Transformer Fault Diagnosis based on RBF Neural Network

DOI

10.2991/meees-18.2018.52How to use a DOI?

Keywords

neural network; transformer; fault diagnosis; training model.

Abstract

With respect to the transformer fault diagnosis, this paper proposed a fault diagnosis model based on RBF neural network, realized RBF neural network based on center vector of gauss basis function, the weight calculation method of RBF based on Kalman filtering ,the training and testing algorithm of the data classification model is given. The proposed method of the transformer fault diagnosis based on RBF neural network is discussed in detail. Because the modularized structure is adopted and each sub-model is only used to recognize one fault, the difficulty of training model is reduced, it is more important that the ability and application flexibility of the fault diagnosis are improved obviously. Research results show that the proposed method has strong robustness and high accuracy.

Copyright

© 2018, 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  - Xicheng Teng
PY  - 2018/05
DA  - 2018/05
TI  - Transformer Fault Diagnosis based on RBF Neural Network
BT  - Proceedings of the 2018 International Conference on Mechanical, Electrical, Electronic Engineering & Science (MEEES 2018)
PB  - Atlantis Press
SP  - 298
EP  - 302
SN  - 2352-5401
UR  - https://doi.org/10.2991/meees-18.2018.52
DO  - 10.2991/meees-18.2018.52
ID  - Teng2018/05
ER  -