Risk assessment of mine ignition sources using fuzzy Bayesian network

The types of ignition sources in coal mines have complicated diversity and susceptibility due to the environmental complexity in the coal mine production process. To determine the actual ignition cause of a potential accident scene and prevent the occurrence of gas explosions, this work provides a new risk analysis method for mine ignition source based on the fuzzy Bayesian network (FBN). The first step relates to risk factor analysis and the BN model establishment. In light of the expert group decision-making method, risk topological structural models of ignition sources are constructed. The second step is fuzzification and defuzzification. To ensure the reliability of data in the process of expert investigation, this study proposes to calculate the weights of experts using a fuzzy analytic hierarchy process (FAHP) method based on subjective and objective expert weights. The last step uses causal reasoning, logical reasoning and sensitivity analysis to calculate the probability of occurrence of potential risk events and the probability distribution of risk factors. Through the case study of Babao Coal Mine in China, it is demonstrated that the FBN simulation provides a feasible method for accurately identifying the cause of gas explosion ignition. The proposed model can be used by analysts and decision-makers in the coal mine as a decision support tool to increase the probability of the ignition source in complex environments. (C) 2019 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.