• 한국가스학회지
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• 제22권1호
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• pp.45-52
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• 2018

이 논문에서는 도시가스 배관 중 교량에 설치된 배관 398개소에 대해 현황을 조사하고, 배관을 설치연도별, 길이별, 원격차단장치 설치여부 등 특성별로 분류하여 분석하였다. 분석결과 20년 이상 장기사용배관이 43.0%를 차지하고 있었고, 원격차단장치 미설치 교량배관은 89.4%에 달하는 등 드러난 현상에 대한 안전관리 방안을 제시하였다. 또한 조사된 교량설치 배관 중 76개소를 선정한 후 응력해석 전용프로그램인 CAESAR-II를 이용하여 응력특성을 연구하고, 교량배관 중 루프관을 설치할 경우 루프관의 위치 및 크기가 배관의 합성응력에 미치는 영향을 분석하였다. 본 연구의 결과를 통해 교량 배관의 설치, 검사 및 진단 기준 개선 등에 활용하여 교량설치 배관에 대한 안전성 향상에 도움이 될 수 있을 것으로 판단한다.

• 센서학회지
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• 제33권2호
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• pp.112-116
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• 2024

Gas-sensor technology for volatile organic compounds (VOC) biomarker detection offers significant advantages for noninvasive diagnostics, including rapid response time and low operational costs, exhibiting promising potential for disease diagnosis. Colorimetric gas sensors, which enable intuitive analysis of gas concentrations through changes in color, present additional benefits for the development of personal diagnostic kits. However, the traditional method of visually monitoring these sensors can limit quantitative analysis and consistency in detection threshold evaluation, potentially affecting diagnostic accuracy. To address this, we developed a machine vision platform based on metal-organic framework (MOF) for colorimetric gas sensor arrays, designed to accurately detect disease-related VOC biomarkers. This platform integrates a CMOS camera module, gas chamber, and colorimetric MOF sensor jig to quantitatively assess color changes. A specialized machine vision algorithm accurately identifies the color-change Region of Interest (ROI) from the captured images and monitors the color trends. Performance evaluation was conducted through experiments using a platform with four types of low-concentration standard gases. A limit-of-detection (LoD) at 100 ppb level was observed. This approach significantly enhances the potential for non-invasive and accurate disease diagnosis by detecting low-concentration VOC biomarkers and offers a novel diagnostic tool.

• 비파괴검사학회지
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• 제29권2호
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• pp.171-180
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• 2009

• International Journal of Aeronautical and Space Sciences
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• 제15권2호
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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.

• 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.

• 대한전기학회논문지:전기물성ㆍ응용부문C
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• 제53권10호
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• pp.523-529
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• 2004

Faults of cellulosic insulations greatly affect the life span of oil immersed transformers because their performance recovery is impossible. Therefore, the reliable diagnosis technologies are needed for detection of the faults. Dissolved gas analysis technologies using CO and $CO_2$ gases have been widely used for fault diagnosis of cellulosic insulations. In this research, we described Degradation diagnosis of insulation paper CO and $CO_2$ gases in oil immersed Transformers using. We considered the distribution characteristics of CO, $CO_2$ gases' concentrations and ratios of $CO_2$/CO not only in serviced transformers but in experiments with typical fault causes such as heat, partial discharge and moisture. As result, the reliability of diagnosis results for the cellulosic insulations can be improved when the concentrations of CO, $CO_2$ and the ratio of CO/$CO_2$ satisfy each diagnosis criterion at a tim

• 조명전기설비학회논문지
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• 제21권9호
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• pp.18-24
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• 2007

When faults occur in the power equipment that is used a great deal in industrial sites, it may lead to fatal accidents that cause losses both economically and in manpower. In this paper, the effect of particle impact on the partial discharge of $SF_6$ gas was measured by simulating a partial discharge following the type of fault found in the GIS using $SF_6$ insulating gas as the insulating material. A spectrum analysis was performed on the radiate electromagnetic waves emitted upon partial discharge by using the UHF insulation diagnosis method. This subject of this study is insulation diagnosis by the measurement of radiate electromagnetic waves when particles exist in the GIS and power equipment insulated with $SF_6$ gas.

• 한국유체기계학회 논문집
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• 제9권6호
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• pp.35-44
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• 2006

Operation conditions of a reheat cycle gas turbine for a combined cycle power plant was analyzed. Based on measured performance parameters of the gas turbine, a performance analysis program predicted component characteristic parameters such as compressor air flow, compressor efficiency, efficiencies of both the high and low pressure turbines, and coolant flows. The predicted air flow and its variation with the inlet guide vane setting were sufficiently accurate. The compressor running characteristic in terms of the relations between air flow, pressure ratio and efficiency was presented. The variations of the efficiencies of both the high and low pressure turbines were also presented. Almost constant flow functions of both turbines were predicted. The current methodology and obtained data can be utilized for performance diagnosis.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.493-495
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• 2005

This paper proposes a swarm-based fuzzy system modeling technique for coke oven combustion control diagnosis. The coke plant produces coke for the blast furnace plant in steel making process by charging coal into oven and supplying gas to carbonize it. A conventional mathematical model for coke oven combustion control has been used to control the amount of gas input, but it does not work well because of highly nonlinear feature of coke plant. To solve this problem, swarm-based fuzzy system modeling technique is suggested to construct a diagnosis model of coke oven combustion control. Based on the measured input-output data pairs, the fuzzy rules are generated and the parameters are tuned by the PSO(Particle Swarm Optimizer) to increase the accuracy of the fuzzy system is operated. This system computes the proper amount of gas input taking the operation conditions of coke oven into account, and compares the computed result with the supplied gas input.

• 대한전기학회논문지:전기물성ㆍ응용부문C
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• 제54권8호
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• pp.343-349
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• 2005

The gas in oil analysis of transformer is the most widely used technology for diagnosis of transformer in the world. It has brought excellent results to prevention of transformer failure. The criteria for maintenance and judgement, however, is still required continuous supplement to improve the accuracy of the diagnosis on the basis of accumulated data of gas analysis and investigations in the transformer In this study, the relationship between the detection rate of the defects and the source of troubles are analyzed according to the investigation in the transformer, which was conducted by KEPCO in 2004. As a result, the validity of the criteria being used at present was examined thoroughly.