DocumentCode :
306400
Title :
Sequential fuzzy diagnosis method and identification method of membership function by probability and possibility theories
Author :
Toyota, Toshio ; Chen, Peng
Author_Institution :
Fac. of Comput. Sci. & Syst. Eng., Kyushu Inst. of Technol., Iizuka, Japan
Volume :
2
fYear :
1996
fDate :
14-17 Oct 1996
Firstpage :
1079
Abstract :
When building up a fuzzy diagnosis system for machinery diagnosis, fuzzy relation between failure symptoms and failure categories must be defined for fuzzy inference. However, it is not easy to search out the failure symptoms by which all failure categories can be distinguished perfectly and automatically. In order to resolve the problem, we proposed (1) a new type of symptom parameter function called off-group type of symptom parameter (OGSP); (2) the identification method of the OGSP; (3) the identification method of the membership function of OGSP; (4) the algorithm of sequential fuzzy inference by using the OGSP and its membership function for diagnosis. The efficiency of the above methods has been verified by applying them to the ball bearing diagnosis system
Keywords :
fault diagnosis; fuzzy set theory; inference mechanisms; possibility theory; probability; quality control; OGSP; ball bearing diagnosis system; failure categories; failure symptoms; fuzzy inference; machinery diagnosis; membership function identification method; off-group type; possibility theories; probability theories; sequential fuzzy diagnosis method; Computer science; Density measurement; Fuzzy systems; Inference algorithms; Machinery; Pattern recognition; Possibility theory; Probability density function; Signal processing; Systems engineering and theory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man, and Cybernetics, 1996., IEEE International Conference on
Conference_Location :
Beijing
ISSN :
1062-922X
Print_ISBN :
0-7803-3280-6
Type :
conf
DOI :
10.1109/ICSMC.1996.571233
Filename :
571233
Link To Document :
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