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A Study on the Extraction of Feature Variables for the Pattern Recognition of Welding Flaws  

Kim, Jae-Yeol (조선대학교 기계공학부)
Roh, Byung-Ok (선문대학교 산업공학과)
You, Sin (목포과학대학 컴퓨터응용기계과)
Kim, Chang-Hyun (조선대학교 대학원 정밀기계공학과)
Ko, Myung-Soo (조선대학교 대학원 정밀기계공학과)
Publication Information
Journal of the Korean Society for Precision Engineering / v.19, no.11, 2002 , pp. 103-111 More about this Journal
Abstract
In this study, the natural flaws in welding parts are classified using the signal pattern classification method. The storage digital oscilloscope including FFT function and enveloped waveform generator is used and the signal pattern recognition procedure is made up the digital signal processing, feature extraction, feature selection and classifier design. It is composed with and discussed using the distance classifier that is based on euclidean distance the empirical Bayesian classifier. feature extraction is performed using the class-mean scatter criteria. The signal pattern classification method is applied to the signal pattern recognition of natural flaws.
Keywords
Non Destructive Test; Ultrasonic Inspection; Welding Flaw; Feature Variables Extraction; Pattern Recognition;
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