Journal of Jilin University Science Edition

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Abnormality Detection of Capacitive Equipment Based on Wavelet Tree

YU Qiangyuan1,2, FAN Shichao1, JIN Chengye3   

  1. 1. College of Computer Science and Technology, Jilin University, Changchun 130012, China;2. Key Laboratory of Symbolic Computation and Knowledge
     Engineering of Ministry of Education, [JP+1]Jilin University, Changchun 130012, China; 3. Jilin Province Lejin Electronic Co. Ltd., Changchun 130062, China
  • Received:2014-10-27 Online:2015-11-26 Published:2015-11-23
  • Contact: YU Qiangyuan E-mail:qiangyuan@jlu.edu.cn

Abstract:

To solve the abnormality detection problem of capacitive equipment in the power system, a method of electric insulativity detection based on wavelet tree was proposed with dielectric loss factor as detecting parameter. It basically solves the problem of abnormality automatic detection. In this method, twolayered wavelet tree was used to deal with the data of dielectric loss factor, which can detect abrupt change and continuous change of dielectric loss factor. The real dielectric loss factor data obtained from power substation were used to analyze the electric insulativity of capacitive equipment. The result proves the effectivity and practicality of the method, which can assist the early warning of abnormality.

Key words: abnormality detection, wavelet tree, capacitive equipment, dielectric loss factor

CLC Number: 

  • TP274