Abstract
In response to the relevant provisions of safety design criteria for fuze, and considering that Traditional Fault Tree Analysis (TFTA) struggles to describe system failure behavior, such as in its multi-state system faults and probabilistic logic linkages among components, this paper proposed a method for analyzing fuze system failure based on the integration of T-S Fuzzy Fault Tree (T-SFFT) and Bayesian Network (BN), introducing an interval triangular fuzzy subset method for describing failure rates in the safety assessment of the fuze system. Taking the fault tree of the fuze function prior to the initiation of the ordained arming and safety-interruption sequence as an example, using this approach, the analysis and calculation results indicated that the fuzzy subsets of failure probability for the top event under the complete failure state of the fuze system were of the same order of magnitude as those obtained using the TFTA method. This therefore validated the feasibility and effectiveness of this method in fuze system safety assessment. Furthermore, using BN to obtain the posterior probabilities of nodes, this approach provided a data foundation for fuze system fault diagnosis, holding significant engineering significance for fuze system safety assessment.