• DocumentCode
    554445
  • Title

    Research on the milling tool monitoring system based on wavelet neural network

  • Author

    Guizhong Guo ; Xinhua Mao

  • Author_Institution
    Xinxiang Univ., Xinxiang, China
  • Volume
    3
  • fYear
    2011
  • fDate
    12-14 Aug. 2011
  • Firstpage
    1421
  • Lastpage
    1423
  • Abstract
    Among the milling process, the signal representation tools sharply wearing in primary stage, is weaker. While the work piece accuracy have already at this time obvious change. Wavelet neural network can effectively handle various signals with different frequency, but it is possible that it can not detect the faint signal. Based on monitoring accuracy change of the workpiece, do modify the parameter of wavelet transform in time, and it can enhance the ability of monitoring faint signal, decrease missing rate and false alarm rate.
  • Keywords
    computerised monitoring; milling machines; neural nets; signal detection; signal representation; wavelet transforms; faint signal detection; false alarm rate; milling tool monitoring system; signal representation tools; wavelet neural network; wavelet transform; Accuracy; Biological neural networks; Force; Milling; Monitoring; Surface roughness; Wavelet transforms; Monitoring; The milling Cutter; Wavelet neural network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electronic and Mechanical Engineering and Information Technology (EMEIT), 2011 International Conference on
  • Conference_Location
    Harbin, Heilongjiang, China
  • Print_ISBN
    978-1-61284-087-1
  • Type

    conf

  • DOI
    10.1109/EMEIT.2011.6023313
  • Filename
    6023313