The Application of Artificial Neural Network in the Transformer Oil Chromatographic Test
Authors
Qinghao Wang, Weijun Li, Yanjun Pang, Bo Liu, Yi Wang, Zhitong Liu, Peng Liu, Xiao Liu, LiShuai He, Shuyi Tao
Corresponding Author
Qinghao Wang
Available Online April 2017.
- DOI
- 10.2991/icmmct-17.2017.192How to use a DOI?
- Keywords
- oil chromatogram; artificial neural network; fault diagnosis; sample library; transformer
- Abstract
Power transformer is the core equipment in power system. Power transformer can be regarded as the structure of several nonlinear dynamic systems. In the fault diagnosis of transformer, there are still many shortcomings in the traditional experimental analysis methods. Artificial neural network technology, because of its irreplaceable advantages, is applied in transformer fault diagnosis field.In this paper, the principle and technical characteristics of artificial neural network and the process of establishing the sample library are introduced. The application of artificial neural network in the fault diagnosis of transformer is also illustrated.
- 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/).
Cite this article
TY - CONF AU - Qinghao Wang AU - Weijun Li AU - Yanjun Pang AU - Bo Liu AU - Yi Wang AU - Zhitong Liu AU - Peng Liu AU - Xiao Liu AU - LiShuai He AU - Shuyi Tao PY - 2017/04 DA - 2017/04 TI - The Application of Artificial Neural Network in the Transformer Oil Chromatographic Test BT - Proceedings of the 2017 5th International Conference on Machinery, Materials and Computing Technology (ICMMCT 2017) PB - Atlantis Press SP - 962 EP - 968 SN - 2352-5401 UR - https://doi.org/10.2991/icmmct-17.2017.192 DO - 10.2991/icmmct-17.2017.192 ID - Wang2017/04 ER -