Article(id=1322161710446785038, tenantId=1146029695717560320, journalId=1225396423026438145, issueId=1322161562689847927, articleNumber=null, orderNo=null, doi=null, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1732032000000, receivedDateStr=2024-11-20, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793157516346, onlineDateStr=2026-10-28, pubDate=1756051200000, pubDateStr=2025-08-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793157516346, onlineIssueDateStr=2026-10-28, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793157516346, creator=13701087609, updateTime=1793157516346, updator=13701087609, issue=Issue{id=1322161562689847927, tenantId=1146029695717560320, journalId=1225396423026438145, year='2025', volume='45', issue='8', pageStart='1', pageEnd='278', issueExtLink='null', onlineDate='null', pubDate='1756051200000', pubDateStr='2025-08-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793157481119, creator='13701087609', updateTime=1793158854568, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1322167323411198934, tenantId=1146029695717560320, journalId=1225396423026438145, issueId=1322161562689847927, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1322167323411198935, tenantId=1146029695717560320, journalId=1225396423026438145, issueId=1322161562689847927, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=61, endPage=69, ext={EN=ArticleExt(id=1322161710618751503, articleId=1322161710446785038, tenantId=1146029695717560320, journalId=1225396423026438145, language=EN, title=Research and Application on Key Parameters of High Concentration Continuous Filling Process for Tailings in Shizhuyuan Polymetallic Mine, columnId=null, journalTitle=Mining Research and Development, columnName=null, runingTitle=null, highlight=null, articleAbstract=

Aiming at the problems of large ore depletion rate and serious surface subsidence in Shizhuyuan Polymetallic Mine by caving mining, it is proposed to use filling mining method. Physical and chemical properties test of tailings, static and dynamic flocculation and settlement test were carried out, combined with the actual production capacity of the mine, the optimum thickening parameters of tailings and thickener size were determined. The particle swarm optimization support vector machine (PSO-SVM) was used to establish the sand discharge stability prediction model, and the optimum sand discharge process parameters were obtained. The results show that the optimum type of flocculant is CKYZ-24S, its optimum dosage is 30 g/t, the optimum feed mass concentration of the unclassified tailings is 12.5%, the optimum feeding rate of the tailings is 0.744 t/(m2h), and the diameter of the thickener is determined to be 12 m. The optimum sand discharge process parameters are as follows: the height of the tailings mud layer is 15.2 m, the thickening time is 3.9 h, the flow rate of sand discharge is 96 m3/h, and the average mass concentration of slurry is 70%, with fluctuation of ± 1.5%, which realizes 24 h continuous filling of tailings, and the filling capacity reaches 4 800 m3/d. The research results show that the filling mining method can improve the economic benefits and ensure the green and safe mining of the mine.

, authors=Guohui CHEN1, Bokun ZHENG2, 3, Yong SHI2, 3, Ziqi YUAN2, authorsList=Guohui CHEN, Bokun ZHENG, Yong SHI, Ziqi YUAN, authorCompany=null, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1322161712971756066, articleId=1322161710446785038, tenantId=1146029695717560320, journalId=1225396423026438145, language=CN, title=柿竹园多金属矿尾砂高浓度连续充填工艺的关键参数研究及应用, columnId=1226462294490657775, journalTitle=矿业研究与开发, columnName=采矿与矿山充填, runingTitle=null, highlight=null, articleAbstract=

针对柿竹园多金属矿采用崩落法开采存在矿石贫化率大、地表塌陷严重等问题,提出改用充填采矿法开采。开展了尾砂物化性质试验、静动态絮凝沉降试验,结合矿山实际生产能力,确定了尾砂最佳浓密参数和浓密机尺寸,并应用粒子群优化支持向量机(PSO-SVM)建立了放砂稳定性预测模型,得到了最佳放砂工艺参数。结果表明:絮凝剂最佳种类为CKYZ-24S,其最优掺量为30 g/t,全尾砂入料最佳质量浓度为12.5%,尾砂最佳给料速度为0.744 t/(m2·h),确定浓密机直径D=12 m。最佳放砂工艺参数为:尾砂泥层高度15.2 m、浓密时间3.9 h、放砂流量96 m3/h、料浆平均放砂质量浓度70%,质量浓度波动控制在±1.5%,标准偏差为0.71,实现了尾砂24 h连续充填,充填能力达4 800 m3/d。研究结果表明,采用充填采矿法开采提高了矿山经济效益,保障了矿山绿色、安全开采。

, authors=陈国辉1, 郑伯坤2, 3, 石勇2, 3, 袁子淇2, authorsList=陈国辉, 郑伯坤, 石勇, 袁子淇, authorCompany=null, correspAuthors=null, authorNote=

陈国辉(1985—),男,江西贵溪人,硕士,高级工程师,主要研究方向为有色金属矿山开采技术。E-mail:

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陈国辉(1985—),男,江西贵溪人,硕士,高级工程师,主要研究方向为有色金属矿山开采技术。E-mail:

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陈国辉(1985—),男,江西贵溪人,硕士,高级工程师,主要研究方向为有色金属矿山开采技术。E-mail:

