Feature vector extraction for the automatic classification of power quality disturbances

C. H. Lee, J. S. Lee, J. O. Kim, S. W. Nam

Research output: Contribution to journalConference article

10 Scopus citations

Abstract

The objective of this paper is to present a systematic approach to feature vector extraction for the automatic classification of power quality (PQ) disturbances, where discrete wavelet transform (DWT), signal power estimation and data compression methods are utilized to improve the classification performance and reduce computational complexity. To demonstrate the performance and applicability of the proposed method, some test results obtained by analyzing 7-class power quality disturbances, generated by the EMTP, with white Gaussian noise are also provided.

Original languageEnglish
Pages (from-to)2681-2684
Number of pages4
JournalProceedings - IEEE International Symposium on Circuits and Systems
Volume4
Publication statusPublished - 1997 Jan 1
EventProceedings of the 1997 IEEE International Symposium on Circuits and Systems, ISCAS'97. Part 4 (of 4) - Hong Kong, Hong Kong
Duration: 1997 Jun 91997 Jun 12

    Fingerprint

Cite this