Fault diagnosis approach of traction transformers in high‐speed railway combining kernel principal component analysis with random forest-Reference-Cited by-同舟云学术

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Fault diagnosis approach of traction transformers in high‐speed railway combining kernel principal component analysis with random forest

Published:2016-09 Issue:3 Volume:6 Page:202-206
ISSN:2042-9738
Container-title:IET Electrical Systems in Transportation
language:en
Short-container-title:IET Electrical Systems in Transportation

Author:

Dai Chenxi¹,Liu Zhigang¹,Hu Keting¹,Huang Ke¹

Affiliation:

1. School of Electrical EngineeringSouthwest Jiaotong UniversityChengduPeople's Republic of China

Funder

National Natural Science Foundation of China

Sichuan Province Youth Science and Technology Innovation Team

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-est.2015.0018

Reference15 articles.

1. A Hybrid Tool for Detection of Incipient Faults in Transformers Based on the Dissolved Gas Analysis of Insulating Oil

2. A review of dissolved gas analysis in power transformers;Sun H.‐C.;Energy Procedia,2012

3. Application of an artificial neural network in the use of physicochemical properties as a low cost proxy of power transformers DGA data;Barbosa F.R.;IEEE Trans. Dielectr. Electr. Insul.,2012

4. A comparative study of neural network efficiency in power transformers diagnosis using dissolved gas analysis

5. Time and frequency domain analyses based expert system for impulse fault diagnosis in transformers

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2. The Effect of Source Data on Graphical Pentagons DGA Methods for Detecting Incipient Faults in Power Transformers;2023 International Conference on Decision Aid Sciences and Applications (DASA);2023-09-16

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4. Machine learning for fault diagnosis of high-speed train traction systems: A review;Frontiers of Engineering Management;2023-05-31

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