Reliability Analysis of the Sliding Plug Door System Based on Bayesian Network

  • Lingli Mao
  • Zhaoyi Su
  • Jing Long
  • Limin Jia
  • Zongyi Xing
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 288)


The metro door system is one of the high failure rate systems of metro vehicles, and the failure of driver motor is the major cause of the door failure, so the Bayesian network (BN) is applied to analyze the reliability of drive motor. First, the BN of the drive motor is established according to its fault tree, and the failure probability of drive motor is calculated by the method of bucket elimination. Then the fault diagnosis of the drive motor is made through the posterior probability. Finally, the key links of door system are affirmed based on the sensitivity of each basic event, which can provide support and reference for the maintenance of door system.


Reliability Metro door Bayesian network Fault diagnosis 



This research is supported by National High-tech R&D program of China (863 Program, No.2011AA110501) and National Technology R&D Program of China (No. BAG01B05 The supports are gratefully acknowledged.


  1. 1.
    Aoxue S, Mingtian F, Zhonglai L (2012) Reliability analysis of distribution system based on dynamic Bayesian Network. East China Electr Power 40(11):1912–1916 (in Chinese)Google Scholar
  2. 2.
    Lei Y, Shuo T (2012) Research on missile defense effectiveness evaluation based on Bayesian network model. J Spacecr TT&C Technol 31(50):89–94 (in Chinese)Google Scholar
  3. 3.
    Hui S, Fei Y, Kaicheng L (2011) The application of Bayesian network in safety assessment of the platform screen door system of rail transit system. Urban Mass Transit 14(11):47–52 (in Chinese)Google Scholar
  4. 4.
    Simon Ch, Weber Ph, Levrat E (2007) Bayesian networks and evidence theory to model complex systems reliability. J Comput 2(1):33–43 Google Scholar
  5. 5.
    Bobbio A, Portinale L, Minichino M (2001) Improving the analysis of dependable systems by mapping fault trees into Bayesian networks. Reliab Eng Syst Saf 71:249–260CrossRefGoogle Scholar
  6. 6.
    Mahadevan S, Zhang R, Smith N (2001) Bayesian networks for system reliability reassessment. Struct Saf 23:231–251CrossRefGoogle Scholar
  7. 7.
    Dechter R (1996) Bucket elimination: a unifying framework for probabilistic inference. In: Proceedings of 12th conference on uncertency in artificial intellience. Morgan Kaufmann, San Francisco, pp 211–219Google Scholar
  8. 8.
    Xiaowei Y (2012) Elements importance and sensitivity analysis based on Bayesian network. J Shenyang Inst Eng 8(3):262–265 (in Chinese)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Lingli Mao
    • 1
  • Zhaoyi Su
    • 2
  • Jing Long
    • 2
  • Limin Jia
    • 3
  • Zongyi Xing
    • 1
  1. 1.School of Mechanical EngineeringNanjing University of Science and TechnologyNanjingChina
  2. 2.Engineering Technology Research CenterGuangzhou Metro CorporationGuangzhouChina
  3. 3.State Key Laboratory of Rail Traffic Control and SafetyBeijing Jiaotong UniversityBeijingChina

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