Application Research for Ultrasonic Flaw Identification Based on Support Vector Machine

DOI

10.2991/icmmcce-15.2015.206How to use a DOI?

Keywords

Ultrasonic Testing; Flaw Identification; Support Vector Machine (SVM); Pattern Classification

Abstract

Automatic identification of flaws is very important for ultrasonic nondestructive testing and evaluation of pipelines. A novel automatic identification approach of flaws using support vector machine (SVM) is presented. Wavelet transform is applied to feature extraction of ultrasonic echo signals, and SVM is to perform the identification task. To validate this approach, some experiments are performed. The results show that unlike conventional and artificial neural networks (ANN) identification methods the new technique performs better than conventional evaluation ones with advantages of high identification performance for pipeline flaws, lower cost, excellent generalization.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jing Huang
AU  - Binglei Guan
PY  - 2015/12
DA  - 2015/12
TI  - Application Research for Ultrasonic Flaw Identification Based on Support Vector Machine
BT  - Proceedings of the 4th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering 2015
PB  - Atlantis Press
SP  - 986
EP  - 990
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmcce-15.2015.206
DO  - 10.2991/icmmcce-15.2015.206
ID  - Huang2015/12
ER  -