Journal of the Korean Society of Propulsion Engineers (한국추진공학회지)

The Korean Society of Propulsion Engineers (한국추진공학회)
권호 표지
DOI QR코드

DOI QR Code

Study on Condition Monitoring of 2-Spool Turbofan Engine Using Non-Linear GPA(Gas Path Analysis) Method and Genetic Algorithms

2 스풀 터보팬 엔진의 비선형 가스경로 기법과 유전자 알고리즘을 이용한 상태진단 비교연구

  • 공창덕 (조선대학교 항공우주공학과) ;
  • 강명철 (조선대학교 항공우주공학과) ;
  • 박광림 (조선대학교 항공우주공학과)
  • Received : 2013.01.16
  • Accepted : 2013.03.18
  • Published : 2013.04.01
Download PDF
⟨ Previous Next ⟩

Abstract

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.

항공기 가스터빈의 운용율을 극대화 하고 정비 비용을 최소화하기 위해 최근 모델기반방법이나 인공지능방법을 이용한 첨단상태진단기법들을 적용하고 있다. 이 진단 방법들 중 비선형 GPA방법과 유전자 알고리즘을 이용한 엔진 진단방법들이 선형 GPA, 퍼지 로직 및 신경망 이론 등의 타 방법들에 비해 장점을 가지고 있는 것으로 알려졌다. 이에 본 연구에서는 항공기용 AE3007H 터보팬엔진의 상태진단에 비선형 GPA기법과 유전자 알고리즘을 적용한 후 비교를 통해 센서 노이즈와 바이어스가 있는 경우 유전자 알고리즘이 보다 우수한 진단 기법임을 확인하였다.

Keywords

References

  1. Li, Y. G., "Gas Turbine Diagnostics," Lecture notes, Cranfield University, UK, 2002
  2. Urban, L. A., "Gas Turbine Engine Parameter Interrelationships," 2nd Edition, HS UAC, Windsor Locks, CT, 1969
  3. Escher, P. C., "Pythia: An object-oriented Gas Path Analysis Computer Program for General Applications," Ph. D. Thesis, Cranfield University, UK, 1995
  4. Baswell, M. J., "COMPASS-Ground Based Engine Monitoring Program for General Application," SAE-TP-871734, 1987
  5. Winston, H., "Integrating Numeric and Symbolic Processing for Gas Path Maintenance," AIAA-91-501, 1991
  6. Doel, D. I., "TEMPER-A Gas-Path Analysis Tool for Commercial Jet Engines," Journal of Engineering for Gas Turbines and Power, Vol. 116, Jan, 1994
  7. Patel, V. C., "Utilising a Simulink Gas Turbine Engine Motor for Fault Diagosis," Reprints of The IFAC Symposium on Control of Power Plants and Power Systems, Cancum, Mexico, 1995, pp.171-176
  8. Jhou, Ji., "Intelligent Fault Diagnosis with Application to Gas Turbine Engines," PH. D. Thesis, The University of Sheffield, 1998
  9. Taylor, D. L., "Engine Health Diagnostics Using Multiple Operating Point Analysis and Genetic Algorithm Optimization," MSC. Thesis, Cranfield University, 2000
  10. Zedda, M., "Gas Turbine Engine and Sensor Fault Diagnosis," Ph. D. Thesis, Cranfield University, 2000
  11. Smith, H., "U-2000 project description," Cranfield University, 2000
  12. Jane's, Jane's Aero Engine, issue 8, 2000
  13. 공창덕, 강명철, 박광림, "SIMULINK를 이용한 2-스풀 분리 배기방식 터보팬엔진의 구성품 성능 맵 생성 및 성능모사에 관한 연구," 추진공학회지, 제17권, 제1호, 2013, pp.70-79
  14. Diakunchak, I. S., "Performance Deterioration in Industrial Gas Turbines," Journal of Engineering for GasTurbinesand Power, Vol. 114, No 2, 1992, pp.161-167