Fault tree analysis combined with quantitative analysis for high-speed railway accidents

This paper focuses on employing the fault tree analysis method combined with quantitative analysis to investigate high-speed railway accidents. Specifically, by establishing a fault tree logic diagram based on a high-speed railway accident, an in-depth fault tree analysis combined with quantitative analysis is given to present a more comprehensive view of the accident. In quantitative analysis process, each basic event in the fault tree is endowed with uncertain characteristic due to the incompleteness of the prior information and the complexity of decision environments. With this concern, a novel method within the framework of intuitionistic fuzzy set theory is proposed to handle this problem, in which the failure possibilities of basic events are particularly treated as intuitionistic trapezoidal fuzzy numbers (ITFNs). In addition, a new ranking method for ITFNs is proposed by defining the expected values and compromise possibilities, and is efficiently employed to determine the importance degrees of all basic events. As an application, two numerical experiments are implemented to illustrate the effectiveness of the proposed fault tree analysis method, and some conclusions and suggestions are also given to decrease the occurrence possibilities of similar accidents.