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Acoustic Emission Source Classification of Finite-width Plate with a Circular Hole Defect using k-Nearest Neighbor Algorithm  

Rhee, Zhang-Kyu (Department of Mechanical Engineering, University of Incheon)
Oh, Jin-Soo (Graduate School, University of Incheon)
Publication Information
Journal of the Korea Safety Management & Science / v.11, no.1, 2009 , pp. 27-33 More about this Journal
Abstract
A study of fracture to material is getting interest in nuclear and aerospace industry as a viewpoint of safety. Acoustic emission (AE) is a non-destructive testing and new technology to evaluate safety on structures. In previous research continuously, all tensile tests on the pre-defected coupons were performed using the universal testing machine, which machine crosshead was move at a constant speed of 5mm/min. This study is to evaluate an AE source characterization of SM45C steel by using k-nearest neighbor classifier, k-NNC. For this, we used K-means clustering as an unsupervised learning method for obtained multi -variate AE main data sets, and we applied k-NNC as a supervised learning pattern recognition algorithm for obtained multi-variate AE working data sets. As a result, the criteria of Wilk's $\lambda$, D&B(Rij) & Tou are discussed.
Keywords
Acoustic Emission; Source Classification; Circular Hole Defect; Pattern Recognition; k-Nearest Neighbor Classifier;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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