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China Mine Engineering, 2022, 51(3):58-61., articleTitle=Study on optimization of filling technology and key equipment of green tailings-free mine, refAbstract=null), Reference(id=1322161720789938827, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, doi=null, pmid=null, pmcid=null, year=2024, volume=24, issue=5, pageStart=266, pageEnd=270, url=null, language=null, rfNumber=[17], rfOrder=32, authorNames=王小平, 冯亮, journalName=采矿技术, refType=null, unstructuredReference=王小平,冯亮.全尾砂–废石膏体充填材料特性及工艺参数研究[J].采矿技术,2024, 24(5):266-270., articleTitle=全尾砂–废石膏体充填材料特性及工艺参数研究, refAbstract=null), Reference(id=1322161720869630604, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, doi=null, pmid=null, pmcid=null, year=2024, volume=24, issue=5, pageStart=266, pageEnd=270, url=null, language=null, rfNumber=[17], rfOrder=33, authorNames=WANG Xiaoping, FENG Liang, journalName=Mining Technology, refType=null, unstructuredReference=WANG Xiaoping, FENG Liang. Study on the characteristics and process parameters of full tailings-waste gypsum filling material[J]. Mining Technology, 2024, 24(5):266-270., articleTitle=Study on the characteristics and process parameters of full tailings-waste gypsum filling material, refAbstract=null), Reference(id=1322161720932545165, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, doi=null, pmid=null, pmcid=null, year=2023, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[18], rfOrder=34, authorNames=李文波, journalName=null, refType=null, unstructuredReference=李文波.磷矿超细全尾砂膏体浓密技术研究[D].长沙:长沙矿山研究院,2023., articleTitle=磷矿超细全尾砂膏体浓密技术研究, refAbstract=null), Reference(id=1322161720995459726, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, doi=null, pmid=null, pmcid=null, year=2023, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[18], rfOrder=35, authorNames=LI Wenbo, journalName=null, refType=null, unstructuredReference=LI Wenbo. Research on the technology of thickening of phosphate ore ultra-fine whole tailing sand[D]. Changsha: Changsha Institute of Mining Research, 2023., articleTitle=Research on the technology of thickening of phosphate ore ultra-fine whole tailing sand, refAbstract=null), Reference(id=1322161721079345807, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, doi=null, pmid=null, pmcid=null, year=2015, volume=38, issue=6, pageStart=1, pageEnd=7, url=null, language=null, rfNumber=[19], rfOrder=36, authorNames=王新民, 张国庆, 赵建文, journalName=重庆大学学报, refType=null, unstructuredReference=王新民,张国庆,赵建文,等.深锥浓密机底流浓度预测与外部结构参数优化[J].重庆大学学报,2015, 38(6): 1-7., articleTitle=深锥浓密机底流浓度预测与外部结构参数优化, refAbstract=null), Reference(id=1322161721142260368, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, doi=null, pmid=null, pmcid=null, year=2015, volume=38, issue=6, pageStart=1, pageEnd=7, url=null, language=null, rfNumber=[19], rfOrder=37, authorNames=WANG Xinmin, ZHANG Guoqing, ZHAO Jianwen, journalName=Journal of Chongqing University, refType=null, unstructuredReference=WANG Xinmin, ZHANG Guoqing, ZHAO Jianwen, et al. Underflow concentration prediction and external structure parameter optimization of deep cone thickener[J]. Journal of Chongqing University, 2015, 38(6): 1-7., articleTitle=Underflow concentration prediction and external structure parameter optimization of deep cone thickener, refAbstract=null), Reference(id=1322161721226146449, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, doi=null, pmid=null, pmcid=null, year=1955, volume=47, issue=1, pageStart=38, pageEnd=41, url=null, language=null, rfNumber=[20], rfOrder=38, authorNames=TALMAGE W P, FITCH E B, journalName=Industrial & Engineering Chemistry, refType=null, unstructuredReference=TALMAGE W P, FITCH E B. Determining thickener unit areas[J]. Industrial & Engineering Chemistry, 1955, 47(1): 38-41., articleTitle=Determining thickener unit areas, refAbstract=null)], funds=[Fund(id=1322161718042669674, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, awardId=ZX23J070, language=CN, fundingSource=长沙矿山研究院有限责任公司科创项目(ZX23J070), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1322161713210831395, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, xref=1., ext=[AuthorCompanyExt(id=1322161713223414308, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, companyId=1322161713210831395, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.Hunan Shizhuyuan Nonferrous Metals Co., Ltd.,Chenzhou, Hunan 423037, China), AuthorCompanyExt(id=1322161713231802917, tenantId=1146029695717560320, journalId=1225396423026438145, 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remark=2.长沙矿山研究院有限责任公司,湖南 长沙 410012)]), AuthorCompany(id=1322161713441518121, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, xref=3., ext=[AuthorCompanyExt(id=1322161713445712426, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, companyId=1322161713441518121, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3.Hunan Engineering and Technology Research Center for Comprehensive Utilization of Mine Solid Waste, Changsha, Hunan 410012, China), AuthorCompanyExt(id=1322161713454101035, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, companyId=1322161713441518121, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3.湖南省矿山固废综合利用工程技术研究中心,湖南 长沙 410012)])], figs=[ArticleFig(id=1322161715291206220, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, language=EN, label=Fig.1, caption=The particle size distribution of unclassified tailings, figureFileSmall=D/qCV9Sr2v7/L8yVFHRHMg==, figureFileBig=l1a2vQYCK3k5uKrG+UwKlw==, tableContent=null), ArticleFig(id=1322161715370897997, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, language=CN, label=图1, caption=全尾砂粒径分布, figureFileSmall=D/qCV9Sr2v7/L8yVFHRHMg==, figureFileBig=l1a2vQYCK3k5uKrG+UwKlw==, tableContent=null), ArticleFig(id=1322161715555447374, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, language=EN, label=Fig.2, caption=The varying curves of solid-liquid separation interface height with time under different flocculants, figureFileSmall=2PMCUU9xgBZjMPWQ1NEAfQ==, figureFileBig=CKiWzzi+bwdhDdysqKkg+w==, tableContent=null), ArticleFig(id=1322161715635139151, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, language=CN, label=图2, caption=不同絮凝剂下固液分离界面高度随时间变化曲线, figureFileSmall=2PMCUU9xgBZjMPWQ1NEAfQ==, figureFileBig=CKiWzzi+bwdhDdysqKkg+w==, tableContent=null), ArticleFig(id=1322161715706442320, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, language=EN, label=Fig.3, caption=The varying curves of solid-liquid separation interface height with time under different flocculant dosages, figureFileSmall=lg5/rkCqcidFnf9VFB+SwA==, figureFileBig=Zs/Lt78/Ppribfh8JIhzcA==, tableContent=null), ArticleFig(id=1322161715798717009, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, language=CN, label=图3, caption=不同絮凝剂掺量下固液分离界面高度随时间变化曲线, figureFileSmall=lg5/rkCqcidFnf9VFB+SwA==, figureFileBig=Zs/Lt78/Ppribfh8JIhzcA==, tableContent=null), ArticleFig(id=1322161715949711954, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, language=EN, label=Fig.4, caption=The varying curves of solid-liquid separation interface height with time under different mass concentration of tailings slurry, figureFileSmall=HRwc1ogoCsp56U/JdEAeLA==, figureFileBig=jbtyzd4Z6s+sCli6MLvoxA==, tableContent=null), ArticleFig(id=1322161716029403731, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, language=CN, label=图4, caption=不同尾砂浆质量浓度下固液分离界面高度随时间变化曲线, figureFileSmall=HRwc1ogoCsp56U/JdEAeLA==, figureFileBig=jbtyzd4Z6s+sCli6MLvoxA==, tableContent=null), ArticleFig(id=1322161716096512596, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, language=EN, label=Fig.5, caption=Process flow of filling system, figureFileSmall=MvpmenQR2kOkIesl/Pg/fg==, figureFileBig=BF2VMxASuhmO1Ye7H9A0FQ==, tableContent=null), ArticleFig(id=1322161716163621461, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, language=CN, label=图5, caption=充填系统工艺流程, figureFileSmall=MvpmenQR2kOkIesl/Pg/fg==, figureFileBig=BF2VMxASuhmO1Ye7H9A0FQ==, tableContent=null), ArticleFig(id=1322161716251701846, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, language=EN, label=Fig.6, caption=Industrial test results, figureFileSmall=7yhjDZlUZv/cJwlezyz5Ig==, figureFileBig=z/JUN0h7Tx3kJHXSNkvHRA==, tableContent=null), ArticleFig(id=1322161716356559447, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, language=CN, label=图6, caption=工业试验结果, figureFileSmall=7yhjDZlUZv/cJwlezyz5Ig==, figureFileBig=z/JUN0h7Tx3kJHXSNkvHRA==, tableContent=null), ArticleFig(id=1322161716423668312, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, language=EN, label=Table 1, caption=

