Model-matching and individuation for model-based diagnosis

In model-based systems that reason about the physical world, models must be matched to portions of the physical system. To make model-based systems more readily extensible and re-usable, this thesis explores automating model matching. If matching is automated, one can add a model without specifying every place in the physical equipment where it can be used. One can apply the system to new equipment without identifying every place that every model may be used. However, models address particular individuals, portions of the physical world identified as separate entities. If the set of models is not fixed, one cannot carve the physical system into a fixed set of individuals. Our goals are to develop methods for individuating and matching and to identify characteristics of physical equipment and model that must be made explicit to do so.; Our investigation involves three steps. First we explore examples of engineering models applied to physical systems in textbooks or in manufacturing equipment to identify relevant characteristics. Second, we represent the characteristics and implement matching and individuating methods. Third, we test re-usability and extensibility. If the system can correctly define individuals and match models, even when models call for individuals not previously defined, then we can conclude that we identified some subset of the characteristics required to automate model matching.; We implement two matching and two reconfiguration algorithms which use descriptions of the space occupied by the equipment and the space required by models to reconfigure equipment descriptions for correct matching. Two series of equipment description replacements demonstrate re-usability. Each equipment description in a series has content to match the same model, but has different individuals. Two series of model additions demonstrate extensibility. In each series, the equipment description remain constant, and the added models' individuals vary. The system correctly reconfigures and matches in all cases. We conclude that the 3-dimensional space occupied by the equipment and models along with the distribution of phases, materials, and functional components within that space are required for model matching. The locations and spatial extents of parameters are also required.