• DocumentCode
    2862465
  • Title

    An Alternative Approach to Estimate Load Torque in Industrial Environment Using Neural Networks

  • Author

    Goedtel, A. ; da Silva, I.N. ; Serni, P. J A ; Flauzino, R.A.

  • Author_Institution
    Eng. Sch. of Sao Carlos, Sao Paulo Univ.
  • fYear
    2006
  • fDate
    24-26 May 2006
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    The induction motors are largely used in several industry sectors. The dimensioning of an induction motor has still been inaccurate because in most of the cases the load behavior in its shaft is completely unknown. The proposal of this paper is to use artificial neural networks as a tool for estimating the load torque applied to the induction motor shaft rather than conventional methods, which use classical identification techniques and mechanical load modeling. Simulation results are also presented to validate the proposed approach
  • Keywords
    induction motors; neural nets; power engineering computing; production engineering computing; torque; artificial neural networks; identification techniques; induction motors; industrial environment; load torque estimation; mechanical load modeling; Artificial neural networks; Differential equations; Electrical equipment industry; Induction motors; Industrial control; Neural networks; Shafts; State estimation; Steady-state; Torque measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics and Applications, 2006 1ST IEEE Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    0-7803-9513-1
  • Electronic_ISBN
    0-7803-9514-X
  • Type

    conf

  • DOI
    10.1109/ICIEA.2006.257362
  • Filename
    4025963