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Article(id=1241046463757734618, tenantId=1146029695717560320, journalId=1240670690148397066, issueId=1241046461174043350, articleNumber=null, orderNo=null, doi=10.3963/j.issn.1001-487X.2025.01.001, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1728489600000, receivedDateStr=2024-10-10, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773818134487, onlineDateStr=2026-03-18, pubDate=1739894400000, pubDateStr=2025-02-19, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773818134487, onlineIssueDateStr=2026-03-18, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773818134487, creator=13701087609, updateTime=1773818134487, updator=13701087609, issue=Issue{id=1241046461174043350, tenantId=1146029695717560320, journalId=1240670690148397066, year='2025', volume='42', issue='1', pageStart='1', pageEnd='198', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=0, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773818133871, creator=13701087609, updateTime=1773820872662, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241057948554817923, tenantId=1146029695717560320, journalId=1240670690148397066, issueId=1241046461174043350, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241057948554817924, tenantId=1146029695717560320, journalId=1240670690148397066, issueId=1241046461174043350, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1, endPage=9, ext={EN=ArticleExt(id=1241046464474960608, articleId=1241046463757734618, tenantId=1146029695717560320, journalId=1240670690148397066, language=EN, title=Shared Control Theory and Experimental Study on Open-pit Mine Blasting, columnId=1240702071733801442, journalTitle=Blasting, columnName=THEORETICAL AND TECHNOLOGICAL EXPLORATION, runingTitle=null, highlight=null, articleAbstract=

Ore crushing is a crucial phase in hard rock mining and mineral resource recovery, significantly focusing on optimizing the energy consumption balance between blasting and mechanical crushing. This study analyzed industrial test data from an iron mine to explore the relationship between parent rock size distribution characteristics and mechanical crushing energy sensitivity, providing a theoretical foundation for process optimization and energy efficiency improvement. Initially, the connection between the key parameters of the parent rock size distribution curve and crushing power consumption was investigated. Subsequently, the maximum block size under the screen (D75) was identified as a sensitive indicator for crushing power consumption through correlation analysis. Finally, a theoretical model based on shared blasting control was developed, utilizing an optimal parent rock size distribution curve, R=1−exp[−(X282.1)1.69] to control the block size. Field application of this model demonstrates a cost reduction of 17.63%, affirming its potential for enhancing energy management and cost efficiency in mining operations.

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矿石破碎是矿石开采和矿石加工的关键环节，爆破破碎与机械破碎的能耗关系一直是行业关注的重点。依据某铁矿的工业性试验数据，通过分析母岩块度级配曲线特征参数与机械破碎电量消耗的关联，确定了筛下最大块度（D75）作为机械破碎电量消耗的敏感指标。构建了爆破共享理论模型，采用最佳母岩级配曲线R=1−exp[−(X282.1)1.69]调控母岩块度级配，验证了其对矿山总成本优化的有效性，最终实现了矿山总成本降低17.63%的目标。

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李萍丰（1966-），男，江西萍乡人，博士、正高级工程师，主要从事工程爆破技术和管理方面研究，（E-mail）。

LI Ping-feng (1966-), male, born in Pingxiang, Jiangxi Province, Ph. D, senior engineer, mainly engaged in engineering blasting technology and management research, (E-mail) .

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李萍丰（1966-），男，江西萍乡人，博士、正高级工程师，主要从事工程爆破技术和管理方面研究，（E-mail）。

LI Ping-feng (1966-), male, born in Pingxiang, Jiangxi Province, Ph. D, senior engineer, mainly engaged in engineering blasting technology and management research, (E-mail) .

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李萍丰（1966-），男，江西萍乡人，博士、正高级工程师，主要从事工程爆破技术和管理方面研究，（E-mail）。

LI Ping-feng (1966-), male, born in Pingxiang, Jiangxi Province, Ph. D, senior engineer, mainly engaged in engineering blasting technology and management research, (E-mail) .