Basic physical parameters of unclassified tailings

, figureFileSmall=null, figureFileBig=null, tableContent=
相对密度松散容重/(t/m3)密实容重/(t/m3)松散孔隙率/%密实孔隙率/%
2.901.291.5755.5245.86
), ArticleFig(id=1322161716494971481, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, language=CN, label=表1, caption=

全尾砂基本物理参数

, figureFileSmall=null, figureFileBig=null, tableContent=
相对密度松散容重/(t/m3)密实容重/(t/m3)松散孔隙率/%密实孔隙率/%
2.901.291.5755.5245.86
), ArticleFig(id=1322161716562080346, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, language=EN, label=Table 2, caption=

Results of chemical composition analysis of unclassified tailings

, figureFileSmall=null, figureFileBig=null, tableContent=
SiCaAlFeFKMgMn
49.5616.4912.897.9114.372.371.280.902 9
NaSTiSnRbPbWP
0.8320.6440.1480.1090.755 70.6410.060.04
BiClZnCuCrMoSrZr
0.3220.3090.3060.028 30.0090.009 30.008 40.004 4
), ArticleFig(id=1322161716645966427, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, language=CN, label=表2, caption=

全尾砂化学成分分析结果

, figureFileSmall=null, figureFileBig=null, tableContent=
SiCaAlFeFKMgMn
49.5616.4912.897.9114.372.371.280.902 9
NaSTiSnRbPbWP
0.8320.6440.1480.1090.755 70.6410.060.04
BiClZnCuCrMoSrZr
0.3220.3090.3060.028 30.0090.009 30.008 40.004 4
), ArticleFig(id=1322161716746629724, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, language=EN, label=Table 3, caption=

Results of slump test

, figureFileSmall=null, figureFileBig=null, tableContent=
灰砂比不同料浆质量浓度的坍落度
78%76%74%72%70%68%
1∶69.722.527.028.228.428.8
1∶2011.522.825.727.528.428.9
), ArticleFig(id=1322161716847293021, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, language=CN, label=表3, caption=

坍落度试验结果

, figureFileSmall=null, figureFileBig=null, tableContent=
灰砂比不同料浆质量浓度的坍落度
78%76%74%72%70%68%
1∶69.722.527.028.228.428.8
1∶2011.522.825.727.528.428.9
), ArticleFig(id=1322161716918596190, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, language=EN, label=Table 4, caption=

Results of filling body strength tests

, figureFileSmall=null, figureFileBig=null, tableContent=
编号灰砂比料浆质量浓度/%抗压强度/MPa
3 d7 d28 d
1722.273.975.74
21∶6701.983.335.03
3681.733.224.67
4721.653.144.30
51∶8701.452.383.79
6681.232.383.37
7720.972.383.11
81∶10700.831.932.43
9680.741.642.13
10720.561.371.92
111∶12700.451.221.90
12680.330.721.47
1372—0.551.34
141∶1570—0.561.23
1568—0.230.67
), ArticleFig(id=1322161717031842399, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, language=CN, label=表4, caption=

充填体强度试验结果

, figureFileSmall=null, figureFileBig=null, tableContent=
编号灰砂比料浆质量浓度/%抗压强度/MPa
3 d7 d28 d
1722.273.975.74
21∶6701.983.335.03
3681.733.224.67
4721.653.144.30
51∶8701.452.383.79
6681.232.383.37
7720.972.383.11
81∶10700.831.932.43
9680.741.642.13
10720.561.371.92
111∶12700.451.221.90
12680.330.721.47
1372—0.551.34
141∶1570—0.561.23
1568—0.230.67
), ArticleFig(id=1322161717119922784, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, language=EN, label=Table 5, caption=

