• DocumentCode
    1199624
  • Title

    Genetic algorithms for nondestructive testing in crack identification

  • Author

    Arkadan, A.A. ; Sareen, T. ; Subramaniam, S.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Marquette Univ., Milwaukee, WI, USA
  • Volume
    30
  • Issue
    6
  • fYear
    1994
  • fDate
    11/1/1994 12:00:00 AM
  • Firstpage
    4320
  • Lastpage
    4322
  • Abstract
    A method to identify the nature of a crack on the surface of a region using nondestructive testing (NDT) and inverse problem methodology is presented. A genetic algorithm (GA) based approach, which involves a global search to avoid local minima, is presented and applied to solve the inverse problem of identifying the position, shape and the orientation of a surface crack. A fine tuning algorithm is combined with the GA to reach the optimum solution
  • Keywords
    crack detection; genetic algorithms; inverse problems; nondestructive testing; crack identification; fine tuning algorithm; genetic algorithms; global search; inverse problem methodology; local minima; nondestructive testing; optimum solution; surface crack; Artificial neural networks; Electronic switching systems; Genetic algorithms; Genetic mutations; Inverse problems; Nondestructive testing; Shape; Simulated annealing; Stochastic processes; Surface cracks;
  • fLanguage
    English
  • Journal_Title
    Magnetics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9464
  • Type

    jour

  • DOI
    10.1109/20.334074
  • Filename
    334074
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1199624