Multi-level Methods for Combined Diagnostics and Prognostics

vides the ability to maintain system health and performance over the life of safety-critical systems. This paper discusses a model-based approach to diagnosis and prognosis of safety-critical systems that combines fault detection, isolation and identification, faultadaptive control, and prognosis into a common framework. At the core of this framework are a set of component oriented physical system models. By incorporating physics of failure models into component models the dynamic behavior of a failing or degrading system can be derived by simulation. Current state information predicts future behavior and performance of the system to guide decision making on system operation and maintenance.