A diagnosis methodology for continuous time measurements using hierarchical signal representations

Abstract

A methodology for automated diagnosis of systems characterized by continuous signals is presented. The methodology requires the definition and construction of several fuzzy automatons each capable of identifying a particular condition. When the diagnostic system is in operation, the time sampled system measurements are presented to all automatons simultaneously. The fuzziness in automaton operation enables input processing from several perspectives, consistent with the operation of the automatons, allowing for toleration of measurement noise and other ambiguities. The methodology is applied to the problem of automatic electrocardiogram diagnosis.