China Safety Science Journal ›› 2022, Vol. 32 ›› Issue (8): 146-153.doi: 10.16265/j.cnki.issn1003-3033.2022.08.1633

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Risk assessment of ventilation system in coal mines based on DS theory and Bayesian network

LI Jinrong(), YANG Yuzhong**()   

  1. School of Energy Science and Engineering, Henan Polytechnic University, Jiaozuo Henan 451460, China
  • Received:2022-01-09 Revised:2022-05-10 Online:2022-09-05 Published:2023-02-28
  • Contact: YANG Yuzhong


In order to evaluate risk level of ventilation system in coal mines, firstly, an assessment index system was established with 16 main indicators from perspectives of human, equipment, environment and management according to characteristics of ventilation system, and related literatures and technical standards. Then, DS theory-Bayesian network model that could achieve information fusion was introduced to establish a risk assessment model. Finally, with actual investigation data from a coal mine in Henan province as an example, index weight and risk probability were calculated, and its risk level and sensitive indicators were obtained through risk reasoning and sensitivity analysis. The results show that the ventilation system is at a general risk level, and its sensitivity indicators include disrepair rate of ventilation laneway, percentage of return air resistance, average length of service and efficiency of main ventilation fan.

Key words: ventilation system in coal mine, DS theory, Bayesian network, risk assessment, indicator system, sensitivity analysis