Flaw classification in ultrasonic guided waves signal using Wavelet Transform and PNN classifier - Details

Author：

Zhang, Xiaohui (Zhang, Xiaohui.) | Sun, Guangmin (Sun, Guangmin.) (Scholars：孙光民) | Liu, Haomiao (Liu, Haomiao.) | Wang, Qite (Wang, Qite.)

Indexed by：

EI Scopus

Abstract：

In　this　paper,　a　synthesized　algorithm　for　flaw　classification　in　ultrasonic　guided　waves　signal　is　presented,　in　which　Wavelet　Transform　is　utilized　in　the　process　of　noise　suppression　and　envelop　extraction,　and　the　Probabilistic　Neural　Network　(PNN)　is　introduced　for　flaw　classification　of　the　ultrasonic　testing　signal.　Besides,　in　the　process　of　feature　extraction,　the　necessity　of　attenuation　correction　and　feature　selection　of　ultrasonic　signal　is　discussed.　The　comparison　of　the　performances　of　PNN　and　BP　classifier　is　made　in　the　last　chapter,　which　demonstrates　that　the　performance　of　flaw　classification　is　significantly　improved　by　the　synthesized　algorithm　presented　in　this　paper.　©　2011　IEEE.

Keyword：

Nondestructive examination Feature extraction Signal processing Neural networks Ultrasonic testing Wavelet transforms Guided electromagnetic wave propagation Ultrasonic waves Extraction

Author Community：

[ 1 ] [Zhang, Xiaohui]Department of Electrical Engineering, Beijing University of Technology, Beijing, 100124, China
[ 2 ] [Sun, Guangmin]Department of Electrical Engineering, Beijing University of Technology, Beijing, 100124, China
[ 3 ] [Liu, Haomiao]Department of Electrical Engineering, Beijing University of Technology, Beijing, 100124, China
[ 4 ] [Wang, Qite]Department of Electrical Engineering, Beijing University of Technology, Beijing, 100124, China