Detection and Prediction of the Performance Deterioration of a Turbofan Engine

Many airlines nowadays demand payment for their engine maintenance costs on an hourly-utilization basis. Thus engine manufacturers have become more focused on performancedeterioration modelling and prognostics capability in order to achieve greater confidence in their cash-flow projections. Hence a method for predicting the performance deterioration of civil aeroengines has been devised. The main aims are to achieve significant benefits in mission scheduling and maintenance planning, as well as to reduce both fuel consumption and the costs of maintenance servicing. An example concerning performancedeterioration prognosis is studied.

[1]  R. A. Pawlowski,et al.  Gas Turbine Engine Health Monitoring and Prognostics , 1999 .

[2]  Michael Roemer,et al.  Probabilistic integration of relevant technologies for a risk-based life prediction of GTE components , 1999 .

[3]  Michael J. Roemer,et al.  Assessment of data and knowledge fusion strategies for prognostics and health management , 2001, 2001 IEEE Aerospace Conference Proceedings (Cat. No.01TH8542).

[4]  Gwilym M. Jenkins,et al.  Time series analysis, forecasting and control , 1971 .

[5]  R. Friend,et al.  ICEMS: a platform for advanced condition-based health management , 2001, 2001 IEEE Aerospace Conference Proceedings (Cat. No.01TH8542).

[6]  Yi-Guang Li,et al.  Performance-analysis-based gas turbine diagnostics: A review , 2002 .

[7]  Hans R. Depold,et al.  The Application of Expert Systems and Neural Networks to Gas Turbine Prognostics and Diagnostics , 1998 .

[8]  Michael J. Roemer,et al.  Advanced diagnostics and prognostics for gas turbine engine risk assessment , 2000, 2000 IEEE Aerospace Conference. Proceedings (Cat. No.00TH8484).

[9]  Dan Ghiocel,et al.  Critical modeling issues for prediction of turbine performance degradation - Use of a stochastic-neuro-fuzzy inference system , 2001 .

[10]  William Scheuren,et al.  Joint Strike Fighter Prognostics and Health Management , 1998 .

[11]  Robert B. Abernethy,et al.  The new Weibull handbook , 1993 .

[12]  Gwilym M. Jenkins,et al.  Time series analysis, forecasting and control , 1972 .

[13]  Andrew Green,et al.  Artificial intelligence for real time diagnostics of gas turbine engines , 1997 .

[14]  M.J. Roemer,et al.  Prognostic enhancements to diagnostic systems for improved condition-based maintenance [military aircraft] , 2002, Proceedings, IEEE Aerospace Conference.

[15]  Michael J. Roemer,et al.  A Prognostic Modeling Approach for Predicting Recurring Maintenance for Shipboard Propulsion Systems , 2001 .

[16]  Douglas C. Montgomery,et al.  Forecasting and time series analysis , 1976 .