A Combined Model-Based and Data-Driven Prognostic Approach for Aircraft System Life Management

Failure prognostic algorithms aim to characterize the evolution of incipient fault conditions in complex dynamic processes, thus allowing to estimate of the remaining useful life (RUL) of subsystems and components.

Several examples can be used here to illustrate the range of possible applications for these algorithms: electro-mechanical systems, continuous-time manufacturing processes, structural damage analysis, and even fault tolerant software architectures. Most of them have in common the fact that they are highly complex, nonlinear, and affected by large-grain uncertainty. We introduce in this chapter an integrated failure prognosis architecture that is applicable to a variety of aircraft systems and industrial processes.