Results of dynamic flocculation sedimentation tests

, figureFileSmall=null, figureFileBig=null, tableContent=
试验序号给料速度qc/(t/(m2·h))底流排矿密度ρ2/(t/m3)底流质量浓度C2/%溢流水含固量/(mg/L)
10.6081.2072.8898.01
20.6461.1970.28180.90
30.7441.1868.41209.12
40.7731.1866.80306.98
50.8701.1764.72320.61
), ArticleFig(id=1322161717220586081, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, language=CN, label=表5, caption=

动态絮凝沉降试验结果

, figureFileSmall=null, figureFileBig=null, tableContent=
试验序号给料速度qc/(t/(m2·h))底流排矿密度ρ2/(t/m3)底流质量浓度C2/%溢流水含固量/(mg/L)
10.6081.2072.8898.01
20.6461.1970.28180.90
30.7441.1868.41209.12
40.7731.1866.80306.98
50.8701.1764.72320.61
), ArticleFig(id=1322161717325443682, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, language=EN, label=Table 6, caption=

Production capacity of filling system

, figureFileSmall=null, figureFileBig=null, tableContent=
年充填采空区量/m3单套系统充填能力/(m3/h)年工作天数/d年平均充填量/m3日平均充填量/m3充填站日充填时间/h
80×10490~10033092.4×1042 80018
), ArticleFig(id=1322161717409329763, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, language=CN, label=表6, caption=

充填系统生产能力

, figureFileSmall=null, figureFileBig=null, tableContent=
年充填采空区量/m3单套系统充填能力/(m3/h)年工作天数/d年平均充填量/m3日平均充填量/m3充填站日充填时间/h
80×10490~10033092.4×1042 80018
), ArticleFig(id=1322161717484827236, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, language=EN, label=Table 7, caption=

Schemes of orthogonal test

, figureFileSmall=null, figureFileBig=null, tableContent=
水平泥层高度 H/m放砂质量浓度 C2/%放砂流量 Q2/(m3/h)浓密时间 t/h
1136899.102.94
2146998.263.16
3157096.043.89
4167194.694.61
5177293.375.14
), ArticleFig(id=1322161717551936101, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, language=CN, label=表7, caption=

正交试验方案

, figureFileSmall=null, figureFileBig=null, tableContent=
水平泥层高度 H/m放砂质量浓度 C2/%放砂流量 Q2/(m3/h)浓密时间 t/h
1136899.102.94
2146998.263.16
3157096.043.89
4167194.694.61
5177293.375.14
), ArticleFig(id=1322161717665182310, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, language=EN, label=Table 8, caption=

Results of orthogonal test

, figureFileSmall=null, figureFileBig=null, tableContent=
序号泥层高度H/m放砂质量浓度C2/%放砂流量Q2/(m3/h)浓密时间t/h底流质量浓度的标准偏差σ
1136899.102.942.39
2136996.044.616.78
3137093.373.165.31
4137198.265.144.92
5137294.693.893.88
6146893.374.612.37
7146998.263.162.35
8147094.695.143.16
9147199.103.8910.54
10147296.042.944.89
11156894.693.164.14
12156999.105.143.06
13157096.043.890.05
14157193.372.942.59
15157298.264.613.33
16166896.045.144.16
17166993.373.896.87
18167098.262.942.56
19167194.694.613.58
20167299.103.163.03
21176898.263.894.74
22176994.692.947.23
23177099.104.618.56
24177196.043.165.07
25177293.375.141.57
), ArticleFig(id=1322161717749068391, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, language=CN, label=表8, caption=

正交试验结果

, figureFileSmall=null, figureFileBig=null, tableContent=
序号泥层高度H/m放砂质量浓度C2/%放砂流量Q2/(m3/h)浓密时间t/h底流质量浓度的标准偏差σ
1136899.102.942.39
2136996.044.616.78
3137093.373.165.31
4137198.265.144.92
5137294.693.893.88
6146893.374.612.37
7146998.263.162.35
8147094.695.143.16
9147199.103.8910.54
10147296.042.944.89
11156894.693.164.14
12156999.105.143.06
13157096.043.890.05
14157193.372.942.59
15157298.264.613.33
16166896.045.144.16
17166993.373.896.87
18167098.262.942.56
19167194.694.613.58
20167299.103.163.03
21176898.263.894.74
22176994.692.947.23
23177099.104.618.56
24177196.043.165.07
25177293.375.141.57
), ArticleFig(id=1322161717832954472, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, language=EN, label=Table 9, caption=

Sand discharge schemes

, figureFileSmall=null, figureFileBig=null, tableContent=
编号方案泥层高度H/m放砂质量浓度C2/%放砂流量Q2/(m3/h)浓密时间t/h底流质量浓度标准差预测值底流质量浓度标准差试验值
1初始方案16.0071.0094.692.61—2.53
2优化方案15.2469.8296.343.870.702—
3应用方案15.2070.0096.003.90—0.71
), ArticleFig(id=1322161717925229161, tenantId=1146029695717560320, journalId=1225396423026438145, articleId=1322161710446785038, language=CN, label=表9, caption=

放砂方案

, figureFileSmall=null, figureFileBig=null, tableContent=
编号方案泥层高度H/m放砂质量浓度C2/%放砂流量Q2/(m3/h)浓密时间t/h底流质量浓度标准差预测值底流质量浓度标准差试验值
1初始方案16.0071.0094.692.61—2.53
2优化方案15.2469.8296.343.870.702—
3应用方案15.2070.0096.003.90—0.71
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柿竹园多金属矿尾砂高浓度连续充填工艺的关键参数研究及应用
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陈国辉 1 , 郑伯坤 2, 3 , 石勇 2, 3 , 袁子淇 2
矿业研究与开发 | 采矿与矿山充填 2025,45(8): 61-69
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矿业研究与开发 |采矿与矿山充填 2025 , 45 (8) : 61 -69
柿竹园多金属矿尾砂高浓度连续充填工艺的关键参数研究及应用
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陈国辉(1985—),男,江西贵溪人,硕士,高级工程师,主要研究方向为有色金属矿山开采技术。E-mail:

