NDLI: On-line disturbance recognition utilizing vector quantization based fast match

Content Provider	IEEE Xplore Digital Library
Author	Abdel-Galil, K. El-Saadany, E.F. Youssef, A.M. Salama, M.M.A.
Copyright Year	2002
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Waterloo Univ., Ont., Canada (Abdel-Galil, K.; El-Saadany, E.F.; Youssef, A.M.; Salama, M.M.A.)
Abstract	In this paper, a given power quality event is matched against a set of known power quality events in a database. Matlab was utilized in constructing this database by simulating different power quality phenomena. Feature vectors are extracted from windowed Fourier transform or windowed Walsh transform. These features are further processed by vector quantization for minimizing the calculation burden. A fast match (FM) algorithm is proposed to find the degree of similarity between the labels of tested phenomena and the pre-stored labels for different power quality phenomena. In this paper we study the effect of changing the codebook size, and type of feature extraction used on the classification accuracy of the proposed classifier. Results show that the implementation of such a classifier is simple, yet it results in high classification rate, which makes it a very competitive alternative for already existing classifiers, which suffer from large computation burden and complicated structure.
Starting Page	1027
Ending Page	1032
File Size	535945
Page Count	6
File Format	PDF
ISBN	0780375181
DOI	10.1109/PESS.2002.1043561
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-07-21
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vector quantization Power quality Feature extraction Fourier transforms Artificial neural networks Fuzzy logic Spatial databases Voltage Neural networks Frequency
Content Type	Text
Resource Type	Article

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