Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/53496
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Type: | Journal article |
Title: | Automatic classification and characterization of power quality events |
Author: | Gargoom, A. Ertugrul, N. Soong, W. |
Citation: | IEEE Transactions on Power Delivery, 2008; 23(4):2417-2425 |
Publisher: | IEEE-Inst Electrical Electronics Engineers Inc |
Issue Date: | 2008 |
ISSN: | 0885-8977 1937-4208 |
Statement of Responsibility: | Ameen M. Gargoom, Nesimi Ertugrul and Wen. L. Soong |
Abstract: | This paper presents a new technique for automatic monitoring of power quality events, which is based on the multiresolution S-transform and Parseval's theorem. In the proposed technique, the S-transform is used to produce instantaneous frequency vectors of the signals, and then the energies of these vectors, based on the Parseval's theorem, are utilized for automatically monitoring and classification of power quality events. The advantage of the proposed algorithm is its ability to distinguish different power quality classes easily. In addition, the magnitude, duration, and frequency content of the disturbances can be accurately identified in order to characterize the disturbances. The paper provides the theoretical background of the technique and presents a wide range of analyses to demonstrate its effectiveness. |
Keywords: | Automatic classification Parseval’s theorem power quality monitoring S-transform |
Description: | Copyright © 2008 IEEE |
DOI: | 10.1109/TPWRD.2008.923998 |
Published version: | http://dx.doi.org/10.1109/tpwrd.2008.923998 |
Appears in Collections: | Aurora harvest 5 Electrical and Electronic Engineering publications Environment Institute publications |
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hdl_53496.pdf | 827.5 kB | Publisher's PDF | View/Open |
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