• DocumentCode
    3572987
  • Title

    Robotic impact-echo Non-Destructive Evaluation based on FFT and SVM

  • Author

    Bing Li ; Jing Cao ; Jizhong Xiao ; Xiaochen Zhang ; Hongfan Wang

  • Author_Institution
    Dept. of Electr. Eng., City Coll. of New York, New York, NY, USA
  • fYear
    2014
  • Firstpage
    2854
  • Lastpage
    2859
  • Abstract
    Previous research has shown that the impact-echo emission signals contain information about the flaws of structural integrity and deterioration levels of concrete bridges. This paper presents a method of using the mobile robot equipped with an impact-echo Non-Destructive Evaluation (NDE) device to autonomously collect data, perform automatic classification and 3D visualization of the detected flaws. This method is based on Power Spectral Density (PSD) analysis for the Fast Fourier Transform (FFT) of the impact-echo signals, and Support Vector Machine (SVM) classification. Therefore, health condition of concrete bridge decks can be automatically recorded, analyzed and visualized in 3D.
  • Keywords
    acoustic emission testing; concrete; condition monitoring; data visualisation; fast Fourier transforms; flaw detection; impact (mechanical); industrial robots; mobile robots; nondestructive testing; pattern classification; solid modelling; structural engineering; support vector machines; FFT; NDE device; PSD analysis; SVM classification; automatic detected flaw 3D visualization; automatic detected flaw classification; concrete bridge deck health condition analysis; concrete bridges; deterioration levels; fast Fourier transform; impact-echo emission signals; impact-echo nondestructive evaluation device; impact-echo signals; mobile robot; power spectral density analysis; robotic impact-echo nondestructive evaluation; structural integrity flaws; support vector machine classification; Bridges; Concrete; Data models; Inspection; Support vector machines; Three-dimensional displays; Training; FFT; impact-echo technology; mobile robot; non-destructive evaluation; support vector machine;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation (WCICA), 2014 11th World Congress on
  • Type

    conf

  • DOI
    10.1109/WCICA.2014.7053181
  • Filename
    7053181