Abstract
A software environment, called EDEN, that prototypes a recent approach to model-based diagnosis of discrete-event systems, is presented. The environment integrates a specification language, called SMILE, a model base, and a diagnostic engine. SMILE enables the user to create libraries of models and systems, which are permanently stored in the model base, wherein both final and intermediate results of the diagnostic sessions are hosted as well. Given the observation of a physical system gathered during its reaction to an external event, the diagnostic engine performs the a posteriori reconstruction of all the possible evolutions of the system over time and, then, draws candidate diagnoses out of them. The diagnostic method is described using a simplified example within the domain of power transmission networks. Strong points of the method include compositional modeling, support for model update, ability to focus on any sub-system, amenability to parallel execution, management of multiple faults, and broad notions of system and observation.
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Lamperti, G., Zanella, M. EDEN: An Intelligent Software Environment for Diagnosis of Discrete-Event Systems. Applied Intelligence 18, 55–77 (2003). https://doi.org/10.1023/A:1020974704946
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DOI: https://doi.org/10.1023/A:1020974704946