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陈国辉(1985—),男,江西贵溪人,硕士,高级工程师,主要研究方向为有色金属矿山开采技术。E-mail:

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陈国辉1 , 郑伯坤2, 3, 石勇2, 3, 袁子淇2
作者信息
  • 1.湖南柿竹园有色金属有限公司,湖南 郴州市 423037
  • 2.长沙矿山研究院有限责任公司,湖南 长沙 410012
  • 3.湖南省矿山固废综合利用工程技术研究中心,湖南 长沙 410012
作者简介:

陈国辉(1985—),男,江西贵溪人,硕士,高级工程师,主要研究方向为有色金属矿山开采技术。E-mail:

Research and Application on Key Parameters of High Concentration Continuous Filling Process for Tailings in Shizhuyuan Polymetallic Mine
Guohui CHEN1 , Bokun ZHENG2, 3, Yong SHI2, 3, Ziqi YUAN2
Affiliations
  • 1.Hunan Shizhuyuan Nonferrous Metals Co., Ltd.,Chenzhou, Hunan 423037, China
  • 2.Changsha Institute of Mining Research Co., Ltd., Changsha, Hunan 410012, China
  • 3.Hunan Engineering and Technology Research Center for Comprehensive Utilization of Mine Solid Waste, Changsha, Hunan 410012, China
出版时间: 2025-08-25
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针对柿竹园多金属矿采用崩落法开采存在矿石贫化率大、地表塌陷严重等问题,提出改用充填采矿法开采。开展了尾砂物化性质试验、静动态絮凝沉降试验,结合矿山实际生产能力,确定了尾砂最佳浓密参数和浓密机尺寸,并应用粒子群优化支持向量机(PSO-SVM)建立了放砂稳定性预测模型,得到了最佳放砂工艺参数。结果表明:絮凝剂最佳种类为CKYZ-24S,其最优掺量为30 g/t,全尾砂入料最佳质量浓度为12.5%,尾砂最佳给料速度为0.744 t/(m2·h),确定浓密机直径D=12 m。最佳放砂工艺参数为:尾砂泥层高度15.2 m、浓密时间3.9 h、放砂流量96 m3/h、料浆平均放砂质量浓度70%,质量浓度波动控制在±1.5%,标准偏差为0.71,实现了尾砂24 h连续充填,充填能力达4 800 m3/d。研究结果表明,采用充填采矿法开采提高了矿山经济效益,保障了矿山绿色、安全开采。

充填采矿法  /  高浓度连续充填  /  充填工艺  /  放砂工艺参数  /  PSO-SVM模型

Aiming at the problems of large ore depletion rate and serious surface subsidence in Shizhuyuan Polymetallic Mine by caving mining, it is proposed to use filling mining method. Physical and chemical properties test of tailings, static and dynamic flocculation and settlement test were carried out, combined with the actual production capacity of the mine, the optimum thickening parameters of tailings and thickener size were determined. The particle swarm optimization support vector machine (PSO-SVM) was used to establish the sand discharge stability prediction model, and the optimum sand discharge process parameters were obtained. The results show that the optimum type of flocculant is CKYZ-24S, its optimum dosage is 30 g/t, the optimum feed mass concentration of the unclassified tailings is 12.5%, the optimum feeding rate of the tailings is 0.744 t/(m2h), and the diameter of the thickener is determined to be 12 m. The optimum sand discharge process parameters are as follows: the height of the tailings mud layer is 15.2 m, the thickening time is 3.9 h, the flow rate of sand discharge is 96 m3/h, and the average mass concentration of slurry is 70%, with fluctuation of ± 1.5%, which realizes 24 h continuous filling of tailings, and the filling capacity reaches 4 800 m3/d. The research results show that the filling mining method can improve the economic benefits and ensure the green and safe mining of the mine.

