• DocumentCode
    2982955
  • Title

    The Fault Diagnosis Research Based on SOM-BP Composite Neural Network Learning Algorithm

  • Author

    Song Yu ; Wang Fengxia ; Yi Lu

  • Author_Institution
    Coll. of Control & Comput. Eng., North China Electr. Power Univ., Baoding, China
  • fYear
    2012
  • fDate
    7-9 Dec. 2012
  • Firstpage
    535
  • Lastpage
    539
  • Abstract
    Introduce the basic principle and learning algorithm of the SOM network and BP network. The diagnosis mode is established with the common breakdown condition and the related parameters of the gear boxes used as the training sample. Due to the complex nonlinear relation between breakdown mode and characteristic parameters of gear-boxes, the SOM-BP composite neural net work is used. First have a preliminary pattern recognition classification for training samples by SOM network and details of fault classification by BP network under the MATLAB 7.1 environment, through the simulation test and comparison with BP network, reliability of the composite neural network for gear box failure diagnosis are verified.
  • Keywords
    backpropagation; fault diagnosis; mechanical engineering computing; power transmission (mechanical); self-organising feature maps; MATLAB 7.1 environment; SOM-BP composite neural network learning algorithm; breakdown condition; fault classification; fault diagnosis research; gear box failure diagnosis; pattern recognition classification; Biological neural networks; Educational institutions; Fault diagnosis; Neurons; Training; Vectors; composite neural network; fault diagnosis; simulation and test;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Engineering and Communication Technology (ICCECT), 2012 International Conference on
  • Conference_Location
    Liaoning
  • Print_ISBN
    978-1-4673-4499-9
  • Type

    conf

  • DOI
    10.1109/ICCECT.2012.103
  • Filename
    6413773