For aircraft actuation systems, the use of an online diagnostic tool to detect the system damages at their early stages could be exploited to optimize the condition-based maintenance planning, with improvements in safety and operating costs. This paper proposes a computational strategy for the online diagnostics of actuation systems faults, combining an optimal sampling strategy with dierent approaches for parameter identication and exploiting the information gathered from dierent numerical models of the system to estimate its health status. The method leverages low dimensional representations of the quantity to monitor using a signal compression method, based on Proper Orthogonal Decomposition and Self-Organizing Maps, to speed up the solution of the parameter identification problem with the limited hardware resources available onboard. The method is tested for the fault detection of an electromechanical actuator for aircraft flight control systems.

DIAGNOSTICS OF ACTUATION SYSTEMS FAULTS FROM DYNAMIC DATA / Berri, PIER CARLO; Dalla Vedova, Matteo D. L.; Mainini, Laura. - ELETTRONICO. - (2018). ((Intervento presentato al convegno 6th European Conference on Computational Mechanics (ECCM 6) tenutosi a Glasgow nel 11-15 june 2018.

DIAGNOSTICS OF ACTUATION SYSTEMS FAULTS FROM DYNAMIC DATA

BERRI, PIER CARLO;Matteo D. L. Dalla Vedova;Laura Mainini
2018

Abstract

For aircraft actuation systems, the use of an online diagnostic tool to detect the system damages at their early stages could be exploited to optimize the condition-based maintenance planning, with improvements in safety and operating costs. This paper proposes a computational strategy for the online diagnostics of actuation systems faults, combining an optimal sampling strategy with dierent approaches for parameter identication and exploiting the information gathered from dierent numerical models of the system to estimate its health status. The method leverages low dimensional representations of the quantity to monitor using a signal compression method, based on Proper Orthogonal Decomposition and Self-Organizing Maps, to speed up the solution of the parameter identification problem with the limited hardware resources available onboard. The method is tested for the fault detection of an electromechanical actuator for aircraft flight control systems.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2710288
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