New Approaches for Solving the Diagnosis Problem
Amir Fijany, Farrokh Vatan, Anthony Barrett, Ryan Mackey · 2002
Over the past decade, the number of Earth orbiters and deep-space probes has grown dramatically and is expected to continue to do so in the future as miniaturization technologies drive spacecraft to become more numerous and more complex. This rate of growth has brought a new focus on autonomous and self-preserving systems that depend on fault diagnosis. Although diagnosis is needed for any autonomous system, current approaches are almost uniformly ad hoc, inefficient, and incomplete. Systematic methods of general diagnosis exist in literature, but they all suffer from two major drawbacks that severely limit their practical applications. First, they tend to be large and complex and hence difficult to apply. Second and more importantly, in order to find the minimal diagnosis set, i.e., the minimal set of faulty components, they rely on algorithms with exponential computational cost and hence are highly impractical for application to many systems of interest. In this article, we propose a two-fold approach to overcoming these two limitations and to developing a new and powerful diagnosis engine. First, we propose anovel and compact reconstruction of the general diagnosis engine (GDE) as one