Impact technologies have developed a robust modeling paradigm for actuator fault detection and failure prediction. This model-based approach to prognostics and health management (PHM) applies physical modeling and advanced parametric identification techniques, along with fault detection and failure prediction algorithms, in order to predict the time-to-failure for each of the critical, competitive failure modes within the system. Advanced probabilistic fusion strategies are also leveraged to combine both collaborative and competitive sources of evidence, thus producing more reliable health state information. These algorithms operate only on flight control command/response data. This approach for condition-based maintenance provides reliable early detection of developing faults. As an advantage over 'black-box' health-monitoring schemes, faults and failure modes are traced back to physically meaningful system parameters, providing the maintainer with invaluable diagnostic and prognostic information. The developed model-based reasoner was validated and demonstrated on an electromechanical actuator (EMA) provided by Moog, Inc.
A model-based approach to prognostics and health management for flight control actuators
2004 IEEE Aerospace Conference Proceedings (IEEE Cat. No.04TH8720) ; 6 ; 3551-3562 Vol.6
2004-01-01
1050463 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
11.0702 A Model-Based Approach to Prognostics and Health Management for Flight Control Actuators
British Library Conference Proceedings | 2004
|Prognostics and Health Management Guidelines for Electro-Mechanical Actuators
SAE Technical Papers | 2020
PROGNOSTICS HEALTH MANAGEMENT (PHM) FOR V-22 FLIGHT CONTROL SYSTEM
British Library Conference Proceedings | 2013
|Air Vehicle Prognostics & Health Management
British Library Conference Proceedings | 2000
|