• DocumentCode
    777126
  • Title

    Model-Based Real-Time Dynamic Power Factor Measurement in AC Resistance Spot Welding With an Embedded ANN

  • Author

    Gong, Liang ; Liu, Cheng-Liang ; Zha, Xuan F.

  • Author_Institution
    Inst. of Mechatronics, Shanghai Jiao Tong Univ.
  • Volume
    54
  • Issue
    3
  • fYear
    2007
  • fDate
    6/1/2007 12:00:00 AM
  • Firstpage
    1442
  • Lastpage
    1448
  • Abstract
    Today, real-time measurement of dynamic power factor in resistance spot welding (RSW) is of increasing importance. On the basis of the welding transformer circuit model, a new method is proposed to measure the peak angle of the welding current and then calculate the dynamic power factor in each half-wave. The tailored sensing and computing system ensures that the measuring method possesses a real-time computational capacity with satisfying accuracy. Since the power factor cannot be represented via an explicit function with respect to measurable parameters, the traditional method(s) has to approximate the power factor angle with a constant phase lag angle and fails to detect its dynamic characteristics. An offline-trained embedded artificial neural network (ANN) successfully realizes the real-time implicit function calculation or estimation. A digital-signal-processor-based RSW monitoring system is developed to perform ANN computation. Experimental results indicate that the proposed method is applicable for measuring the dynamic power factor in single-phase half-wave controlled rectifier circuits
  • Keywords
    neural nets; power factor measurement; rectifying circuits; spot welding; welding; AC resistance spot welding; RSW; artificial neural network; embedded ANN; real-time dynamic power factor measurement; single-phase half-wave controlled rectifier circuits; welding transformer circuit model; Artificial neural networks; Circuits; Current measurement; Electrical resistance measurement; Goniometers; Power measurement; Power system modeling; Reactive power; Real time systems; Spot welding; Dynamic power factor; feedforward neural networks (NNs); miniature Rogowski loop; silicon-controlled rectifier (SCR); voltage transformers; welding;
  • fLanguage
    English
  • Journal_Title
    Industrial Electronics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0278-0046
  • Type

    jour

  • DOI
    10.1109/TIE.2007.892607
  • Filename
    4155075