• DocumentCode
    1275121
  • Title

    Optimal design of a coil arrangement for the identification of hidden ferrous objects

  • Author

    Renhart, W. ; Magele, C.

  • Author_Institution
    Inst. for Fundamentals & Theor. in Electr. Eng., Graz Univ. of Technol., Austria
  • Volume
    38
  • Issue
    2
  • fYear
    2002
  • fDate
    3/1/2002 12:00:00 AM
  • Firstpage
    1121
  • Lastpage
    1124
  • Abstract
    The process of identifying unknown hidden objects, such as the detection of electrical conductors in concrete by taking advantage of electromagnetic effects, is becoming more important. Magnetization and eddy currents are the electromagnetic phenomena which are exploited in general. In this case, the layout and arrangement of the exciting coils and receiving coils crucially influences effectiveness and accuracy. When designing an optimal device, the electromagnetic field has to be simulated over and over, which requires an enormous number of three-dimensional finite-element calculations. One way to overcome this problem is to approximate the electromagnetic data necessary for the identification by a neural network. Investigations on a ferrous conductive rod are described
  • Keywords
    backpropagation; buried object detection; coils; eddy currents; electrical engineering computing; feedforward neural nets; finite element analysis; inverse problems; Levenberg-Marquardt back propagation algorithm; eddy currents; electrical conductor detection; electromagnetic effects; electromagnetic field simulation; exciting coils; feedforward neural network; ferrous conductive rod; hidden ferrous object identification; magnetization; neural network; optimal coil design; receiving coils; three-dimensional finite element calculations; Coils; Computer networks; Eddy currents; Finite element methods; Magnetic field measurement; Magnetization; Neural networks; Numerical models; Signal processing; Voltage;
  • fLanguage
    English
  • Journal_Title
    Magnetics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9464
  • Type

    jour

  • DOI
    10.1109/20.996287
  • Filename
    996287