Quantitative Fault Diagnosability Performance of Linear Dynamic Descriptor Models
A theory is developed for quantifying fault detectability and fault
isolability properties of time discrete linear dynamic models. Based
on the model, a stochastic characterization of system behavior in
different fault modes is defined and a general measure, called
distinguishability, based on the Kullback-Leibler information, is used
to quantify the difference between the modes. An analysis of
distinguishability as a function of the number of observations is
discussed. This measure is also shown to be closely related to the
fault to noise ratios in residual generators. Further, the
distinguishability of the model is shown to give upper limits of the
fault to noise ratios of residual generators.
Daniel Eriksson, Mattias Krysander and Erik Frisk
22nd International Workshop on Principles of Diagnosis (DX-11),
2011
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