Article(id=1236327383951798665, tenantId=1146029695717560320, journalId=1235980550691926019, issueId=1236327378968965364, articleNumber=null, orderNo=null, doi=10.3969/j.issn.0253-6099.2023.05.002, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1681747200000, receivedDateStr=2023-04-18, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1772693018186, onlineDateStr=2026-03-05, pubDate=1696089600000, pubDateStr=2023-10-01, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1772693018186, onlineIssueDateStr=2026-03-05, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1772693018186, creator=13701087609, updateTime=1772693018186, updator=13701087609, issue=Issue{id=1236327378968965364, tenantId=1146029695717560320, journalId=1235980550691926019, year='2023', volume='43', issue='5', pageStart='1', pageEnd='177', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1772693016997, creator=13701087609, updateTime=1772693111855, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1236327776882577759, tenantId=1146029695717560320, journalId=1235980550691926019, issueId=1236327378968965364, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1236327776882577760, tenantId=1146029695717560320, journalId=1235980550691926019, issueId=1236327378968965364, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=6, endPage=10, ext={EN=ArticleExt(id=1236327384643858866, articleId=1236327383951798665, tenantId=1146029695717560320, journalId=1235980550691926019, language=EN, title=Influencing Factors Analysis and Parameter Optimization for Rock Fragmentation by Deep-Hole Cut Blasting Based on Grey Correlation Analysis, columnId=1236276106018484431, journalTitle=Mining and Metallurgical Engineering, columnName=MINING, runingTitle=null, highlight=null, articleAbstract=

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%.

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以内蒙古三贵口铅锌矿为背景,利用理论分析、图像处理和工程试验等技术手段对地下深孔切割槽爆破块度影响因素及参数优化开展研究。首先针对现场粉矿率高、平均块度小等问题,开展了爆破块度影响因素试验并采集现场数据,利用Split-Desktop 4.0软件处理试验爆堆图像;然后运用灰色关联理论确定影响爆破块度的主次因素;最后利用趋势分析法并结合现场实际情况,确定爆破参数优化方案,并进行工程试验验证。结果表明,该矿山切割槽粉矿率主要受排间延期时间和孔距影响,平均块度主要受孔距和排数影响;优化后的爆破参数为:孔距1.2 m,排距1.5 m,抵抗线0.8 m,爆破排数3排,4孔孔间延期时间分别为13、0、9、18 ms,排间延期时间42 ms,该参数条件下爆破粉矿率降低了27.19%,平均块度提高了62.89%。

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楼晓明(1972—),男,浙江东阳人,博士,教授,主要从事工程爆破方面的研究。
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林杰(1998—),男,福建莆田人,硕士研究生,主要研究方向为爆破工程及采矿工程。

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林杰(1998—),男,福建莆田人,硕士研究生,主要研究方向为爆破工程及采矿工程。

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林杰(1998—),男,福建莆田人,硕士研究生,主要研究方向为爆破工程及采矿工程。

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基于灰色关联理论深孔切割槽爆破块度影响因素分析及参数优化
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林杰 1, 2 , 刘少光 3 , 李广斌 4 , 楼晓明 1, 2 , 韩启民 4
矿冶工程杂志 | 采矿 2023,43(5): 6-10
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矿冶工程杂志 | 采矿 2023, 43(5): 6-10
基于灰色关联理论深孔切割槽爆破块度影响因素分析及参数优化
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林杰1, 2, 刘少光3, 李广斌4, 楼晓明1, 2, 韩启民4
作者信息
  • 1.福州大学 紫金地质与矿业学院,福建 福州 350108
  • 2.福州大学 爆破技术研究所,福建 福州 350108
  • 3.宁德市公安局,福建 宁德 352100
  • 4.乌拉特后旗紫金矿业有限公司,内蒙古 巴彦淖尔 015500
  • 林杰(1998—),男,福建莆田人,硕士研究生,主要研究方向为爆破工程及采矿工程。

通讯作者:

楼晓明(1972—),男,浙江东阳人,博士,教授,主要从事工程爆破方面的研究。
Influencing Factors Analysis and Parameter Optimization for Rock Fragmentation by Deep-Hole Cut Blasting Based on Grey Correlation Analysis
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
出版时间: 2023-10-01 doi: 10.3969/j.issn.0253-6099.2023.05.002
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以内蒙古三贵口铅锌矿为背景,利用理论分析、图像处理和工程试验等技术手段对地下深孔切割槽爆破块度影响因素及参数优化开展研究。首先针对现场粉矿率高、平均块度小等问题,开展了爆破块度影响因素试验并采集现场数据,利用Split-Desktop 4.0软件处理试验爆堆图像;然后运用灰色关联理论确定影响爆破块度的主次因素;最后利用趋势分析法并结合现场实际情况,确定爆破参数优化方案,并进行工程试验验证。结果表明,该矿山切割槽粉矿率主要受排间延期时间和孔距影响,平均块度主要受孔距和排数影响;优化后的爆破参数为:孔距1.2 m,排距1.5 m,抵抗线0.8 m,爆破排数3排,4孔孔间延期时间分别为13、0、9、18 ms,排间延期时间42 ms,该参数条件下爆破粉矿率降低了27.19%,平均块度提高了62.89%。

深孔爆破  /  切割槽  /  灰色关联理论  /  爆破块度  /  粉矿率  /  平均块度  /  影响因素  /  参数优化

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
林杰, 刘少光, 李广斌, 楼晓明, 韩启民. 基于灰色关联理论深孔切割槽爆破块度影响因素分析及参数优化. 矿冶工程杂志, 2023 , 43 (5) : 6 -10 . DOI: 10.3969/j.issn.0253-6099.2023.05.002
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
  • 国家自然科学基金(52109124)
  • 乌后紫金采场深孔回采爆破控制技术研究项目(01612203)
2023年第43卷第5期
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doi: 10.3969/j.issn.0253-6099.2023.05.002
  • 接收时间:2023-04-18
  • 首发时间:2026-03-05
  • 出版时间:2023-10-01
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  • 收稿日期:2023-04-18
基金
国家自然科学基金(52109124)
乌后紫金采场深孔回采爆破控制技术研究项目(01612203)
作者信息
    1.福州大学 紫金地质与矿业学院,福建 福州 350108
    2.福州大学 爆破技术研究所,福建 福州 350108
    3.宁德市公安局,福建 宁德 352100
    4.乌拉特后旗紫金矿业有限公司,内蒙古 巴彦淖尔 015500

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楼晓明(1972—),男,浙江东阳人,博士,教授,主要从事工程爆破方面的研究。
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2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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