Research on Classification of Power Quality Disturbance Based on Weighted SVM Model

DOI

10.2991/iiicec-15.2015.463How to use a DOI?

Keywords

power quality; support vector machine; wavelet transform; fractal theory.

Abstract

In this paper, the mathematical models of the disturbance signal were to be designed. Adaptive LMS algorithm generalized morphological filter was set up based on the mathematical morphological, and the noise of power quality disturbance signal was managed. The different frequency energy distributions and fractal dimension of the power quality disturbance signals were extracted separately through the wavelet transform and the fractal theory. According to the time of the power quality disturbance to give different weights, to realize online training and testing. The simulation results show that structured the weighted support vector machine has very good classification effect for power quality disturbance.

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/).

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TY  - CONF
AU  - Xiangzheng Xu
AU  - Jinwei Ye
PY  - 2015/03
DA  - 2015/03
TI  - Research on Classification of Power Quality Disturbance Based on Weighted SVM Model
BT  - Proceedings of the 2015 International Industrial Informatics and Computer Engineering Conference
PB  - Atlantis Press
SP  - 2132
EP  - 2135
SN  - 2352-538X
UR  - https://doi.org/10.2991/iiicec-15.2015.463
DO  - 10.2991/iiicec-15.2015.463
ID  - Xu2015/03
ER  -