S-transform-based intelligent system for classification of power quality disturbance signals

Lee, I.W.C. and Dash, P.K. (2003) S-transform-based intelligent system for classification of power quality disturbance signals. IEEE Transactions on Industrial Electronics, 50 (4). pp. 800-805. ISSN 0278-0046

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Official URL: http://dx.doi.org/10.1109/TIE.2003.814991

Abstract

In this paper, a new approach is presented for the detection and classification of nonstationary signals in power networks by combining the S-transform and neural networks. The S-transform provides frequency-dependent resolution that simultaneously localizes the real and imaginary spectra. The S-transform is similar to the wavelet transform but with a phase correction. This property is used to obtain useful features of the nonstationary signals that make the pattern re cognition much simpler in comparison to the wavelet multiresolution analysis. Two neural network configurations are trained with features from the S-transform for recognizing the waveform class. The classification accuracy for a variety of power network disturbance signals for both types of neural networks is shown and is found to be a significant improvement over multiresolution wavelet analysis with multiple neural networks.

Item Type: Article
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Engineering (FOE)
Depositing User: Ms Rosnani Abd Wahab
Date Deposited: 22 Aug 2011 06:24
Last Modified: 06 Feb 2014 02:44
URI: http://shdl.mmu.edu.my/id/eprint/2550

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