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式中：W为最小抵抗线，m；ϕ为炮孔直径，mm；ΔW为凿岩精度的标准误差，即孔底偏离设计位置的平均距离，m；A为孔距/最小抵抗线；V0为每孔破碎岩石体积，m3；Q为相当于每孔中药包能量的TNT的当量，kg；E为炸药重量威力；K为岩石系数

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Characteristic value of fragment degree and the power consumption of crude crushing per unit tone of ore

, figureFileSmall=null, figureFileBig=null, tableContent=
试验号 D5/mm D20/mm D50/mm X c/mm D75/mm D80/mm D90/mm N破碎单位矿石耗电量kWh/t
145.8101.34250.5316.9425.16452.83599.91.645.55
247.693.79221.3298.1398.3449.1592.81.644.93
344.588.65229.7334.6431.5481.1615.71.564.67
448.195.29218.9304.6378.2433.1623.51.654.95
536.266.55149.7206.6271.4309.7432.51.693.68
628.551.60102.5137.3178.9198.9284.51.793.13
791.0161.61275.5336.6408.4446.6581.71.694.53
846.788.51204.4280.9368.8411.1547.91.644.17
931.161.00150.8210.7290.7339.2485.81.553.65
1031.766.58171.6234.9342.3349.0518.61.544.11
1132.970.34171.9224.1289.9325.5425.31.673.74
1235.272.67174.4242.7318.9361.6488.91.553.31
1391.0161.61275.5336.6408.4446.6581.72.275.41
1433.864.27139.2188.5239.4271.8372.32.273.80
1549.3125.17224.7282.1348.9392.9519.01.692.92
1677.6127.10205.9249.6309.2342.9449.72.243.23
1779.9133.45220.0272.9331.9370.8490.82.243.19
1873.7115.90182.6219.4276.5312.8427.82.433.77
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矿石块度特征值与粗破单位矿石耗电数量

, figureFileSmall=null, figureFileBig=null, tableContent=
试验号 D5/mm D20/mm D50/mm X c/mm D75/mm D80/mm D90/mm N破碎单位矿石耗电量kWh/t
145.8101.34250.5316.9425.16452.83599.91.645.55
247.693.79221.3298.1398.3449.1592.81.644.93
344.588.65229.7334.6431.5481.1615.71.564.67
448.195.29218.9304.6378.2433.1623.51.654.95
536.266.55149.7206.6271.4309.7432.51.693.68
628.551.60102.5137.3178.9198.9284.51.793.13
791.0161.61275.5336.6408.4446.6581.71.694.53
846.788.51204.4280.9368.8411.1547.91.644.17
931.161.00150.8210.7290.7339.2485.81.553.65
1031.766.58171.6234.9342.3349.0518.61.544.11
1132.970.34171.9224.1289.9325.5425.31.673.74
1235.272.67174.4242.7318.9361.6488.91.553.31
1391.0161.61275.5336.6408.4446.6581.72.275.41
1433.864.27139.2188.5239.4271.8372.32.273.80
1549.3125.17224.7282.1348.9392.9519.01.692.92
1677.6127.10205.9249.6309.2342.9449.72.243.23
1779.9133.45220.0272.9331.9370.8490.82.243.19
1873.7115.90182.6219.4276.5312.8427.82.433.77
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Calculation results of correlation between characteristic value of ore block and power consumption of crude broken unit

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指标 D5 D20 D50 X c D75 D80 D90
r0.200.260.620.640.730.710.72
P0.420.290.00660.00440.0010.0010.001
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矿石块度特征值与粗破单位矿石耗电数量相关性计算结果

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指标 D5 D20 D50 X c D75 D80 D90
r0.200.260.620.640.730.710.72
P0.420.290.00660.00440.0010.0010.001
), ArticleFig(id=1241057558622949731, tenantId=1146029695717560320, journalId=1240670690148397066, articleId=1241046463757734618, language=EN, label=Table 3, caption=

