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Research on Rapid Acceptance Technology of Underground Mine Blasting based on 3D Laser Scanning
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Bao-jin ZHANG1, Hong-di JING2, Ying-ying LIU3, Qiang CHI1, Chang-qing CHU4, Xing-fan ZHANG2
Blasting | 2025, 42(1) : 192 - 198
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Blasting | 2025, 42(1): 192-198
BLASTING SAFETY
Research on Rapid Acceptance Technology of Underground Mine Blasting based on 3D Laser Scanning
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Bao-jin ZHANG1, Hong-di JING2, Ying-ying LIU3, Qiang CHI1, Chang-qing CHU4, Xing-fan ZHANG2
Affiliations
  • 1.Ansteel Mining Co., Ltd., Yanqianshan Branch, Anshan 114000, China
  • 2.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
  • 3.Ansteel Guanbaoshan Mining Co., Ltd., Anshan 114000, China
  • 4.Anshan Steel Mining Co., LTD., Anshan 114000, China
Published: 2025-12-27 doi: 10.3963/j.issn.1001-487X.2025.01.023
Outline
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Measurement acceptance plays a crucial supervisory and guiding role in mining engineering. However, traditional blasting acceptance processes and methods in underground mines are insufficient to meet modern production needs and affect the efficiency and quality of underground mining. To address this issue, the Yanqianshan Iron Mine -213 m level roadway was studied to explore a new measurement and acceptance method based on a high-precision laser SLAM (Simultaneous Localization and Mapping) algorithm. By obtaining point cloud data of the roadway before and after underground mine excavation, the foundation for subsequent data analysis and processing was established. In the data processing phase, methods such as point cloud denoising, ICP (Iterative Closest Point) registration, point cloud segmentation, and slicing were employed to create comprehensive measurement and acceptance processes for underground mining engineering. Point cloud denoising effectively removes noise and enhances data purity and credibility. The ICP registration method ensures precise alignment of point clouds through iterative optimization, maintaining high data consistency. Point cloud segmentation and slicing techniques offer practical solutions for accurately calculating irregular explosion volumes. The research results demonstrate that this high-precision laser SLAM measurement acceptance method improves work quality and efficiency. It ensures construction quality in underground mining and provides critical technical support for optimizing underground blasting designs.

underground mine  /  blasting  /  acceptance  /  Laser SLAM  /  point cloud
Bao-jin ZHANG, Hong-di JING, Ying-ying LIU, Qiang CHI, Chang-qing CHU, Xing-fan ZHANG. Research on Rapid Acceptance Technology of Underground Mine Blasting based on 3D Laser Scanning[J]. Blasting, 2025 , 42 (1) : 192 -198 . DOI: 10.3963/j.issn.1001-487X.2025.01.023
  • Joint Fund project of National Natural Science Foundation of China(U21A20106)
Year 2025 volume 42 Issue 1
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Article Info
doi: 10.3963/j.issn.1001-487X.2025.01.023
  • Receive Date:2023-05-04
  • Online Date:2026-03-18
  • Published:2025-12-27
Article Data
Affiliations
History
  • Received:2023-05-04
Funding
Joint Fund project of National Natural Science Foundation of China(U21A20106)
Affiliations
    1.Ansteel Mining Co., Ltd., Yanqianshan Branch, Anshan 114000, China
    2.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
    3.Ansteel Guanbaoshan Mining Co., Ltd., Anshan 114000, China
    4.Anshan Steel Mining Co., LTD., Anshan 114000, China

Corresponding:

JING Hong-di (1988-), male, born in Chifeng, Inner Mongolia, Ph. D, associate researcher, mainly engaged in the research work of smart mining, (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
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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