Title :
Improved identifier to build fuzzy models for qualitative fault diagnosis systems
Author_Institution :
Tech. Univ. of Cluj Napoca, Cluj-Napoca, Romania
fDate :
Aug. 31 1999-Sept. 3 1999
Abstract :
The work suggests some arguments to develop a general structure for a FDI system. Further a possible identifier to be included in this structure is approached. For this kind of identifier we combine a clustering stage followed by a given technique (the Wang´s approach as a case study). The such obtained models are evaluated on the standard experimental Box-Jenkins´ data set and some practical conclusions able to improve the identification approaches with fuzzy models are formulated.
Keywords :
autoregressive moving average processes; fault diagnosis; fuzzy set theory; identification; pattern clustering; Box-Jenkins data set; FDI system; clustering stage; fault diagnosis and isolation; fuzzy models; identifier; qualitative fault diagnosis systems; Control systems; Data models; Fault diagnosis; Fuzzy sets; Mathematical model; Pragmatics; Predictive models; classification; dynamic modelling; fault diagnosis systems; fuzzy data; identification algorithms;
Conference_Titel :
Control Conference (ECC), 1999 European
Conference_Location :
Karlsruhe
Print_ISBN :
978-3-9524173-5-5
