Reliability Assessment on CTCS-3 Train Control System Using Faults Trees and Bayesian Networks

Abstract

China Train Control System (CTCS-3) is a safety critical computer system that features large-scale, complex structure, and redundant configuration. CTCS-3 and as well as the equipment and technologies related to it can ensure the safety and reliability running of high-speed trains, and so the assessment on its reliability becomes very important. Generally, the two elements such as common cause factor (CCF) and failure mode polymorphism can not be ignored when assessing the reliability on a large complicated system. There are some limitations existing when applying the traditional fault tree analysis (FTA) is used to deal with the two factors mentioned above, and considering that Bayesian network (BN) possesses the abilities of bidirectional reasoning and the uncertain knowledge solving, and therefore BN is introduced to change the flaws. The method firstly establishes the FTA model of system from top to bottom, and then converts the FTA model into BN model from the lower to the upper, hierarchically. Eventually, the reliability indices are calculated using the BN with regard to the CCF and multi-state factors. Through integrating and evaluating sub-models using the approach with FTA combined with BN in the CTCS-3 system, some interesting results are acquired. The relative results show that the proposed approach is quite effective, and also provides a theoretical basis to improve the system reliability.

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