• Journal of the Korean Society of Propulsion Engineers
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• v.8 no.2
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• pp.18-24
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• 2004

A fuel spiking test was performed to measure the surge margin of the compressor in a gas turbine engine. During the test, fuel spiking signal is superposed on the engine controller demand signals and the combined signals are used to control a fuel control valve. For the superposition, a subsystem composed of a fuel controller and a function generator is used. The real engine test was performed at the Altitude Engine Test Facility (AETF) in Korea Aerospace Research Institute (KARI). In the preliminary test, the fuel spiking signals are in good agreement with the dynamic pressure at the fuel line and at the compressor discharge point. After the preliminary test, a fuel spiking test to measure the surge point at a specific engine speed was performed. The test results show that the fuel spiking test is very effective in the measurement of surge.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2012.05a
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• pp.586-591
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• 2012

The solution of maintenance decision support system for the gas turbine engine, which is currently operating in GUNSAN combined cycle power plant, was developed and is consist of online monitoring module, periodic performance trending module, optimal compressor washing interval analysis module and hot component management module. Also, GUI platform was applied to this solution for the user to monitoring the analyzed result of engine performance condition and then to make a decision of the consequent maintenance action. In online condition monitoring module, the performance degradation of engine is provided by the analysis of difference between the real time measurement data compared to exist engine performance. The optimal compressor washing interval module produced the washing interval of maximum net profit value by researching the maintenance expense and the loss profit value corresponds to the performance degradation with economic assessment algorithm. Thus, this solution support the user to enable the optimal maintenance and operation of gas turbine engine with overall analysis of engine condition and main information.

• 한국신재생에너지학회:학술대회논문집
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• 2007.11a
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• pp.642-645
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• 2007

석탄, 폐기물 등 다양한 시료의 가스화 반응을 통해서 발생되는 합성가스는 CO, $H_2$, $CO_2$가 주성분으로 가스엔진, 가스터빈 등의 연료로 사용하여 발전하거나 합성반응을 통해 다양한 화학원료로의 전환이 가능하다. 합성가스를 가스엔진, 가스터빈, 연료전지등의 연료로 사용하는 경우는 고효율 발전이 가능하여 기존 연소방식의 발전과 비교하여 단위 전력 생산량 당 $CO_2$의 배출량이 감소 되며, 여기에 $CO_2$ 분리공정을 적용하면 $CO_2$ 배출량 감소효과를 극대화 할 수 있다. 화석연료의 연소 및 가스화 반응을 통해서 발생하는 이산화탄소의 분리에 대한 많은 연구가 진행되고 있으나, 본 연구에서는 흡착방식을 이용한 합성가스 내의 이산화탄소 분리를 위하여 흡착제를 이용한 이산화탄소의 흡착, 탈착 성능 분석 연구를 수행하였다. 합성가스내의 이산화탄소를 분리하기 위한 흡착제로는 NaX 계열의 zeolite를 이용하였으며, 가스화 반응을 통해 발생한 합성가스를 흡착제에 통과시켜 이산화탄소의 선택적 흡착 여부를 확인하였다. 또한 TPD(Temperature Programmed Desorption)방법을 이용하여 흡착제의 이산화탄소 흡착 성능을 분석하였다.

• Proceedings of the KSME Conference
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• 2001.11b
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• pp.788-793
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• 2001

Test experience with a micro-turbine jet engine is introduced. The engine provides us with valuable opportunities to experience know-hows essential for engine development. It consists of a single radial compressor and a single stage turbine. Engine starting procedure has been established after many trials and errors. Static and dynamic engine performance tests were conducted. Static performance was found to be inferior to that advertised by the manufacturer. Further improvement is needed. Dynamic performance revealed that engine thrust overshoots unfavorably for the purpose of UAV control.

