Study on cause of coal and gas outburst accident based on D-S evidence theory and Bayesian network

Abstract

To explore the mechanism and influencing factors of coal and gas outburst accidents in coal mines, the factors inducing coal and gas outburst accidents were selected from four aspects: human, machine, environment and management, and the risk of accidents was studied by D-S evidence theory and Bayesian network. D-S evidence theory fuses expert knowledge to get the network structure, and then optimizes and corrects the network structure through greedy search algorithm. The EM algorithm is used to learn the parameters, obtain the conditional probability and posterior probability among the related factors, find out the key factors leading to the accident and identify the sensitive factors, and get the maximum risk source chain and analyze it. The results show that the main cause of coal and gas outburst is environmental factors(87.4%), followed by management factors (84.7%), mechanical factors(80.3%) and human factors(82.7%). Poor coal structure, geological conditions, without outburst prevention measures, inadequate investigation of potential safety hazards, gas overrun, imperfect monitoring system and insufficient ventilation facilities are the important influencing factors that induce coal and gas outburst accidents in coal mines.

Keywords

• coal and gas outburst
• accident cause study
• d-s evidence theory
• bayesian network model
• parameter learning
• sensitivity analysis