• DocumentCode
    2559079
  • Title

    The recognition of train wheel tread damages based on PSO-RBFNN algorithm

  • Author

    Zhao Yong ; Ye Hong ; Kang Zheng-sheng ; Shi Song-shan ; Zhou Lin

  • Author_Institution
    Mech. Dept., Chang´an Univ., Xi´an, China
  • fYear
    2012
  • fDate
    29-31 May 2012
  • Firstpage
    1093
  • Lastpage
    1095
  • Abstract
    In order to the recognition of the train wheel tread damages, the pattern recognition method of the train wheel tread damages based on PSO-RBFNN was developed. The algorithm uses PSO-RBFNN algorithm to optimize center and spread of RBFNN, the connection weight value is sovled by least squares method. Compared with the traditional RBFNN,BP and GA-RBFNN, the experiment results show that the recognition rate of testing samples is higher than the traditional RBFNN, BP and GA-RBFNN, the evolutional generations of PSO-RBFNN algorithm were less than RBFNN, BP and GA-RBFNN.
  • Keywords
    least squares approximations; particle swarm optimisation; pattern recognition; radial basis function networks; railway engineering; wheels; BP; GA-RBFNN; PSO-RBFNN algorithm; connection weight value; least squares method; pattern recognition; train wheel tread damages; Accuracy; Feature extraction; Inspection; Pattern recognition; Signal processing algorithms; Training; Wheels; PSORBFNN; recognition; train wheel; tread damage;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation (ICNC), 2012 Eighth International Conference on
  • Conference_Location
    Chongqing
  • ISSN
    2157-9555
  • Print_ISBN
    978-1-4577-2130-4
  • Type

    conf

  • DOI
    10.1109/ICNC.2012.6234662
  • Filename
    6234662