Research on Major Disaster Risk Situation Prevention and Control System Based on Stamp / Stpa Control and Feedback Model in Coal Mine

Ziming Xu; Junwei Shi; Jianguo Xu; Gang Liu; Yongzhen Wang

doi:10.47297/taposatWSP2633-456942.20250609

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Research on Major Disaster Risk Situation Prevention and Control System Based on Stamp / Stpa Control and Feedback Model in Coal Mine

Volume 6, Issue 9

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Research on Major Disaster Risk Situation Prevention and Control System Based on Stamp / Stpa Control and Feedback Model in Coal Mine
Research on Major Disaster Risk Situation Prevention and Control System Based on Stamp / Stpa Control and Feedback Model in Coal Mine
1.Shandong Technology and Business University, Yantai, Shandong, 264005, China
2.Linyi Mining Group Heze Coal and Electricity Co., Ltd. Pengzhuang Coal Mine, Linyi, Shandong, 276018, China
Vol. 6, Issue 9, Pages: 221-225(2025)
Published：30 September 2025
DOI：10.47297/taposatWSP2633-456942.20250609
Accepted：

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Xu Ziming,Shi Junwei,Xu Jianguo,et al.Research on Major Disaster Risk Situation Prevention and Control System Based on Stamp / Stpa Control and Feedback Model in Coal Mine[J].Theory and Practice of Science and Technology,2025,06(09):221-225.
DOI：

Xu Ziming,Shi Junwei,Xu Jianguo,et al.Research on Major Disaster Risk Situation Prevention and Control System Based on Stamp / Stpa Control and Feedback Model in Coal Mine[J].Theory and Practice of Science and Technology,2025,06(09):221-225. DOI： 10.47297/taposatWSP2633-456942.20250609.

摘要

Abstract

Coal mine safety production serves as a crucial safeguard for China's energy strategy. However

major disasters such as gas

water

fire

roof collapse

and dust remain serious threats to its sustainable development. Traditional single-disaster prevention systems suffer from issues like "information silos

" insufficient accuracy of early warning models

and lack of multi-disaster coordination capabilities. To address these challenges

this study aims to develop an integrated and intelligent risk management system for major coal mine disasters. The research first analyzes the risk characteristics and coupling mechanisms of primary coal mine hazards

establishing a four-layer architecture comprising perception layer

transmission layer

storage-analysis layer

and application layer. By integrating multi-source heterogeneous data from safety monitoring

personnel positioning

and geological information through fusion technology

the system employs machine learning algorithms and multi-field coupling models to build an intelligent early warning framework for disaster risks. This enables dynamic risk assessment and proactive alerts. Furthermore

digital twin and visualization technologies are utilized to visually present mine safety conditions and simulate disaster progression. Practical applications demonstrate that this system significantly improves early warning accuracy and timeliness

facilitates coordinated multi-system operations and emergency command

establishes a closed-loop risk management system

and provides crucial theoretical support and technical solutions for coal mining enterprises to build intelligent safety assurance systems.

关键词

Keywords

references

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