• Proceedings of the KIEE Conference
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• 2000.07c
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• pp.1936-1938
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• 2000

In this paper, a frequency spectra of AE (acoustic emission) signals detected from the partial discharges of an epoxy resin void and a cast resin transformer in operating were analyzed to offer the proper frequency range of AE signals from the corona discharge for the purpose of AE sensor selection, From these results, a frequency spectra of AE signals emitted from the corona discharges in the void of an epoxy resin sample were about 190[kHz] to 220[kHz] by the FFT(fast fourier transform), A frequency spectra of AE signals emitted from a cast. resin transformer with non-load were appeared to be downward of about 140[kHz] by the FFT, and then a frequency spectra of AE signals emitted from the above of cast resin transformer with load were appeared to increase from about 190[kHz] to 220[kHz] by the FFT.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.34 no.2
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• pp.136-141
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• 2021

Heating cables, widely used in office buildings, factories, streets and railways, deteriorate in electrical insulation during operation. The insulation deterioration of heating cables leads to electric discharges that can cause electrical fires. With this background, this paper dealt with a condition monitoring technique for heating cables by the analysis of discharge signals to prevent electrical fires. Insulation deterioration was simulated using an arc generator specified in UL1699 under AC operation, and the characteristic and propagation of discharge signals were analyzed on a 100 meter-long heating cable. Discharge signals produced by insulation deterioration were detected as a voltage pulse because they are as small as a few mV and they are attenuated through propagation path. The frequency spectrum of discharge signals mainly existed in the range from 70 kHz to 110 kHz, and the maximum attenuation of the signal was 84.8% at 100 meters away from the discharge point. Based on the experimental results, a monitoring device, which is composed of a high pass filter with the cut-off frequency of 70 kHz, a comparator, a wave shaper and a microprocessor, was designed and fabricated. Also, an algorithm was designed to discriminate the discharge signal in the presence of noise, compared with the pulse repetition period and the number of pulse counts per 100ms. In the experiment, the result showed that the prototype monitoring device could detect and discriminate the discharge signals produced at every discharge point on a heating cable.

• Journal of Electrical Engineering and Technology
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• v.8 no.6
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• pp.1468-1473
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• 2013

This paper dealt with the propagation characteristics of acoustic signals produced by partial discharges and the positioning of PD origin in insulation oil to develop insulation diagnostic techniques of oil-immerged transformers. Electrode systems such as needle to plane, plane to plane, and particle electrodes were fabricated to simulate some defects of power transformers. In addition, the frequency spectrum and propagation characteristics of acoustic signals with partial discharge (PD) in insulation oil were analyzed. Although there were differences based on the type of defect, the frequency spectra of the acoustic signals measured by wide and narrow band acoustic emission (AE) sensors were distributed in the range of 50 kHz-400 kHz. Therefore, a narrowband AE sensor is suitable for the diagnosis of oil-immersed power transformers. We could find the position of the PD source with an error margin of 10% in the experiments by calculating the position of the PD occurrence using the time difference of arrival measured by five AE sensors.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2000.11a
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• pp.246-250
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• 2000

In this paper, Frequency spectra of AE(acoustic emission) signals generated from the magnetizing and the load currents in the actual operating cast-resin power transformer of 500[kVA] under distribution system of22.9[kV] were also analysed to distinguish the AE signals due to void discharges from the magnetic circuit noises in the core of cast-resin power transformer. As the experimental results, we could distinguish the AE signals whether those signals were caused due to the void discharges or due to the magnetic circuit noises by analyzing the frequency spectrum of AE signals. Frequency spectra of AE signals generated from the cast-resin power transformer in operation due to both the magnetizing and the load currents appeared in the range of 40-120[khz].

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.5
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• pp.643-649
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• 1999

In this paper, we proposed that ｉ) noise-tolerant four kinds of AM(Amplitude Modulation)-FM(Frequency Modulation) demodulators are designed, ⅱ) we derived undersampling frequency through the product via energy operator of the monocomponent AM-FM signals separated form two-component AM-FM signals, and ⅲ) these four kinds of AM-FM demodulators detect respectively information signals of the IA(Instantaneous Amplitude) and IF(Instantaneous Frequency) by undersampling frequency to be different each other from the undersampled monocomponet AM-FM signals. Particularly, the proposed algorithm can control undersampling frequency by an integer factor. And these efficient AM-FM demodulators are well worked with the undersampled AM-FM signals.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.8
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• pp.1454-1463
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• 2008

Blind source separation by independent component analysis (ICA) has applied in signal processing, telecommunication, and image processing to recover unknown original source signals from mutually independent observation signals. Neural networks are learned to estimate the original signals by unsupervised learning algorithm. Because the outputs of the neural networks which yield original source signals are mutually independent, then mutual information is zero. This is equivalent to minimizing the Kullback-Leibler convergence between probability density function and the corresponding factorial distribution of the output in neural networks. In this paper, we present a learning algorithm using information theory and higher order statistics to solve problem of blind source separation. For computer simulation two deterministic signals and a Gaussian noise are used as original source signals. We also test the proposed algorithm by applying it to several discrete images.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.59 no.4
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• pp.440-443
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• 2010

This paper deals with the method of vibration measurement of a gun barrel structure using mechanical filter. When a bullet with high speed is moving within a gun barrel type structure with low bending vibration frequencies, it is difficult to measure the bending vibration signals of the structure. For example, noncontact type sensors such as displacement or velocity sensor are not appropriate for the measurement of vibrational signals because of the movement effect of the equipment frame through the moving structures or effect of the ground vibration. One of contact type sensors such as accelerometer is profitable for measurement of vibrational signals because of its wide measurement ranges. In the case of a gun barrel structure including high vibrational signals like shock waves, however, it is necessary to propose vibration measurement method filtering high frequencies. The purpose of the paper is to propose the proper vibrational measurement technique filtering high frequencies of a gun barrel type structure.

• Proceedings of the KIEE Conference
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• 1997.07e
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• pp.1847-1849
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• 1997

This paper describes the analysis of vibration signals of distorted mold transformer. For experiment, the acceleration sensors were adhered on the surface of winding and on the core. The vibration signals measured as variation of control variables were analyzed using data acquisition system. It was shown that the vibration signals of distorted mold transformer were distinguished from those of normal mold transformer.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2622-2624
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• 2001

In this thesis, speaker separation is employed when speech from two talkers has been summed into one signal and it is desirable to recover one or both of the speech signals from the composite signal. This paper proposed the method that separated the summed speeches and proved the similarity between the signals by the cross correlation between the signals for exact between original signal and separated signal. This paper uses frequency sampling method based on sinusoidal model to separate the composite signal with vocalic speech and vocalic speech and noise masking method based on psycoacoustics model to separate the composite signal with vocalic speech and nonvocalic speech.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.4
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• pp.319-325
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• 2020

In order to propose new satellite navigation signals, it is essential to analyze the increased level of interference effect that the existing signals suffer. In this paper, a method for estimating the power density of the interference signals on GPS signals is proposed before and after the additional transmission of the KPS signals in the L1, L2 and L5 bands. For estimation, we assume the number of visible satellites observed over the Korean peninsular and the minimum received power of the satellite navigation signals. The comparison of the estimated values shows that the power density of the interfering signal increases by up to 1.37 dB due to the introduction of KPS, but this leads to an increase in interference plus noise power density below 0.47 dB.