Title of article :
Fault detection and isolation based on fuzzy automata
Author/Authors :
Gerasimos G. Rigatos، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2009
Abstract :
Fuzzy automata are proposed for fault diagnosis. The output of the monitored system is partitioned into linear segments which in turn are assigned to pattern classes (templates) with the use of membership functions. A sequence of templates is generated and becomes input to fuzzy automata which have transitions that correspond to the templates of the properly functioning system. If the automata reach their final states, i.e. the input sequence is accepted by the automata with a membership degree that exceeds a certain threshold, then normal operation is deduced, otherwise, a failure is diagnosed. Fault diagnosis of a DC motor and detection of abnormalities in the ECG signal are used as case studies.
Keywords :
Fuzzy automata , fault detection and isolation , pattern matching , Syntactic analysis
Journal title :
Information Sciences
Journal title :
Information Sciences