DocumentCode :
3483180
Title :
Fuzzy neural networks pattern recognition method and its application in ultrasonic detection for bonding defect of thin composite materials
Author :
Yan-Hong, Xu ; Ze, Zhang ; Kun, Liu ; Guan-Ying, Zhang
Author_Institution :
Coll. of Electron. Inf. Eng., Inner Mongolia Univ., Hohhot, China
fYear :
2009
fDate :
5-7 Aug. 2009
Firstpage :
1345
Lastpage :
1349
Abstract :
Aiming at the problems in pattern recognition of bonding defect of thin composite materials, a new fuzzy neural network (FNN) pattern recognition method was proposed via taking full advantage of processing fuzzy information of the fuzzy pattern recognition and self-learning of the neural network (NN) pattern recognition. The structure characteristics and realization approach of the algorithm were discussed detailed. The results indicated that the method could effectively recognize the bonding defect of thin composite materials, and also lay the foundation for quantization of results.
Keywords :
bonds (chemical); fuzzy neural nets; nanocomposites; pattern recognition; bonding defect; fuzzy neural networks; pattern recognition method; self-learning; thin composite materials; ultrasonic detection; Automation; Bonding; Composite materials; Fuzzy logic; Fuzzy neural networks; Fuzzy reasoning; Fuzzy sets; Fuzzy systems; Neural networks; Pattern recognition; Fuzzy neural network; bonding defect; pattern recognition; ultrasonic detection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Automation and Logistics, 2009. ICAL '09. IEEE International Conference on
Conference_Location :
Shenyang
Print_ISBN :
978-1-4244-4794-7
Electronic_ISBN :
978-1-4244-4795-4
Type :
conf
DOI :
10.1109/ICAL.2009.5262784
Filename :
5262784
Link To Document :
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