• DocumentCode
    501549
  • Title

    Crack detection using a hybrid finite difference frequency domain and particle swarm optimization techniques

  • Author

    Zainud-Deen, S.H. ; Hassen, W.M. ; Awadalla, K.H.

  • Author_Institution
    Fac. of Electron. Eng, Menoufia Univ., Shibin El Kom, Egypt
  • fYear
    2009
  • fDate
    17-19 March 2009
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    A hybrid technique based on finite-difference frequency domain (FDFD) and particle swarm optimization (PSO) techniques is proposed to reconstruct the angular crack width and its position in the conductor and ability to detect the crack width, position, and its depth in single and multilayer dielectric objects. FDFD is formulated to calculate the scattered field after illuminating the object by a microwave transmitter. Two-dimensional model for the object is used. Computer simulations have been performed by means of a numerical program; results show the capabilities of the proposed approach. This paper presents a computational approach to the two dimensional inverse scattering problem based on FDFD method and PSO technique to determine the crack position, width and depth. By using the scattered field, the specifications of the crack are reconstructed.
  • Keywords
    finite difference methods; image reconstruction; object detection; particle swarm optimisation; angular crack width; crack detection; hybrid finite difference frequency domain; microwave transmitter; object detection; particle swarm optimization technique; two-dimensional inverse scattering problem; Computer simulation; Conductors; Dielectrics; Finite difference methods; Frequency domain analysis; Nonhomogeneous media; Object detection; Particle scattering; Particle swarm optimization; Transmitters;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Radio Science Conference, 2009. NRSC 2009. National
  • Conference_Location
    New Cairo
  • ISSN
    1110-6980
  • Print_ISBN
    978-1-4244-4214-0
  • Type

    conf

  • Filename
    5234019