Crack Identification of Drawing Parts Based on Loccal Wave Demomposition and Neural Network

DOI

10.2991/wiet-13.2013.18How to use a DOI?

Keywords

Acoustic emission; Local wave; Back-propagation neural network; Drawing parts; Crack

Abstract

This paper relates to local wave decomposition and back-propagation (BP) neural network.With local wave method, an arbitrary acoustic emission signal can be decomposed efficiently and accurately into a set of intrinsic mode functions (IMFs) and a residual trend. The energy feature parameters extracted from IMFs were employed as the input parameters of the neural network to identify the acoustic emission signals of drawing parts.The experimental results showed this method was effective for crack identification of drawing parts.

Copyright

© 2013, 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  - Zhigao Luo
AU  - Qiang Chen
AU  - Xin He
PY  - 2013/12
DA  - 2013/12
TI  - Crack Identification of Drawing Parts Based on Loccal Wave Demomposition and Neural Network
BT  - Proceedings of the AASRI Winter International Conference on Engineering and Technology (AASRI-WIET 2013)
PB  - Atlantis Press
SP  - 79
EP  - 82
SN  - 1951-6851
UR  - https://doi.org/10.2991/wiet-13.2013.18
DO  - 10.2991/wiet-13.2013.18
ID  - Luo2013/12
ER  -