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An application of discrete wavelet transform and support vector machines algorithm for classification of fault types on underground cable

Author(s)
Ngaopitakkul, A.
Pothisarn, C.
Bunjongjit, S.
Suechoey, B.
Date Issued
December 12, 2012
Type
Conference Paper
DOI
10.1109/IBICA.2012.21
Abstract
This paper proposes a new technique using discrete wavelet transform (DWT) and support vector machines (SVM) to classify the fault types in underground distribution systems. The DWT is used to detect the high frequency components from fault signals. Positive sequence current signals are used in fault detection decision algorithm. The variations of first scale high frequency component that detects fault are used as an input for the SVM. Various cases studies based on Thailand electricity underground distribution systems have been investigated so that the algorithm can be implemented. SVM is also compared with the coefficients DWT comparison technique. The proposed method gives satisfactory accuracy, and will be very useful in the development of a modern protection scheme for electrical power transmission and distribution systems. © 2012 IEEE.
Citation
Proceedings 3rd International Conference on Innovations in Bio Inspired Computing and Applications Ibica 2012, 85-88, 2012
Subjects

Fault Classification

Support Vector Machin...

Underground Cable

Wavelet Transform

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