Classification of voltage sag based on wavelet transform and wavelet network

Author

Zheng, Gang ; Yan, Xiao-Mei ; Li, Hao-Wen ; Liu, Ding

Author_Institution

Res. Center of Inf. & Control Eng., Xi´´an Univ. of Technol., China

Volume

1

fYear

2004

fDate

26-29 Aug. 2004

Firstpage

466

Abstract

Voltage sag due to line fault, transformer energizing and induction motor starting was analyzed in this paper. The respective sag waveform was presented. The analysis results illustrate that interference source would be identified based on characteristics of voltage sag. An interference source identification method is brought forward by using wavelet transform and wavelet network. The wavelet Daubechies 6 is used to extract the character vector. The voltage sag can be classified by using the wavelet network.

Keywords

induction motors; interference (wave); neural nets; power distribution faults; power supply quality; signal processing; transformers; wavelet transforms; artificial neural network; character vector; electric power distribution system operation; induction motor starting; interference source identification; line fault; power quality analysis; power system fault signal processing; transformer energization; voltage sag classification; wavelet network; wavelet transform; Artificial neural networks; Circuit faults; Frequency; Induction motors; Power quality; Signal resolution; Threshold voltage; Voltage fluctuations; Wavelet analysis; Wavelet transforms;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on

Print_ISBN

0-7803-8403-2

Type

conf

DOI

10.1109/ICMLC.2004.1380734

Filename

1380734