• International Journal of Aeronautical and Space Sciences
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• v.10 no.2
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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.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2005.11a
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• pp.289-292
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• 2005

Because of accumulation of operation time, the performance of main components(compressor, combustor, turbine, etc.) come to be deteriorated in gas-turbine engine. So, high reliability and minimun of expense are important problem for engine manufacturer and user in operation of gas-turbine engine. In this study, the diagnostic code of the engine performance using the thermodynamic sensitivity between the sensed parameters and the health parameters has been developed without an application of the commercial program. The single performance deterioration of the turbo-shaft engine has been estimated with this code.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.187-194
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• 2008

Because the types and severities of most engine faults are various and complex, it is not easy that the conventional model based fault detection approach like the GPA(Gas Path Analysis) method can monitor all engine fault conditions. Therefore this study proposed newly a diagnostic algorithm for isolating and diagnosing effectively the faulted components of the smart UAV propulsion system, which has been developed by KARI(Korea Aerospace Research Institute), using the fuzzy logic and the neural network algorithms. A precise performance model should be needed to perform the model-based diagnostics. The based engine performance model was developed using SIMULINK. For the work and mass flow matching between components of the steady-state simulation, the state-flow library was applied. The proposed steady-state performance model can simulate off-design point performance at various flight conditions and part loads, and in order to evaluate the steady-state performance model their simulation results were compared with manufacturer's performance deck data. According to comparison results, it was confirm that the steady-state model well agreed with the deck data within 3% in all flight envelop. The diagnosis procedure of the proposed diagnostic system has the following steps. Firstly after obtaining database of fault patterns through performance simulation, then secondly the diagnostic system was trained by the FFBP networks. Thirdly after analyzing the trend of the measuring parameters due to fault patterns, then fourthly faulted components were isolated using the fuzzy logic. Finally magnitudes of the detected faults were obtained by the trained neural networks. Because the detected faults have almost same as degradation values of the implanted fault pattern, it was confirmed that the proposed diagnostic system can detect well the engine faults.

• 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.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.24 no.9
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• pp.1157-1165
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• 2000

A classic examples of the abnormal combustions are the knock and misfire, which raise noxious performance and life of the engine. A heavy knock can also cause severe damages to the engine itself, which gives more reason why it must be detected and corrected. With the response of the today's requirements, we have researched the new diagnostic system which uses the breakdown voltage characteristics between electrodes of spark plug. This breakdown voltage depends on the pressure, temperature and even the shape and material of electrodes. But there is no data of breakdown voltage in case of using the spark plug as a electrodes. So, in this study, we show the breakdown voltage characteristic by pressure and temperature in constant volume bomb, which will make it possible to diagnose the engine combustion phenomenon.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• v.y2005m4
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• pp.252-255
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• 2005

The operation of a gas-turbine engine gradually deteriorates the performance of its main components and often generates the defects of its components. The GPA method has been usually used for the diagnosis of the deterioration. In this study, the diagnostic code of the engine performance using the thermodynamic sensitivity between the sensed parameters and the health parameters has been developed without an application of the commercial program. The single performance deterioration of the turbo-shaft engine for SUAV has been estimated with this code.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.7
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• pp.1-14
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• 1999

In the present study, the flame factor which primarily influence the simulation accuracy of the combustion process in a gasoline engine was modeled as a nonlinear function of turbulent intensity to laminar flame speed ratio. Multi-length-scale production rate model for turbulent kinetic energy equation was introduced to consider the different length scales of the swirling and tumbling motions in cylinder on the production rte of turbulent kinetic energy. By7 introducing the multi-length-scale production rate model for the turbulent kinetic energy equation, the predictions of turbulent burning velocity , cylinder pressure, mass burning rate and engine performance of a gasoline engine can much be improved.

• International Journal of Aeronautical and Space Sciences
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• v.9 no.1
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• pp.100-110
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• 2008

It is not easy to monitor and identify all engine faults and conditions using conventional fault detection approaches like the GPA (Gas Path Analysis) method due to the nature and complexity of the faults. This study therefore focuses on a model based diagnostic method using Neural Network algorithms proposed for fault detection on a turbo shaft engine (PW 206C) selected as the power plant for a tilt rotor type unmanned aerial vehicle (Smart UAV). The model based diagnosis should be performed by a precise performance model. However component maps for the performance model were not provided by the engine manufacturer. Therefore they were generated by a new component map generation method, namely hybrid method using system identification and genetic algorithms that identifies inversely component characteristics from limited performance deck data provided by the engine manufacturer. Performance simulations at different operating conditions were performed on the PW206C turbo shaft engine using SIMULINK. In order to train the proposed BPNN (Back Propagation Neural Network), performance data sets obtained from performance analysis results using various implanted component degradations were used. The trained NN system could reasonably detect the faulted components including the fault pattern and quantity of the study engine at various operating conditions.

• Transactions of the Korean Society of Automotive Engineers
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• v.5 no.1
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• pp.27-37
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• 1997

Internal combustion engine is the main source of environmental pollutants and therefore better technology is required to reduce harmful elements from the exhaust gases all over the world. Especially, harmful elements from the exhaust gases are caused by incomplete combustion of mixture inside the engine cylinder and this abnormal combustion like misfire or partial burning is the direct cause of the air pollution and engine performance degradation. the object of this research is to detect abnormal combustion like misfire and to keep the engine performance in the optimal operating state. Development of a new system therefore could be applied to a real car. To realize this, the spark-plug in a conventional ignition system is used as a misfire detection sensor and breakdown voltage is analyzed. In this research, bias voltage(about 3kV) was applied to the electrodes of spark-plug and breakdown voltage signal is obtained. This breakdown voltage signal is analyzed and found that a combustion phenomena in engine cylinder has close relationship with harmonic coefficient K which was introduced in this research. Newly developed combustion diagnostic method( breakdown voltage signal analysis) from this research can be used for the combustion diagnostic and combustion control system in an real car.

• 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.