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Research on Dynamic Response and Parameter Optimization of Blasting in Near-Surface Mining
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Ning Yang1, 2, Xiangang Yin1, 2, Zhouying Zhong1, 2, Zepeng Li1, 2
Mining Research and Development | 2026, 46(7) : 62 - 70
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Mining Research and Development | 2026, 46(7): 62-70
Research on Dynamic Response and Parameter Optimization of Blasting in Near-Surface Mining
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Ning Yang1, 2, Xiangang Yin1, 2, Zhouying Zhong1, 2, Zepeng Li1, 2
Affiliations
  • 1.Changsha Institute of Mining Research Co., Ltd., Changsha, Hunan 410012, China
  • 2.National Engineering Research Center for Metal Mining, Changsha, Hunan 410012, China
Published: 2026-07-25
Outline
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To solve the problem that the cultural relic area and cultural relic group directly above a copper ore body are affected by mining blasting vibration, the dynamic response and parameter optimization of blasting in near-surface mining were systematically studied. Firstly, the relationship between the surface cultural relic area and the ore body was analyzed, and the maximum allowable blasting vibration velocity was determined by combining domestic and international safety criteria for blasting vibration. Based on the M. A. Sadovsky empirical formula, the maximum single-delay blasting explosive charge within the blast safety distance was obtained. Then, blasting simulations of the four levels at 1 945 m, 2 020 m, 2 095 m and 2 245 m closest to the surface throughout the mine's life cycle were carried out by numerical simulation, and the rationality of the maximum single-delay blasting explosive charge was verified. Finally, during blasting at the representative level underground, surface vibration tests were conducted using measuring points arranged on the surface. The results show that the maximum single-delay explosive charges at the four level are 745 kg, 390 kg, 172.5 kg and 10 kg, respectively, all of which are equal to or less than the allowable maximum single-delay explosive charge. The surface peak vibration induced by blasting velocity at the 2 245 m level is 0.5 cm/s, which is greater than that of the other three levels, but remains less than the maximum allowable vibration velocity, indicating that the blasting seismic wave has no effect on the surface structures. Based on the field blasting vibration data, an SSA-Elman neural network model for predicting Y-direction blasting vibration was constructed and compared with the traditional Elman neural network model. The predicted values of the SSA-Elman neural network model are basically consistent with the measured values, with an average MAE of 0.01, which verifies its accuracy. The research results provide a basis for the design of blasting parameters for other levels of the copper mine.

Blasting vibration  /  Parameter optimization  /  Single-delay blasting explosive charge  /  SSA-Elman neural network prediction model
杨宁, 尹贤刚, 钟周颖, 李泽鹏. 近地表开采爆破动力响应及参数优化研究. 矿业研究与开发, 2026 , 46 (7) : 62 -70 .
Ning Yang, Xiangang Yin, Zhouying Zhong, Zepeng Li. Research on Dynamic Response and Parameter Optimization of Blasting in Near-Surface Mining[J]. Mining Research and Development, 2026 , 46 (7) : 62 -70 .
Year 2026 volume 46 Issue 7
50
8
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Article Info
  • Receive Date:2025-08-18
  • Online Date:2026-10-27
  • Published:2026-07-25
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  • Received:2025-08-18
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Affiliations
    1.Changsha Institute of Mining Research Co., Ltd., Changsha, Hunan 410012, China
    2.National Engineering Research Center for Metal Mining, Changsha, Hunan 410012, 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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