• DocumentCode
    2094029
  • Title

    Crack Fault Diagnosis Based on MEP Based Neural Network

  • Author

    Liu, Mingjun ; Xiu, Liming ; Jia, Guangfeng ; Chen, Yuehui

  • Author_Institution
    Sch. of Electr. Eng. & Autom., Harbin Inst. of Technol., Harbin, China
  • Volume
    1
  • fYear
    2008
  • fDate
    20-22 Dec. 2008
  • Firstpage
    635
  • Lastpage
    639
  • Abstract
    The Multi Expression Programming (MEP) and Neural Network (NN) is applied to the crack fault diagnosis of structure. The inherent frequency and the position of the crack obtained by ANSYS are used as parameters of the neural network. This approach employs MEP to evolve the architecture and the parameters encoded in the NN. This framework allows input variables selection, over-layer connections for the various nodes involved. It is showed that the proposed method is feasible to diagnose the crack fault of structure.
  • Keywords
    cracks; fault diagnosis; mathematical programming; mechanical engineering computing; neural nets; ANSYS; MEP based neural network; crack fault diagnosis; input variables selection; multi expression programming; overlayer connections; Algorithm design and analysis; Artificial neural networks; Bridges; Fault diagnosis; Feedforward neural networks; Feedforward systems; Input variables; Inspection; Neural networks; Safety;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Computational Technology, 2008. ISCSCT '08. International Symposium on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-3746-7
  • Type

    conf

  • DOI
    10.1109/ISCSCT.2008.274
  • Filename
    4731508