Parameters of optimal graded curve of parent rock mass

, figureFileSmall=null, figureFileBig=null, tableContent=
指标 D5/mm D20/mm D50/mm X c/mm D75/mm D80/mm D90/mm N单耗kWh/t
数值49.26125.17224.7282.1348.96392.95519.021.692.92
), ArticleFig(id=1241057558719418728, tenantId=1146029695717560320, journalId=1240670690148397066, articleId=1241046463757734618, language=CN, label=表3, caption=

母岩块度最佳级配曲线参数表

, figureFileSmall=null, figureFileBig=null, tableContent=
指标 D5/mm D20/mm D50/mm X c/mm D75/mm D80/mm D90/mm N单耗kWh/t
数值49.26125.17224.7282.1348.96392.95519.021.692.92
), ArticleFig(id=1241057558807499116, tenantId=1146029695717560320, journalId=1240670690148397066, articleId=1241046463757734618, language=EN, label=Table 4, caption=

Table of optimized blasting parameters and grading curves of burst blocks

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爆堆位置爆破参数爆堆块度曲线参数
爆堆号爆破时间炸药单耗/(g·m－3)孔距/m排距/m孔数/个台阶高度 D5/mm D20/mm D50/mm X c/mm D75/mm D80/mm D90/mm
596－69.290.495.84.34412.846.36114.89231.28289.94354.78389.02485.28
), ArticleFig(id=1241057558916551027, tenantId=1146029695717560320, journalId=1240670690148397066, articleId=1241046463757734618, language=CN, label=表4, caption=

优化爆破参数表以及爆堆块度级配曲线

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爆堆位置爆破参数爆堆块度曲线参数
爆堆号爆破时间炸药单耗/(g·m－3)孔距/m排距/m孔数/个台阶高度 D5/mm D20/mm D50/mm X c/mm D75/mm D80/mm D90/mm
596－69.290.495.84.34412.846.36114.89231.28289.94354.78389.02485.28
), ArticleFig(id=1241057559029797240, tenantId=1146029695717560320, journalId=1240670690148397066, articleId=1241046463757734618, language=EN, label=Table 5, caption=

The cost change before and after the best mother rock block degree curve test is used

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成本构成试验前试验后单项成本比较
费用(元/t铁精粉)占比/%费用(元/t铁精粉)占比/%费用(元/t铁精粉)占比/%
钻孔13.463.6013.854.500.392.91
爆破39.1810.4840.6313.191.453.71
铲装29.467.8829.719.650.250.85
运输40.6310.8741.0413.330.400.99
破碎40.4110.8125.908.41－14.51－35.91
磨矿210.6856.36156.8050.92－53.88－25.57
合计373.81100307.92100－65.89－17.63
), ArticleFig(id=1241057559126266238, tenantId=1146029695717560320, journalId=1240670690148397066, articleId=1241046463757734618, language=CN, label=表5, caption=

采用最佳母岩块度曲线试验前后成本变化表

, figureFileSmall=null, figureFileBig=null, tableContent=
成本构成试验前试验后单项成本比较
费用(元/t铁精粉)占比/%费用(元/t铁精粉)占比/%费用(元/t铁精粉)占比/%
钻孔13.463.6013.854.500.392.91
爆破39.1810.4840.6313.191.453.71
铲装29.467.8829.719.650.250.85
运输40.6310.8741.0413.330.400.99
破碎40.4110.8125.908.41－14.51－35.91
磨矿210.6856.36156.8050.92－53.88－25.57
合计373.81100307.92100－65.89－17.63
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露天矿爆破共享控制理论与试验研究
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李萍丰 1, 2 , 过江 3 , 赵培东 3 , 唐洪佩 1, 2
爆破 | 理论与技术探索 2025,42(1): 1-9
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爆破 | 理论与技术探索 2025, 42(1): 1-9
露天矿爆破共享控制理论与试验研究
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李萍丰1, 2 , 过江3, 赵培东3, 唐洪佩1, 2
作者信息
  • 1.非煤露天矿山安全智能开采国家矿山安全监察局重点实验室，肇庆　526530
  • 2.宏大爆破工程集团有限责任公司，广州　510623
  • 3.中南大学，长沙　410083

