DocumentCode :
441881
Title :
A fault diagnosis method for polymeric reaction process based on soft measuring hybrid model
Author :
Yang, Hui-Zhong ; Zhang, Su-Zhen ; Tao, Zhen-Lin ; Cui, Bao-Tong
Author_Institution :
Res. Center of Control Sci. & Control Eng., Southern Yangtze Univ., Wuxi, China
Volume :
4
fYear :
2005
fDate :
18-21 Aug. 2005
Firstpage :
2499
Abstract :
This paper presented a fault diagnostic method for polymeric reaction process by means of the technique of adopted fuzzy pattern recognition. Based on soft measuring hybrid model, a threshold value principle and maximum membership degree principle are combined to diagnose faults. The fault diagnostic method is used for a typical polymeric reaction productive process - Polyacrylonitrile productive process, and it is proved that it can not only get accurate diagnosis results but also rectify the output of the hybrid model with the help of the information from morbid symptom set.
Keywords :
fault diagnosis; fuzzy systems; pattern recognition; polymerisation; process control; Polyacrylonitrile productive process; fault diagnosis; fuzzy pattern recognition; polymeric reaction productive process; soft measuring hybrid model; threshold value principle; Automatic control; Control engineering; Electrical equipment industry; Fault detection; Fault diagnosis; Fuzzy control; Fuzzy systems; Nonlinear dynamical systems; Pattern recognition; Polymers; Fault diagnosis; Fuzzy pattern recognition; Polymeric reaction process; Soft measuring hybrid model; Threshold value principle;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location :
Guangzhou, China
Print_ISBN :
0-7803-9091-1
Type :
conf
DOI :
10.1109/ICMLC.2005.1527364
Filename :
1527364
Link To Document :
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