• DocumentCode
    2553684
  • Title

    A method for condition evaluation based on DSmT

  • Author

    Aihua, Liu

  • Author_Institution
    Sch. of Energy & Power Eng., Wuhan Univ. of Technol., Wuhan, China
  • fYear
    2010
  • fDate
    16-18 April 2010
  • Firstpage
    263
  • Lastpage
    266
  • Abstract
    Condition-based maintenance (CBM) is an optimal maintenance strategy due to improved planning for rehabilitation or replacement based on current evaluation of condition. In this paper, a new method of information fusion-DSmT(Dezert-Smarandache Theory) developed from DST(Dempster-Shafer Theory) and Bayesian theory is introduced to dealing with condition evaluation. With the research and analysis of condition evaluation, the model of condition evaluation based on DSmT is presented in which the generalized basic belief assignment and the rule of information fusion are built. The performance is compared with DSmT and DST for challenging realistic condition evaluation. The result shows that the DSmT enhance the performance of condition evaluation by reducing the time on computing and increasing the quality of fusion result.
  • Keywords
    Bayes methods; condition monitoring; maintenance engineering; strategic planning; Bayesian theory; DSmT; Dezert-Smarandache theory; condition evaluation; condition-based maintenance; information fusion; maintenance strategy; rehabilitation; replacement; Bayesian methods; Condition monitoring; Diesel engines; Information analysis; Power engineering and energy; Power generation; Power system modeling; Predictive models; Recurrent neural networks; Strategic planning; CBM; Condition Evaluation; DST; DSmT; information fusion;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Management and Engineering (ICIME), 2010 The 2nd IEEE International Conference on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4244-5263-7
  • Electronic_ISBN
    978-1-4244-5265-1
  • Type

    conf

  • DOI
    10.1109/ICIME.2010.5478066
  • Filename
    5478066