• Proceedings of the Korean Society of Propulsion Engineers Conference
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• v.y2005m4
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• pp.248-251
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• 2005

In this paper, health monitoring technique has been studied for performance deterioration caused by the defects of the gas turbine. The parameters for performance diagnostics have been extracted by using GSP program for modeling the target engine. The virtual sensor model for the health monitoring has been built of those data. The position and magnitude of the defects of the engine components have been determined by using Multiple Linear Regression technique and the method using the weight in order to diagnose the single and multiple defects.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.369-373
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• 2012

최근 강화된 국내외의 배출가스 규제 조건을 충족시키기 위해, 사용자의 요구대로 연료의 분사시기와 분사량을 조절할 수 있는 CRDI ECU 제어 알고리즘의 개발이 필요하다. 따라서 본 논문에서는 산업용 CRDI 엔진 전용 ECU에 적용할 수 있는 노킹 판별 및 엔진 밸런스 보정이 가능한 노킹 분석 시뮬레이터를 개발하였다. 개발한 노킹 분석 시뮬레이터의 결과를 OBD-II 표준을 사용하여 차량 위주의 진단기를 개발하여 운전자가 직접 차량을 진단할 수 있는 운전자 중심의 진단 서비스를 제공하고자 한다. 이를 위해 자동차 고장진단 신호 및 센서 출력 신호를 유선시스템과 무선 시스템인 블루투스 모듈을 이용하여 실시간 통신이 제공 될 수 있는 OBD-II 진단기 S/W 설계 방안을 제안함으로써 차량의 연비를 향상시키고, 유해 배출가스의 발생을 최소화하여 엔진 효율성의 개선 방안을 제시하고자 한다.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2000.11a
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• pp.12-12
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• 2000

국내에서 최초로 개발된 초등훈련기 KT-1의 추진기관인 터보프롭 엔진(PT6A-62)을 위한 정상상태 성능모사 및 진단 프로그램을 개발하였다. 개발된 정상상태 성능해석 프로그램의 검증을 위해 해석 결과를 엔진 제작사에서 제공한 성능 데이터 및 가스터빈 엔진의 성능모사 프로그램으로 잘 알려진 GASTURB와 비교하였다.(중략)

• Journal of Aerospace System Engineering
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• v.13 no.1
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• pp.38-46
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• 2019

There is a growing interest in engine diagnostic technology for gas turbine engines. An engine simulation program, precisely simulating the engine performance, is required in order to apply it to the engine diagnosis technology for engine health monitoring. In particular, the simulation program can predict not only design point performance but also off-design point and partial load performance in accurate. So the engine simulation program for the 2-spool separate flow type turbofan engine was developed and the JT9D-7R4G engine of PW(Pratt & Whitney) was analyzed. The steady-sate performance analysis is conducted at both design and off-design points in flight path and the differences between analysis results of takeoff and cruise conditions are compared. The effect of Reynold's correction method was analyzed as a scaling method of the engine component performance. The simulation results was compared with NPSS.

• Journal of Advanced Marine Engineering and Technology
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• v.38 no.6
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• pp.744-750
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• 2014

The monitoring and abnormality warning of marine diesel engine are important to take appropriate responses for safety navigation. If maintenance engineers do not take appropriate response because of diagnosis mistakes, it will occur a nasty accident. Therefore, we need integrated monitoring and diagnosis system for supporting a diagnosis objectively. In this paper, we analyze time-series data which measured by real-time, monitor the changing of conditions and trends of the analyzed data. Furthermore, we design and implement a monitoring and diagnosis system for objective supporting of real-time diagnosis. When the integrated monitoring and diagnosis system is adopted, it can help to improve stability of marine diesel engine by providing abnormality warning alarm with appropriate responses.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.12
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• pp.1238-1244
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• 2009

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 for reducing computer calculating time and a signal generation module for simulating real time performance data are used. 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. The reliability and capability of the proposed on-line diagnostic program were confirmed through application to the helicopter engine health monitoring.

• Journal of the Korean Society of Propulsion Engineers
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• v.17 no.2
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• pp.71-83
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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.

• Journal of the Korean Society of Propulsion Engineers
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• v.15 no.2
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• pp.1-7
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• 2011

The UAV(Unmanned Aerial Vehicle) which is remotely operating with long endurance in high altitude must have a very reliable propulsion system. The precise fault diagnostic system of the turboprop engine as a propulsion system of this type UAV can promote reliability and availability. This work proposes a diagnostic method which can identify the faulted components from engine measuring parameter changes using Fuzzy Logic and quantify its faults from the identified fault pattern using Neural Network Algorithms. It is found by evaluation examples that the proposed diagnostic method can detect well not only single type faults but also multiple type faults.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2010.11a
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• pp.499-505
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• 2010

The UAV(Unmanned Aerial Vehicle) which is remotely operating with long endurance in high altitude must have a very reliable propulsion system. The precise fault diagnostic system of the turboprop engine as a propulsion system of this type UAV can promote reliability and availability. This work proposes a diagnostic method which can identify the faulted components from engine measuring parameter changes using Fuzzy Logic and quantify its faults from the identified fault pattern using Neural Network Algorithms. It is found by evaluation examples that the proposed diagnostic method can detect well not only single type faults but also multiple type faults.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2017.05a
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• pp.218-223
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• 2017

This paper deals with a fault diagnosis algorithm using the Kalman filter for a 75-ton Liquid Propellant Rocket Engine (LPRE). To design the Kalman filter, we linearized a non-linear simulation model of a 75-ton LPRE at an operating point, and checked the performance of the Kalman filter by comparing the measured values with estimated values of the states. Then, we artificially injected a fault of the turbopump efficiency into the simulation to confirm the performance of the fault diagnosis algorithm with the developed Kalman filter by comparing the variation of the residuals of the normal state with that of the fault cases.