DocumentCode :
2438867
Title :
Power Quality Disturbance Classification Using S-Transform and Decision Tree
Author :
Quan, Huimin ; Dai, Yuxing
Author_Institution :
Coll. of Electr. & Inf., Hunan Univ., Changsha
Volume :
2
fYear :
2008
fDate :
19-20 Dec. 2008
Firstpage :
602
Lastpage :
606
Abstract :
In order to solve the detection and classification of power quality disturbances, a new approach combining S-transform and decision tree is proposed. First, some disturbances are decomposed through S-transform time-frequency analysis, three feature functions are defined, then feature components are extracted, and decision rules are found, finally the decision tree approach for disturbances classification is presented. The simulation results show that the method could detect and classify the power quality disturbances effectively and has high classification correct ratio even though in noise condition. The reasons are also analyzed in this paper.
Keywords :
decision trees; power supply quality; time-frequency analysis; transforms; S-transform; decision tree; noise condition; power quality disturbance classification; time-frequency analysis; Classification tree analysis; Decision trees; Fast Fourier transforms; Feature extraction; Frequency domain analysis; Neural networks; Power quality; Voltage fluctuations; Wavelet domain; Wavelet transforms; S-transform; decision tree; power quality;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Industrial Application, 2008. PACIIA '08. Pacific-Asia Workshop on
Conference_Location :
Wuhan
Print_ISBN :
978-0-7695-3490-9
Type :
conf
DOI :
10.1109/PACIIA.2008.115
Filename :
4756846
Link To Document :
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