• DocumentCode
    2229050
  • Title

    Prediction of the laser sheet bending using neural network

  • Author

    Dragos, Valentina ; Dan, V. ; Kovacevic, Radovan

  • Author_Institution
    Dept. of Mech. Eng., Southern Methodist Univ., Dallas, TX
  • Volume
    3
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    686
  • Abstract
    In this paper, a neural network algorithm is used in predicting the future shape obtained by laser forming. Aluminum and steel samples were used and the thickness of the materials, the laser power beam and the scanning speed were the variable parameters of the process. The bending angles versus the number of scanning passes obtained experimentally are in good agreement with angle values given by the training process algorithm
  • Keywords
    bending; feedforward neural nets; forming processes; laser beam machining; metalworking; neurocontrollers; bending angles; laser forming; laser power beam; laser sheet bending; material thickness; neural network algorithm; scanning passes; scanning speed; training process algorithm; variable parameters; Aluminum; Building materials; Laser beams; Neural networks; Optical materials; Power lasers; Shape; Sheet materials; Steel; Structural beams;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 2000. Proceedings. ISCAS 2000 Geneva. The 2000 IEEE International Symposium on
  • Conference_Location
    Geneva
  • Print_ISBN
    0-7803-5482-6
  • Type

    conf

  • DOI
    10.1109/ISCAS.2000.856153
  • Filename
    856153