Separation of corona using wavelet packet transform and neural network for detection of partial discharge in gas-insulated substations

Please use this identifier to cite or link to this item: https://doi.org/10.1109/TPWRD.2004.839187

Title:	Separation of corona using wavelet packet transform and neural network for detection of partial discharge in gas-insulated substations
Authors:	Chang, C.S. Jin, J. Chang, C. Hoshino, T. Hanai, M. Kobayashi, N.
Keywords:	Gas-insulated substations (GIS) Neural network Noise reduction Partial discharge Wavelet packet transform
Issue Date:	Apr-2005
Citation:	Chang, C.S., Jin, J., Chang, C., Hoshino, T., Hanai, M., Kobayashi, N. (2005-04). Separation of corona using wavelet packet transform and neural network for detection of partial discharge in gas-insulated substations. IEEE Transactions on Power Delivery 20 (2 II) : 1363-1369. ScholarBank@NUS Repository. https://doi.org/10.1109/TPWRD.2004.839187
Abstract:	It is essential to detect partial discharge (PD) as a symptom of insulation breakdown in gas-insulated substations (GIS). However, the accuracy of such measurement is often degraded due to the existence of noise in the signal. In this paper, a method using wavelet packet transform and neural network is proposed to separate the PD pulses from corona in air, which enables more accurate detection of insulation breakdown of GIS. © 2005 IEEE.
Source Title:	IEEE Transactions on Power Delivery
URI:	http://scholarbank.nus.edu.sg/handle/10635/57382
ISSN:	08858977
DOI:	10.1109/TPWRD.2004.839187
Appears in Collections:	Staff Publications

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