| Abstract
|
In model-based systems that reason about t … In model-based systems that reason about the physical world,models must be matched to portions of the physical system. To makemodel-based reasoning and diagnosis systems more readily extensible andre-usable, this thesis explores automating model matching. If matchingis automated, one can add a model without specifying every place in thephysical equipment where it can be used. One can apply the system to newequipment without identifying every place that every model may be used.However, models address particular {\em individuals}, portions of the physicalworld 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 models and toidentify characteristics of physical equipment that must made explicit forthose methods. Our investigation involves three steps. First we explore examples ofengineering models applied to physical systems found in textbooks or inmanufacturing equipment to identify relevant characteristics. Second, we implement matching methods using the characteristics. Third, we testre-usability and extensibility. If the system can correctly defineindividuals and match some models, even when models call for individuals not previously defined, then we can conclude that we have identified some subset of the characteristics required to automate model matching. The first step of the investigation revealed that a number of modelsused in the domain of fluid processing and chemical manufacturing do notcorrespond to {\em components} such as valves, tanks, or pumps. Manyprinciples apply to regions containing particular materials or phases, orhaving particular parameter values. An example is the Ideal Gas Law, whichapplies to any volume of space occupied by molecules in the gas phase. Individuals for these kinds of models cannot be identified in advance becausethere are too many possible individuals. Previous model-based diagnosiswork assumes the set of individuals is given and fixed. This assumptionexcludes real world diagnosis problems where models like the Ideal Gas Laware required. Identification of this class of models also shows that run-timeindividuation is required to solve certain kinds of problems. We develop two matching and two reconfiguration algorithms which usedescriptions of the space occupied by the equipment and the space required by models to reconfigure individuals at run-time. Two series of equipmentdescription replacements demonstrate re-usability. Each equipment descriptionin a series has content to match the same model, but had represented asdifferent individuals. Two series of model additions demonstrateextensibility. In each series, the equipment description remains constant,and the added models' individuals vary. The system correctly reconfigures and matches in all cases. We conclude that the 3-dimensional space occupiedby the equipment and required by the models along with the distribution ofphases, materials, and functional components within that space are requiredfor model matching. The locations and spatial extents of parameters are alsorequired. al extents of parameters are alsorequired.
|
