Title :
Wavelet and neural structure: a new tool for diagnostic of power system disturbances
Author :
Borrás, Dolores ; Castilla, M. ; Moreno, Narciso ; Montaño, J.C.
Author_Institution :
Dept. of Electr. Eng., Seville Univ., Spain
Abstract :
The Fourier transform can be used for the 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
Keywords :
fault diagnosis; harmonic distortion; neural nets; power system analysis computing; power system faults; power system harmonics; wavelet transforms; computer simulation; diagnostic tool; neural structure; nonstationary signals analysis; power system disturbances; spectral components time localization; time-frequency signal representation; wavelet transform; Continuous wavelet transforms; Discrete wavelet transforms; Fourier transforms; Neural networks; Power system analysis computing; Power system harmonics; Power systems; Signal analysis; Wavelet analysis; Wavelet transforms;
Journal_Title :
Industry Applications, IEEE Transactions on
