Artificial Intelligence
A theory of diagnosis from first principles
Artificial Intelligence
Characterizing diagnoses and systems
Artificial Intelligence
Possible conflicts: a compilation technique for consistency-based diagnosis
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Fault diagnosis of electric railway traction substation with model-based relation guiding algorithm
Expert Systems with Applications: An International Journal
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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.