ZHENG Wei. Petri net model of maglev train running across different control systems[J]. Journal of Traffic and Transportation Engineering, 2012, 12(2): 112-118. doi: 10.19818/j.cnki.1671-1637.2012.02.016
Citation: ZHENG Wei. Petri net model of maglev train running across different control systems[J]. Journal of Traffic and Transportation Engineering, 2012, 12(2): 112-118. doi: 10.19818/j.cnki.1671-1637.2012.02.016

Petri net model of maglev train running across different control systems

doi: 10.19818/j.cnki.1671-1637.2012.02.016
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  • Author Bio:

    ZHENG Wei (1975-), male, associate professor, PhD, +86-10-51684971, wzheng1@bjtu.edu.cn

  • Received Date: 2011-11-17
  • Publish Date: 2012-04-25
  • The general framework of running control system on maglev train was studied according to the running requirements of maglev train running across different control systems.Functional subsystems need to be added was defined.The hierarchical models of system key attributes, maglev operation procedures and the subsystem function were built based on the system theory by using Petri net.The key attributes of whole system were described by the highest model, and the operation procedures of maglev train and the reliabilities of subsystems were presented in the lower level model.The relationship between the failure rates of maglev train running across different control systems and the reliabilities of subsystem components was quantitatively analyzed with the model.It is pointed that the loss ratio of network connecting neibouring control systems should be lower than 10-6 times per hour when the required failure number of maglev train running across different systems is no more than 1 time per year.The failure rates of maglev train running across different control systems are 1.95×10-5 and 1.65×10-5 times per hour when the triggering times equal 0.2 and 2.0 min respectively, and the stepping times equal 4 and 16 min respectively.Simulation result shows that the failure rates of train running across the boundary decrease when the reliabilities of a and b networks are improved, or the triggering time and stepping time of train are prolonged.The reliability requirements of subsystem components based on the required key attributes of system level are quantantatively identified by using the proposed approach.

     

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