• DocumentCode
    620589
  • Title

    Survey on hidden Markov model based fault diagnosis and prognosis

  • Author

    Xia Li-sha ; Fang Hua-jing ; Zheng Luo

  • Author_Institution
    Dept. of Control Sci. & Eng., Huazhong Univ. of Sci. & Technol., Wuhan, China
  • fYear
    2013
  • fDate
    25-27 May 2013
  • Firstpage
    4880
  • Lastpage
    4884
  • Abstract
    In this paper, the achievements of HMM-based fault diagnosis and prognosis are introduced. The importance of fault diagnosis and prognosis in complex dynamic industrial systems, together with the basic and the extended algorithm of HMM, are briefly presented. Then the research process of HMM-based fault diagnosis and prognosis methods in available literatures are reviewed and analyzed. After concluding the hot spots and technical difficulties, the main challenges that need to be solved and the developing trends in this field are also presented.
  • Keywords
    fault diagnosis; hidden Markov models; industrial engineering; HMM-based fault diagnosis method; HMM-based fault prognosis method; complex dynamic industrial systems; extended HMM algorithm; hidden Markov model based fault diagnosis method; hidden Markov model based fault prognosis method; Computational modeling; Conferences; Electronic mail; Europe; Fault diagnosis; Hidden Markov models; Silicon; Hidden Markov Model; fault diagnosis; fault prognosis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference (CCDC), 2013 25th Chinese
  • Conference_Location
    Guiyang
  • Print_ISBN
    978-1-4673-5533-9
  • Type

    conf

  • DOI
    10.1109/CCDC.2013.6561818
  • Filename
    6561818