Application of Classified Elastic Waves for AE Source Localization Based on Self-Organizing Map

Acoustic emission (AE) source localization has been used to visualize progress failures generated in a wide variety of materials. In the conventional approaches, AE algorithms assume that signal is propagated as straight line. However, it supposed form heterogeneity elastic wave velocity distributions. Hence, with localization, expected accuracy reduced heterogeneous materials since diffraction and refraction waves are generated. Thus, if propagation classified, localizations performed The self-organizing map (SOM) one unsupervised learning methods, SOM potential classify for localizations. application classified signals not popular. If applied time difference arrival (TDOA) method, which popular number visualized sources decreased because algorithm does consider selection wave. Although ray tracing localize larger than TDOA localized less accurate comparison results method. this study, were two localizations, model tests based on pencil-lead breaks (PLBs) generating artificial conducted validate performance waves. validation confirmed maximum error method 20 mm intervals candidates. Moreover, localizes same PLB tests. Therefore, more practically applied.