    • 李萍丰（1966-），男，江西萍乡人，博士、正高级工程师，主要从事工程爆破技术和管理方面研究，（E-mail）。

    LI Ping-feng (1966-), male, born in Pingxiang, Jiangxi Province, Ph. D, senior engineer, mainly engaged in engineering blasting technology and management research, (E-mail) .

Shared Control Theory and Experimental Study on Open-pit Mine Blasting
Ping-feng LI1, 2 , Jiang GUO3, Pei-dong ZHAO3, Hong-pei TANG1, 2
Affiliations
  • 1.Safety Intelligent Mining of Non-Coal Open-Pit Mines Key Laboratory of National Mine Safety Supervision Bureau, Zhaoqing 526530, China
  • 2.Hongda Blasting Engineering Group Co., Ltd., Guangzhou 510623, China
  • 3.Central South University, Changsha, 410083, China
出版时间: 2025-02-19 doi: 10.3963/j.issn.1001-487X.2025.01.001
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摘要
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矿石破碎是矿石开采和矿石加工的关键环节，爆破破碎与机械破碎的能耗关系一直是行业关注的重点。依据某铁矿的工业性试验数据，通过分析母岩块度级配曲线特征参数与机械破碎电量消耗的关联，确定了筛下最大块度（D75）作为机械破碎电量消耗的敏感指标。构建了爆破共享理论模型，采用最佳母岩级配曲线R=1−exp[−(X282.1)1.69]调控母岩块度级配，验证了其对矿山总成本优化的有效性，最终实现了矿山总成本降低17.63%的目标。

爆破共享理论  /  母岩块度级配  /  机械破碎能耗  /  特征值

Ore crushing is a crucial phase in hard rock mining and mineral resource recovery, significantly focusing on optimizing the energy consumption balance between blasting and mechanical crushing. This study analyzed industrial test data from an iron mine to explore the relationship between parent rock size distribution characteristics and mechanical crushing energy sensitivity, providing a theoretical foundation for process optimization and energy efficiency improvement. Initially, the connection between the key parameters of the parent rock size distribution curve and crushing power consumption was investigated. Subsequently, the maximum block size under the screen (D75) was identified as a sensitive indicator for crushing power consumption through correlation analysis. Finally, a theoretical model based on shared blasting control was developed, utilizing an optimal parent rock size distribution curve, R=1−exp[−(X282.1)1.69] to control the block size. Field application of this model demonstrates a cost reduction of 17.63%, affirming its potential for enhancing energy management and cost efficiency in mining operations.

