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A Case Study of Accident Analysis and Prevention for Coal Mining Transportation System Based on FTA-BN-PHA in the Context of Smart Mining Process

Author

Listed:
  • Longlong He

    (Shaanxi Key Laboratory of Mine Electromechanical Equipment Intelligent Detection and Control, Xi’an University of Science and Technology, Xi’an 710049, China)

  • Ruiyu Pan

    (Shaanxi Key Laboratory of Mine Electromechanical Equipment Intelligent Detection and Control, Xi’an University of Science and Technology, Xi’an 710049, China)

  • Yafei Wang

    (Shaanxi Key Laboratory of Mine Electromechanical Equipment Intelligent Detection and Control, Xi’an University of Science and Technology, Xi’an 710049, China)

  • Jiani Gao

    (Shaanxi Key Laboratory of Mine Electromechanical Equipment Intelligent Detection and Control, Xi’an University of Science and Technology, Xi’an 710049, China)

  • Tianze Xu

    (Shaanxi Key Laboratory of Mine Electromechanical Equipment Intelligent Detection and Control, Xi’an University of Science and Technology, Xi’an 710049, China)

  • Naqi Zhang

    (Shaanxi Key Laboratory of Mine Electromechanical Equipment Intelligent Detection and Control, Xi’an University of Science and Technology, Xi’an 710049, China)

  • Yue Wu

    (Shaanxi Key Laboratory of Mine Electromechanical Equipment Intelligent Detection and Control, Xi’an University of Science and Technology, Xi’an 710049, China)

  • Xuhui Zhang

    (Shaanxi Key Laboratory of Mine Electromechanical Equipment Intelligent Detection and Control, Xi’an University of Science and Technology, Xi’an 710049, China)

Abstract

In the face of the increasing complexity of risk factors in the coal mining transportation system (CMTS) during the process of intelligent transformation, this study proposes a method for analyzing accidents in CMTS based on fault tree analysis (FTA) combined with Bayesian networks (BN) and preliminary hazard analysis (PHA). Firstly, the fault tree model of CMTS was transformed into a risk Bayesian network, and the inference results of the fault tree and Bayesian network were integrated to identify the key risk factors in the transportation system. Subsequently, based on the preliminary hazard analysis of these key risk factors, corresponding rectification measures and a risk control system construction plan are proposed. Finally, a case study was carried out on the X coal mine as a pilot mine to verify the feasibility of the method. The application of this method effectively identifies and evaluates potential risk factors in CMTS, providing a scientific basis for accident prevention. This research holds significant importance for the safety management and decision making of coal mine enterprises during the process of intelligent transformation and is expected to provide strong support for enhancing the safety and reliability of CMTS.

Suggested Citation

  • Longlong He & Ruiyu Pan & Yafei Wang & Jiani Gao & Tianze Xu & Naqi Zhang & Yue Wu & Xuhui Zhang, 2024. "A Case Study of Accident Analysis and Prevention for Coal Mining Transportation System Based on FTA-BN-PHA in the Context of Smart Mining Process," Mathematics, MDPI, vol. 12(7), pages 1-31, April.
  • Handle: RePEc:gam:jmathe:v:12:y:2024:i:7:p:1109-:d:1371484
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    References listed on IDEAS

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    1. Li, Xin & Chen, Chao & Hong, Yi-du & Yang, Fu-qiang, 2023. "Exploring hazardous chemical explosion accidents with association rules and Bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    2. Zhang, Yan & Wang, Si-Xia & Yao, Jian-Ting & Tong, Rui-Peng, 2023. "The impact of behavior safety management system on coal mine work safety: A system dynamics model of quadripartite evolutionary game," Resources Policy, Elsevier, vol. 82(C).
    3. Binay Prakash Pandey & Devi Prasad Mishra, 2023. "Developing an Alternate Mineral Transportation System by Evaluating Risk of Truck Accidents in the Mining Industry—A Critical Fuzzy DEMATEL Approach," Sustainability, MDPI, vol. 15(8), pages 1-22, April.
    4. Jimei Li & Yunhui Wang & An Chen & Guanghui Wang & Xiaohui Yao & Tongtong Wang, 2023. "Construction and empirical testing of comprehensive risk evaluation methods from a multi-dimensional risk matrix perspective: taking specific types of natural disasters risk in China as an example," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 117(2), pages 1245-1271, June.
    5. Kejiang Lei & Dandan Qiu & Shilong Zhang & Zichao Wang & Yan Jin, 2023. "Coal Mine Fire Emergency Rescue Capability Assessment and Emergency Disposal Research," Sustainability, MDPI, vol. 15(11), pages 1-19, May.
    6. Leping He & Tao Tang & Qijun Hu & Qijie Cai & Zhijun Li & Shaowu Tang & Yichun Wang, 2021. "Integration of Interpretive Structural Modeling with Fuzzy Bayesian Network for Risk Assessment of Tunnel Collapse," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-14, December.
    7. Hunte, Joshua L. & Neil, Martin & Fenton, Norman E., 2024. "A hybrid Bayesian network for medical device risk assessment and management," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    8. Xianzhong Li & Shigang Hao & Tao Wu & Weilong Zhou & Jinhao Zhang, 2023. "Data Mining Technology and Its Applications in Coal and Gas Outburst Prediction," Sustainability, MDPI, vol. 15(15), pages 1-17, July.
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