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Influencing Factors Analysis and Parameter Optimization for Rock Fragmentation by Deep-Hole Cut Blasting Based on Grey Correlation Analysis
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Jie LIN1, 2, Shaoguang LIU3, Guangbin LI4, Xiaoming LOU1, 2, Qimin HAN4
Mining and Metallurgical Engineering | 2023, 43(5) : 6 - 10
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Mining and Metallurgical Engineering | 2023, 43(5): 6-10
• MINING •
Influencing Factors Analysis and Parameter Optimization for Rock Fragmentation by Deep-Hole Cut Blasting Based on Grey Correlation Analysis
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Jie LIN1, 2, Shaoguang LIU3, Guangbin LI4, Xiaoming LOU1, 2, Qimin HAN4
Affiliations
  • 1.Zijin College of Geology and Mining, Fuzhou University, Fuzhou 350108, Fujian, China
  • 2.Institute of Explosive Technology, Fuzhou University, Fuzhou 350108, Fujian, China
  • 3.Ningde Public Security Bureau, Ningde 352100, Fujian, China
  • 4.Wulatehouqi Zijin Mining Co Ltd, Bayannur 015500, Inner Mongolia, China
Published: 2023-10-01 doi: 10.3969/j.issn.0253-6099.2023.05.002
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With Sanguikou Lead Zinc Mine in the Inner Mongolia Autonomous Region taken for study, the influencing factors and parameter optimization for rock fragmentation by deep-hole cut blasting were explored by performing theoretical analysis, image processing and engineering tests. Firstly, in view of the problems of high fines generation rate and small fragment size on average, the factors influencing blasting fragmentation were tested and field data were collected. Also, image processing and analysis were performed for the muckpile in the test by using Split-Desktop 4.0 software. Then, the primary and secondary factors affecting blasting fragmentation were determined based on grey correlation analysis. Finally, an optimal scheme of blasting parameters was determined by using trend analysis based on actual situation of the site, and was then verified in the practical engineering test. The results show that the fines generation rate by the cut blasting in the mine is mainly affected by the delay time between rows and the borehole spacing, and the average fragment size is mainly affected by the borehole spacing and the number of rows for blasting. The optimized blasting parameters are finally determined as follows: borehole spacing of 1.2 m, row spacing of 1.5 m, burden of 0.8 m, 3 rows of boreholes, delay interval of 13 ms, 0 ms, 9 ms and 18 ms, respectively, between 4 holes, and a delay interval of 42 ms between rows. With the above-mentioned parameters, the blasting can result in the fines generation rate down by 27.19% and the average fragment size up by 62.89%.

deep-hole blasting  /  cut  /  grey correlation analysis  /  rock fragmentation by blasting  /  fines generation rate  /  average fragment size  /  influencing factor  /  parameter optimization
Jie LIN, Shaoguang LIU, Guangbin LI, Xiaoming LOU, Qimin HAN. Influencing Factors Analysis and Parameter Optimization for Rock Fragmentation by Deep-Hole Cut Blasting Based on Grey Correlation Analysis[J]. Mining and Metallurgical Engineering, 2023 , 43 (5) : 6 -10 . DOI: 10.3969/j.issn.0253-6099.2023.05.002
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doi: 10.3969/j.issn.0253-6099.2023.05.002
  • Receive Date：2023-04-18
  • Online Date：2026-03-05
  • Published：2023-10-01
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  • Received：2023-04-18
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Affiliations
    1.Zijin College of Geology and Mining, Fuzhou University, Fuzhou 350108, Fujian, China
    2.Institute of Explosive Technology, Fuzhou University, Fuzhou 350108, Fujian, China
    3.Ningde Public Security Bureau, Ningde 352100, Fujian, China
    4.Wulatehouqi Zijin Mining Co Ltd, Bayannur 015500, Inner Mongolia, China
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表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
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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