DocumentCode :
128771
Title :
Time-frequency analysis for power transformer fault detection using vibration method
Author :
Hong Kaixing ; Huang Hai ; Zheng Jing ; Zhou Jianping ; Zhou Yangyang ; Liu Jiangming
Author_Institution :
Dept. of Instrum. Sci. & Eng., Zhejiang Univ., Hangzhou, China
fYear :
2014
fDate :
9-11 June 2014
Firstpage :
2110
Lastpage :
2114
Abstract :
The vibration methods are widely employed in the machinery condition monitoring and the time-frequency analysis has been applied in many fault detection applications. In this paper, the study of the vibrations using Wigner-Ville distribution is presented to assess the power transformer condition. First, the distribution contour plots of power transformer vibrations under different conditions are compared. Then, the pattern recognition based on the energy distribution similarity is presented. Finally, a health metric is proposed to represent the transformer health state. The results from more than 10 transformers are compared, and the preliminary study shows that the proposed method is effective to assess the power transformer condition.
Keywords :
condition monitoring; fault diagnosis; machinery; power transformers; time-frequency analysis; vibrations; Wigner-Ville distribution; distribution contour plots; energy distribution similarity; health metric; machinery condition monitoring; pattern recognition; power transformer fault detection; time-frequency analysis; transformer health state representation; vibration method; Pattern recognition; Power transformer insulation; Time-frequency analysis; Vibrations; Windings; Wigner-Ville distribution; fault detection; transformer vibration;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics and Applications (ICIEA), 2014 IEEE 9th Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4799-4316-6
Type :
conf
DOI :
10.1109/ICIEA.2014.6931519
Filename :
6931519
Link To Document :
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