The emulsifier fault early warning on BP neural network theory

DOI

10.2991/icmmita-15.2015.343How to use a DOI?

Keywords

emulsifier; fault warning; BP neural network

Abstract

Emulsifier is the key equipment in the production of emulsion explosive. The condition of the emulsifier is very important to the production safety of the emulsion explosive. The paper focuses on emulsifier fault warning in the production of emulsion explosive. Now the emulsifier fault warning is based on the threshold. That method can not warn fault timely. The paper proposes a fault early warning method which is on the BP neural network. The neural network model is established by the method. The condition of the emulsifier which is important to the production safety can be predicted through the model. According to the simulation example, the model can predict the conduction of the emulsifier well.

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/).

Download article (PDF)

TY  - CONF
AU  - Yuesheng Wang
AU  - Kangjian Lu
PY  - 2015/11
DA  - 2015/11
TI  - The emulsifier fault early warning on BP neural network theory
BT  - Proceedings of the 2015 3rd International Conference on Machinery, Materials and Information Technology Applications
PB  - Atlantis Press
SP  - 1836
EP  - 1839
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmita-15.2015.343
DO  - 10.2991/icmmita-15.2015.343
ID  - Wang2015/11
ER  -