximate offsets is used to compensate the offset between the I and Q components of the received OQPSK signal. The STO in the time domain is represented as a phase in the cyclic frequency domain. The STO is therefore calculated by obtaining the phase of the cyclic peak at the symbol rate frequency. The method is validated through extensive theoretical study, simulation, and testbed implementation. The proposed estimation method exhibits robust performance in the presence of unknown carrier phase offset and frequency offset.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.8
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• pp.924-931
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• 1999

Most conventional protection relays are based on processing information in the spectrum that is close to or at power frequency. It is, however, widely known that faults on transmission lines produce frequency components of a wide range. High frequency signals caused by sudden changes in system voltage that occurs in the immediate post-fault period are generally outside the bandwidth of receptibility of most protection scheme. In this respect, a specially designed stack tuner is connected to the coupling capacitor of CVT, in order to capture the high frequency signals. Digital signal processing is then applied to the captured information to determine whether the fault is inside or outside the protected zone, and to discriminate the fault type. In this paper, modal transform is not applied to fault generated signals, because signals which are converted by modal transform are not have an information of each phase any longer. Instead, using peak voltage value of data windows is able to discriminate fault type. The paper concludes by presenting fault detection and discrimination of various faults on transmission line which are based on extensive simulation studies carried out on a typical 154kV Korean transmission line, using the EMTP software.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.12 no.4
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• pp.136-145
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• 1998

This paper describes the FFT and coefficient analysis of vibration signals for preventive diagnosis of a mold transformer at normal and abnormal state. Varying applied voltage, loading current and temperature as control variables for he experiment, measurement variables such as magnitude of vibration signals, frequency spectrum and time series coefficient were analyzed. The vibration signals by variation of control variables were measured by acceleration sensor adhered on the surface of winding and core, and measurement variables were calculated using dat acquisition system. After analyzing the normal state, the structural distortion was also simulated. The vibration signals at abnormal state were measured by the same control variables variation as the normal state. As a result, vibration signals between normal and abnormal state could be distinguished by comparison of the perpendicular and horizontal vibration signal.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.4
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• pp.805-810
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• 2011

This paper deals with the method and algorithm used to find fault locations in gas insulated transmission line. The method uses UHF sensors and digital oscilloscope to detect discharge signals emitted to the outside through insulating spacer in the event of breakdown inside GIL. UHF sensors are the external type and installed at outside of insulating spacers of GIL. And we used wavelet signal processing to analyze the discharge signals and confirm the exact fault location findings in the GIL test line. This method can overcome demerit of TDR(Time Domain Reflectometer) method having been applied to detect fault location for conventional underground transmission lines, and Ground Fault Sensors used in conventional GIS systems. TDR method requires high level of specialty and experience in analyzing the measured signals. Ground fault sensors are installed inside GIL and can be destroyed by high transient voltage. This paper's method can simplify the fault location process and minimize the damage of sensors. In addition, this method can estimate the fault location only by the time difference when discharge signals are arrived to detecting sensors at the ends of GIL sections without reasons of breakdown. To test the performance of our method, we installed sensors at the ends of test line of GIL(84m) and sensed discharge signals occurred in GIL, energized with AC voltage generator up to 700kV.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.4
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• pp.729-734
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• 2008

Vibroarthrographic(VAG) signals, emitted by human knee joints, are non-stationary and multi-component in nature and time-frequency distributions(TFD) provide powerful means to analyze such signals. The objective of this paper is to classify VAG signals, generated during joint movement, into two groups(normal and patient group) using the characteristic parameters extracted by time-frequency transform, and to evaluate the classification accuracy. Noise within TFD was reduced by singular value decomposition and back-propagation neural network(BPNN) was used for classifying VAG signals. The characteristic parameters consist of the energy parameter, energy spread parameter, frequency parameter, frequency spread parameter by Wigner-Ville distribution and the amplitude of frequency distribution, the mean and the median frequency by fast Fourier transform. Totally 1408 segments(normal 1031, patient 377) were used for training and evaluating BPNN. As a result, the average value of the classification accuracy was 92.3(standard deviation ${\pm}0.9$)%. The proposed method was independent of clinical information, and showed good potential for non-invasive diagnosis and monitoring of joint disorders such as osteoarthritis and chondromalacia patella.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2000.07a
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• pp.585-591
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• 2000

The wavelet transform is the most recent technique for processing signals with time-varying spectra. In this paper, the wavelet transform is utilized to improved the assessment and multi-resolution analysis of acoustic emission signals generating in partial discharge. This paper especially deals with the assessment of process statistical parameter using the features extracted from the wavelet coefficients of measured acoustic emission signals in case of applied voltage 20[kv]. Since the parameter assessment using all wavelet coefficients will often turn out leads to inefficient or inaccurate results, we selected that level-3 stage of multi decomposition in discrete wavelet transform. We applied FIR(Finite Impulse Response)digital filter algorithm in discrete to suppression for random noise. The white noise be included high frequency component denoised as decomposition of discrete wavelet transform level-3. We make use of the feature extraction parameter namely, maximum value of acoustic emission signal, average value, dispersion, skewness, kurtosis, etc. The effectiveness of this new method has been verified on ability a diagnosis transformer go through feature extraction in stage of acting(the early period, the last period) .

• Journal of Electrical Engineering and Technology
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• v.2 no.4
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• pp.505-512
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• 2007

The object of this paper is to study a new control structure for sensorless induction machines dedicated to electrical drives using a three-level voltage source inverter VSI-NPC. The amplitude and the rotating speed of the flux vector can be controlled freely. The scheme investigated is an Enhanced direct torque control "EDTC" for electric vehicle propulsion. The considered application imposes some constraints which are achieved in EDTC control (fast torque response, optimal switching logic, torque control at zero speed, and large speed control. The results obtained for an induction motor indicate superior performance over the FOC type without need for any mechanical sensor.