• DocumentCode
    3580385
  • Title

    Bayesian method applied to analyzing reliability of engineering machinery engine

  • Author

    Guo Jie ; Zhi Jun ; Fu Cheng-qun ; Ran Hong-liang ; Zhao Xian-li

  • Author_Institution
    Coll. of Field Eng., PLA Univ. of Sci. & Technol., Nanjing, China
  • fYear
    2014
  • Firstpage
    371
  • Lastpage
    374
  • Abstract
    Based on the complexity of the construction machinery system and the complicated characteristics of its reliability analysis, we put Bayesian Network to use in reliability analysis. Taking construction machinery engine as an example, the first thing to do is to construct a Fault Tree of engine system; then, a Bayesian Network model of reliability assessment of engine system is established according to the transforming principle of the Fault Tree and Bayesian network; followed by an reliability analysis of construction engine system and its operation system. By the way of analyzing the known node failure rate of system reliability, the known system at its place of failure and the failure rate of each node at its known system failure mode. An effective method is provided to carry out a reliability analysis of construction engine.
  • Keywords
    belief networks; construction equipment; engines; failure analysis; fault trees; Bayesian method; Bayesian network model; complicated characteristics; construction engine system; construction machinery engine; construction machinery system complexity; engineering machinery engine reliability; fault tree; node failure rate; operation system; reliability analysis; reliability assessment; system failure mode; system reliability; Analytical models; Bayes methods; Engines; Fault trees; Machinery; Reliability engineering; Bayesian Network; Bayesian reasoning; construction machinery; fault tree; reliability analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Technology and Artificial Intelligence Conference (ITAIC), 2014 IEEE 7th Joint International
  • Print_ISBN
    978-1-4799-4420-0
  • Type

    conf

  • DOI
    10.1109/ITAIC.2014.7065073
  • Filename
    7065073