• DocumentCode
    2321884
  • Title

    The selection of time domain characteristic parameters of rotating machinery fault diagnosis

  • Author

    Chang, Ji-bin ; Li, Tai-fu ; Li, Peng Fei

  • Author_Institution
    Chongqing Univ. of Sci. & Technol., Chongqing, China
  • Volume
    1
  • fYear
    2010
  • fDate
    9-10 Jan. 2010
  • Firstpage
    619
  • Lastpage
    623
  • Abstract
    In order to choose the rotating machinery fault diagnosis characteristics accurately, in this paper, a kind of choice method of fault diagnosis characteristics was put forward based on the time domain statistical analysis. Through analysis the probability distribution of the time domain dimensionless characteristic parameters, choose the parameters witch is obviously different from others and used as rotating machinery´s fault diagnosis characteristic parameters. Through MATLAB simulation, we can draw a conclusion from the results that this method can improve the efficiency and accuracy of fault diagnosis effectively.
  • Keywords
    backpropagation; fault diagnosis; machinery; mathematics computing; mechanical engineering computing; neural nets; statistical distributions; time-domain analysis; MATLAB simulation; backpropagation neural network; probability distribution; rotating machinery fault diagnosis; time domain dimensionless characteristic parameters; time domain statistical analysis; Appraisal; Business; Costs; Fault diagnosis; Knowledge management; Machinery; Production; Raw materials; Supply chain management; Supply chains; Characteristics Parameters; Fault Diagnosis; Rotating Machinery; Selection; Time Domain;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Logistics Systems and Intelligent Management, 2010 International Conference on
  • Conference_Location
    Harbin
  • Print_ISBN
    978-1-4244-7331-1
  • Type

    conf

  • DOI
    10.1109/ICLSIM.2010.5461346
  • Filename
    5461346