Crack Identification of Drawing Parts Based on Loccal Wave Demomposition and Neural Network
Zhigao Luo, Qiang Chen, Xin He
Available Online December 2013.
- https://doi.org/10.2991/wiet-13.2013.18How to use a DOI?
- Acoustic emission; Local wave; Back-propagation neural network; Drawing parts; Crack
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
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 - AASRI Winter International Conference on Engineering and Technology (AASRI-WIET 2013) PB - Atlantis Press SN - 1951-6851 UR - https://doi.org/10.2991/wiet-13.2013.18 DO - https://doi.org/10.2991/wiet-13.2013.18 ID - Luo2013/12 ER -