• 대한전기학회:학술대회논문집
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• 대한전기학회 2015년도 제46회 하계학술대회
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• pp.447-448
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• 2015

In order to looking for method of detecting inner fault of a 154kV GIT(Gas Insulated Transformer), it was considered that diagnosis partial discharge(PD) in UHF band and that analyze the ingredients of SF6 insulating gas. UHF PD diagnosis that is optimized to GIS was considered unsuitable through checking of inner part of a transformers which PD is detected excessively. The method analyzing the content of six kinds of gas(SOF2, SO2F2, etc)was decided through analysis of chemical degradation and combination process and discharge experiment. With the result applying this method to analyze the content of insulated gas of eighty five Gas Insulated Transformers.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2017년도 춘계 학술논문 발표대회
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• pp.142-143
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• 2017

An analysis of the current water leak status of understand structure (underground parking lots, staircases, plumbing systems, water reservoirs, etc.) of multi-family housing in South Korea shows that water leaks are found from cracks in all areas of the underground structure caused by the degradation environment (water pressure by underground water, humidity, temperature, earth pressure, soil behaviour and vibration, etc.), which result in various problems, including mold, malodour, debonding of finishing materials, exfoliation, breakout, water leaks in electrical boxes, efflorescence, sedimentation of calcium hydroxide, decoloration, rusting, damages and pollution among others. Therefore, this study aims to analyse the current status of water leaks in underground structure and use the results as the basic data for developing a standard guideline for water leaks and maintenance by parts of the underground structure of multi-family housing.

• Nuclear Engineering and Technology
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• 제53권4호
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• pp.1181-1188
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• 2021

When abnormal events occur in a nuclear power plant, operators must conduct appropriate abnormal operating procedures. It is burdensome though for operators to choose the appropriate procedure considering the numerous main plant parameters and hundreds of alarms that should be judged in a short time. Recently, various research has applied deep-learning algorithms to support this problem by classifying each abnormal condition with high accuracy. Most of these models are trained with simulator data because of a lack of plant data for abnormal states, and as such, developed models may not have tolerance for plant data in actual situations. In this study, two approaches are investigated for a deep-learning model trained with simulator data to overcome the performance degradation caused by noise in actual plant data. First, a preprocessing method using several filters was employed to smooth the test data noise, and second, a data augmentation method was applied to increase the acceptability of the untrained data. Results of this study confirm that the combination of these two approaches can enable high model performance even in the presence of noisy data as in real plants.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2017년도 추계 학술논문 발표대회
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• pp.221-222
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• 2017

An analysis of the current water leak status of understand structure (underground parking lots, staircases, plumbing systems, water reservoirs, etc.) of multi-family housing in South Korea shows that water leaks are found from cracks in all areas of the underground structure caused by the degradation environment (water pressure by underground water, humidity, temperature, earth pressure, soil behaviour and vibration, etc.), which result in various problems, including mold, malodour, debonding of finishing materials, exfoliation, breakout, water leaks in electrical boxes, efflorescence, sedimentation of calcium hydroxide, decoloration, rusting, damages and pollution among others. Therefore, this study aims to analyse the current status of water leaks in underground structure and use the results as the basic data for developing a standard guideline for water leaks and maintenance by parts of the underground structure of multi-family housing.

• Nuclear Medicine and Molecular Imaging
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• 제42권2호
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• pp.172-180
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• 2008

PET/CT fused image with anatomical and functional information have improved medical diagnosis and interpretation. This fusion has resulted in more precise localization and characterization of sites of radio-tracer uptake. However, a motion during whole-body imaging has been recognized as a source of image quality degradation and reduced the quantitative accuracy of PET/CT study. The respiratory motion problem is more challenging in combined PET/CT imaging. In combined PET/CT, CT is used to localize tumors and to correct for attenuation in the PET images. An accurate spatial registration of PET and CT image sets is a prerequisite for accurate diagnosis and SUV measurement. Correcting for the spatial mismatch caused by motion represents a particular challenge for the requisite registration accuracy as a result of differences in PET/CT image. This paper provides a brief summary of the materials and methods involved in multiple investigations of the correction for respiratory motion in PET/CT imaging, with the goal of improving image quality and quantitative accuracy.

• 한국산학기술학회논문지
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• 제22권6호
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• pp.27-35
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• 2021

일반적으로, 태양광모듈은 20년 이상의 장기간 동안 사용할 수 있다고 알려져 있지만, 설치된 주변 환경요인(염분, 온도, 습도, 자외선, 음영 등)에 따라 다양한 열화현상이 발생하여, 전기적 성능과 수명이 크게 감소할 수 있어 태양광 모듈에 대한 정확한 열화특성 분석이 요구되고 있다. 그러나, 태양광모듈의 출력을 STC조건으로 보정하여 초기 사양과 비교분석하는 기존의 열화특성 분석방법은 데이터 보정 시 필연적으로 발생하는 데이터 오류로 인하여 객관성이 결여될 수 있다. 따라서, 본 논문에서는 태양광전원 모듈부와 모니터링부로 구성된 열화진단 시험장치를 구축하여 모듈별 출력 데이터를 측정 및 수집하고, 태양광모듈의 출력 변동성과 통신 에러 및 지연에 따른 영향을 최소화하기 위하여, MATLAB을 이용한 열화특성 분석 모델링을 통하여 실측 데이터를 평활화한다. 또한, 이를 바탕으로 태양광모듈의 열화 상태를 계절별 실측 출력특성에 따라 분석한 결과, 전체 구형모듈의 평균 열화율은 총 25.73%이고, 연평균 1.55%씩 열화됨을 진단할 수 있어, 본 논문에서 구축한 열화진단 시험장치의 유용성을 확인하였다.

