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.
Highlights
With the shortage of oil resources in China and the increasingly serious air pollution in cities, natural gas energy has developed rapidly in recent years
The number of gas stations provided by natural gas vehicles and large CNG energy vehicles is increasing
The fault tree analysis method is combined with Bayesian network method, aiming at the fire and explosion accident of gas station, and fuzzy mathematics is introduced in the process of transforming the fault tree into Bayesian network
Summary
With the shortage of oil resources in China and the increasingly serious air pollution in cities, natural gas energy has developed rapidly in recent years. The number of filling stations that provide fuel for natural gas vehicles and large CNG energy vehicles is increasing day by day. The number of gas stations provided by natural gas vehicles and large CNG energy vehicles is increasing. Yuan Changfeng [1] used fuzzy dynamic fault tree to analyze the contributing factors in the emergency process of oil and gas storage and transportation fire accidents, and introduced triangular fuzzy numbers to refine the occurrence probability of each factor. In order to improve the accuracy of fire risk assessment, Mi Hongfu [4] used bow analysis method to establish potential fire accident scenarios, and introduced Bayesian network to predict and analyze fire probability. The fault tree analysis method is combined with Bayesian network method, aiming at the fire and explosion accident of gas station, and fuzzy mathematics is introduced in the process of transforming the fault tree into Bayesian network
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