Seonghee Kho

Component Map Generation of a Gas Turbine Using Genetic Algorithms

In order to estimate the precise performance of the existing gas turbine engine, the component maps with more realistic performance characteristics are needed. Because the component maps are the engine manufacturers propriety obtained from very expensive experimental tests, they are not provided to the customers, generally. Therefore, because the engineers, who are working the performance simulation, have been mostly relying on component maps scaled from the similar existing maps, the accuracy of the performance analysis using the scaled maps may be relatively lower than that using the real component maps. Therefore, a component map generation method using experimental data and the genetic algorithms are newly proposed in this study. The engine test unit to be used for map generation has a free power turbine type small turboshaft engine. In order to generate the performance map for compressor of this engine, after obtaining engine performance data through experimental tests, and then the third order equations, which have relationships with the mass flow function, the pressure ratio, and the isentropic efficiency as to the engine rotational speed, were derived by using the genetic algorithms. A steady-state performance analysis was performed with the generated maps of the compressor by the commercial gas turbine performance analysis program GASTURB (Kurzke, 2001). In order to verify the proposed scheme, the experimental data for verification were compared with performance analysis results using traditional scaled component maps and performance analysis results using a generated compressor map by genetic algorithms (GAs). In comparison, it was found that the analysis results using the generated map by GAs were well agreed with experimental data. Therefore, it was confirmed that the component maps can be generated from the experimental data by using GAs and it may be considered that the more realistic component maps can be obtained if more various conditions and accurate sensors would be used.

Intelligent performance diagnostics of a gas turbine engine using user‐friendly interface neural networks

In this study, in order to facilitate application of the NNs as well as to provide user‐friendly conditions, a performance diagnostic computer code using MATLAB® was newly proposed. As a result, not only more precise and prompt analysis results can be obtained due to use of the toolbox in MATLAB® on diagnosis and numerical analysis, but also the graphical user interface platform can be realized. The proposed engine diagnostics system is able to train the BPN with each fault pattern and then construct the total training network by assembling the trained BPNs. The database for network learning and test was constructed using a gas turbine performance simulation program. In order to investigate reliability on construction of the database for diagnostic results, an analysis is performed with five combination cases of 40 fault patterns. Finally, a diagnostic application example for the PT6A‐62 turboprop engine is performed using the trained network with the database, which represents the best diagnostic results among test sets.

Steady-State and Transient Performance Modeling of Smart UAV Propulsion System Using SIMULINK

Because an aircraft gas turbine operates under various flight conditions that change with altitude, flight velocity, and ambient temperature, the performance estimation that considers the flight conditions must be known before developing or operating the gas turbine. More so, for the unmanned aerial vehicle (UAV) where the engine is activated by an onboard engine controller in emergencies, the precise performance model including the estimated steady-state and transient performance data should be provided to the engine control system and the engine health monitoring system. In this study, a graphic user interface (GUI) type steady-state and transient performance simulation model of the PW206C turboshaft engine that was adopted for use in the Smart UAV was developed using SIMULINK for the performance analysis. For the simulation model, first the component maps including the compressor, gas generator turbine, and power turbine were inversely generated from the manufacturer’s limited performance deck data by the hybrid method. For the work and mass flow matching between components of the steady-state simulation, the state-flow library of SIMULINK 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 the manufacturer’s performance deck data. According to comparison results, it was confirmed that the steady-state model agreed well with the deck data within 3% in all flight envelopes. In the transient performance simulation model, the continuity of mass flow (CMF) method was used, and the rotational speed change was calculated by integrating the excess torque due to the transient fuel flow change using the Runge–Kutta method. In this transient performance simulation, the turbine overshoot was predicted.

Development of On-Line Performance Diagnostics Program of a Helicopter Propulsion System

The engine health monitoring system has been generally applied to the aircraft system to improve reliability and durability of the aircraft propulsion system and to minimize its operational cost. The helicopter flies at low altitude level flight mode in its own operational range comparing to other aircraft categories. The low level flight means that the engine operates at variable atmospheric condition such as hot and cold temperature, snow, heavy rain, etc. Furthermore, it may increase the possibility of foreign object ingestion, such as sand, dust, etc., i.e. this operating condition gives rise to damages of engine gas path components. Because types and severities of most helicopter engine faults are very complicate, the conventional model based fault diagnostic approach like the GPA (Gas Path Analysis) method is not adequate to monitor such a complex engine fault condition. An on-line diagnostic program was developed by using SIMULINK, where measurement signals were simulated by an input module. This study proposes a neural network algorithm for calculating variation of mass flow and efficiency in each engine component from measuring data. The neural network was trained by damages at each component such as compressor, compressor turbine or power turbine. The used database for training the neural network was obtained from simulation under various flight conditions. Reliability and capability of the developed on-line diagnostics program were evaluated through application to a helicopter engine health monitoring.Copyright

