Please use this identifier to cite or link to this item:
Title: Characterization of Phase Resolved Partial Discharge waveforms from instrument transformer using statistical signal processing technique
Authors: Thayoob, Y.H.M. 
Ahmed, S.K. 
Piau, C.C. 
Ping, C.Y. 
Balasubramaniam, Y. 
Issue Date: 2016
Journal: IEEE 2015 International Conference on Signal and Image Processing Applications, ICSIPA 2015 - Proceedings 17 February 2016, Article number 7412217, Pages 355-360 
Abstract: Partial Discharge (PD) detection is one of the important methods used to evaluate the insulation condition of in-service high voltage (HV) electrical equipment. On-site PD detection methods are preferred compared to other methods as non-intrusive sensors are easier to install and have no interruptions on the operation. An electrical PD testing utilizing High Frequency Current Transformer (HFCT) installed at the ground terminal of the in-service instrument transformer was used to detect partial discharge activities. However, the limitation of this method is the measurement often lacks of accuracy due to interference in the measured PD waveforms. Therefore, such PD signals are hard to be distinguished from the stochastic noise pulses. Hence, the characteristics of PD signals and interference signals are studied in the Phase Resolved Partial Discharge (PRPD) pattern in order to identify the extent of PD occurrence in the signals. The discharge magnitude could increase significantly because of the noise signals superposed with PD signals. Therefore a method that can remove high magnitude noise will be proposed by using statistical signal processing technique. © 2015 IEEE.
DOI: 10.1109/ICSIPA.2015.7412217
Appears in Collections:COE Scholarly Publication

Show full item record

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.