Combined qualitative-quantitative steady-state diagnosis of continuous-valued systems

This paper discusses systematic methods for diagnosis of complex engineering systems combining qualitative and quantitative analysis of analytic constraint equation system models to generate more precise and accurate candidates. Candidates generated from a qualitative steady-state partial explanation model are refined with available ordinal information on the magnitude of component parameter deviations. In addition, an incremental algorithm is implemented to efficiently process sequences of measurements. Empirical analysis demonstrates that accuracy and resolution of minimal candidate generation are improved by including ordinal information. This avoids the practical problems encountered when reasoning with pure quantitative information.