Filling mining method  /  High concentration continuous filling  /  Filling process  /  Sand discharge process parameter  /  PSO-SVM model
陈国辉, 郑伯坤, 石勇, 袁子淇. 柿竹园多金属矿尾砂高浓度连续充填工艺的关键参数研究及应用. 矿业研究与开发, 2025 , 45 (8) : 61 -69 .
Guohui CHEN, Bokun ZHENG, Yong SHI, Ziqi YUAN. Research and Application on Key Parameters of High Concentration Continuous Filling Process for Tailings in Shizhuyuan Polymetallic Mine[J]. Mining Research and Development, 2025 , 45 (8) : 61 -69 .
随着矿山开采的不断深入,地下采空区和塌陷区对矿山地质环境的影响愈发显著,可能诱发滚石、滑坡等地质灾害,危及矿山安全及周边环境,因此开采方法的转型至关重要。充填采矿法将采矿过程中产生的废料(如尾砂、废石等)回填至采空区,是稳定采空区、减少地表沉陷和降低灾害风险的有效手段[1-5]。相比于传统的采矿方法,充填采矿法能使矿石回采率大幅度提升,资源利用最大化,并且对环境影响较小,符合现代矿业绿色发展和可持续开采的理念,在采空区处理方面得到了广泛应用[6-7]。因此,继续深入研究充填采矿法的工艺、材料等方面的内容,对推动现代矿业绿色发展十分重要[8-13]。
已有诸多学者对优化充填工艺方面进行了研究,彭亮等[14]为改善料浆输送时分层离析现象,开展了料浆输送性能和流变特性试验,对全尾砂胶结充填工艺进行改进,结果表明:随着料浆输送浓度的提升,料浆分层离析的现象有所改善,能够实现长时间连续输送。史采星等[15]针对某铜矿充填成本高的问题,开展了尾砂物化性质测试,提出了尾砂高浓度充填技术,并进行了工业验证。在浓密工艺参数中,入料质量浓度和絮凝剂单耗、停留时间、泥层高度都是影响底流质量浓度的重要因素[16-18]。王新民等[19]融合遗传算法优化框架,构建了以深锥浓缩设备结构参数(高度/锥角)为特征参量、底流质量浓度为优化目标的GA-SVM智能预测系统,并基于司家营铁矿工程数据实现运行参数的全局寻优。
柿竹园多金属矿原采用崩落法采矿,存在矿石贫化率大、地表塌陷严重等问题。矿区的开采需要考虑以下因素。一是安全因素,由于地表发生塌陷,周围的岩石失去支撑,松动的岩石顺着塌陷的边缘滚落,可能造成滚石灾害。柿竹园多金属矿区内有公路经过,滚石可能对附近的设施、交通造成巨大威胁,甚至直接伤害人员。如果不变更采矿方法,也可能造成井下泥石流灾害,威胁井下生产安全。二是经济因素,地表塌陷引发的环境问题会增加矿区的环境治理成本,矿山企业必须支付大量费用用于土地恢复。同时,塌陷会导致矿山采空区失稳,造成未开采矿石的流失或破坏,导致可开采资源量减少,产量下降。某些区域的严重塌陷可能使整个矿床无法继续开采,如果不变更采矿方法,将严重影响矿山的经济效益。三是环境因素,崩落法不仅导致植被破坏、土壤流失,而且会破坏地下水系统,与绿色矿山减少对生态环境影响的目标冲突。
综合以上分析,为了减少采空区坍塌风险、控制地表塌陷、提高矿石回采率、减少环境破坏,矿山拟采用充填采矿法进行开采。在充填采矿法中,地表与地下采空区之间的关联复杂,需要调节充填体密度和强度,精确控制地表塌陷程度,避免诱发地质灾害,因此选择合适的充填材料至关重要。同时,为了提升充填效率,使充填系统能保持稳定高效的运行,保证生产的连续性,充填工艺的优化也很关键。实际生产中,需要提升料浆制备的效率、以及料浆输送的稳定性,综合考虑经济因素和生产实际,确保达到最佳充填效果。
基于此,本文针对柿竹园多金属矿充填系统建设,开展了尾砂物化性质试验、静动态絮凝沉降试验,并应用粒子群优化支持向量机(PSO-SVM)放砂稳定性预测模型优化了放砂工艺参数。根据矿山的生产需求,建设了双浓密机协作的充填系统,采用了柔性导向搅拌技术,建立的充填系统运行稳定,料浆制备输送浓度提高,料浆均匀连续泵送,实现24 h连续充填。
采用比重瓶法对全尾砂的真密度进行测定,并依据《建筑用砂》(GB/T 14684—2011)中的标准对全尾砂的容重、孔隙率进行测量,测试结果见表1。采用Mastersizer 3000激光衍射粒度分析仪对全尾砂的粒径分布参数进行分析,测试结果如图1所示。采用X-射线荧光光谱分析仪对全尾砂的化学成分进行定量分析,分析结果见表2。
从图1中的数据可以看出,所取全尾砂样品的粒度小于308.803 μm、粒径小于74 μm的尾砂颗粒占比为73.66%,粒径在35.335 μm以下的颗粒占比达到50%,20 μm以下的颗粒含量占比为35.92%,采用全尾砂作为骨料能够保证充填料浆长距离输送。表2化学成分分析检测结果表明,全尾砂中基本不含有毒有害物质,满足井下充填环保要求,且硅含量相对较高,对充填体强度具有益处,适宜于用作充填骨料。
采用自主研发的5种有机絮凝剂(CKYD-10S、CKF06、CKYZ-24S、CKFA02、CKYg-30S)进行试验,配置5组质量浓度为10%的尾砂浆,分别添加这5种絮凝剂,掺量均为30 g/t,试验结果如图2所示。由图2可以发现,CKYZ-24S絮凝剂在前30 s的絮凝沉降速度最快,因此后续试验采用CKYZ-24S絮凝剂。
配置4组质量浓度为10%的尾砂浆,分别添加20,30,40,50 g/t的CKYZ-24S絮凝剂,试验结果如图3所示。从图3可以发现,当絮凝剂掺量从20 g/t增加到30 g/t时,固液分界面下降的速度明显提升。当絮凝剂掺量从30 g/t增加到50 g/t时,固液分界面下降的速度变化较小,这主要是絮凝剂掺量过高引起全尾砂絮团过大,沉降过程中阻力增大,导致沉降速率减小。从沉降成本和沉降效率综合考虑,CKYZ-24S絮凝剂的最优掺量为30 g/t。
