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Automatic detection-localization of fault point on waveform and classification of power quality disturbance waveshape fault using wavelet and neural network

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4 Author(s)
Dilokratanatrakool, C. ; Dept. of Electr. Eng., King Mongkut''s Univ. of Technol., Bangkok, Thailand ; Na Ayudhya, P.N. ; Chayavanich, Tasanee ; Prapanavarat, C.

In this paper a new method for automatically detecting, localizing and classifying various types of disturbance waveshape fault is presented. The method is based on wavelet transform analysis, artificial neural networks, and the mathematical theory of evidence. The proposed detection and localization algorithm is carried out in the wavelet transform using multiresolution signal decomposition techniques. The proposed classification is carried out in sets of multiple neural network using a learning vector quantization networks. The outcomes of the networks are then integrated using voting decision making scheme.

Published in:

Robotics, Intelligent Systems and Signal Processing, 2003. Proceedings. 2003 IEEE International Conference on  (Volume:1 )

Date of Conference:

8-13 Oct. 2003