• DocumentCode
    3195680
  • Title

    State Assessment System of Power Transformer Equipments Based on Data Mining and Fuzzy Theory

  • Author

    Zhong Wenhui ; Sun Yixue ; Xu Min ; Liu Jingping

  • Author_Institution
    Sch. of Inf. Eng., Nanchang Univ., Nanchang, China
  • Volume
    3
  • fYear
    2010
  • fDate
    11-12 May 2010
  • Firstpage
    372
  • Lastpage
    375
  • Abstract
    The state assessment system of power transformer equipments based on data mining and fuzzy theory is introduced briefly in this article. The statistics-based association rule mining will be used as data preprocessing method. Assess model of power transformer equipments is created according to standards of Transformation Condition-Based Maintenance equipment which is carried out by State Power Grid on May 1, 2005, test data are treated with fuzzy comprehensive evaluation, then a software platform that includes functionality to collect and store experimental data, analyze data and trend, generate assessment report and put forward suggestions on repairing of transformer equipment status is built.
  • Keywords
    data mining; fuzzy set theory; maintenance engineering; power apparatus; power engineering computing; power grids; power transformers; data mining; fuzzy comprehensive evaluation; fuzzy theory; power transformer equipments; repairing; software platform; state assessment system; state power grid; statistics-based association rule mining; transformation condition-based maintenance equipment; Association rules; Data mining; Data preprocessing; Fuzzy systems; Power grids; Power system modeling; Power transformers; Software maintenance; Software standards; Software testing; Condition-Based Maintenance (CBM); Data Mining; Fuzzy Theory; power transformer equipment;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computation Technology and Automation (ICICTA), 2010 International Conference on
  • Conference_Location
    Changsha
  • Print_ISBN
    978-1-4244-7279-6
  • Electronic_ISBN
    978-1-4244-7280-2
  • Type

    conf

  • DOI
    10.1109/ICICTA.2010.308
  • Filename
    5522879