• DocumentCode
    1416897
  • Title

    The reliability of multi-parameter insulation diagnosis

  • Author

    Wu, Kai ; Shen, Wei ; Meng, Yongpeng ; Cao, Wen ; Pan, Cheng ; Cheng, Yonghong ; Zhang, Xiaohong

  • Author_Institution
    State Key Lab. of Electr. Insulation & Power Equip., Xi´´an Jiaotong Univ., Xi´´an, China
  • Volume
    17
  • Issue
    1
  • fYear
    2010
  • fDate
    2/1/2010 12:00:00 AM
  • Firstpage
    280
  • Lastpage
    286
  • Abstract
    On the basis of statistical theory, a method to determine quantitatively the reliability of multi-parameter diagnosis and to optimize the algorithm of multi-parameter diagnosis is put forward. Moreover, as an example, this method is applied to the estimation of residual breakdown voltage of generator bars and the optimized multi-parameter diagnosis algorithm is determined on the basis of actual data. Comparing with experimental data, it shows that the result of multi-parameter prediction model is more accurate than that of single-parameter prediction model when choosing the appropriate parameters group, however the quantity of parameters is not the more the better. To choose appropriate parameters for assessing insulation condition is important.
  • Keywords
    electric generators; fault diagnosis; insulation testing; statistical analysis; generator bars; multiparameter insulation diagnosis reliability; multiparameter prediction model; residual breakdown voltage; single-parameter prediction model; statistical theory; Aging; Current measurement; Dielectrics and electrical insulation; Dispersion; Failure analysis; Investments; Life estimation; Optimization methods; Power generation; Predictive models; Multi parameter; choice of parameters; insulation diagnosis;
  • fLanguage
    English
  • Journal_Title
    Dielectrics and Electrical Insulation, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1070-9878
  • Type

    jour

  • DOI
    10.1109/TDEI.2010.5412028
  • Filename
    5412028