Fire and explosion analysis of filling station based on fuzzy mathematics and Bayesian network model

Abstract

In order to explore the basic events and risk occurrence probability of fire and explosion accidents in CNG (Compressed Natural Gas) filling station, a corresponding Bayesian network risk model was established based on the fault tree of filling station. The prior probability was modified by introducing fuzzy mathematics in the process of transforming the fault tree into Bayesian network, and the posterior probability of the basic events of CNG filling station fire and explosion accidents was analyzed and calculated by GeNIe software. Finally, through case analysis, it is found out that the most dangerous factors that lead to the greatest risk of fire and explosion accidents in a filling station are: personnel misoperation, management defects, etc. After verifying the model, it shows that paying attention to the polymorphism of the base events and determining the rationality of the logical relationship between the base events can calculate the more accurate probability distribution of the base events, and at the same time provide reasonable suggestions for the accident prevention of the gas filling station.