Application of EEMD and high-order singular spectral entropy to feature extraction of partial discharge signals
Author:
Affiliation:
1. Department of Electrical Engineering; Shanghai Jiao Tong University; Shanghai 200240 China
Funder
National Basic Research Program of China (973 program)
Publisher
Wiley
Subject
Electrical and Electronic Engineering
Reference31 articles.
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2. Impact of velocity on partial discharge characteristics of moving metal particles in transformer oil using UHF technique;Tang;IEEE Transactions on Dielectrics and Electrical Insulation,2016
3. Feature extraction of partial discharge signals using the wavelet packet transform and classification with a probabilistic neural network;Evagorou;IET Science, Measurement & Technology,2009
4. Partial discharge pattern recognition method based on variable predictive model-based class discriminate and partial least squares regression;Zhu;IET Science, Measurement & Technology,2016
5. Feature extraction and severity assessment of partial discharge under protrusion defect based on fuzzy comprehensive evaluation;Zeng;IET Generation, Transmission & Distribution,2015
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