• 대한전기학회:학술대회논문집
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• 대한전기학회 1994년도 하계학술대회 논문집 C
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• pp.1649-1651
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• 1994

This paper presents a new method for estimating partial discharge position using improved cross-correlation technique and neural networks in the power transformer. When ultrasonic signal is occurred by partial discharge, we detected these signals and calculated cross-correlation values with Hamming window. Also, we estimated partial discharge position using neural network with cross-correlation values. In the result of case study, we can estimate more accurately the partial discharge position than any other algorithms.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 C
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• pp.1951-1953
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• 2000

Partial Discharge is non-disruptive discharge, which can be discriminated to 3 kinds as firstly, internal discharge which is caused by internal voids inside of insulator, secondly, surface discharge which occurs from the surface of insulator and finally, corona discharge which is from the surface of an electrode. In this thesis, three kinds of defects are artificially made to the inside and the surface of the epoxy resine busing with internal voltage detection sensor, which is practically equipped into SF6 gas insulated switchgear for 22.9kV distribution line, so that discrimination of three kinds of PD signals by means of phi-q-n pattern analysis method was performed.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.346-348
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• 2003

In this study, we attempted to estimate the discharge of the Amazon River branches from JERS-1/SAR images, which are independent of the weather. We visualized some traces of the Amazon River branches, transformed river shapes into a one-dimensional signal, and calculated the characteristics of the river shapes such as the meandering wavelength and the amplitude with Fourier and wavelet analysis. Then, we related the characteristics of the river shapes with the existing discharge data and derived some regression equations. Finally, we estimated the discharge of the Amazon River branches from the SAR images.

• 동력기계공학회지
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• 제20권2호
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• pp.66-72
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• 2016

As a method to improve the equipment reliability, early warning researches that can be detected fault symptom of an equipment at an early stage are being performed out among developed countries. In this paper, when abnormal signal is input to actual normal signal of a pump, early detection studies on pump's fault symptom were carried out with auto-associative kernel regression as an advanced pattern recognition algorithm. From analysis, correlations among power of motor driving pump, discharge flow of pump, power output of pump, and discharge pressure of pump are exited. When the abnormal signal is input to one of those normal signals, the other expected values are changed due to the influence of the abnormal signal. Therefore, the fault symptom of pump through the early-warning index is able to detect at an early stage.

• 한국전기전자재료학회논문지
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• 제23권1호
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• pp.53-60
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• 2010

This paper dealt with the acoustic detection of partial discharge (PD) in insulation oil for insulation diagnostics of oil immersed transformers. Electrode systems such as needle to plane, plane to plane, and floating were fabricated to simulate some defects in transformers. A wide band acoustic emission(AE) sensor with the frequency ranges of 100 kHz~1 MHz and a narrow band AE sensor with the resonant frequency of 140 kHz were used in the experiment. Also, a decoupler and an amplifier were designed to detect and amplify the acoustic signal only. The decoupler separates acoustic signal from DC source without any distortion, and the amplifier has the gain of 40 dB in frequency ranges of 11 kHz~4 MHz. In the experiment, frequency components and propagation characteristics of acoustic signal were analyzed, and an algorithm of positioning of PD occurrence by the time difference of arrival was proposed. From the results, the frequency components of the acoustic signal exist from 50 kHz to 200 kHz and the positioning error of PD calculated by three AE sensors was within 1%.

• 한국전기전자재료학회논문지
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• 제11권11호
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• pp.1035-1042
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• 1998

After the 1990's, a computer-aided partial discharge(PD) measurement system was referred in part of aging diagnosis using digital signal processing as the new technology has been studied. The PD patterns and relevant information for pattern recognition are discussed in PD research area, because discharge quantity(q), the number of discharge pulse(n) and the applied boltage phase($\varphi$) was combined with the system information of the aging state. This paper investigates the discharge phase and quantity, as well as the number of discharge(n) with regard to discharge signals generated in power cable. therefore, according to characteristic analysis on the distribution of $\varphi$, q and n, it is able to apply in the aging analysis of power cable which visual observation is impossible and distribution change of discharge signals offers much information for risk degree on aging progress of insulation materials.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 춘계학술대회 논문집 전력기술부문
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• pp.217-219
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• 2001

This paper presents new diagnosis technique for detecting a partial discharge(PD) using antenna. The wavelet transform is applied for the analysis of PD pulse signal because it is difficult to identify PD signal using electromagnetic waves detected by antenna. The capabilities of the proposed diagnosis methodology for detecting PD signal is verified on experiment in laboratory.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 추계학술대회 논문집 학회본부 C
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• pp.537-539
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• 2000

In this paper, the measured ultrasonic signal in GIS was filtered by wavelet transform, and then the origin signal and the filtered signals were analyzed by statistic operators. As a result, it was confirmed that different characteristics were obtained with the impact of particle and with partial discharge inception.

• 한국전기전자재료학회논문지
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• 제19권2호
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• pp.162-168
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• 2006

Recently, diagnosis techniques have been investigated to detect a Partial Discharge associated with a dielectric material defect in a high voltage electrical apparatus, However, the properties of detection technique of Partial Discharge aren't completely understood because the physical process of Partial Discharge. Therefore, this paper analyzes the process on surface discharge of polymer insulator using wavelet transform. Wavelet transform provides a direct quantitative measure of spectral content in the time~frequency domain. As it is important to develop a non-contact method for detecting the kaolin contamination degree, this research analyzes the electromagnetic waves emitted from Partial Discharge using wavelet transform. This result experimentally shows the process of Partial Discharge as a two-dimensional distribution in the time-frequency domain. Feature extraction parameter namely, maximum and average of wavelet coefficients values, wavelet coefficients value at the point of $95\%$ in a histogram and number of maximum wavelet coefficient have used electromagnetic wave signals as input signals in the preprocessing process of neural networks in order to identify kaolin contamination rates. As result, root sum square error was produced by the test with a learning of neural networks obtained 0.00828.

• 대한전기학회논문지:전기물성ㆍ응용부문C
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• 제51권8호
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• pp.354-360
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• 2002

The partial discharge detecting method using the ultrasonic technique has been investigated to monitor the insulation ageing of a transformer. However, the result of the studies on the ultrasonic technique for detecting of partial discharge in the operating transformer is not enough yet to utilize. This paper presents the analysis of the ultrasonic signals due to the partial discharge in a model transformer and the corona in air at a shielded high voltage room. In addition, the ultrasonic signals due to the vibration from the core, operation of the cooling pump, the fan and the OLTC at the 345㎸ power transformer, were analyzed and corona noise from overhead transmission line in 345㎸ substation were measured to remove the electrical and mechanical noises from the transformer. Furthermore, ultrasonic signal due to the partial discharge in the 154㎸ power transformer with in $C_2$$H_2$ gas warning condition was measured. The inside of the transformer was examined with care. which confirms the existence of the partial discharge source.