Detection and Classification of Power Quality Disturbances Using Double Resolution S-Transform and DAG-SVMs

The accurate detection and classification of power quality (PQ) disturbances in power systems is a key step to determine the causes of these events before any proper countermeasure could be taken. This paper presents a new algorithm for detection and classification of PQ disturbances based on the co...

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Bibliographic Details

Published in:	IEEE transactions on instrumentation and measurement Vol. 65; no. 10; pp. 2302 - 2312
Main Authors:	Li, Jianmin, Teng, Zhaosheng, Tang, Qiu, Song, Junhao
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.10.2016 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Artificial neural networks Digital signal processors Disturbance classification Feature extraction Harmonic analysis power quality (PQ) Power system harmonics S-transform (ST) Signal processing algorithms support vector machines (SVMs) time–frequency analysis White noise
ISSN:	0018-9456, 1557-9662
Online Access:	Get full text
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