• DocumentCode
    1566856
  • Title

    Residual Adaptive Algorithm Applied in Intelligent Real-time Calculation of Current RMS Value During Resistance Spot Welding

  • Author

    Gong, Liang ; Liu, Cheng-Liang ; Guo, Lei

  • Author_Institution
    Mechatronics Inst., Shanghai Jiao Tong Univ.
  • Volume
    3
  • fYear
    2005
  • Firstpage
    1800
  • Lastpage
    1806
  • Abstract
    To solve the large residual problems, which may occur during feed-forward neural network weight training, a comprehensive residual adaptive algorithm is proposed to give a better stability compared to standard Levenberg-Marquardt (L-M) algorithm and has less computational complexity than classical Newton method. The comparison with standard L-M algorithm checks the better performance of this algorithm. Then the well-trained neural network is embedded into a DSP controller to perform real-time calculation of current RMS value during resistance spot welding. Experimental result shows the validity of the residual adaptive algorithm and the feasibility of an intelligent current measuring method
  • Keywords
    adaptive systems; calculation; computational complexity; electric current measurement; feedforward neural nets; neurocontrollers; spot welding; stability; computational complexity; current RMS value; feedforward neural network; intelligent real-time calculation; residual adaptive algorithm; resistance spot welding; Adaptive algorithm; Computational complexity; Computational intelligence; Digital signal processing; Feedforward neural networks; Feedforward systems; Neural networks; Newton method; Spot welding; Stability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks and Brain, 2005. ICNN&B '05. International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    0-7803-9422-4
  • Type

    conf

  • DOI
    10.1109/ICNNB.2005.1614976
  • Filename
    1614976