• International Journal of Aeronautical and Space Sciences
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• 제16권2호
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• pp.247-253
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• 2015

The components of an aero-engine gas path cannot be monitored in a timely way due to a lack of real-time monitoring technologies. As an attempt to address this problem, we have conducted research on a condition monitoring technology based on the charging characteristics of particles in an aero-engine gas path, and emphatically analyze the formation of particles in an aero-engine gas path, the charging mechanism of carbon particles and the factors that influence the charge quantity and polarity. The verification experiments are performed on the simulated experiment platform and a turbo-shaft engine test bench. The results show the carbon particles' carry charge, and an obvious change in the total electrostatic charge level in the aero-engine gas path due to the increased carbon particles produced by burning or abnormal metal particles; the charge number is related to the size of particles, and the bigger carbon particles carry a negative charge and metal particles carry a positive charge; the change in engine power can lead to an obvious change in the level of electrostatic charge in the gas path, and the change in electrostatic charge results from the extra carbon particles formed in the rich-oil burning process. The research provides a reference for establishing the baseline of electrostatic charge while the engine runs on different power. The study also demonstrates the validity of the electrostatic monitoring technology and establishes a base for developing the application of electrostatic monitoring technology in aero-engines.

• 전자공학회논문지SC
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• 제49권2호
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• pp.1-9
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• 2012

본 논문에서는 이원화된 필드버스 기반의 선박 엔진용 분산 제어시스템을 설계 및 구현한다. 구현된 시스템은 엔진의 상태 값을 감시하기 위해서 CAN과 MODBUS 프로토콜을 혼합 형태로 이용하여 서로 다른 영역의 통신 구조로 구성한다. 첫 번째 층은 CAN프로토콜을 이용하여 엔진의 상태 값을 공유하게 된다. 두 번째 층은 MODBUS를 이용하여 엔진룸에서 기관실의 AMS로 모니터링 데이터 전송을 위한 통신을 지원한다. 테스트 베드 환경을 구축하여 구현된 시스템을 선급기술규칙의 요구사항에 의거하여 테스트 및 성능 검증하였다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2009년도 추계학술대회 논문집
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• pp.607-610
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• 2009

The abnormal combustion in the running engine results to knocking which increases the pressure and temperature in the cylinder, thereby decreasing the generated power by reducing the thermal efficiency. When the temperature and pressure in the cylinder increased rapidly by knocking, abnormal combustion takes place and the engine power is decreased. To investigate the knocking phenomenon, accelerometers are installed in the cylinder head to monitor and diagnose the vibration signal. As method of signal analysis, the time-frequency analysis method was adapted for acquisition of vibration signal and analyzes engine combustion in the short time. In this experiment, after analyzing time data which is stored in the signal recorder in one unit work (4 strokes: 2 revolutions), the signal with frequency and Wavelet methods with extracted one engine combustion data was also analyzed. Then, normal condition with no knocking signal is analyzed at this time. Hereafter, the experiments made a standard for distinguishing normal and abnormal condition to be carried out in acquisition of vibration signal at all cylinders and extracting knocking signal. In addition, analyzing methods can be diverse with Symmetry Dot Patterns (SDP), Time Synchronous Average (TSA), Wigner-Ville Distribution (WVD), Wigner-Ville Spectrum (WVS) and Mean Instantaneous Power (MIP) in the cold test [2]. With signal processing of vibration from engine knocking sensor, the authors adapted a part of engine /rotor vibration analysis and monitoring system for marine vessels to prevent several problems due to engine knocking

• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2012년도 제38회 춘계학술대회논문집
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• pp.586-591
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• 2012

군산 복합화력 발전소에서 운용중인 가스터빈 엔진의 정비 의사 결정을 지원하기 위한 솔루션을 개발하였다. 솔루션은 온라인 상태감시, 기간별 성능 경향분석, 최적 압축기 세정주기 분석, 고온부품 관리 모듈로 구성되어 있다. 운용자가 엔진의 상태 분석 결과를 쉽게 모니터하고 그에 따른 정비의사를 결정할 수 있도록 GUI 플랫폼을 적용하였다. 온라인 상태감시 모듈에서는 기준 성능 대비 실시간 계측데이터의 차이를 분석하여 엔진의 성능저하율을 가시적으로 제시한다. 최적 압축기 세정주기 분석 모듈에서는 경제성 평가 알고리즘을 통해 정비 소요 비용과 성능 저하에 따른 비용 손실의 분석을 통해 순이익이 최대가 되는 세정주기를 제시한다. 엔진의 상태 및 주요 정보를 종합적으로 분석하여 제공함으로써 최적 정비 및 운용이 가능하도록 의사 결정을 지원한다.