blasting sharing theory  /  parent rock size distribution  /  mechanical crushing energy consumption  /  characteristic value
李萍丰, 过江, 赵培东, 唐洪佩. 露天矿爆破共享控制理论与试验研究. 爆破, 2025 , 42 (1) : 1 -9 . DOI: 10.3963/j.issn.1001-487X.2025.01.001
Ping-feng LI, Jiang GUO, Pei-dong ZHAO, Hong-pei TANG. Shared Control Theory and Experimental Study on Open-pit Mine Blasting[J]. Blasting, 2025 , 42 (1) : 1 -9 . DOI: 10.3963/j.issn.1001-487X.2025.01.001
正文
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对于矿山而言，如何实现能量高效利用，是矿山开采能耗的重要研究方向。就破岩能耗而言，不仅包括炸药破岩的能耗，而且包括机械设备碎磨矿石的能耗，在20世纪90年代初，国外提出了将采矿与选矿进行综合考虑以达到矿山全流程总成本最优的联合优化理念(Mine to Mill)[1]。Varannai等通过矿石运输模型研究了艾提克矿的碎矿和磨矿阶段之间的碎磨作业链的优化[2]。国内的鞍钢、唐钢都进行了以爆代破的联合优化的研究，取得了较好的经济效益。鞍钢齐大山铁矿通过优化爆破设计，炸药单耗增加20%~30%，电铲装车时间缩短了6.9%，机械粗破碎的小时处理矿石量提高了3.9%[3]。唐钢石人沟铁矿通过提高炸药单位成本0.974元/t，破碎能耗增加0.76 kWh/t，磨矿能耗降低了8.14 kWh/t，矿石粉碎总成本下降了3.84元/t(原矿)[4，5]，攀钢朱家包铁矿应用“以爆代破”技术后，对矿山装运及破碎机处理情况进行了跟踪调查，发现选矿厂粗、中破台时分别提高了7.64%和13.4%，岩破系统破碎台时提高了31.6%，铲装效率提高了20.31%，汽车运输效率提高了14.28%，采、选综合成本明显下降了8%左右[6]。
在采选联合优化相关研究中，爆破对矿石破碎和碾磨具有加强作用得到普遍认可，爆破环节对整个采选系统成本优化是至关重要的。然而，就目前以爆代破的联合工艺存在着以下不足：(1)以爆代破仅仅通过加大炸药单耗、缩小孔网参数等简单手段降低机械破碎电量消耗，爆破的有害效应却大幅增加，给矿山安全环保带来隐患，同时加大铲装的难点，不利于绿色矿山发展；(2)入粗破机矿石的块度分布与碎矿能耗的关联性没有针对性的量化分析，尤其影响机械破碎的岩石块度特征值没有深入研究，无法指导以爆代破的联合工艺；(3)以爆代破仅强调爆破的矿石块度，大量研究表明入粗破机矿石的块度才是降低机械破碎电量消耗的实体，入粗破机矿石的块度可以通过爆破块度的控制技术和矿石块度调配技术实现。因此，机械破碎能量消耗与破碎机入料口矿石块度(母岩块度级配曲线)密切相关[7]。随着智能矿石与绿色矿山建设的深入，研究既降低机械破碎的电耗又控制爆破有害效应的新理论与新工艺对矿山高质量发展的意义重大。
1　爆破共享控制理论
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共享就是分享，将一件物品(或者信息)与其他所有人共同拥有，共享入选“2017年度中国媒体十大流行语”[8]。爆破共享就是矿山其它工序享受爆破质量提高的增值服务。通俗解释就是通过透明地质、定制设计、责任施工和科学配矿的精准爆破技术提高爆破质量，使得矿山全链条效益最大化[9]。
