• DocumentCode
    2469562
  • Title

    A Novel method for online prognostics performance evaluation

  • Author

    Liu, Shunli ; Sun, Bo

  • Author_Institution
    Sch. of Reliability & Syst. Eng., Beihang Univ., Beijing, China
  • fYear
    2012
  • fDate
    23-25 May 2012
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Prognostics performance assessment technologies are necessary for building and qualifying a real and mature prognostics and health management (PHM) system. The further refinements in concepts and definitions for prognostics performance are made in this paper. The limitations for the application of offline prognostics performance evaluation are discussed. Two novel metrics: Relative Accuracy (RA) and Relative Precision (RP) are proposed for online prognostics performance evaluation according to the random uncertainty existing in both the prediction values and the actual values. A novel method for impartially evaluating the prognostics performance is presented. It synthesizes the evaluations of the predictions at different times before and close to the End-of-Useful-Predictions time tEOUP to achieve the evaluation of the minimum effective prediction horizon (MEPH) prognostics performance. A BP neural network prognostics method for hydraulic pump is evaluated for the demonstration intents. The results show the online evaluation method can work well without the failure data of the product.
  • Keywords
    backpropagation; condition monitoring; neural nets; production engineering computing; pumps; BP neural network prognostics method; MEPH prognostics; PHM system; end-of-useful-prediction time; hydraulic pump; minimum effective prediction horizon; online prognostics performance evaluation; prognostics performance assessment technology; prognostics-and-health management system; relative accuracy; relative precision; Relative Accuracy; Relative Precision; offline evaluation; online evaluation; prognostics performance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Prognostics and System Health Management (PHM), 2012 IEEE Conference on
  • Conference_Location
    Beijing
  • ISSN
    2166-563X
  • Print_ISBN
    978-1-4577-1909-7
  • Electronic_ISBN
    2166-563X
  • Type

    conf

  • DOI
    10.1109/PHM.2012.6228859
  • Filename
    6228859