• DocumentCode
    2999745
  • Title

    Characteristic extraction of ultrasonic detection of bonding interface of thin composite plate based on wavelet transformation

  • Author

    Ze, Zhang ; Zhiqi, Gao ; Yueqing, Ren ; Kun, Liu

  • Author_Institution
    Dept. of Autom., Inner Mongolia Univ., Hohhot
  • fYear
    2008
  • fDate
    1-3 Sept. 2008
  • Firstpage
    1891
  • Lastpage
    1895
  • Abstract
    This paper studies an algorithm of characteristic extraction of ultrasonic detection based on wavelet transformation. The object of ultrasonic detection is thin composite plate. At first, we discuss characteristic and composing principle of the detail of echo signal, based on this a math model is designed. And then, wavelet transformation is used to process echo signal model and defect signal model of different viscid quality, we extract characteristic about energy and dimension in time-frequency domain. Simulation by the Matlab proves that the algorithm can recognize different echo signals effectively, and it is helpful to quantitative detection and recognition.
  • Keywords
    flaw detection; mathematics computing; plates (structures); time-frequency analysis; ultrasonic materials testing; wavelet transforms; Matlab; characteristic extraction; defect signal model; echo signal model; math model; quantitative detection; quantitative recognition; thin composite plate; time-frequency domain; ultrasonic detection; wavelet transformation; Attenuation; Automation; Bonding; Composite materials; Mathematical model; Object detection; Signal analysis; Signal processing; Time frequency analysis; Wavelet analysis; Characteristic extraction; Math model; Ultrasonic detection; Wavelet transformation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Automation and Logistics, 2008. ICAL 2008. IEEE International Conference on
  • Conference_Location
    Qingdao
  • Print_ISBN
    978-1-4244-2502-0
  • Electronic_ISBN
    978-1-4244-2503-7
  • Type

    conf

  • DOI
    10.1109/ICAL.2008.4636467
  • Filename
    4636467