• DocumentCode
    663303
  • Title

    Reliability analysis based on the statistical models method for the subway door system

  • Author

    Qin Yong ; Yu Shan ; Shi Jingxuan ; Mao Lingli

  • Author_Institution
    State Key Lab. of Rail Traffic Control & Safety, Beijing Jiaotong Univ., Beijing, China
  • fYear
    2013
  • fDate
    Aug. 30 2013-Sept. 1 2013
  • Firstpage
    215
  • Lastpage
    220
  • Abstract
    At present, the vehicle door system is the key subsystem to the subway vehicle faults. Therefore, its reliability is of great significance to ensure the subway safe operation. In order to analyze the reliability status of the subway vehicle door system quantitatively, the failure data was collated in this paper. Furthermore, the failure distribution models of the vehicle door system were determined by the experience-based statistical models method. And then failure distribution function, reliability function and failure rate function were derived respectively. Finally, the reliability characteristic parameter, such as reliability, unreliability and the MTBF, were calculated by the above three functions to help arrange the vehicle overhaul plan and reduce the accident.
  • Keywords
    doors; failure analysis; railway accidents; railway safety; reliability; statistical analysis; MTBF; accident reduction; failure distribution; failure rate function; reliability analysis; reliability function; statistical models; subway safe operation; subway vehicle door system; subway vehicle faults; vehicle overhaul plan; Analytical models; Biological system modeling; Distribution functions; Reliability theory; Vehicles; Weibull distribution; Door system; Failure distribution; Reliability; Statistical models method;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Rail Transportation (ICIRT), 2013 IEEE International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4673-5278-9
  • Type

    conf

  • DOI
    10.1109/ICIRT.2013.6696296
  • Filename
    6696296