Research on Optimization of Feature Extracting Based on PD Fingerprints in Pattern Recognition

DOI

10.2991/cnct-16.2017.113How to use a DOI?

Keywords

PD, Fingerprints, Pattern recognition, BP neural network

Abstract

In order to investigate the effect of feature extraction on pattern classification for partial discharge (PD) signals appearing potential insulating failures in high voltage apparatus while operation, the PD-fingerprints acquired by Hipotronics DDX-7000 digital PD detector are taken as database and method on the feature extracting from the database is carried out, and its practicability is demonstrated by the mathematics and experiment, respectively. The BP neural network is made of three layers and the transfer function of hidden layer and output layer are tansig, then the influence of the structure of neural network on recognition results is studied at the same time. As a result, the optimal characteristic vector with obvious separability and the number of hidden layer are obtained, and achievements of research show that the network convergence is not only quickly, but also the recognition rate very high so much as up to 100%.

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/).

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TY  - CONF
AU  - Wei LI
AU  - Lei SHI
AU  - Hong-Jing LIU
AU  - Huan XIE
AU  - Yuan GUI
AU  - Dian-Chun ZHENG
AU  - Pei-Jing HOU
PY  - 2016/12
DA  - 2016/12
TI  - Research on Optimization of Feature Extracting Based on PD Fingerprints in Pattern Recognition
BT  - Proceedings of the International Conference on Computer Networks and Communication Technology (CNCT 2016)
PB  - Atlantis Press
SP  - 811
EP  - 816
SN  - 2352-538X
UR  - https://doi.org/10.2991/cnct-16.2017.113
DO  - 10.2991/cnct-16.2017.113
ID  - LI2016/12
ER  -