• DocumentCode
    525706
  • Title

    Artificial neural network based radial bending characteristics of mixed-flow pump impeller

  • Author

    Ruixuan, Jia

  • Author_Institution
    Key Lab. of Condition Monitoring & Control for Power Plant Equip. Minist. of Educ., North China Electr. Power Univ., Beijing, China
  • fYear
    2010
  • fDate
    23-25 June 2010
  • Firstpage
    237
  • Lastpage
    239
  • Abstract
    Impeller radial bending characteristic has applied to many type turbine machines except of pump. Specially, there is no news about application on the mixed-flow pump. In this study, an artificial neural network (ANN) was used for modeling the performance of mixed-flow pump impeller. Thirty seven results were used to train and test. Many patterns have been randomly selected and used as the test date. The main parameters for the experiments are the Gamma, Betal and Beta2. Gamma, Betal and Beta2 have been used as the input layer, and η has been used as the output layer. The best training algorithm and number of neurons were obtained. At last, a new type, high efficiency mixed-flow pump impeller can be designed.
  • Keywords
    Artificial neural networks; Blades; Compressors; Impellers; Laboratories; Numerical simulation; Polynomials; Pumps; Testing; Turbines; artificial neural networkt; mbced-flow pump; radial bending;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Engineering and Data Mining (SEDM), 2010 2nd International Conference on
  • Conference_Location
    Chengdu, China
  • Print_ISBN
    978-1-4244-7324-3
  • Electronic_ISBN
    978-89-88678-22-0
  • Type

    conf

  • Filename
    5542920