Southwest Research Institute (SwRI) investigated the feasibility of integrating remote sensing technology with probability of failure analyses into a monitoring system capable of assessing the structural integrity of critical airframe components. The project demonstrated the viability of remote sensing to discern structural flaw growth along with the integration of sensor data with crack growth analyses in order to assess the health and integrity of a critical structural component.

Particle filters (PF) have been established as the de facto state of the art in failure prognosis, and particularly in the representation and management of uncertainty in long-term predictions when used in combination with outer feedback correction loops. This paper presents a novel Risk-Sensitive PF (RSPF) framework that complements the benefits of the classic approach, by representing the probability of rare and costly events within the formulation of the nonlinear dynamic equation that describes the evolution of the fault condition in time.