A Novel Double-Stacked Autoencoder for Power Transformers DGA Signals With An Imbalanced Data Structure

Artificial intelligence is the general trend in the field of power equipment fault diagnosis. However, limited by operation characteristics and data defects, the application of the intelligent diagnosis method in power transformers is still in the initial stage. To fill this research gap, in this ar...

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Veröffentlicht in:	IEEE transactions on industrial electronics (1982) Jg. 69; H. 2; S. 1977 - 1987
Hauptverfasser:	Yang, Dongsheng, Qin, Jia, Pang, Yongheng, Huang, Tingwen
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.02.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Aging Artificial intelligence Clustering Data structures Fault diagnosis Feature extraction Imbalanced data intelligent fault diagnosis Loss measurement Oil insulation Power transformer insulation power transformers stacked autoencoder (SAE) Training Transformers
ISSN:	0278-0046, 1557-9948
Online-Zugang:	Volltext
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