Title :
Online source recognition of partial discharge for gas insulated substations using independent component analysis
Author :
Chang, C.S. ; Jin, J. ; Chang, C. ; Hoshino, T. ; Hanai, M. ; Kobayashi, N.
Author_Institution :
Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore
Abstract :
To perform reliable insulation diagnosis for gas-insulated substation (GIS), detectable partial discharge (PD) should be identified quickly and effectively. With the increasing application of high voltage DC transmission, PD identification in such systems becomes more and more important. Therefore, a novel technique based on the analysis of ultra high frequency (UHF) resonance waveforms is proposed in this paper to meet the requirement. With the help of independent component analysis, the most dominating features are identified directly from UHF resonance signals without phase information. Using the identified features as the input, a neural network is implemented for recognizing sources of PD in SF6 and separating from the corona in air within a very short time
Keywords :
SF6 insulation; UHF measurement; condition monitoring; corona; feature extraction; gas insulated substations; independent component analysis; partial discharge measurement; signal detection; source separation; SF6; condition monitoring; corona; gas insulated substation; high voltage DC transmission; independent component analysis; insulation diagnosis; neural network; online source recognition; partial discharge detection; ultra high frequency resonance waveform; Gas insulation; Geographic Information Systems; Independent component analysis; Neural networks; Partial discharges; Resonance; Resonant frequency; Signal processing; Substations; Voltage;
Journal_Title :
Dielectrics and Electrical Insulation, IEEE Transactions on
DOI :
10.1109/TDEI.2006.1667751
