• DocumentCode
    791600
  • Title

    Quality inspection of electroplated materials using planar type micro-magnetic sensors with post-processing from neural network model

  • Author

    Mukhopadhyay, S.C.

  • Author_Institution
    Inst. of Inf. Sci. & Technol., Massey Univ., Palmerston North, New Zealand
  • Volume
    149
  • Issue
    4
  • fYear
    2002
  • fDate
    7/1/2002 12:00:00 AM
  • Firstpage
    165
  • Lastpage
    171
  • Abstract
    The possibility of employing planar type micro-magnetic sensors for the evaluation of the quality of electroplated materials as well as to inspect the presence of defects in its near-surface is investigated. The impedance of a planar type micro-magnetic sensor in the proximity of any metal surface is a complex function of many parameters including near-surface material properties. A two-dimensional model of two types of planar micro-magnetic sensors having meander and mesh type configurations has been developed for the analytical calculation of magnetic vector potential, flux-linkage and impedance. The impedance of the sensor is used for the evaluation of the quality of the electroplated materials. Usually an off-line generated grid system is used for the online evaluation of near-surface material properties. Use of a simple neural network model is proposed for the post-processing of output parameters from the measured impedance data as an alternative to the grid system
  • Keywords
    coils; electroplating; magnetic sensors; microsensors; quality control; electroplated materials; flux-linkage; impedance; magnetic vector potential; meander configurations; mesh type configurations; near-surface material properties; neural network model; off-line generated grid system; output parameters; planar type micro-magnetic sensors; post-processing; proximity; quality inspection; two-dimensional model;
  • fLanguage
    English
  • Journal_Title
    Science, Measurement and Technology, IEE Proceedings -
  • Publisher
    iet
  • ISSN
    1350-2344
  • Type

    jour

  • DOI
    10.1049/ip-smt:20020340
  • Filename
    1020878