An interval propagation and conflict recognition engine for diagnosing continuous dynamic systems
In this paper, a domain-independent conflict recognition engine for model-based diagnosis is presented. The original feature of this engine is that it deals with numerical values that change with time and manages inaccuracies in these values. This is achieved by working on data that are arrays of numerical intervals. Imprecision in models is also processed by means of numerical intervals.
An ATMS extension which encompasses the management of intervals is described. A general coupling of this ATMS to any given constraint propagation procedure by interval refinement is defined in such a way as to focus on the detection of all minimal nogoods.
This engine is thus well adapted for diagnosing continuous time-varying physical systems; a provisional implementation of it has been successfully applied to the diagnosis of analog electronic circuits.
KeywordsIntersection Rule Interval Propagation Total Saturation Sampling Increment Numerical Interval
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