This paper describes a novel time-varying prognostic modeling framework for computing condition-based residual life distributions of partially degraded aircraft electrical power system (EPS) components. This advanced methodology is suitable for modeling the evolution of degradation signals acquired from aircraft electrical power system components through condition monitoring techniques. The evolution of the degradation signals is modeled as a stochastic process, with fixed and random parameters, and takes into consideration environmental covariates that capture the time-varying nature of the equipment's operating condition. The modeling methodology correlates the degradation signals with the underlying physical transitions that occur prior to component failures to estimate and update the residual life distribution of the system. Since these updated distributions capture current health information as well as the latest operating conditions, they provide precise remaining useful life (RUL) estimates.
Advanced Prognostics for Aircraft Electrical Power Systems
Sae Int. J. Aerosp
Power Systems Conference ; 2008
Sae International Journal of Aerospace ; 1 , 1 ; 1059-1063
2008-11-11
5 pages
Aufsatz (Konferenz)
Englisch
Aircraft Electrical Power Systems Prognostics and Health Management (AEPHM)
SAE Technical Papers | 2004
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