Automatic Detection of Weld Defects in Pressure Vessels using Fuzzy Neural Network
نویسندگان
چکیده
منابع مشابه
Automatic Detection of Weld Defects in Pressure Vessels using Fuzzy Neural Network
The interpretation of possible weld discontinuities in industrial radiography is ensured by human interpreters. The types of defects are porosity, lack of penetration, shrinkage, and fracture. It is thus desirable to develop computer-aided techniques to assist the interpreter in evaluating the quality of the welded joints. Using back propagation algorithm the images of weld defects are trained....
متن کاملAutomatic Detection of Weld Defects in Pressure Vessels using Fuzzy Neural Network
The interpretation of possible weld discontinuities in industrial radiography is ensured by human interpreters. The types of defects are porosity, lack of penetration, shrinkage, and fracture. It is thus desirable to develop computer-aided techniques to assist the interpreter in evaluating the quality of the welded joints. Using back propagation algorithm the images of weld defects are trained....
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The radiography technique (RT) used in non-destructive testing (NDT) of welds has evolved rapidly in recent decades and has become an established technology in the field of weld assessment. RT is widely used as an inspection tool for detecting flaws inside welded structures, pressure vessels, structural members and pipelines(1). Most radiographic exposures and film interpretations in RT are sti...
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ژورنال
عنوان ژورنال: International Journal of Computer Applications
سال: 2010
ISSN: 0975-8887
DOI: 10.5120/35-638