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

• Main Authors: Tho N.T.N., Chakrabarty C.K., Siah Y.K., Ghani A.B.Abd.
• Other Authors: 54584502600
• Format: Conference paper
• Published: 2023
• Subjects: neural network; partial discharge; pattern recognition; statistical method; time-resolved signals; wavelet de-noising; Backpropagation; Feature extraction; Magnetic sensors; Partial discharges; Pattern recognition; Pattern recognition systems; Statistical methods; De-Noise; Feature extraction methods; Multi layer perceptron; Partial discharge signal; Time-resolved; Wavelet denoising; Wavelet transformations; XLPE cables; Neural networks

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. � 2011 IEEE.