• DocumentCode
    1123729
  • Title

    Spectral dynamic analysis of power transmission towers using ANN imperfection Simulator

  • Author

    Safi, Mohammad ; Horr, Amir Masoud

  • Author_Institution
    Abbaspour Power & Water Inst. of Technol., Tehran, Iran
  • Volume
    19
  • Issue
    4
  • fYear
    2004
  • Firstpage
    1907
  • Lastpage
    1912
  • Abstract
    One major division in the mathematical modeling of power transmission towers is to include the effect of imperfections in the dynamical response of the system. The neural-network simulators as a nonparametric system identification approach present a robust and efficient way to simulate the nonlinear behavior of engineering systems. In the paper herein, an artificial-neural-network (ANN) simulator, a general back error propagating perceptron, is used to simulate random imperfection for spectral dynamic analysis of power transmission towers. There have been considerable efforts to apply the method of spectral analysis to the vibration of a structure using spectral frame elements. In the first part of the paper, the analytical development of the spectral method has been presented, while the second part deals with the ANN simulator and its base field data. The final part presents numerical examples which highlight the efficiency of the proposed method.
  • Keywords
    backpropagation; neural nets; poles and towers; power system simulation; power transmission; ANN imperfection simulator; artificial neural networks; back error propagation perceptron; dynamical response; neural network simulators; nonparametric system identification approach; power transmission towers; spectral analysis; spectral dynamic analysis; Analytical models; Artificial neural networks; Mathematical model; Poles and towers; Power engineering and energy; Power transmission; Robustness; Spectral analysis; System identification; Systems engineering and theory; Imperfection; neural network; power transmission towers; spectral method;
  • fLanguage
    English
  • Journal_Title
    Power Delivery, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8977
  • Type

    jour

  • DOI
    10.1109/TPWRD.2004.832394
  • Filename
    1339363