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.
Highlights
In the construction of the national economy, mining is an important raw material industry that provides a large amount of primary energy, industrial raw materials and agricultural means of production for economic development and daily life [1]
The mining industry must be fully aware that the situation of mining safety is still rather serious
In view of the problems faced by underground mining enterprises, namely, the bottleneck in safety management theory development, the lack of a systematic standardized process, and the deficient implementation of safety management, this study proposes an accident analysis method based on explanation graph-probabilistic multi-plan analysis (EG-PMPA) by introducing the theoretical basis of process node management and probability risk identification and combining the advantages of multi-planning identification in the multi-objective, procedural and interpretive aspects of behaviour analysis
Summary
In the construction of the national economy, mining is an important raw material industry that provides a large amount of primary energy, industrial raw materials and agricultural means of production for economic development and daily life [1]. Gao et al.: An Underground Mine Risk Identification Model and Safety Management Method Based on Explanation Graph-PMPA (EG-PMPA). In view of the problems faced by underground mining enterprises, namely, the bottleneck in safety management theory development, the lack of a systematic standardized process, and the deficient implementation of safety management, this study proposes an accident analysis method based on explanation graph-probabilistic multi-plan analysis (EG-PMPA) by introducing the theoretical basis of process node management and probability risk identification and combining the advantages of multi-planning identification in the multi-objective, procedural and interpretive aspects of behaviour analysis. Combined with the identification results of the process node risk factors in the case, the EG accident analysis model is adopted to quantitatively analyse and rank the key risk factors, based on which a refined risk factor management and control scheme is constructed. The research results can be effectively applied in engineering practice
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