采矿业主要有矿石开采和矿石加工两个阶段。这两个阶段涉及各种操作，其中任何一个阶段的优化都会促进另一个阶段的优化[10]。在矿石加工作业链中，破碎机能量消耗和矿石回收利用效率受到上游钻孔、爆破、装载和运输等作业的影响。在这些作业中，爆破是最具挑战性和最重要的作业。虽然在爆破作业中减小矿石碎块的大小可以方便矿石的处理，但额外的细粒对后续的碎矿作业可能会增加粒径控制的困难。理想的爆破破碎对下游作业和工艺有相当大的影响，它可以大大降低从爆破到碎磨的能源消耗和生产成本[11]。因此，爆破的优化有必要考虑其对下游环节能耗及成本的影响。而爆破成本优化需要考虑两个方面：一是爆破可能给后续作业造成的额外费用，二是根据发生的概率和随时间推移的后果严重程度用相对成本来处理爆炸引起的不利效果，在露天矿中，一个最佳爆破方案可使大部分爆轰能量用于岩石破碎。但爆炸能量往往以压缩、剪切和瑞利波的形式从爆破点向各个方向释放和传输。这些能量的一部分可能会造成不良的环境影响，如空气污染、冲击波、爆破振动、后冲拉裂、飞石、边坡稳定等有害效应，这些隐性成本应当充分考虑[12，13]。
理想的爆破破碎对下游工序有相当大的促进作用，它可以降低从爆破到破碎的能源消耗和生产成本。因此，在机械破碎用电成本高居不下的露天矿山中，有必要分析研究母岩块度级配与能耗的关系。建立爆破共享控制理论，通过对爆破与下游工序的协同优化，让矿山其它工序也能享受到爆破质量提高的增值服务。
爆破共享与以爆代破的主要区别：以爆代破是降低进机口岩石的平均块度来达到矿山全流程成本最低的目标，通过增加炸药单耗、缩减孔网参数的提高爆破成本和增加爆破的有害效应为手段；而爆破共享是控制母岩块度级配来达到矿山全流程成本最低的目标，通过精准爆破和科学调度控制母岩块度级配为手段。因此，本研究通过在某铁矿现场试验研究，对母岩块度级配曲线特征参数与机械破碎电量消耗的敏感度分析，提出了最佳的母岩块度级配曲线，建立了爆破共享理论模型，对其他矿山有指导意义。
2　母岩块度级配曲线与机械破碎电量消耗关联试验研究
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爆破产生的原矿，经过矿车运输、破碎、碾磨与提纯等工序加工成为可以销售的资源产品。机械碎矿是通过碎矿设备对矿石的挤压、劈裂、折断和冲击等做功方式，使得矿石块度变小。破碎矿石所做的功，一部分是使被破碎的矿石变形，并以热的形式散失于周围空间；另一部分则用于形成新表面，变成矿石的自由表面能，主要矿石破碎理论有面积假说、体积假说、裂缝假说，矿石破碎能耗主要受矿石硬度和矿石块度分布两个因素影响[14]。
2.1　试验矿山基本情况
矿区资源储量矿石量3.2亿t，年铁矿生产设计能力280万t，开采方式为露天开采，最高开采标高752 m，露天底标高452 m。铁矿为沉积变质型铁矿，矿石类型有磁铁矿、赤铁矿、混合矿[15]。
在露天矿中，钻孔和爆破是生产主要作业环节。后续生产通过矿石的装载、运输和破碎碾磨来开展(如图1)。
在破碎工段，母岩块度经过粗碎、中碎、细碎三阶段后显著变小。破碎工段以颚式破碎机和圆锥破碎机对矿石输入能量进而破碎矿石，该工段用皮带转运矿石和振动筛筛分矿石，粗碎机入料口栅格对矿石大小进行限制，栅格尺寸为700×700 mm。破碎设备配置及块度要求如下：粗碎机为PE900×1200颚式破碎机和JC1300颚式破碎机，最大控制块度200 mm；中碎机为GP200S圆锥破碎机和MC500STD-EC圆锥破碎机，最大控制块度50 mm；细碎机为HP400圆锥破碎机和MC500SH-C多缸液压圆锥破碎机；最大控制块度14 mm(图2、图3)，破碎系统的粗、中、细破碎设备有着固定的出料块度值要求，意味着对于中碎和细碎，矿石的破碎比是固定的。但对于粗碎，进机口的矿石块度分布(母岩块度级配)是波动的。因此，粗碎机入料块度是破碎系统的矿石主要变量，也即研究需要统计数据的实体。
2.2　数据收集
根据采场矿石爆堆方量大，单个爆堆挖运时间长，破碎机入料有矿车直接卸载和装载机铲入2种方式，为保障破碎块度与爆破参数、破碎能耗的对应关系，以短周期(连续几个小时)来统计挖运方量和破碎电耗。入料块度照片通过查看视频监控和现场拍照两种方式获取。具体试验步骤如下：
(1)矿车过磅后将矿石卸载进粗碎机入料口，第一车卸载完的时刻记下起始时间和车辆编号，并通知配电室拍下电表读数。
(2)通过拍下入料矿石照片分析粗碎机入料矿石块度，每卸载一车矿石拍N张照片。
(3)最后一车卸载完15 min左右为结束时刻，拍下电表度数，算出该段时间的电耗。
