Classification of Voltage Sag based on Elliptic Metric
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Jiao Hao, Zongbao Zhang, Lei Li, Yonghan Ding, Liangliang Ge, Yonggang Wang, Lvfu Zhu
Voltage sag is one of the most serious power quality problems at present. The classification and recognition of voltage sag is the premise and foundation of other voltage research work. In this paper, after adding gauss window with adjustable window width to S transform, four types of voltage sag classification and recognition are realized by using elliptical metric method. The experimental results show that the S transform of single fundamental frequency can accurately judge the amplitude of the sag under different indentation amplitudes. Even if there is relatively large noise interference, its judgment results can meet the requirements. The classification effect of voltage sag based on ellipse metric is better and the recognition rate can reach 99.75%.
Single baseband S transform voltage sag, Ellipse metric, Feature extraction, Classification and recognition