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Availability Verification of Feature Variables for Pattern Classification on Weld Flaws  

Kim, Chang-Hyun (전남대학교 공과대학 전자컴퓨터공학부)
Kim, Jae-Yeol (조선대학교 공과대학 메카트로닉스공학과)
Yu, Hong-Yeon (전남대학교 공과대학 전자컴퓨터공학부)
Hong, Sung-Hoon (전남대학교 공과대학 전자컴퓨터공학부)
Publication Information
Transactions of the Korean Society of Machine Tool Engineers / v.16, no.6, 2007 , pp. 62-70 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 Test; Welding Flaw; Feature Variables; Pattern Classification;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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