• DocumentCode
    569666
  • Title

    Fault diagnosis for hydraulic hoisting system based on the probabilistic SDG model

  • Author

    Lei, Su ; Hua, Song ; Hong, Wang

  • Author_Institution
    Sch. of Autom. Sci. & Electr. Eng., BeiHang Univ., Beijing, China
  • fYear
    2012
  • fDate
    25-27 July 2012
  • Firstpage
    627
  • Lastpage
    630
  • Abstract
    Focusing on the hoisting mechanism of crane hydraulic, this paper gives the fault mechanism analysis and fault probability calculation method based on the probabilistic SDG model. The fault mechanism is described by the probabilistic SDG model while the fault propagation is presented by the conditional probability. And so the connection tree algorithm and figure elimination algorithm can be used in Bayesian inference to calculate the fault probability. In case of the given fault, the fault probabilities of the part components can be given.
  • Keywords
    Bayes methods; cranes; fault diagnosis; hoists; hydraulic systems; inference mechanisms; trees (mathematics); Bayesian inference; conditional probability; connection tree algorithm; crane hydraulic; fault diagnosis; fault mechanism analysis; fault probability calculation method; figure elimination algorithm; hoisting mechanism; hydraulic hoisting system; part component; probabilistic SDG model; Analytical models; Cranes; Data models; Probabilistic logic; Valves; Winches; Bayesian inference; Fault mechanism analysis; Hydraulic; Probabilistic SDG model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Informatics (INDIN), 2012 10th IEEE International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4673-0312-5
  • Type

    conf

  • DOI
    10.1109/INDIN.2012.6301196
  • Filename
    6301196