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Data reliability evaluation for coal mine disaster monitoring system
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Kai Qin1, 2, 3, Zhigang Deng1, 3, **, Longyong Shu1, 2, 3, Shuaihao Wei1
China Safety Science Journal | 2026, 36(5) : 190 - 198
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China Safety Science Journal | 2026, 36(5): 190-198
Safety Technology and Engineering
Data reliability evaluation for coal mine disaster monitoring system
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Kai Qin1, 2, 3, Zhigang Deng1, 3, **, Longyong Shu1, 2, 3, Shuaihao Wei1
Affiliations
  • 1 China Coal Research Institute, Beijing 100013, China
  • 2 State Key Laboratory of Digital Intelligent Technology for Unmanned Coal Mining, Beijing 100013, China
  • 3 Beijing Engineering and Research Center of Mine Safe, Beijing 100013, China
Published: 2026-05-28 doi: 10.16265/j.cnki.issn1003-3033.2026.05.1025
Outline
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Data reliability is essential for accurate identification of coal mine disaster risks. To accurately evaluate the data reliability of coal mine disaster monitoring and early warning systems, relevant policies, regulations, standards and literatures including the One Regulation and Four Detailed Rules were systematically reviewed, and a reliability evaluation method for coal mine disaster monitoring systems was proposed by integrating big data and GIS spatial analysis technology. The method was verified via field practice in disaster prevention and control at a coal mine in Shanxi Province. Results indicate that extracting the characteristics of imprecision, heterogeneity and conflict from multi-source monitoring information is the core to accurately identify unreliable data, including over-limit values, equipment failures, missing information, positional errors and abnormal frequencies. A reliability evaluation index system covering 3 primary categories (legitimacy, compliance and rationality) and 437 subcategories is constructed, which can fully restore multi-source associated information of the monitoring system throughout its full life cycle. During normal production in February 2025 at the test mine, 56 753 pieces of unreliable information were identified by this method, with a 100% accuracy rate verified by manual inspection. Furthermore, this method can dynamically assess whether existing mine monitoring systems meet disaster early warning requirements during the data preprocessing stage, and timely prompt mine maintenance and system upgrading.

coal mine disaster  /  monitoring system  /  data reliability  /  reliability evaluation  /  geographic information system (GIS)  /  spatial analysis
Kai Qin, Zhigang Deng, Longyong Shu, Shuaihao Wei. Data reliability evaluation for coal mine disaster monitoring system[J]. China Safety Science Journal, 2026 , 36 (5) : 190 -198 . DOI: 10.16265/j.cnki.issn1003-3033.2026.05.1025
Year 2026 volume 36 Issue 5
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Article Info
doi: 10.16265/j.cnki.issn1003-3033.2026.05.1025
  • Receive Date:2025-12-20
  • Online Date:2026-06-29
  • Published:2026-05-28
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History
  • Received:2025-12-20
  • Revised:2026-03-10
Funding
Affiliations
    1 China Coal Research Institute, Beijing 100013, China
    2 State Key Laboratory of Digital Intelligent Technology for Unmanned Coal Mining, Beijing 100013, China
    3 Beijing Engineering and Research Center of Mine Safe, Beijing 100013, China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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