Wavelet and neural structure:: A new tool for diagnostic of power system disturbances

被引：83

作者：

Borrás, D ^{[1
]}

Castilla, M

Moreno, N

Montaño, JC

机构：

[1] Univ Sevilla, Dept Elect Engn, Seville 41011, Spain

[2] CSIC, E-41080 Seville, Spain

来源：

IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS | 2001年 / 37卷 / 01期

关键词：

harmonic distortion; neural networks; signal analysis; transforms; wavelets;

D O I：

10.1109/28.903145

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

The Fourier transform can be used for analysis of nonstationary signals, but the Fourier spectrum does not provide any time-domain information about the signal. When the time localization of the spectral components is needed, a wavelet transform giving the time-frequency representation of the signal must be used. In this paper, using wavelet analysis and neural systems as a new tool for the analysis of power system disturbances, disturbances are automatically detected, compacted, and classified. An example showing the potential of these techniques for diagnosis of actual power system disturbances is presented.

引用

页码：184 / 190

页数：7

共 14 条

[1]

Donoho DL, 1996, ANN STAT, V24, P508

[2]

DONOHO DL, 1992, 400 STANF U DEP STAT

[3]

GUO H, 1995, P INT C DIG SIGN PRO, P332

[4] CONSTRAINED NEURAL NETWORK-BASED IDENTIFICATION OF HARMONIC SOURCES [J].