An Underground Mine Risk Identification Model and Safety Management Method Based on Explanation Graph-Probabilistic Multi-Plan Analysis (EG-PMPA)

Abstract

In view of the problems of an imprecise safety system and the inefficient implementation of responsibility in current underground mining, this study reveals the internal relationship of underground mining safety management on the theoretical basis of process node management and probabilistic multi-plan analysis (PMPA). By introducing a probabilistic multi-planning identification accident analysis algorithm, a behavioural event planning library and a basic event explanation graph (EG) are constructed to determine all possible behavioural explanation sets of the top event plan/goal. By defining the importance of the explanation sets, the importance of the explanation set paths is sorted, and the important explanation set achieved by the top event goal is found. Based on the validation, the EG accident analysis model proposed in this paper is used to quantitatively analyse and rank the key risk factors in the modelling calculation of the risk control case of stope blasting operations and to propose a risk factor management control implementation plan, further verifying the feasibility of applying the explanation graph-probabilistic multi-plan analysis (EG-PMPA) framework model in underground mining safety systems.