Several approaches can be employed in prognostics, to detect incipient failures of primary flight command electromechanical actuators (EMA), caused by progressive wear. The development of a prognostic algorithm capable of identifying the precursors of an electromechanical actuator failure is beneficial for the anticipation of the incoming failure: a correct interpretation of the failure degradation pattern, in fact, can trig an early alert of the maintenance crew, who can properly schedule the servomechanism replacement. The research presented in this paper proposes a prognostic technique, based on approaches derived from optimization methods, able to identify symptoms of an EMA degradation before the actual exhibition of the anomalous behavior; in this case friction failures are considered. An experimental test bench was developed: results show that the method exhibit adequate robustness and a high degree of confidence in the ability to early identify an eventual fault, minimizing the risk of false alarms or not annunciated failures.

Effects of Dry Friction on Linear Electromechanical Actuators: A New Prognostic Method based on Simulated Annealing Algorithm / DALLA VEDOVA, MATTEO DAVIDE LORENZO; Maggiore, Paolo; Pace, Lorenzo. - STAMPA. - (2015), pp. 54-62. ((Intervento presentato al convegno 2015 International Conference on Pure Mathematics - Applied Mathematics (PM-AM 2015) tenutosi a Vienna nel 15-17 March 2015.

Effects of Dry Friction on Linear Electromechanical Actuators: A New Prognostic Method based on Simulated Annealing Algorithm

DALLA VEDOVA, MATTEO DAVIDE LORENZO;MAGGIORE, Paolo;PACE, LORENZO
2015

Abstract

Several approaches can be employed in prognostics, to detect incipient failures of primary flight command electromechanical actuators (EMA), caused by progressive wear. The development of a prognostic algorithm capable of identifying the precursors of an electromechanical actuator failure is beneficial for the anticipation of the incoming failure: a correct interpretation of the failure degradation pattern, in fact, can trig an early alert of the maintenance crew, who can properly schedule the servomechanism replacement. The research presented in this paper proposes a prognostic technique, based on approaches derived from optimization methods, able to identify symptoms of an EMA degradation before the actual exhibition of the anomalous behavior; in this case friction failures are considered. An experimental test bench was developed: results show that the method exhibit adequate robustness and a high degree of confidence in the ability to early identify an eventual fault, minimizing the risk of false alarms or not annunciated failures.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2604983
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