(4)根据矿车编号导出地磅称重数据，并根据统计时间段查看破碎工段皮带秤监控视频，记录并算出破碎的矿石数量。
(5)分别算出地磅称重和皮带秤对应的粗碎机破碎单位矿石量的电量消耗，两者作为比较。
2.3　粗碎机入料矿石块度图像处理
矿车卸料后，选取矿堆表面较为平整区域，在该区域放置标尺作为软件图像处理尺寸参考。现场拍照尽量保证与矿堆平行，画面清晰没有灰尘遮挡。采用BlastSprite爆破块度分析软件处理粗碎机入料矿石块度图像，如图4所示[16-18]，图像基本处理流程见图5。
矿车卸料后，选取矿堆表面较为平整区域，在该区域放置长度为22 cm的标尺作为软件图像处理尺寸参考。现场拍照尽量保证与矿堆平行，画面清晰没有灰尘遮挡。
本研究收集了11月2日到11月25日的粗碎机矿石入料块度照片，研究中收集的粗碎机矿石入料块度部分照片或视频监控截图如图6、图7、图8所示。
2.4　母岩块度特性方程
众所周知，颗粒材料粒度特性方程均为经验公式，常用的有双对数正态分布、Gaudin-Schutzmann分布和Rosin-Rammler分布，其中，粉体材料大多适用于Rosin-Rammler分布[19](以下简称R-R分布)根据粒度测量结果，探求更能反映粉体材料真实状态的特征参数，对于准确计算平均粒径和方差、客观评价粉体材料性能、工艺参数选择、配料选择以及粉体材料的实际应用具有重要意义。罗辛-拉姆勒(Rosin-Rammler)分布
式中：R为某矿石粒径的筛下累积率，%；X为筛网孔径或者岩块的粒径，m；Xc为特征粒径值，为筛下累积率为的63.21%的岩石块度尺寸，m；Xc越大说明岩石块度较大，反之亦然；n为不均匀指数，表示粒度分布范围的宽窄程度，n值越大，说明粒度分布范围越窄；n值越小，说明粒度分布范围越宽。
2.5　母岩块度分布曲线与能耗相关性分析
母岩块度级配曲线是用来描述母岩中不同粒径岩块的数量分布情况，为了进一步研究岩石块度级配对粗碎机破碎电耗的影响，通过BlastSprite爆破块度分析软件获得每一车入料矿石的块度曲线分布，提取特征指标与统计时间段内的粗碎机破碎单位矿石量的电量消耗相对应，总共记录了18组数据(表1)。从块度分布曲线中选取的特征指标有D5(筛下矿石占比5%的最大块度)、D20、D50、Xc、D75、D80、D90和块度分布曲线级配指标有均匀度N。
以相关系数r、显著性水平P值作为矿石块度特征值与粗破单位矿石耗电数量相关性强弱的指标。其中，r最大取1，最小取－1，r的绝对值越大，变量之间的相关性越强；P取0.05来判断变量的相关关系是否显著。在工程实际中，判断变量相关性强弱的r最小可以取到±0.4。相关系数的计算公式如式(2)所示。相关性指标计算值见表2，母岩块度曲线特征参数的相关性变化图见图9。
式中：x和y分别是两个变量的取值；n为样本容量；∑表示求和符号；xy表示变量x和变量y的乘积。该公式用于度量两个变量之间的线性关系的强度。
从表2和图9来看，不同特征块度与机械碎矿系统单耗之间存在的相关性强弱存在差异，其中筛下占比75%时的最大块度D75与碎矿单耗的相关性系数最大。从回归线的走向和相关系数r取值的正负可知，筛下最大块度(D5、D20、D50、XC、D75、D80、D90)与碎矿单耗呈正相关。
图9表明，筛下最大块度与碎矿单位消耗电量相关性折线图表明块度大小对碎矿系统单耗的影响具有“双峰性”，第一个块度与单耗相关性峰值在D75处取得。第二个峰值在矿石最大块度处取得，即矿石过大容易造成入料堵塞，进而造成设备空转及碎矿效率下降，最终使得碎矿能耗增加。通过上述试验确定某铁矿影响粗破机破碎电量消耗敏感指标为D75，最低的破碎电量消耗对应的母岩块度级配曲线为R＝1－exp，参数如表3。
3　试验结果与验证
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爆炸过程的复杂性及爆破岩体的复杂物理力学性质，在爆炸力作用下岩体破碎块度的大小和分布状况相当复杂，块度效果的影响因素有很多。
按照文献[17]爆破作业方法，采用表3级配曲线参数依据流程图(图10)设计爆破参数，调控母岩块度级配。