在最优絮凝剂CKYZ-24S和絮凝剂最优掺量30 g/t的基础上,测定尾砂浆质量浓度分别为7.5%、10%、12.5%、15%下的絮凝沉降速度,试验结果如图4所示。由图4可以看出,随着尾砂浆质量浓度变大,絮凝沉降速度变慢,其中7.5%低质量浓度尾砂浆的沉降效果最好。当全尾砂浆质量浓度为10%~12.5%时,固液分离界面高度随时间的变化速率也具有较好的沉降效果。由于在现实生产中难以保证尾砂维持在过低的浓度,从试验结果和实际情况综合考虑,确定全尾砂最佳入料质量浓度为12.5%。
全尾砂坍落度试验结果见表3。从表3试验数据可以看出,随料浆质量浓度降低,充填料浆坍落度增加,充填料浆流动性提升;灰砂比对充填料浆流动性影响很小。由于充填的面积较大,充填料浆在满足长距离、长时间输送的同时需要考虑料浆流平性。根据工程经验,当充填料浆坍落度为27~29 cm时,料浆具有良好的和易性,且无明显的离析现象,符合结构流特征,具备良好的管道输送性能。根据坍落度试验结果,坍落度为27~29 cm对应的充填料浆质量浓度为68%~72%。
根据坍落度试验结果,在能够满足泵送的充填料浆质量浓度范围内,对灰砂比为1∶6~1∶15,不同养护龄期(3 d、7 d、28 d)下的充填体强度进行了分析,试验结果见表4。由表4可知,随着养护龄期增加,料浆质量浓度增大,充填体强度也提高。而质量浓度降低会引起充填体强度降低,这主要是低浓度的料浆有较多自由水存在,会导致充填体孔隙率增加,从而使强度降低。
根据现场不同采场位置对充填体强度的要求,采场关键部位的充填体强度要求大于4.5 MPa。在灰砂比为1∶6、充填料浆质量浓度为68%~72%时,充填体28 d强度为4.67~5.74 MPa,满足井下充填的强度要求。
采用静态絮凝沉降的最优参数开展动态絮凝沉降试验:絮凝剂为CKYZ-24S,絮凝剂浓度为0.3%,絮凝剂掺量为30 g/t,尾砂入料质量浓度为12.5%。动态絮凝沉降试验系统由尾砂进料系统、絮凝剂进料系统、浓密沉降系统和底流出料系统组成,共配置了3台蠕动泵分别输送尾砂浆、絮凝剂和放砂料浆。调节泵转速按照试验方案控制尾砂浆给料速度分别为0.608 t/(m2·h)、0.646 t/(m2·h)、0.744 t/(m2·h)、0.773 t/(m2·h)、0.870 t/(m2·h),进行5组试验。等待砂面到达240 mm,调节底流出料速度,使底流高度稳定在240 mm附近。系统稳定运行20 min后,对底流料浆和溢流水进行取样,测得底流排矿密度ρ2、底流质量浓度C2和溢流水含固量,试验结果见表5。
由表5可知,随着给料速度增大,底流质量浓度逐渐降低,溢流水含固量不断增大。这是由于给料速度增大,尾砂和絮凝剂的反应时间变短,絮凝剂难以充分发生作用。由1.3节内容可知,设计要求尾砂质量浓度不小于68%;依据行业标准,要求溢流水含固量不超过300 mg/L。因此选取表5中第3组试验作为设计数据,此时给料速度为0.744 t/(m2·h),底流质量浓度为68.41%,溢流水含固量为209.12 mg/L。
柿竹园多金属矿采场需求的平均采空区处理能力为2 424 m3/d,充填尾砂平均用量为3 200 t/d,最大用量为3 840 t/d。考虑增大仓储能力同时兼顾尾砂压滤站供料,选用2台浓密机协同工作,单台浓密机应能满足24 h至少处理1 920 t尾砂,即处理能力应大于80 t/h。根据动态絮凝沉降试验结果,基于Kynch理论和T-F算法[20]计算,得出浓密机面积不小于107.51 m2,浓密机设计直径D=12 m。
柿竹园多金属矿充填系统按年处理采空区80 万 m3设计,采用2套90~100 m3/h充填制备系统24 h连续生产作业可满足生产需要,充填系统生产能力见表6。
柿竹园多金属矿充填系统工艺流程为:选厂尾砂供料,充填站双浓密机协同高效浓密,柔性导向复合流场搅拌制浆,充填工业泵连续泵送,工艺流程如图5所示。
(1)选厂尾砂供料。渣浆泵房标高约+473 m,充填站标高+457 m,浓密机基础平台标高约+466 m,浓密机高度为20 m,管道高差约13 m,因此选厂低浓度的尾砂浆需要通过渣浆泵和输送管道泵送至充填站浓密机内。在选厂尾砂收集池附近布置4台渣浆泵(两用两备),分别与充填站两台浓密机连接。选择的渣浆泵流量为500 m3/h,扬程30 m,变频电机功率110 kW,并可通过变频进行流量调节。
(2)充填站双浓密机协同高效浓密。絮凝剂通过絮凝剂加药机进入中心桶进行多点添加,选厂质量浓度为10%~12.5%的尾砂浆经泵送进入浓密机的中心桶,与絮凝剂混合后进行自稀释沉降。尾砂在浓密机内进行高效浓密,在泥层到达指定高度后开启底部阀门使砂浆进入高速柔性搅拌机,放砂质量浓度达到68%~72%。双浓密机协同作用能够提高充填质量,通过精确地控制充填材料的质量和稳定性,确保充填体的强度和密度达到设计要求;双浓密机协同作用使生产灵活可调,操作人员可以根据具体情况调节每台机器的运行参数,在处理不同性质的尾砂以及进行生产需求调整时效率更高;双浓密机协同作用使设备可靠性提升,一台机器停机维护时,另一台正常运行,充填站的持续生产得以保证,同时通过提高生产效率和减少生产停滞时间降低了生产成本。
(3)柔性导向复合流场搅拌制浆。固态颗粒、液态浆体、高黏性胶状物料三类物料在混合过程中呈现出截然不同的流体动力学行为。固态颗粒混合时,需借助较强的剪切力和对流作用来克服颗粒间的摩擦力,以实现充分均匀的分散;液态浆体则较容易卷入流场,并在较低的剪切力下迅速均匀混合;而高黏性胶状物料由于其黏度较大,容易产生团聚现象,因此引入特殊设计的导向活化流场和局部高剪切区域来避免团聚,促进活化。柔性导向复合流场是一种创新的搅拌技术,结合柔性与刚性结构,通过柔性搅拌部件在搅拌过程中引导物料的运动轨迹,从而减少硬质物料与刚性叶片的直接碰撞。柔性导向的复合活化流场能够动态适应物料的黏度变化,使固态、液态及胶状物料依次得到充分的分散、混合与活化,确保各物料之间的耦合机制得以充分发挥,最终实现多性态物料广域弥散与活化的效果。采用两台高速柔性搅拌机,分别给两套充填泵送系统供料,另增设一台高速柔性搅拌机作为压滤系统尾砂调浓,在满足充填需求时兼顾压滤尾砂供应。
