Reliability Research Of Train Control Center Based On Dynamic Fault Tree

Chinese Train Control System (CTCS) is designed based on European Train Control System (ETCS). CTCS is divided into four layers:railway transportation management layer, network layer, ground equipment layer and vehicle equipment layer. Train control center (TCC) is core equipment of ground equipment. TCC generates Movement Authority (MA) based on logic operation. In order to control it operating, TCC sends the MA and SSP to train through balise and track circuit. Because of the functions, the reliability and safety of TCC concerns to the safety of CTCS. Therefore, TCC system is one of the key systems to assure safety of train, it is of great significance to study the reliability of TCC.Early research on the reliability limited to qualitative, more quantitative result should be researched in nowadays. Because of the drawbacks of traditional static fault tree, the concept of dynamic fault tree has been proposed in the research. After modeling, it’s necessary to choose appropriate way to solve the model, it’s essential to explore new solving methods. In this paper, Markov method and Petri Nets are used to solve the TCC dynamic fault tree.In this paper, the dynamic fault tree model of train control center was built and solved with Markov method. In addition, triple modular redundancy model was built to compare with the double 2-vote-2 redundancy of TCC safety unit. Reliability index was calculated to verify the reliability of TMR was better than D2V2R..In this paper, qualitative and quantitative result was analyzed based on the Markov method and Petri Nets method respectively, it concluded that:several methods combined to use is the best way to solve the dynamic fault tree.In summary, using the modeling methods as single would produce obvious disadvantages, if several methods are combined to solve the model, it would get higher efficiency and higher accuracy.