Experiences with transformer diagnosis by DGA: case studies
Author:
Affiliation:
1. PENCOPOWERNo. 24, Floor 6, Sadeqie Trading Center, Sadeqie SquareTehranIran
2. School of Electrical and Computer Engineering, Faculty of EngineeringUniversity of TehranTehran14395–515Iran
Publisher
Institution of Engineering and Technology (IET)
Subject
Electrical and Electronic Engineering,Energy Engineering and Power Technology,Control and Systems Engineering
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-gtd.2019.1056
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4. An online data‐driven technique for the detection of transformer winding deformations;Hong T.;IEEE Trans. Power Deliv.,2018
5. Assessment of computational intelligence and conventional dissolved gas analysis methods for transformer fault diagnosis
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