• DocumentCode
    1896596
  • Title

    Crackle-Image of Swing Bolster Detection Algorithm Based on Visual Perception

  • Author

    Peng Lu ; Yongqiang Li ; Zhizhong Wang ; Yuhe Tang ; Eryang Chen ; Kun Jiao

  • Author_Institution
    Sch. of Electr. Eng., Zhengzhou Univ., Zhengzhou, China
  • fYear
    2010
  • fDate
    25-26 Dec. 2010
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    A novel method based on the visual perception mechanism was proposed for solving the problem of fault-image detection of the running train. The detection of swing bolster crack could be achieved in high efficiency with small samples. Firstly, the receptive field of simple cells in the primary visual cortex was obtained from the image sequence by using the ICA model. Secondly, the neuron response of normal and fault image was calculated, then the neuron responding stronger to the stimulus could be found out, and its corresponding content for fault detecting could be output as well. Experimental results demonstrated that this novel method had a high fault-detecting rate.
  • Keywords
    fault diagnosis; image sequences; independent component analysis; railway industry; ICA model; crackle image; fault image detection; image sequence; running train; swing bolster detection algorithm; visual perception; Algorithm design and analysis; Fault detection; Information processing; Neurons; Transforms; Visual perception; Visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Engineering and Computer Science (ICIECS), 2010 2nd International Conference on
  • Conference_Location
    Wuhan
  • ISSN
    2156-7379
  • Print_ISBN
    978-1-4244-7939-9
  • Electronic_ISBN
    2156-7379
  • Type

    conf

  • DOI
    10.1109/ICIECS.2010.5678147
  • Filename
    5678147