Prognostic Health Management of Aircraft Power Generators

In this paper, prognostic tools are developed to detect the onset of electrical failures in an aircraft power generator, and to predict the generator's remaining useful life (RUL). Focus is on the rotor circuit since failure mode, effects, and criticality analysis (FMECA) studies indicate that it is a high priority candidate for condition monitoring. A signature feature is developed and tested by seeded fault experiments to verify that the initial stages of rotor faults are observable under diverse generator load conditions. A tracking filter is used to assess the damage state and predict generator RUL. This information helps to avoid unexpected failures while reducing the overall life-cycle cost of the system.

[1]  D. C. Swanson,et al.  A general prognostic tracking algorithm for predictive maintenance , 2001, 2001 IEEE Aerospace Conference Proceedings (Cat. No.01TH8542).

[2]  L. Eren,et al.  Detecting motor bearing faults , 2004, IEEE Instrumentation & Measurement Magazine.

[3]  E. Keller,et al.  Real-time nondestructive evaluation of airframe structures for health monitoring and residual life prediction , 2001, 20th DASC. 20th Digital Avionics Systems Conference (Cat. No.01CH37219).

[4]  Roger Shuttleworth,et al.  Brushless exciter model , 1994 .

[5]  M. Poloujadoff,et al.  Modeling of polyphase brushless exciter behavior for failing diode operation , 1998 .

[6]  T. D. Batzel,et al.  Predictive diagnostics for the main field winding and rotating rectifier assembly in the brushless synchronous generator , 2003, 4th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives, 2003. SDEMPED 2003..

[7]  A. Ray,et al.  Anomaly detection for health management of aircraft gas turbine engines , 2005, Proceedings of the 2005, American Control Conference, 2005..

[8]  Thiagalingam Kirubarajan,et al.  Useful lifetime tracking via the IMM , 2002, SPIE Defense + Commercial Sensing.

[9]  Donald C. Wunsch,et al.  Vibration analysis via neural network inverse models to determine aircraft engine unbalance condition , 2003, Proceedings of the International Joint Conference on Neural Networks, 2003..

[10]  L.V. Kirkland,et al.  Avionics health management: searching for the prognostics grail , 2004, 2004 IEEE Aerospace Conference Proceedings (IEEE Cat. No.04TH8720).

[11]  M.G. Pecht,et al.  Prognostics and health management of electronics , 2008, IEEE Transactions on Components and Packaging Technologies.

[12]  C. Wilkinson,et al.  Prognostic and health management for avionics , 2004, 2004 IEEE Aerospace Conference Proceedings (IEEE Cat. No.04TH8720).

[13]  H. W. Gayek Behavior of Brushless Aircraft Generating Systems , 1963, IEEE Transactions on Aerospace.

[14]  C. Teal,et al.  Managed aircraft wiring health directly relates to improved avionics performance , 2000, 19th DASC. 19th Digital Avionics Systems Conference. Proceedings (Cat. No.00CH37126).

[15]  J. Mathew,et al.  The condition monitoring of rolling element bearings using vibration analysis , 1984 .

[16]  H. Mirabedini,et al.  The sort of fault diagnosis in large synchronous generators by analytic hierarchy process (AHP) method , 2001, Canadian Conference on Electrical and Computer Engineering 2001. Conference Proceedings (Cat. No.01TH8555).

[17]  L.U. Gokdere,et al.  Lifetime control of electromechanical actuators , 2005, 2005 IEEE Aerospace Conference.

[18]  F.C. Trutt,et al.  Condition monitoring of brushless three-phase synchronous generators with stator winding or rotor circuit deterioration , 2001, Conference Record of the 2001 IEEE Industry Applications Conference. 36th IAS Annual Meeting (Cat. No.01CH37248).

[19]  J. I. Taylor,et al.  Identification of Bearing Defects by Spectral Analysis , 1980 .

[20]  Om P. Malik,et al.  A MICROPROCESSOR-BASED FAULT MONITOR FOR ROTATING RECTIFIERS OF BRUSHLESS AC EXCITERS USING A PATTERN-RECOGNITION APPROACH , 1996 .

[21]  T. Horiuchi,et al.  Long-term reliability evaluation of power semiconductor devices used in substation rectifiers , 1998, Proceedings of the 10th International Symposium on Power Semiconductor Devices and ICs. ISPSD'98 (IEEE Cat. No.98CH36212).

[22]  Robert J. Marks,et al.  Development of a technique for on-line detection of shorts in field windings of turbine-generator rotors: circuit design and testing , 2000 .

[23]  R. Friend,et al.  A probabilistic, diagnostic and prognostic system for engine health and usage management , 2000, 2000 IEEE Aerospace Conference. Proceedings (Cat. No.00TH8484).

[24]  S. Zein-Sabatto,et al.  Analysis of vibration signal's time-frequency patterns for prediction of bearing's remaining useful life , 2001, Proceedings of the 33rd Southeastern Symposium on System Theory (Cat. No.01EX460).

[25]  B. Vermeire,et al.  Practical application of PHM/prognostics to COTS power converters , 2005, 2005 IEEE Aerospace Conference.

[26]  Yaakov Bar-Shalom,et al.  Estimation and Tracking: Principles, Techniques, and Software , 1993 .

[27]  R. A. Boenning,et al.  Marginal checking-a technique to detect incipient failures , 1989, Proceedings of the IEEE National Aerospace and Electronics Conference.

[28]  David C. Swanson,et al.  PROGNOSTIC MODELLING OF CRACK GROWTH IN A TENSIONED STEEL BAND , 2000 .

[29]  J. L. Miller,et al.  In-line oil debris monitor for aircraft engine condition assessment , 2000, 2000 IEEE Aerospace Conference. Proceedings (Cat. No.00TH8484).

[30]  R. M. Kent,et al.  Structural health monitoring: degradation mechanisms and system requirements , 2000, 19th DASC. 19th Digital Avionics Systems Conference. Proceedings (Cat. No.00CH37126).

[31]  David C. Swanson Signal Processing for Intelligent Sensor Systems , 2000 .