Classification of dynamic insulation failures in transformer winding during impulse test using cross-wavelet transform aided foraging algorithm
Author:
Publisher
Institution of Engineering and Technology (IET)
Subject
Electrical and Electronic Engineering
Link
https://digital-library.theiet.org/content/journals/10.1049/iet-epa.2010.0082?crawler=true&mimetype=application/pdf
Reference20 articles.
1. Recognition of impulse fault patterns in transformers using Kohonen's self-organizing feature map
2. Pattern classification of impulse faults in transformers by wavelet analysis
3. Impulse fault classification in transformers by fractal analysis
4. Time and frequency domain analyses based expert system for impulse fault diagnosis in transformers
Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Short‐term wind speed forecasting using wavelet transformation and AdaBoosting neural networks in Yunnan wind farm;IET Renewable Power Generation;2016-07-08
2. Insulation failure detection in transformer winding using cross-correlation technique with ANN and k-NN regression method during impulse test;International Journal of Electrical Power & Energy Systems;2013-12
3. Detection of internal incipient faults in transformers during impulse test using hyperbolic S-transform;International Transactions on Electrical Energy Systems;2012-07-09
4. Characterisation of internal incipient faults in transformers during impulse test using index based on S matrix energy and standard deviation;IET Electric Power Applications;2012
5. Hyperbolic S-transform-based method for classification of external faults, incipient faults, inrush currents and internal faults in power transformers;IET Generation, Transmission & Distribution;2012
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