Identification of ultra-high-frequency PD signals in gas-insulated switchgear based on moment features considering electromagnetic mode

Identification of ultra-high-frequency PD signals in gas-insulated switchgear based on moment features considering electromagnetic mode

The feature extraction and pattern recognition techniques are of great importance to assess the insulation condition of gas-insulated switchgear. In this work, the ultra-high-frequency partial discharge (PD) signals generated from four types of typical insulation defects are analysed using S-transfo...

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Bibliographic Details
Main Authors: Feng Bin, Feng Wang, Qiuqin Sun, She Chen, Jingmin Fan, Huisheng Ye
Format: Article
Language:English
Published: Wiley 2020-02-01
Series:High Voltage
Subjects:
feature extraction
time-frequency analysis
learning (artificial intelligence)
pattern recognition
support vector machines
gas insulated switchgear
particle swarm optimisation
partial discharge measurement
power engineering computing
ultra-high-frequency partial discharge signals
typical insulation defects
time-frequency representation
cutoff frequencies
low-order moments
feature selection
selected moment features
electromagnetic mode
nearest neighbour
real-time pd detection
ultra-high-frequency pd signals
gas-insulated switchgear
pattern recognition techniques
insulation condition
Online Access:https://digital-library.theiet.org/content/journals/10.1049/hve.2019.0098

Internet

https://digital-library.theiet.org/content/journals/10.1049/hve.2019.0098

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