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Knowledge Graph-based Q&A System for Blasting Safety Management in Open-pit Mines
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Jia-yi SUN1, Ping-feng LI2, 3, Wei-ming GUAN1, Jie TAN1, Ming-sheng ZHAO2, 3, Hong-bing YU2, 3, Ying-yuan WEN1, Hong-pei TANG2, 3
Blasting | 2025, 42(2) : 188 - 201
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Blasting | 2025, 42(2): 188-201
BLASTING SAFETY
Knowledge Graph-based Q&A System for Blasting Safety Management in Open-pit Mines
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Jia-yi SUN1, Ping-feng LI2, 3, Wei-ming GUAN1, Jie TAN1, Ming-sheng ZHAO2, 3, Hong-bing YU2, 3, Ying-yuan WEN1, Hong-pei TANG2, 3
Affiliations
  • 1.Xinjiang University, Xinjiang 830017, China
  • 2.Xinjiang Hongda Blasting Engineering Co., Ltd., Xinjiang 831399, China
  • 3.Hongda Blasting Engineering Group Co., Ltd., Hunan 410011, China
Published: 2025-06-01 doi: 10.3963/j.issn.1001-487X.2025.02.023
Outline
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Safety management plays a vital role in blasting operations, and blasting safety is closely related to the processes of drilling, blasting, loading, transportation, and dumping, with significant interactions among these procedures. However, due to the diverse sources and complex structure of current blasting safety data, the lack of systematic integration poses challenges for on-site personnel to accurately acquire critical safety knowledge under complex working conditions. To address this issue, this study applies a BERT-BiLSTM-CRF-based method for entity recognition in the field of blasting safety management. The BERT pre-trained model is first used to obtain dynamic word embeddings, followed by optimal label sequence tagging using the BiLSTM-CRF model. A knowledge graph covering seven entity types and nine relationship types is constructed and stored using the open-source Neo4j graph database system. Experimental results show that the F1-score for all entity types exceeds 60%, demonstrating that the proposed model significantly improves entity recognition accuracy compared to traditional models. Based on this, a knowledge graph-based Q&A system for blasting process safety management in open-pit coal mines is developed, enabling rapid querying of domain knowledge and efficient matching of various blasting processes with safety standards. With the support of this Q&A system, on-site engineers can make timely and informed decisions in complex blasting safety management scenarios.

knowledge graph  /  Q&A System  /  blasting safety  /  process flow  /  pre-trained language model
Jia-yi SUN, Ping-feng LI, Wei-ming GUAN, Jie TAN, Ming-sheng ZHAO, Hong-bing YU, Ying-yuan WEN, Hong-pei TANG. Knowledge Graph-based Q&A System for Blasting Safety Management in Open-pit Mines[J]. Blasting, 2025 , 42 (2) : 188 -201 . DOI: 10.3963/j.issn.1001-487X.2025.02.023
  • Graduate Student Innovation Project of Xinjiang Uygur Autonomous Region(XJ2025G100)
  • Science and Technology Major Project of Xinjiang Uygur Autonomous Region(2024A03001-2)
Year 2025 volume 42 Issue 2
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Article Info
doi: 10.3963/j.issn.1001-487X.2025.02.023
  • Receive Date:2025-04-26
  • Online Date:2026-03-19
  • Published:2025-06-01
Article Data
Affiliations
History
  • Received:2025-04-26
Funding
Graduate Student Innovation Project of Xinjiang Uygur Autonomous Region(XJ2025G100)
Science and Technology Major Project of Xinjiang Uygur Autonomous Region(2024A03001-2)
Affiliations
    1.Xinjiang University, Xinjiang 830017, China
    2.Xinjiang Hongda Blasting Engineering Co., Ltd., Xinjiang 831399, China
    3.Hongda Blasting Engineering Group Co., Ltd., Hunan 410011, China

Corresponding:

GUAN Wei-ming (1981-), male, professor, doctoral supervisor, His research focuses on intelligent mining, mine ecological restoration, and open-pit blasting, (E-mail) .
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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
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占总种数比例
Percentage of
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Genus
种数
Number of
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Percentage of total
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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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