Penetration Pattern Recognition Based on Artificial Neural Network

DOI

10.2991/msmee-17.2017.209How to use a DOI?

Keywords

artificial neural network; penetration model; finite element simulation; pattern recognition

Abstract

In order to study the specific pattern of fragmentation penetrating the target plate under the influence of multi factors, this paper uses the artificial neural network method to identify the input parameters and obtain the corresponding target damage model. Based on the orthogonal design principal, this paper uses the ANSYS/LS-DYNA simulation to simulate the input data of the 60 groups of fragments penetrating the target plate as the input data trained by the neural network. In addition, three sets of data are selected as the verification data to the training effect of the neural network verification. The results show that the artificial network can effectively identify the specific damage pattern of fragment on the target under the multi-factor effect.

Copyright

© 2017, 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  - Shuo Wang
AU  - Quan Shi
PY  - 2017/05
DA  - 2017/05
TI  - Penetration Pattern Recognition Based on Artificial Neural Network
BT  - Proceedings of the 2017 2nd International Conference on Materials Science, Machinery and Energy Engineering (MSMEE 2017)
PB  - Atlantis Press
SP  - 1075
EP  - 1079
SN  - 2352-5401
UR  - https://doi.org/10.2991/msmee-17.2017.209
DO  - 10.2991/msmee-17.2017.209
ID  - Wang2017/05
ER  -