An adaptive fault diagnosis method of power transformers based on combining oversampling and cost‐sensitive learning

An adaptive fault diagnosis method of power transformers based on combining oversampling and cost‐sensitive learning

Abstract Dissolved gas analysis is an important technique for the insulation condition assessment and incipient fault diagnosis of power transformers. However, the performance of the traditional ratio methods can be hardly improved due to the overreliance on absolute ratio threshold. In this paper,...

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Bibliographic Details
Main Authors: Lijing Zhang, Gehao Sheng, Huijuan Hou, Nan Zhou, Xiuchen Jiang
Format: Article
Language:English
Published: Wiley 2021-12-01
Series:IET Smart Grid
Subjects:
learning (artificial intelligence)
belief networks
pattern classification
fault diagnosis
power transformers
power engineering computing
Online Access:https://doi.org/10.1049/stg2.12044

Internet

https://doi.org/10.1049/stg2.12044

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