(4)充填工业泵连续泵送。充填站配置3台锥阀式工业充填泵(两用一备),搅拌后的均质料浆通过充填泵24 h连续泵送到井下采空区,料浆流动性满足泵送要求,泵送连续稳定,充填效率高。
综合考虑柿竹园多金属矿采场充填实际生产需要,在静态絮凝沉降试验得到的最佳的入料质量浓度和絮凝剂掺量的基础上,选取浓密机的泥层高度H、放砂质量浓度C2、放砂流量Q2和浓密时间t作为影响底流质量浓度稳定性的最主要因素,设计L25(55)正交试验方案,见表7。
应用动态絮凝沉降系统进行正交试验,对浓密机底流进行取样,监测并记录一段时间内底流放砂质量浓度的变化,根据数据计算底流质量浓度的标准偏差,得到PSO-SVM模型的样本数据,见表8。
(1)对数据进行归一化,作为样本集,从样本集中随机选出部分数据作为训练集X,剩下的样本作为测试集Y。
(2)设定模型参数寻优范围,对于RBF核函数的宽度系数γ、惩罚系数C,寻优范围为0.1≤γ≤100,0.1≤C≤100,设定初始化进化代数K0=1,最大进化代数Kmax=100,种群最大数量S=10。
(3)随机初始化种群速度的个体最优和全局最优位置并进行支持向量机训练,将训练结果经5折交叉验证,得到的均方根误差作为各个粒子的适应度函数值,通过适应度值判断优劣从而更新极值,若适应度值满足要求或达到最大遗传代数,进行步骤(4)。
(4)输出最佳参数,构建代理模型,采用PSO优化算法进行寻优,根据均方根误差最小加点准则选取新样本xnew,将xnew加入训练集X。
(5)判断代理模型的预测误差是否满足要求,如果满足要求则结束加点,进行步骤(6);否则重复步骤(2)至步骤(4)。
(6)输出经过样本更新后的SVR模型,得出最佳参数组合:γ=67.36,C=8.53。模型的均方根误差(RMSE)为0.165 2,说明模型的预测效果良好。得到的预测模型T(x)为:
式中:αi、是拉格朗日乘子,其对应的向量xi为支持向量。
柿竹园多金属矿初始放砂方案见表9中方案1,实际生产中为了达到更高的底流质量浓度,指定开始放砂的泥层高度过高,料浆停留时间过长,而放砂流量过大,导致进放砂不平衡。底部料浆出现板结,在出料口附近出现导水通道,通道两侧的高浓度料浆堆积,中部料浆还未充分絮凝沉降就从通道迅速流出。因此实际放砂时初始质量浓度高,后续质量浓度呈现快速下降的趋势。
为了找到最优的放砂参数组合,将优化问题描述为:
应用MultiStart方法对构建的PSO-SVR模型进行全局寻优,得到了优化方案下的参数优化结果,见表9。从表9可以看出,优化方案中的最优参数下浓密机放砂底流质量浓度标准差预测值为0.702,说明料浆整体的质量浓度波动控制在±1.40%,满足稳定放砂的要求。由于优化方案为应用优化算法得出的最佳方案,得到的参数精度高,在实际工业情况中难以控制,因此将优化方案根据实际情况进行调整得到应用方案。
柿竹园多金属矿充填系统建设完成后,根据应用方案进行放砂工业试验,对放砂质量浓度进行取样测试,结果如图6所示。由图6可知,在正常的1个充填班次内,放砂平均质量浓度为70%,料浆质量浓度波动控制在±1.5%,较初始放砂方案有明显提升。工业试验得到的底流质量浓度标准偏差为0.71,与模型预测值0.702相比,相对误差为1.14%,说明PSO-SVM的预测结果较可靠。在实际的生产中,浓密机出料浓度和流量稳定,溢流水澄清。充填系统工作高效可靠,24 h连续充填,日充填能力最大达到4 800 m3,料浆泌水率低,充填体强度满足采矿要求,充填效果良好。
(1)通过开展尾砂物化性质、静动态絮凝沉降试验,结合矿山实际生产能力,确定了尾砂最佳浓密参数和浓密机尺寸:全尾砂入料质量浓度为12.5%、给料速度为0.744 t/(m2·h),使用CKYZ-24S絮凝剂,其最优掺量为30 g/t,浓密机直径D=12 m。
(2)通过正交试验,构建PSO-SVM放砂稳定性预测模型,利用全局优化算法找到最佳的浓密机放砂参数为:泥层高度15.2 m,满足浓密时间3.9 h后开始放砂,放砂流量为96 m3/h,优化后平均放砂质量浓度为70%,波动控制在±1.5%,整体的放砂底流质量浓度标准偏差为0.71。
(3)该矿采用双浓密机协同高效浓密工艺及柔性导向复合流场搅拌制浆技术,并顺利完成了建设和调试。工业试验结果表明,该系统放砂质量浓度高,充填效果良好,实现了尾砂高浓度连续充填,提高了矿山的经济效益,保障了矿山后续绿色、安全开采。
  • 长沙矿山研究院有限责任公司科创项目(ZX23J070)
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2025年第45卷第8期
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  • 接收时间:2024-11-20
  • 首发时间:2026-10-28
  • 出版时间:2025-08-25
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  • 收稿日期:2024-11-20
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长沙矿山研究院有限责任公司科创项目(ZX23J070)
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    1.湖南柿竹园有色金属有限公司,湖南 郴州市 423037
    2.长沙矿山研究院有限责任公司,湖南 长沙 410012
    3.湖南省矿山固废综合利用工程技术研究中心,湖南 长沙 410012
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2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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