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Automatic classification and characterization of power quality events

Authors :
Gargoom, Ameen M.
Ertugrul, Nesimi
Soong, Wen. L.
Source :
IEEE Transactions on Power Delivery. Oct, 2008, Vol. 23 Issue 4, p2417, 9 p.
Publication Year :
2008

Abstract

This paper presents a new technique for automatic monitoring of power quality events, which is based on the multi-resolution 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. Index Terms--Automatic classification, Parseval's theorem, power quality monitoring, S-transform.

Details

Language :
English
ISSN :
08858977
Volume :
23
Issue :
4
Database :
Gale General OneFile
Journal :
IEEE Transactions on Power Delivery
Publication Type :
Academic Journal
Accession number :
edsgcl.187050328