• 동력기계공학회지
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• 제19권5호
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• pp.67-72
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• 2015

The reliable operation of onsite emergency diesel generator(EDG) should be ensured by a conditioning monitoring system designed to maintain, monitor and forecast the reliability level of diesel generator. The purpose of this paper is to develop condition diagnosis algorithm(logic) and analysis program of engine for the accurate diagnosis in actual condition of emergency diesel generator engine. As a result of this study, we confirmed that developed engine condition diagnosis algorithm and analysis program could be efficiently applied for actual EDG engine in nuclear power plant.

• International Journal of Aeronautical and Space Sciences
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• 제10권2호
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• pp.34-42
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• 2009

Gas turbine performance diagnostics is a method for detecting, isolating and quantifying faults in gas turbine gas path components. On-line precise fault diagnosis can promote greatly reliability and availability of gas turbine in real time operation. This work proposes a GUI-type on-line diagnostic program using SIMULINK and Fuzzy-Neuro algorithms for a helicopter turboshaft engine. During development of the diagnostic program, a look-up table type base performance module are used for reducing computer calculating time and a signal generation module for simulating real time performance data. This program is composed of the on-line condition monitoring program to monitor on-line measuring performance condition, the fuzzy inference system to isolate the faults from measuring data and the neural network to quantify the isolated faults. Evaluation of the proposed on-line diagnostic program is performed through application to the helicopter engine health monitoring.

• 항공우주시스템공학회지
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• 제7권1호
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• pp.8-18
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• 2013

Recently, the advanced condition monitoring methods such as the model-based method and the artificial intelligent method have been applied to maximize the availability as well as to minimize the maintenance cost of the aircraft gas turbines. Among them the non-linear GPA(Gas Path Analysis) method and the GA(Genetic Algorithms) have lots of advantages to diagnose the engines compared to other advanced condition monitoring methods such as the linear GPA, fuzzy logic and neural networks. Therefore this work applies both the non-linear GPA and the GA to diagnose AE3007 turbofan engine for an aircraft, and in case of having sensor noise and bias it is confirmed that the GA is better than the GPA through the comparison of two methods.

• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2007년도 제29회 추계학술대회논문집
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• pp.345-349
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• 2007

본 연구에서는 계측 데이터의 성능 추이를 분석하여 엔진의 기계적 결함 여부를 탐지하기 위한 퍼지 경향감시 방법을 제안하였다. 경향감시 방법은 연료유량, 배기가스 온도, 로터회전수, 진동수와 같은 중요 엔진 파라미터를 모니터링하여 시간에 따른 변화를 분석하여 엔진 상태를 진단하는 것이다. 선형회귀분석을 통해 엔진 상태 변화를 수식화하고 퍼지 로직을 통해 진단 결과를 분석하여 예측되는 손상 원인을 제시한다.

• Tribology and Lubricants
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• 제27권3호
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• pp.125-133
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• 2011

The purpose of this study is to develop an engine oil quality monitoring system to warn the abnormal condition of engine oil. To do this, first of all, it is needed a personal controller development to measure the capacitance of a pre-developed engine oil deterioration detection sensor integrated with an oil filter. To measure the capacitance of engine oil in the sensor, it is used the way measuring the electric charging time in a capacitor by impressing DC volt. This method has merits on cost and signal stability. The measured capacitance is compensated by comparing with the one measured by an impedance analyzer. Also, using the dielectric constant gained by an impedance analyzer, the calculating equation of the dielectric constant of engine oil related with the currently developed sensor is decided. Then, the deterioration degree of engine oil is estimated according to the change rate of dielectric constant between green oil and used oil. Finally, using this dielectric constant information together with engine oil temperature and pressure, the currently developed engine oil quality monitoring system is to tell the abnormal state of engine oil.

• 한국추진공학회지
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• 제17권2호
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• pp.71-83
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• 2013

항공기 가스터빈의 운용율을 극대화 하고 정비 비용을 최소화하기 위해 최근 모델기반방법이나 인공지능방법을 이용한 첨단상태진단기법들을 적용하고 있다. 이 진단 방법들 중 비선형 GPA방법과 유전자 알고리즘을 이용한 엔진 진단방법들이 선형 GPA, 퍼지 로직 및 신경망 이론 등의 타 방법들에 비해 장점을 가지고 있는 것으로 알려졌다. 이에 본 연구에서는 항공기용 AE3007H 터보팬엔진의 상태진단에 비선형 GPA기법과 유전자 알고리즘을 적용한 후 비교를 통해 센서 노이즈와 바이어스가 있는 경우 유전자 알고리즘이 보다 우수한 진단 기법임을 확인하였다.