经过计算优化爆破参数爆破的爆堆情况(图11)，采用BlastSprite爆破块度分析软件处理，级配曲线为R＝1－exp，如表4所示，基本符合母岩级配要求。
按照上述爆破参数进行工业性验证试验，经过几个月统计(表5)，验证了依据母岩块度设计参数的合理性。从表5中可以看出：采用表中的母岩块度曲线，试验前后钻孔、爆破、铲装、运输成本略有上升、破碎和磨矿成本大幅度降低，总成本(不完全)降低65.89元/t铁精粉，下降比例17.63%。
4　结论
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以某铁矿的工业试验数据为基础，深入探讨了母岩块度级配曲线与机械破碎能耗之间的关系，提出了创新的爆破共享控制理论，构建了相应的优化模型。研究成果不仅在理论上为矿山硬岩开采及矿产资源回收等全流程成本优化提供了科学依据，也在实践中取得了显著的经济效益，具体结论如下：
(1)通过对不同母岩块度特征值与破碎能耗的关联分析，筛下最大块度75%能够有效反映机械破碎过程中的能量消耗水平，调整D75特征值使其达到最佳块度级配，可以显著降低矿石破碎能耗，进而提高矿山的整体效益。
(2)通过母岩块度级配反向设计(定制化)爆破参数，采用工业试验和数据收集分析对比，反向设计爆破参数比现行的最小抵抗线法和炸药单耗法科学实用，通过反向设计加上科学调度使得母岩级配符合要求，矿山总成本实现了17.63%的显著下降，尤其是在破碎和磨矿环节的能耗大幅减少，可为绿色矿山的建设提供技术支持。
(3)通过现场数据的验证与分析，提出的爆破共享理论及母岩块度级配优化模型，可以为矿山爆破设计、矿山破碎设备选型、破磨工艺优化以及成本控制提供了理论依据和方法指导，为露天矿爆破共享控制理论的工业推广提供了理论支撑与技术保障。
基金
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  • 国家科技重大专项(2024ZD1003406)
  • 国家自然科学基金面上项目(52174140)
文献
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2025年第42卷第1期
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doi: 10.3963/j.issn.1001-487X.2025.01.001
  • 接收时间：2024-10-10
  • 首发时间：2026-03-18
  • 出版时间：2025-02-19
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  • 收稿日期：2024-10-10
基金
National science and technology significant special(2024ZD1003406)
国家科技重大专项(2024ZD1003406)
National Natural Science Foundation of China(52174140)
国家自然科学基金面上项目(52174140)
作者信息
    1.非煤露天矿山安全智能开采国家矿山安全监察局重点实验室，肇庆　526530
    2.宏大爆破工程集团有限责任公司，广州　510623
    3.中南大学，长沙　410083
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2种不同金属材料的力学参数
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Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
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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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