• 전력전자학회논문지
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• 제26권6호
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• pp.381-389
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• 2021

Most diagnosis approaches rely on historical failure data that might not be feasible in real operating conditions because the battery voltage and internal parameters are nonlinear according to various operating conditions, such as cell-to-cell configuration and initial condition. To overcome this issue, the estimator and the predictor require integrated approaches that consider comprehensive data, with the degradation process and measured data taken into account. In this paper, vector autoregressive models (VAR) with various parameters that affect overdischarge to the cell in the battery pack were constructed, and the cell-to-cell parameters were identified using an adaptive model to analyze the influence of failure prognosis. The theoretical analysis is validated using experimental results in terms of the feasibility and advantages of fault prognosis.

• 한국압력기기공학회 논문집
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• 제4권2호
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• pp.34-39
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• 2008

Steam Generator(SG) tubes are classified as one of the key components in nuclear power plants, and they should be periodically examined by the intensified management program for the assurance and diagnosis of their structural integrity. In this study, we use the optimum analysis technique to draw the detection and categorization of bowing(BOW) signals; abnormal tube-to-tube proximity in the SG upper bundle free span area. The locations in which BOW signals are detected likely have latent degradation of ODSCC(Outer Diameter Stress Corrosion Cracking). For the sake of timely and correct detection of BOW signals and diagnosis of ODSCC, we carried out the experimental demonstrations using a reduced mock-up. And we validated the MRPC(Motorized Rotating Pancake Coil) analysis technique is better than the bobbin. Hence, it comes to conclusion that the optimum analysis technique can be a good alternative for the reliable SG tube examination.

• 한국전기전자재료학회논문지
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• 제31권4호
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• pp.255-260
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• 2018

In recent years, increasing electricity use has led to considerable interest in green energy. In order to effectively supply, cut off, and operate an electric power system, many electric power facilities such as gas insulation switch (GIS), cable, and large substation facilities with higher densities are being developed to meet demand. However, because of the increased use of aging electric power facilities, safety problems are emerging. Electromagnetic wave and leakage current detection are mainly used as sensing methods to detect live-line partial discharges. Although electromagnetic sensors are excellent at providing an initial diagnosis and very reliable, it is difficult to precisely determine the fault point, while leakage current sensors require a connection to the ground line and are very vulnerable to line noise. The partial discharge characteristic in particular is accompanied by statistical irregularity, and it has been reported that proper statistical processing of data is very important. Therefore, in this paper, we present the results of analyzing ${\Phi}-q-n$ cluster distributions of partial discharge characteristics by using K-means clustering to develop an expert partial discharge diagnosis system generated in a GIS facility.

• 분석과학
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• 제13권2호
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• pp.166-172
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• 2000

별다른 사고가 없는 경우, 변압기의 수명은 내부 절연지의 수명에 해당되지만 운전중인 변압기에서 고체 상태의 절연지를 채취할 수 없는 반면에, 절연지가 열을 포함한 여러 영향에 의해 분해되어 변압기내에 용존되어 있는 절연유는 운전중인 변압기에서 쉽게 채취할 수가 있다. 그러므로 절연지의 분해산물이 용해되어 있는 절연유의 간접적인 분석을 통해 절연지의 상태, 나아가서는 변압기를 진단할 수 있다면 변압기의 관리 측면에서는 아주 유용할 것이다. 이러한 근거하에서 절연지의 분해산물로 알려진 퓨란(furan) 유도체제중 한전의 변압기에서 특징적으로 관찰되는 2-furfural의 농도를 별다른 전처리 과정없이 HPLC에 의한 분석 방법을 확립하였다. 운전중인 변압기에서 채취한 절연유를 분석한 결과, HPLC에 의한 2-furfural 농도가 현재 일반적으로 실시하고 있는 GC를 이용한 $CO_2$나 CO 가스 농도보다 변압기 내부 절연지의 상태를 보다 정확하게 반영한다는 것을 알 수 있었다. 대략적으로 변압기의 수명이 30-40년 정도라고 가정할 때 한전에서는 노후화된 변압기의 숫자가 증가될 것이므로 변압기의 적기교체를 위한 변압기 수명예측의 필요성이 대두될 것으로 예상되며 본 연구의 수행을 통해 확립된 방법은 절연지의 열화정도를 진단한 분석 방법으로서 변압기의 효율적인 관리는 뭍론 수명예측 혹은 수명진단에 유용하게 이용될 수 있을 것으로 기대된다.