• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.214-216
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• 2001

Data Mining is a issue of Database fields. Data mining is discovered optimally interesting rules for user, which are results of specific requirements of user. through past data. Through to analyze and to statical suppose interesting rules. we can prepare future faults of system. In this paper, we present a new way which is discovered and repaired faults of Electric Power system using Data Mining techniques.

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.261-263
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• 2001

오늘날 전력계통에서 개폐기, 차단기들은 케이블 충전이나 선로충전, 콘덴서 뱅크의 부하전류와 같은 진상 전류의 스위칭을 많이 하게 된다. 이때 진상 전류의 크기는 개폐기나 차단기의 정격 차단전류보다 그 크기가 매우 작다. 그러나 차단 책무는 개폐기나 차단기에 상당히 가혹하며, 이는 차단 후 극간에 걸리는 과도한 회복전압에 기인한다[2,3]. 상용주파 회복전압은 차단 성능을 검증하는 요소중의 하나로서 사고시 임피던스에 의해 변화한다. 본 논문에서는 IEC 60265-1에 따른 케이블 충전 전류 시험(Test duty 4a) 회로를 모의하고 IEC 60265-1에서 규정하는 규정치 이내에서 영상분 임피던스의 변화에 따른 상용주파 회복전압의 변화를 살펴보았다[1].

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.243-245
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• 2001

This paper presents a new classification method for high impedance faults in power systems. Results of phase plane trajectory with Clarke modal transformation using postfault current and voltage are utilized to classify types of arcing faults. The performance of the proposed method is tested on a typical 154 kV korean transmission system under various fault conditions using EMTP. As can be seen from results, phase plane trajectory of postfault current should be combined with that of o component from Clarke modal transformation to give reliability of clear fault classification. Thus the proposed method can classify arcing faults including LIFs and HIFs accurately in power systems.

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.252-254
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• 2001

Accurate detection and classification of faults on transmission lines is vitally important. High impedance faults(HIF) in particular pose difficulties for the commonly employed conventional overcurrent and distance relays, and if not detected, can cause damage to expensive equipment, threaten life and cause fire hazards. Although HIFs are far less common than LIFs, it is imperative that any protection device should be able to satisfactorily deal with both HIFs and LIFs. This paper proposes an algorithm for fault detection and classification for both LIFs and HIFs using Adaptive Network-based Fuzzy Inference System(ANFIS). The performance of the proposed algorithm is tested on a typical 154[kV] Korean transmission line system under various fault conditions. Test results show that the ANFIS can detect and classify faults including (LIFs and HIFs) accurately within half a cycle.

• Proceedings of the KIEE Conference
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• 2006.07b
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• pp.717-718
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• 2006

최근 저압 기중차단기(ACB, Air Circuit Breaker)는 고압중전기 공인시험제도 및 저압전기기기 안전인증제도와 같은 강제인중 대상에서 제외되어 해당 성능에 대한 안전 사각지대에 놓여있다는 지적을 받아왔다. 본 논문에서는 현재의 ACB관련 규격 및 성능평가기술을 분석하고, 국제규격과의 비교 분석을 통하여 국제규격에 준하는 성능평가기술 및 규격을 제시하는 방안을 연구하였다. 특히 내년에 제정이 논의되고 있는 ACB관련 KS 규격의 제정 방향 및 KS 심사기준에 대한 진행방향 설정과 연구되어야할 성능평가기술을 제품성능 특성별로 제시하였다. 향후 본 논문의 성능평가기술 및 제안 방향이 KS규격 제정 및 활용에 중요한 근간을 제공할 것으로 기대한다.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.924-926
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• 1997

A high impedance fault(HIF) in a power system could be due to a downed conductor, and is a dangerous situation because the current may be too small to be detected by conventional means. In this paper, HIF(High impedance fault) and LIF(Low impedance fault) detection methods were reviewed. No single defection method can detect all electrical conditions resulting from downed conductor faults, because high impedance fault have arc phenomena, asymmetry and randomness. Neural network are well-suited for solving difficult signal processing and pattern recognition problem. This paper presents the application of artificial neural network(ANN) to detect the HIF and LIF. Test results show that the neural network was able to identify the high impedance fault by real-time operation. Furthermore, neural network was able to discriminate the HIF from the LIF.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.1012-1014
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• 1997

This paper introduces wavelets and shows that they may be efficient and useful for the detection of general faults in power system. The wavelet transform of a signal consists in measuring the "similarity" between the signal and a set of translated and scaled versions of a "mother wavelet". The "mother wavelet" is a chosen fast decaying oscillation function. A number of mother wavelet for signal analysis have been proposed and some of them are in use in fault detection. However, the performance of fault detection depend on used mother wavelet. In the present paper a comparative evaluation of different mother wavelets for low impedance fault detection is performed. The discussion is focused in well-known mother wavelet based wavelet transform. Several families of wavelets are used to analyse transient earth fault signals in a 345kV model system as generated by EMTP.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.14 no.6
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• pp.519-524
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• 2002

An experimental study has been conducted to investigate the effects of surface energy on frost formation. Test samples with two different surfaces are installed in a wind tunnel and exposed to a humid airflow. Dynamic contact angles (DCA) for these surfaces are $23^{\circ}\;and\;88^{\circ}$, respectively. The thickness and the mass of frost layer are measured and used to calculate the frost density while frost formation is visualized simultaneously with their measurements. Results show that frost density increases as time increases at specific test conditions. The air Reynolds number, the airflow humidity and the cold plate temperature are maintained at 12,000, 0.0042 kg/kg and $-21^{\circ}C$, respectively. The surface with a lower DCA shows a higher frost density during two-hour test, but no differences in the frost density have been found after two hours of frost generation. Empirical correlations for thickness, mass and density are assumed to be the functions of the test time and DCA.

• Journal of the Korean Society of Systems Engineering
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• v.1 no.1
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• pp.1-13
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• 2005

The purpose of this paper analyze development feasibility and alternatives for infrared detector development in both technology and cost. Infrared Detector is core component of Thermal Imaging System and developed by ADD from 2006 10 2008 year. We got raw input data from development and technical expert, and then analyze cost and technology for development feasibility, and alternatives study. Technology level is analyzed by TRL(Technology Readiness Level) and AOA(Analysis of Alternatives) is done by development cost estimate. Estimating the development cost, we use SEER-H that is parametric cost estimating tool based on Knowledge Base. This study can help those who are related to the cost and development feasibility analysis of other weapon systems.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.446-449
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• 2017

인터넷의 보급과 동시에 데이터의 누적으로 생성된 수많은 빅 데이터의 활용을 통해 수 없이 많은 개인에 대한 분석과 추천이 가능해졌다. 그중 영화는 현대인의 문화로 자리 잡으며 수많은 데이터의 누적이 이루어 졌으며 계속해서 누적되어가고 있다. 이런 누적된 데이터를 통해서 개인에게 맞는 영화를 추천하는 협업필터링 시스템을 R을 통해 분석하고 Cold Start 문제를 개인화 요인으로서 보안하여 보다 신뢰성 높은 추천 시스템을 제안 한다.