Two communities work in parallel in model-based diagnosis:
FDI and DX. In this work an integration of the FDI and the DX communities
is proposed. Only relevant information for the identification of the
minimal diagnosis is used. In the first step, the system is divided into
clusters of components, and each cluster is separated into nodes. The
minimal and necessary set of contexts is then obtained for each cluster.
These two steps automatically reduce the computational complexity
since only the essential contexts are generated. In the last step, a signature
matrix and a set of rules are used in order to obtain the minimal
diagnosis. The evaluation of the signature matrix is on-line, the rest of
the process is totally off-line.Ministerio de Ciencia y Tecnología DPI2003-07146-C02-0
