• DocumentCode
    569092
  • Title

    An Improved IGA-BP Algorithm Applied to Fault Diagnosis

  • Author

    Wu, Lichun ; Zhang, Li ; Yang, Yongbo ; Sun, Lijie ; Li, Fengman

  • Author_Institution
    Sch. of Inf., Liaoning Univ., Shenyang, China
  • fYear
    2012
  • fDate
    July 31 2012-Aug. 2 2012
  • Firstpage
    194
  • Lastpage
    197
  • Abstract
    In immune genetic algorithm of float coding, there would be no certain way to calculate the critical value based on the Euclidean distance similarity. For this problem, the paper puts forward a way on "3σ" method; inspired by the elitist strategy, the paper modifies the coefficient of arithmetic crossover method, which can adaptively incline toward the higher fitness value of two pairs of antibody. The improved IGA-BP algorithm is applied to the fault diagnosis of transmission gear. The experiment is simulated on MATLAB, and its result shows that the "3σ" method is an effective solution, and this improved algorithm has several advantages such as fast convergence, good adaptability, high accuracy on transmission gear\´s fault types.
  • Keywords
    fault diagnosis; genetic algorithms; Euclidean distance similarity; arithmetic crossover method; fault diagnosis; float coding; immune genetic algorithm; improved IGA-BP algorithm; Encoding; Euclidean distance; Fault diagnosis; Genetic algorithms; Neural networks; Sociology; Statistics; Arithmetic crossover; Euclidean Distance; Fault Diagnosis; Immune Genetic Algorithm; Neural Network; Self-Adaption;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Digital Manufacturing and Automation (ICDMA), 2012 Third International Conference on
  • Conference_Location
    GuiLin
  • Print_ISBN
    978-1-4673-2217-1
  • Type

    conf

  • DOI
    10.1109/ICDMA.2012.47
  • Filename
    6298287