• DocumentCode
    2810958
  • Title

    Research on Magnetic Flux Leakage Signals Quantity Technology of Tank Floor Corrosion Defects Based on Artificial Neural Network

  • Author

    Yang, Zhijun ; Dai, Guang ; Li, Wei ; Jiang, Yanbiao

  • Author_Institution
    Daqing Pet. Inst., Daqing, China
  • Volume
    2
  • fYear
    2009
  • fDate
    14-16 Aug. 2009
  • Firstpage
    245
  • Lastpage
    249
  • Abstract
    Magnetic flux leakage testing method is a major direction of tank floor testing. In this paper, the spatial distribution of magnetic flux leakage field of tank floor corrosion defects is analyzed based on the features of magnetic flux leakage signals. BP neural network model is applied to the quantity analysis of tank floor corrosion defects. The results in network training and test reach the quantitative accuracy requirements of tank floor corrosion defects, the established BP neural network is effective to the quantitative recognition of depth and width of the defects.
  • Keywords
    backpropagation; corrosion testing; magnetic flux; magnetic leakage; mechanical engineering computing; neural nets; tanks (containers); BP neural network model; artificial neural network; magnetic flux leakage signals quantity technology; magnetic flux leakage testing method; network training; quantity analysis; tank floor corrosion defects; tank floor testing; Artificial neural networks; Biological neural networks; Corrosion; Leak detection; Magnetic analysis; Magnetic fields; Magnetic flux leakage; Magnetic materials; Neural networks; Testing; corrosion defects; neural network; quantity; tank floor;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation, 2009. ICNC '09. Fifth International Conference on
  • Conference_Location
    Tianjin
  • Print_ISBN
    978-0-7695-3736-8
  • Type

    conf

  • DOI
    10.1109/ICNC.2009.460
  • Filename
    5362993