• DocumentCode
    394447
  • Title

    Neural network based on-line detection of drill breakage in micro drilling process

  • Author

    Fu, Lianyu ; Ling, Shih-Fu

  • Author_Institution
    Sch. of Mech. & Production Eng., Nanyang Technol. Univ., Singapore
  • Volume
    4
  • fYear
    2002
  • fDate
    18-22 Nov. 2002
  • Firstpage
    2054
  • Abstract
    The breakage of drill bit often occurs in micro drilling process because of the very small drill diameter. So on-line detection of drill breakage plays an important role in micro drilling process. In this paper, a method for the on-line detection of the drill breakage in micro drilling process based on neural network is presented. The characteristic of the drilling torque during the drilling process is studied first. Five features extracted from the drilling torque signal and the drilling conditions are input to a neural network for the detection of the drill breakage. A three-layer backpropagation neural network with five input nodes, ten hidden nodes and one output node is applied here. The results show that the presented neural network based method can effectively detect the drill breakage in micro drilling process.
  • Keywords
    backpropagation; feature extraction; micromachining; multilayer perceptrons; neural nets; online operation; pattern recognition; drill bit breakage; feature extraction; micro drilling process; microdrilling process; online drill breakage detection; three-layer backpropagation neural network; Drilling; Force measurement; Intelligent networks; Machining; Monitoring; Neural networks; Signal detection; Signal processing; Torque measurement; Vibration measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Information Processing, 2002. ICONIP '02. Proceedings of the 9th International Conference on
  • Print_ISBN
    981-04-7524-1
  • Type

    conf

  • DOI
    10.1109/ICONIP.2002.1199036
  • Filename
    1199036