A transformer fault diagnosis method based on hybrid improved grey wolf optimization and least squares‐support vector machine-Reference-Cited by-同舟云学术

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A transformer fault diagnosis method based on hybrid improved grey wolf optimization and least squares‐support vector machine

Published:2022-01-26 Issue:10 Volume:16 Page:1950-1963
ISSN:1751-8687
Container-title:IET Generation, Transmission & Distribution
language:en
Short-container-title:IET Generation Trans & Dist

Author:

Wu Yuhan¹,Sun Xianbo¹,Dai Baofu¹,Yang Pengfei¹,Wang Zhihao¹

Affiliation:

1. College of Information Engineering Hubei Minzu University Enshi Hubei China

Funder

National Natural Science Foundation of China

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/gtd2.12405

Reference33 articles.

1. An intelligent system based on optimized ANFIS and association rules for power transformer fault diagnosis

2. Conditional probability‐based interpretation of dissolved gas analysis for transformer incipient faults

3. Hybrid RVM–ANFIS algorithm for transformer fault diagnosis

4. Fault diagnosis of transformer based on capsule network;Yang D.;High Volt. Eng.,2020

5. Power Transformer Fault Diagnosis Based on Dissolved Gas Analysis by Correlation Coefficient-DBSCAN

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