Development of Condition Monitoring Test Cell Using Micro Gas Turbine Engine

This study is aim to be programmed the simulation which is available for real-time performance analysis so that is to be developed gas turbine engine’s condition monitoring system with analyzing difference between performance analysis results and measuring data from test cell. In addition, test cell created by this study have been developed to use following applications: to use for learning principals and mechanism of gas turbine engine in school, and to use performance test and its further research for variable operating conditions in associated institutes. The maximum thrust of the micro turbojet engine is 137 N (14 kgf) at 126,000 rpm of rotor rotational speed if the Jet A1 kerosene fuel is used. The air flow rate is measured by the inflow air speed of duct, and the fuel flow is measured by a volumetric fuel flowmeter. Temperatures and pressures are measured at the atmosphere, the compressor inlet and outlet and the turbine outlet. The thrust stand was designed and manufactured to measure accurately the thrust by the load cell. All measuring sensors are connected to a DAQ (Data Acquisition) device, and the logging data are used as function parameters of the program, LabVIEW. The LabVIEW is used to develop the engine condition monitoring program. The proposed program can perform both the reference engine model performance analysis at an input condition and the real-time performance analysis with real-time variables. By comparing two analysis results the engine condition can be monitored. Both engine performance analysis data and monitoring results are displayed by the GUI (Graphic User Interface) platform.Copyright

Development of Practical Integral Condition Monitoring System for a Small Turbojet Engine Using MATLAB/SIMULINK and LabVIEW

Abstract The engine performance condition monitoring systems using various methods such as traditional methods including FSA, MCD, SOAP, etc., model based methods including GPAs, Observers, Party Equations and Parameter Estimations and soft computing methods including Neural Networks, Fuzzy Logic and Expert Systems have been developed to monitor the engine condition. This work proposes a practical condition monitoring system of a small turbojet engine to check not only the engine performance condition through comparing between the on-line performance measuring data and the clean performance data calculated by the base engine performance program but also the gas path component condition through comparing the component performance characteristics between the running degraded engine component and the clean engine component. Here the base performance simulation model is built using the inversely generated component maps from the measured performance data using the modified scaling method. The performance analysis results are compared with the experimental test data at the same operating condition. The proposed condition monitoring system is coded in a friendly GUI type program for easy practical application using commercial programs of MATLAB/SIMULINK and LabVIEW.

Development of On-line Performance Diagnostic Program of a Helicopter Turboshaft Engine

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.

Feasibility Assessment for ORC Generation System Development Using Low Temperature Geothermal Water

Since around 70°C of geothermal water exists in Seokmo-do of Republic of Korea, this study is to assess the feasibility of electricity generation by utilizing ORC system, and the pertinent economic impact.It is generally believed that economic feasibility can be secured only when the source of geothermal water is above 100°C in order to generate electricity by operating ORC system.However, there was an exceptional case that ORC system was commercialized by Pratt-Whitney for around 70 °C of geothermal water in the hot springs of Chena, Alaska.The annual average temperature in the hot springs of Chena, Alaska is approximately 1°C whereas that of Seokmo-do is around 11°C, which makes 10°C of annual average temperature difference in operational environment between the two. Thus, the 2 phases of absorption refrigerating machine is considered for the ORC generation system.With establishing ORC system in consideration of operational environment, the feasibility of the development of ORC system in Seokmo-do is assessed by performance analysis and economic feasibility.As a result of the assessment, it is identified that the economic feasibility can be secured if the price of electricity is over

Development of Practical Integral Condition Monitoring System for A Small Turbojet Engine Using SIMULINK and LabVIEW

0.42/kWh same as that of photovoltaic generation as an incentive of the RPS program granted by the Korean government.Copyright

Study on a GUI Type Fault Diagnostic Program for a Turboshaft Engine Using Fuzzy and Neural Networks

In currently developed engine condition monitoring systems, most field engine maintenance engineers have difficulties to use them in fields due to complexity, unpractical use, lack of understanding, etc. Therefore a practical usable engine condition monitoring system must be needed. This work proposes a practical performance condition monitoring of a small turbojet engine through comparing between the on-line performance monitoring data and the initial clean performance data calculated by the base engine performance model. Moreover the proposed monitoring system checks the gas path components` on-line health condition through comparing the component performance characteristics between the running engine represented as a deteriorated engine or a degraded engine and the base engine performance model represented as a clean engine. The proposed condition monitoring system is coded in a friendly GUI type program for easy practical application by a commercial tool, MATLAB/SIMULINK and LabVIEW.