Risk Assessment of Unsafe Acts in Coal Mine Gas Explosion Accidents Based on HFACS-GE and Bayesian Networks

Even in the context of smart mines, unsafe human acts are still an important cause coal mine gas explosion accidents, but there few models to analyze accidents. This study tries solve this problem through a risk assessment method accidents based on Human Factor Analysis and Classification system (HFACS-GE) Bayesian networks (BN). After verifying reliability HFACS-GE framework, BN model factors was established with Chi-square test odds ratios analysis. reasoning analysis, paths key were obtained, preventive measures granted. Based analysis 100 cases, maximum probability five kinds employees is 38%. Among 22 factors, mental state has greatest influence habitual violation regulations, sensitivity value 12.7%. can provide technical assistance for management explosions.