• Analytical Science and Technology
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• v.13 no.2
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• pp.166-172
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• 2000

The life expectation of power transformers is basically dependent on the aging deterioration of insulating paper which can not be obtained from operating transformers. Therefore, it will be very useful if we can manage transformers by indirect analysis of degradation products. "Furan derivatives" are known the decomposition products which are generated by the degradation of cellulose in insulating paper. We proved that 2-furfural is the only measurable product from our transformers, and determined easily the concentration of 2-furfural by HPLC without any specific pretreatments, Compared to concentration of $CO_2$ and CO by GC, the concentration of 2-furfural by HPLC can estimate more accurately aging characteristics of transformers. We expect that these results can be utilized to predict the aging characteristics and life diagnosis of power transformers.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.27-35
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• 2021

Generally, a proper evaluation method of the aging phenomenon of PV modules is required as the electrical performance and lifespan of PV modules can degrade significantly due to several environmental factors, while they are generally known as devices that are used semi-permanently for more than 20 years. On the other hand, there is a lack of objectivity in the existing evaluation method of the aging phenomenon, which compares the adjusted PV output based on STC with the initial PV module specifications due to the data distortion while adjusting the measured data. Therefore, this study implemented a test device for an aging diagnosis to measure and collect actual data from a PV module section and modeled the data for aging using MATLAB S/W to minimize the variability of the PV output, communication error, and delay. Furthermore, this study confirmed the usefulness of the presented test device for aging diagnosis of the PV modules by diagnosing the total period and yearly-basis degradation rate of aging PV modules as 25.73% and 1.55%, respectively, according to the on-site output characteristics of the PV modules by season.

• International Journal of Aeronautical and Space Sciences
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• v.15 no.2
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• pp.123-137
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• 2014

The aviation gas turbine is composed of many expensive and highly precise parts and operated in high pressure and temperature gas. When breakdown or performance deterioration occurs due to the hostile environment and component degradation, it severely influences the aircraft operation. Recently to minimize this problem the third generation of predictive maintenance known as condition based maintenance has been developed. This method not only monitors the engine condition and diagnoses the engine faults but also gives proper maintenance advice. Therefore it can maximize the availability and minimize the maintenance cost. The advanced gas turbine health monitoring method is classified into model based diagnosis (such as observers, parity equations, parameter estimation and Gas Path Analysis (GPA)) and soft computing diagnosis (such as expert system, fuzzy logic, Neural Networks (NNs) and Genetic Algorithms (GA)). The overview shows an introduction, advantages, and disadvantages of each advanced engine health monitoring method. In addition, some practical gas turbine health monitoring application examples using the GPA methods and the artificial intelligent methods including fuzzy logic, NNs and GA developed by the author are presented.

• Nuclear Medicine and Molecular Imaging
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• v.42 no.2
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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.

• Proceedings of the KIEE Conference
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• 2015.07a
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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.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2017.05a
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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.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.4 no.2
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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.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2017.11a
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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.

• KIEE International Transactions on Electrophysics and Applications
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• v.5C no.3
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• pp.131-137
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• 2005

This paper describes a new approach to the algorithm and fundamental characteristics of the device for monitoring the leakage currents flowing through zinc oxide (ZnO) surge arresters. In order to obtain a technique for a new on-line monitoring device that can be used in the deterioration diagnosis of ZnO surge arresters, the new algorithm and on-line leakage current detection device for extracting the resistive and capacitive currents using the phase shift addition method were proposed. The computer-based on-line monitoring device can sense accurately the power frequency leakage currents flowing through ZnO surge arresters. The on-line leakage current monitoring device of ZnO surge arresters proposed in this work has the high sensitivity compared to the third harmonic leakage current detection devices. As a consequence, it was found that the proposed leakage current monitoring device would be useful for forecasting the defects and degradation of ZnO surge arresters.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.31 no.4
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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.