Research on Faults Diagnosis System of an Air to Ground Missile Based on Wavelet Neural Network
Authors
Xiaoyu Zhang, Guifang Cai
Corresponding Author
Xiaoyu Zhang
Available Online April 2015.
- DOI
- 10.2991/amcce-15.2015.412How to use a DOI?
- Keywords
- wavelet neural network; fault diagnosis system; air to ground missile
- Abstract
The ordinary missile auto-test system has such defects as faults orientation slow, high fault value, database modification hardly and so on. In order to overcome such defects, an faults diagnosis system based on wavelet neural network is designed. The correlative theories of wavelet are introduced, the wavelet neural network structure is analyzed, the network is trained and tested. The tested results illustrate that the system has such advantages as faster execution speed, exact faults orientation, it has widely application foreground.
- 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/).
Cite this article
TY - CONF AU - Xiaoyu Zhang AU - Guifang Cai PY - 2015/04 DA - 2015/04 TI - Research on Faults Diagnosis System of an Air to Ground Missile Based on Wavelet Neural Network BT - Proceedings of the 2015 International Conference on Automation, Mechanical Control and Computational Engineering PB - Atlantis Press SP - 963 EP - 968 SN - 1951-6851 UR - https://doi.org/10.2991/amcce-15.2015.412 DO - 10.2991/amcce-15.2015.412 ID - Zhang2015/04 ER -