• 한국전기전자재료학회논문지
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• 제17권1호
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• pp.101-106
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• 2004

The phenomenon of PD(Partial Discharge) is accompanied by electromagnetic wave which can be detected by UHF(Ultra High Frequency) antenna. The signals obtaining from UHF antenna are very high rapid pulse and have wide band frequency responses. The distribution of PRPD(Phase Resolved Partial Discharge) which consisted of those pulse train can show distinct characteristics of PD sources. But it is not sufficient to discriminate among PD sources. This paper suggests that the stochastic parameters formed by preprocessing of STFT(Short Time Fourier Transform) are good tools for differentiate from PD sources. The stochastic parameters are CC(Cross Correlation) mean value, CC standard deviation, CC skewness, CC kurtosis.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2001년도 하계학술대회 논문집
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• pp.319-322
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• 2001

The proposed system was composed of pre-processor which was executing binary/high-pass filtering and post-processor which ranged from statistic data to prediction. In post-processor work, step one was filter process of image, step two was image recognition, and step three was destruction degree/time prediction. After these processing, we could predict image of the last destruction timestamp. This research was produced variation value according to growth of tree pattern. This result showed improved correction, when this research was applied image Processing. Pre-processing step of original image had good result binary work after high pass- filter execution. In the case of using partial discharge of the image, our research could predict the last destruction timestamp. By means of experimental data, this Prediction system was acquired ${\pm}$3.2% error range.

• 한국전기전자재료학회논문지
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• 제17권8호
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• pp.898-903
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• 2004

In this paper, neural networks is studied to apply as a PD source classification in XLPE power cable specimen. For treeing discharge sources in the specimen, three defected models are made. And these data making use of a computer-aided discharge analyser, statistical and other discharge parameters is calculated to discrimination between different models of discharge sources. And also these parameter is applied to classify PD sources by neural networks. Neural Networks has good recognition rate for three PD sources.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2010년도 춘계학술대회 논문집
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• pp.1768-1773
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• 2010

CEN/TS 45545 is Europe consolidation standard for fire safety on railway behicles. This is based on the International Union of Railways(UIC) and different European countries. It is intended to protect passengers and staff in railway in the event of a fire on board. It will be prepared in 2012. Based on this consolidate standard, they are going to make single market, for raising technical competitiveness, technical innovation and globalization of that standard. For this reason, European academies, manufacturers, and sub-manufacturers confer and stady animated about CEN/TS 45545. In Korea, get out the safety assessment for ues incombustible interior material, the needs of quantitative analysis on fire protection, demand on recognition of fire protection scenario, and define about fire load analysis are becomin more and more important. Therefore, this paper will estimate and compare Flammability, Smoke Density, Toxicity Index( this is the key point for appraised fire safety performance of material) between CEN/TS45545 and fire standards on railway vehicle. Then suggest criteria for fire safety on railway vehicles.

• 한국실내디자인학회:학술대회논문집
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• 한국실내디자인학회 1999년도 춘계학술발표대회 논문집
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• pp.57-60
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• 1999

The eyes are the first sensory organs to perceive the environment. We become accustomed to the environment with our eyes. When we contact the environment, we perceive the appearance of an object with our eyes. Then we recognize our position, and perceive the shape surrounding the object interacting with space. The perception of seeing constructs experiences which control most of our recognition, and the experiences are images of the environment surrounding it. So they are significantly expressed into sensitive and mental elements of material and non-material world. Gibson's ecological perception theory analyzes and information system, which helps man to move effectively, and its component stimulus'. The important thing is that we should understand the combination of systems gathering stimulus not as an individual system but as one whole system.

• 한국전기전자재료학회논문지
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• 제17권9호
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• pp.1006-1012
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• 2004

In this paper, neural networks is studied to apply as a PD source classification in XLPE power cable specimen. Two learning schemes are used to classification; BP(Back propagation algorithm), SOM(self organized map - kohonen network). As a PD source, using treeing discharge sources in the specimen, three defected models are made. And these data making use of a computer-aided discharge analyser, statistical and other discharge parameters is calculated to discrimination between different models of discharge sources. And a]so these distribution characteristics are applied to classify PD sources by two scheme of the neural networks. In conclusion, recognition efficiency of BP is superior to SOM.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 1994년도 추계학술대회 논문집
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• pp.202-205
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• 1994

There is a close relation between electrical treeing and internal partial discharges in solid dielectrics. In this paper, the characteristics of electrical treeing and partial discharge in solid dielectrics are investigated. We carried out the measurements of electrical treeing and PD(partial discharge) characteristics. From the experimental results, we found out that maximum PD magnitude increased linearly with time at first stage, thereafter increased remarkably. These tendencies are very similar to the characteristics of tree growth with time.

• 한국정밀공학회지
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• 제20권2호
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• pp.146-153
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• 2003

Ultrasonic inspection of defects has been focused on the existence of defect in structural material and need has much time and expenses in inspecting all the coordinates (x, y) on material surface. Neural networks can have an application to coordinates (x, y) of defects by multi-point inspection method. Ultrasonic inspection modeling is optimized by neural networks Neural networks has trained training example of absolute and relative coordinate of defects, and defect pattern. This method can predict coordinates (x, y) of defects within engineering estimated mean error $\psi$.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 1998년도 춘계학술대회 논문집
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• pp.297-300
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• 1998

In this paper, we obtained the data, which is required in training the neural network and diagnosing the degradation degree, by introducing the AE detection that is effective method in ordinary degradation diagnosis on activation. Automatic detection system to detect acoustic. As the results of generalization tests by appling neural network to the unknown AE patterns obtained from specimens, firstly as to evaluate an objective performance of neural network, the recognition ratio for no-void specimen is appeared. Also, in the evaluation for the adaptability of neural network with a untrained type of no-void specimen, it is confirmed that the result appears.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 1998년도 춘계학술대회 논문집
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• pp.13-18
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• 1998

After Computer-based PD measurement was referred in the 1970's, the new technology and a number of digital system have been studied. And the selection of PD patterns, extraction of relevant information for PD recognition are discussed because the number of pulse as a function of discharge magnitude and discharge pulse as a function of the power frequency cycl4e offer the information of the aging insulation. This paper investigates the discharge phase($\phi$) and magnitude(q), as well as the number of discharge(n) with regard to discharge signals generated in power cable. Therefore, according to properties analysis on the distribution of $\phi$ , 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.