• DocumentCode
    3418206
  • Title

    Research on parameters identification based on adline neural network for characteristic equation of pump

  • Author

    Wu, Qinghui ; Yu, Zhongdang ; Ding, Shuo ; Yang, Youlin

  • Author_Institution
    Coll. of Eng., Bohai Univ., Jinzhou, China
  • fYear
    2011
  • fDate
    19-21 Oct. 2011
  • Firstpage
    553
  • Lastpage
    556
  • Abstract
    The digitization of the pump characteristic curve between lift and flow rate is crucial for state detection, fault diagnosis and optimal control of large watering and drainage system in modern industry. In this paper, the characteristic equation of pump is analyzed, an adline neural network is designed for parameters identification for the pump characteristic equation. The proposed scheme solves the question how to measure the characteristic equation in arbitrary speed, raises the identification precise with adaptive filtering, learning, and approaching function of adline neural network. The experiment results confirm its feasibility and effectiveness.
  • Keywords
    mechanical engineering computing; neural nets; parameter estimation; pumps; adaptive filtering; adline neural network; drainage system; fault diagnosis; learning; optimal control; parameters identification; pump characteristic curve; pump characteristic equation; state detection; watering system; Biological neural networks; Equations; Fitting; Frequency measurement; Pumps; Training; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Computational Intelligence (IWACI), 2011 Fourth International Workshop on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-61284-374-2
  • Type

    conf

  • DOI
    10.1109/IWACI.2011.6160070
  • Filename
    6160070