DocumentCode
1561551
Title
The research of defect recognition for radiographic weld image based on fuzzy neural network
Author
Xiao-Guang, Zhang ; Xu Jian-Jian ; Yu, Li
Author_Institution
Inst. of Appl. Phys., Nanjing Univ., China
Volume
3
fYear
2004
Firstpage
2661
Abstract
This paper presents a method of automatic recognition of weld defects based on fuzzy neural network (FNN). The weld image is preprocessed to extract defect features, according to which 8 characteristic parameters are selected, and the FNN model used for defects recognition is set up. Here inputted samples of the FNN model are fuzzified using π function. And weld defects of different types are processed using a three-layer neural network and BP learning algorithm. Using forty-two training samples and seven testing samples for examination, the results show that this model can recognize weld defects with better effects. This research indicates that FNN has excellent performance for the defect recognition in weld image.
Keywords
backpropagation; feature extraction; fuzzy neural nets; fuzzy set theory; image recognition; multilayer perceptrons; nondestructive testing; radiography; welding; BP learning algorithm; Pi function; automatic recognition; feature extraction; fuzzy neural network model; fuzzy set theory; radiographic weld image; three layer neural network; weld defect recognition; Biological neural networks; Character recognition; Feature extraction; Fuzzy neural networks; Image recognition; Image segmentation; Inspection; Noise reduction; Radiography; Welding;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
Print_ISBN
0-7803-8273-0
Type
conf
DOI
10.1109/WCICA.2004.1342080
Filename
1342080
Link To Document