• Journal of the Korean Society of Propulsion Engineers
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• v.2 no.1
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• pp.13-20
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• 1998

A steady-state and dynamic simulation program for a small multi-purpose turboshaft engine with the free power turbine was developed. In order to reduce developing cost, time and risk, a turbojet engine whose performance was well-known was used for the gas generator, and life time was improved by replacing turbine material and by using Larson-Miller curves. The component characteristic of the power turbine was derived from scaling the gas generator turbine. Equilibrium equations of mass flow rate and work were used for the steady-state performance analysis, and the Constant Flow Method(CMF) was used for the dynamic performance simulation. The step fuel scheduling was carried out for acceleration in the dynamic simulation. Through this simulation, it was found that the overshoot of the turbine inlet temperature exceeded over the compressor turbine limit temperature.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2006.05a
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• pp.209-212
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• 2006

In this study, Support Vector Machine(SVM) and Artificial Neural Network(ANN) are used for developing the defect diagnostic algorithm of the aircraft turbo-shaft engine. Effect of altitude variation on the Defect Diagnostics algorithm has been included and evaluated. Separate learning Algorithm(SLA) suggested with ANN to loam the performance data selectively after classifying the position of defects by SVM improves the classification speed and accuracy.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2007.04a
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• pp.245-249
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• 2007

In this study a model-based diagnostic method using the Neural Network was proposed for PW206C turbo shaft engine and performance model was developed by SIMULINK. Fault and test database to build the NN was obtained at various off-design operating range such as flight altitude, flight Mach number and gas generator rotational speed variation. According to the fault detection analysis results, it was confirmed that the proposed fault detection method could find well the fault of compressor, compressor turbine and power turbine at on-design point as well as off-design point conditions.

• Journal of the Korean Society of Propulsion Engineers
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• v.11 no.3
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• pp.29-34
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• 2007

In this study a model-based diagnostic method using the Neural Network was proposed for PW206C turbo shaft engine and performance model was developed by SIMULINK. Fault and test database to build the NN was obtained at various off-design operating range such as flight altitude, flight Mach number and gas generator rotational speed variation. According to the fault detection analysis results, it was confirmed that the proposed fault detection method could find well the fault of compressor, compressor turbine and power turbine at on-design point as well as off-design point conditions.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2006.05a
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• pp.213-217
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• 2006

An intelligent performance diagnostic program using the Neural Network was proposed for PW206C turboshaft engine. It was selected as a power plant for the tilt rotor type Smart UAV (Unmanned Aerial Vehicle) which has been developed by KARI (Korea Aerospace Research Institute). For teaming the NN, a BPN with one hidden, one input and one output layer was used. The input layer had seven neurons of variations of measurement parameters such as SHP, MF, P2, T2, P4, T4 and T5, and the output layer used 6 neurons of degradation ratios of flow capacities and efficiencies for compressor, compressor turbine and power turbine. Database for network teaming and test was constructed using a gas turbine performance simulation program. From application results for diagnostics of the PW206C turboshaft engine using the learned networks, it was confirmed that the proposed diagnostics algorithm could detect well the single fault types such as compressor fouling and compressor turbine erosion.

• Journal of the Korean Society of Propulsion Engineers
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• v.10 no.2
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• pp.15-22
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• 2006

An intelligent performance diagnostic program using the Neural Network was proposed for PW206C turboshaft engine. It was selected as a power plant for the tilt rotor type Smart UAV(Unmanned Aerial Vehicle) which is being developed by KARI (Korea Aerospace Research Institute). For teeming the NN(Neural Network), a BPN(Back Propagation Network) with one hidden, one input and one output layer was used. The input layer has seven neurons: variations of measurement parameters such as SHP, MF, P2, T2, P4, T4 and T5, and the output layer uses 6 neurons: degradation ratios of flow capacities and efficiencies for compressor, compressor turbine and power turbine, respectively, Database for network teaming and test was constructed using a gas turbine performance simulation program. From application of the learned networks to diagnostics of the PW206C turboshaft engine, it was confirmed that the proposed diagnostics algorithm could detect well the single fault types such as compressor fouling and compressor turbine erosion.