• DocumentCode
    1571927
  • Title

    The research on sensor fault diagnosis based on the SVM prediction model

  • Author

    Yu, Yaojun ; Zhang, Shengbo

  • Author_Institution
    Coll. of Machinery & Mater. Eng., Jiujiang Univ., Jiujiang, China
  • Volume
    2
  • fYear
    2011
  • Firstpage
    990
  • Lastpage
    992
  • Abstract
    A novel method for sensor fault diagnosis based on support vector machine (SVM) prediction model was proposed. This paper put forward the principle of SVM construction process and the system parameters obtained from using dynamic model identification of sensor. The sensor fault was diagnosed on line by prediction model, which avoided that BP algorithm must have mass data and is likely to fall into local minimum point. Compared to the traditional way, it was much more effective and accurately.
  • Keywords
    computerised instrumentation; fault diagnosis; sensors; support vector machines; BP algorithm; SVM construction process; SVM prediction model; dynamic model identification; sensor fault diagnosis; support vector machine; Gold; Predictive models; Pumps; Support vector machines; dynamic model; fault diagnosis; sensor; support vector machine (SVM);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cross Strait Quad-Regional Radio Science and Wireless Technology Conference (CSQRWC), 2011
  • Conference_Location
    Harbin
  • Print_ISBN
    978-1-4244-9792-8
  • Type

    conf

  • DOI
    10.1109/CSQRWC.2011.6037123
  • Filename
    6037123