Electric Power ›› 2014, Vol. 47 ›› Issue (4): 75-79.DOI: 10.11930/j.issn.1004-9649.2014.4.75.4

• Orginal Article • Previous Articles     Next Articles

Fault Diagnosis of Power Transformer Based on Vibration and Wavelet Neural Network

WANG Chun-ning1, ZHU Yue-guang2, MA Hong-zhong2, ZHAO Hong-fei2, CHEN Ji-ning3   

  1. 1. Jiangsu Nanjing Power Supply Company, Nanjing 210008, China;
    2. Research Center for Renewable Energy Generation Engineering , Hohai University, Ministry of Education, Nanjing 210098, China;
    3. Jiangsu Suqian Power Supply Company, Suqian 223800, China
  • Received:2014-01-22 Online:2015-12-22 Published:2014-04-30
  • Supported by:
    This work is supported by Science and Technology Project of State Grid Corporation (2011-0810-2251)

Abstract: A fault diagnostic method of power transformer based on vibration and wavelet neural network is presented, which gets the characteristics of the vibration in frequency domain from the vibration sampled from the tank of transformers to train for the wavelet neural network(WNN). With the output of the wavelet neural network, we can get the relationship between the faults and the frequency characteristics can be obtained. The experiment results show that the proposed method can be used for diagnosis of power transformer and output the type of the fault, and the wavelet neural has a good generalized performance.

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