Research of circuit breaker intelligent fault diagnosis method based on double clustering-Reference-Cited by-同舟云学术

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Research of circuit breaker intelligent fault diagnosis method based on double clustering

Published:2017 Issue:17 Volume:14 Page:20170463-20170463
ISSN:1349-2543
Container-title:IEICE Electronics Express
language:en
Short-container-title:IEICE Electron. Express

Author:

Mengyuan He¹,Qiaolin Ding¹,Shutao Zhao¹,Yao Wei¹

Affiliation:

1. North China Electric Power University

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Subject

Electrical and Electronic Engineering,Condensed Matter Physics,Electronic, Optical and Magnetic Materials

Link

https://www.jstage.jst.go.jp/article/elex/14/17/14_14.20170463/_pdf

Reference10 articles.

1. [1] J. Huanget al.: “An intelligent fault diagnosis method of high voltage circuit breaker based on improved EMD energy entropy and multi-class support vector machine,” Electr. Power Syst. Res. 81 (2011) 400 (DOI: 10.1016/j.epsr.2010.10.029).

2. [2] B. Xieet al.: “Partition of the development stage of air-gap discharge in oil-paper insulation based on wavelet packet energy entropy,” IEEE Trans. Dielectr. Electr. Insul. 23 (2016) 866 (DOI: 10.1109/TDEI.2015.005430).

3. [3] N. Charbkaewet al.: “Vibration signal analysis for condition monitoring of puffer-type high-voltage circuit breakers using wavelet transform,” IEEJ Trans. Electr. Electron. Eng. 7 (2012) 13 (DOI: 10.1002/tee.21690).

4. [4] D. Pérez-Canaleset al.: “Identification of dynamic instabilities in machining process using the approximate entropy method,” Int. J. Mach. Tools Manuf. 51 (2011) 556 (DOI: 10.1016/j.ijmachtools.2011.02.004).

5. [5] A. Rodriguez and A. Laio: “Clustering by fast search and find of density peaks,” Science 344 (2014) 1492 (DOI: 10.1126/science.1242072).

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