Gas Turbine Engine Real Time Performance Model Presentation for Digital Computers

2008 ◽  
Author(s):  
Author(s):  
Seonghee Kho ◽  
Jayoung Ki ◽  
Miyoung Park ◽  
Changduk Kong ◽  
Kyungjae Lee

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.


1998 ◽  
Vol 31 (4) ◽  
pp. 161-165
Author(s):  
G.G. Kulikov ◽  
T.V. Breikin ◽  
V.Y. Arkov ◽  
P.J. Fleming

Author(s):  
V. Panov

Real-time gas turbine engine models are integral part of techniques such as model-based control and diagnostics. The use of model based techniques to diagnose and adaptively manage degradation of engine components is crucial for operational effectiveness of gas turbines. Since the gas turbine model represents “nominal” engine, it must be adapted or tuned to the performance of the real engine as it deviates from nominal baseline. Implementation of a method for auto-tuning of dynamic gas turbine engine models was considered in this paper, and a non-linear physics based component level model was facilitated as an on-line gas turbine model. Real-time nonlinear dynamic model of an industrial twin-shaft gas turbine with tracking filter was deployed onto the dedicated hardware platform and integrated with the engine control system. In presented application the identified gas turbine health parameters were obtained by the performance estimation tool and included in the observer design. The designed observer detects changes in the engine health parameters and generates model tuners. The model tuning process based on Kalman filtering technique was applied to secure robust execution of real-time dynamic models. Proposed auto-tuning methodology provides a tool for model adaptation, capable of addressing abrupt and gradual degradation of engine performance and at the same time offers a means for model compensation of performance deviation caused by engine-to-engine variation. Although most of performance tracking and diagnostic methods are developed for gas turbine operating at steady state, current trend demonstrates increasing interest in diagnostics during transient operation. Devised method estimates dynamic behaviour of gas turbine health parameters enabling in that way performance tracking under transient conditions. Examples of model adaptation during gas turbine engine transient operation are given in the paper.


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