• DocumentCode
    2052056
  • Title

    Bolt tightening control using neural networks

  • Author

    Fujinaka, Toru ; Nakano, Hikofumi ; Omatu, Slgeru

  • Author_Institution
    Graduate Sch. of Eng., Osaka Prefecture Univ., Japan
  • Volume
    3
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    1390
  • Abstract
    We propose a method of controlling the tightening operation of bolts using a device called an impact wrench. A neural network is used for classifying the material and shape of the work to which the bolts are being tightened. Then another neural network is used for estimating the relationship between the clamping force of the bolt and its incremental angle. The input to the actuator of the impact wrench is determined based on the estimated value of the clamping force. A simulation study shows satisfactory results in comparison to those achieved by a skilled factory worker
  • Keywords
    assembling; backpropagation; factory automation; feedforward neural nets; force control; neurocontrollers; torque control; backpropagation; bolt tightening; clamping force; force control; impact wrench; incremental angle; multilayer neural network; torque control; Automobiles; Clamps; Fasteners; Force measurement; Industrial accidents; Neural networks; Shafts; Shape; Torque; Wheels;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics, 2001 IEEE International Conference on
  • Conference_Location
    Tucson, AZ
  • ISSN
    1062-922X
  • Print_ISBN
    0-7803-7087-2
  • Type

    conf

  • DOI
    10.1109/ICSMC.2001.973476
  • Filename
    973476