Article(id=1236334630979301672, tenantId=1146029695717560320, journalId=1235980550691926019, issueId=1236334630450819368, articleNumber=null, orderNo=null, doi=10.3969/j.issn.0253-6099.2023.06.003, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1689436800000, receivedDateStr=2023-07-16, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1772694746012, onlineDateStr=2026-03-05, pubDate=1701360000000, pubDateStr=2023-12-01, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1772694746012, onlineIssueDateStr=2026-03-05, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1772694746012, creator=13701087609, updateTime=1772694746012, updator=13701087609, issue=Issue{id=1236334630450819368, tenantId=1146029695717560320, journalId=1235980550691926019, year='2023', volume='43', issue='6', pageStart='1', pageEnd='183', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1772694745886, creator=13701087609, updateTime=1772694896382, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1236335261735506524, tenantId=1146029695717560320, journalId=1235980550691926019, issueId=1236334630450819368, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1236335261735506525, tenantId=1146029695717560320, journalId=1235980550691926019, issueId=1236334630450819368, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=11, endPage=14, ext={EN=ArticleExt(id=1236334631256125739, articleId=1236334630979301672, tenantId=1146029695717560320, journalId=1235980550691926019, language=EN, title=Optimization of Blasting Parameters Based on Improved Sparrow Search Algorithm, columnId=1236276106018484431, journalTitle=Mining and Metallurgical Engineering, columnName=MINING, runingTitle=null, highlight=null, articleAbstract=

In order to improve accuracy in selection of blasting parameters for open-pit mines, a mathematical model was established for determining bench blasting parameters in open-pit mines based on production cost of stope, and the blasting parameters were then optimized by using an improved sparrow search algorithm. The results show that the improved sparrow search algorithm can effectively improve the effect of bench blasting in open-pit mine, but also improves the construction efficiency. With Yulong Mining Industry Company in Xizang as an example, the blasting parameters after optimization are as follows: hole spacing of 6.2 m, row spacing of 4.9 m, and unit explosive consumption of 0.32 kg/t. With these blasting parameters, the stope production cost goes down by 7.5% to 11.06 yuan/t, and the bulk rate can be controlled within 10%.

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为了提高露天矿山爆破参数选取精度，基于采场生产成本建立了露天台阶爆破参数数学模型，并利用改进的麻雀搜索算法对爆破参数进行优化。结果表明，改进的麻雀搜索算法用于爆破参数优化，有效改善了露天矿台阶爆破的效果，提高了采矿施工效率。以西藏玉龙矿业为例，通过优化最终得出该矿的爆破参数为：孔间距a=6.2 m、排距b=4.9 m、炸药单耗q=0.32 kg/t，在该参数条件下，采场生产成本为11.06元/t，采场生产成本降低了7.5%，大块率控制在10%以内。

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闫祎然（1997—），女，内蒙古海拉尔人，硕士研究生，主要从事工程爆破方面的研究。

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闫祎然（1997—），女，内蒙古海拉尔人，硕士研究生，主要从事工程爆破方面的研究。

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