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Feature extraction method and neural network pattern recognition on time-resolved partial discharge signals

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4 Author(s)
Nguyen Thi Ngoc Tho ; Department of Electronics and Communication Engineering, Universiti Tenaga Nasional, Selangor Darul Ehsan, Malaysia ; Chandan Kumar Chakrabarty ; Yap Keem Siah ; Ahmad Basri Abd Ghani

Magnetic sensor is a relatively new method to collect time-resolved partial discharge (PD) signals in XLPE cables. This paper proposes a simple yet effective method to recognize patterns of PD signals obtained from the magnetic sensor. The technique consists of wavelet transformation to de-noise the signals, statistical analysis to extract features and multi-layer perceptron back propagation (MLP BP) neural network to classify different types of PD signals. The result is elaborated in this paper.

Published in:

Open Systems (ICOS), 2011 IEEE Conference on

Date of Conference:

25-28 Sept. 2011