Risk analysis of underground debris flows in mines based on a coupled weighted Bayesian network

Mines mined by the natural caving method are prone to underground debris flow disasters, resulting in mud gushing blocking roadways, equipment damage and even casualties, which seriously affect the safe operation of mines. To carry out a risk analysis of underground debris flows in mines, quantify the interactions among risk factors in the process of disasters, and identify the main disaster-causing paths, DEMATEL-ISM was used to analyze 18 risk factors related to material sources, geology, water sources and processes. A multilevel network structure model was constructed, and the model was mapped to a Bayesian network (BN). Based on the N-K model, the degree of risk coupling was calculated, the nodes in the BN were coupled and weighted, and diagnostic reasoning for underground debris flows was realized based on posterior probability. The results showed that the risk of debris flow increases with increasing coupling factor. The factors of water source, geology and ore drawing ranked at the top in terms of the probability change rate of the BN nodes, and a main disaster-causing path was obtained by diagnostic reasoning, which provides a theoretical basis for the formulation of underground debris flow prevention and control measures.