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A NEURAL NETWORK MODEL 0OF A CMM APPLIED FOR MEASUREMENT ACCURACY ASSESSMENT

J. Sladek
  • Abstract:
    The paper presents research on CMM virtual modelling applied for assessment of measurement accuracy and a method of CMM errors identification. The idea of the proposed method of error estimation is based on the measurement of a workpiece plate (hole or ball), placed in the CMM measuring area in such way, that reference points compose a spatial grid. The difference between co-ordinates of particular shape elements midpoints obtained from workpiece calibration and the coordinates given by the CMM creates the error grid. This grid is a basis for a matrix method of CMM error identification. The identification matrix corresponds to the reference points distribution. The matrix model for the CMM error identification is composed of two component parts: one - CMM errors depending on the position in the measuring area of the tested machine and the other - independent of this position. An idea of a virtual model is based on artificial neural networks. Results of comparative research into various virtual models of measuring machines have been discussed.
  • Keywords:
    CMM, neural network, virtual model
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  • DOI:
    _unreg_wc-2000.295

Event details:

  • IMEKO TC:
  • Event name:
    XVI IMEKO World Congress
  • Title:

    Measurement - Supports Science - Improves Technology - Protects Environment ... and Provides Employment - Now and in the Future

  • Place:
    Vienna, AUSTRIA
  • Time:
    25 September 2000 - 28 September 2000