Abstract

 
 
 The PHM (Prognostics and Health Monitoring) applications play an increasingly important role on the aeronautical industry and can provide a wide range of benefits for complex systems, such as aircraft landing gears (LDG). Indeed forecasting the RUL (Remaining Useful Life) of the landing gear subsystems can enable condition–based maintenance, improve the aircraft availability and reduce unscheduled events. The purpose of this work is to investigate nominal and degraded simulated retraction times of a landing gear and to apply a prognostics approach, specifically the particle filter (PF) algorithm, from which the RUL can be predicted at a given confidence level.
 
 
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