Proceedings of the International Conference on Electronics, Mechanics, Culture and Medicine

Optimal Design of Online Measuring System for Water Content of Lubricating Oil System

Authors
Nan Xie, Weimin Chen, Yijia Yuan
Corresponding Author
Nan Xie
Available Online February 2016.
DOI
https://doi.org/10.2991/emcm-15.2016.76How to use a DOI?
Keywords
Oil water content detection; Capacitor; Neural network; Data fusion processing; Optimal design
Abstract
The measuring of water content in oil products affects the reliability and safety of the steel high speed wire rod production. Based on the existing capacitance sensor online water content detector, the neural network algorithm is used to deal with the data fusion processing with the 3D temperature experimental calibration data of the capacitance value, speed and temperature of the lubricating oil and the corresponding dielectric constant of the speed of the rolling mill in the high speed wire mill. And then, we could design optimal for capacitance lubricating oil water content detecting system. The experimental results have indicated that the method can eliminate the influence of lubrication system's air bubble and greatly improve the detection accuracy of lubricating oil water content online. Also, it has a good market promotion and application value.
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Proceedings
International Conference on Electronics, Mechanics, Culture and Medicine
Part of series
Advances in Computer Science Research
Publication Date
February 2016
ISBN
978-94-6252-163-6
ISSN
2352-538X
DOI
https://doi.org/10.2991/emcm-15.2016.76How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Nan Xie
AU  - Weimin Chen
AU  - Yijia Yuan
PY  - 2016/02
DA  - 2016/02
TI  - Optimal Design of Online Measuring System for Water Content of Lubricating Oil System
BT  - International Conference on Electronics, Mechanics, Culture and Medicine
PB  - Atlantis Press
SP  - 407
EP  - 411
SN  - 2352-538X
UR  - https://doi.org/10.2991/emcm-15.2016.76
DO  - https://doi.org/10.2991/emcm-15.2016.76
ID  - Xie2016/02
ER  -