期刊文献+

级配差异巨大全尾砂高效低成本粗细精准分离脱水技术研究

High efficiency and low cost precision separation and dewatering technology of all tailings with huge gradation difference
下载PDF
导出
摘要 柿树底金矿尾砂粗细粒径差异大、分层离析严重,为实际浓缩脱水工艺选择和充填体质量效果带来诸多的技术难题。通过研发以高频振动筛和陶瓷过滤机为核心设备的两段连续固液分离脱水工艺,实现了级配差异巨大全尾砂的高效低成本粗细精准分离脱水,为国内中小型矿山尾矿高效脱水及低成本充填系统建设提供了借鉴。 There are many technical problems in the selection of actual thickening and dewatering process and the quality effect of backfill due to the large difference in particle size and serious stratification and segregation of tailings in Shizhu bottom gold mine.Through the development of a two-stage continuous solid-liquid separation dewatering process with high frequency vibrating screen and ceramic filter as the core equipment,the high efficiency and low cost precision separation and dewatering of all tailings with huge gradation difference is realized,which provides a reference for the construction of high efficiency dewatering and low cost filling system for domestic small and medium-sized mine tailings.
作者 李振龙 王博文 梁毅 潘锋 李帅 LI Zhen-long;WANG Bo-wen;LIANG Yi;PAN Feng;LI Shuai(Henan Zhongkuang Energy Co.,LTD.,Luoyang 471000,China;School of Resources and Safety Engineering,Central South University,Changsha 410083,China)
出处 《世界有色金属》 2023年第18期186-191,共6页 World Nonferrous Metals
基金 湖南省科技创新计划资助(项目编号2023RC3035) 湖南省自然科学基金项目资助(项目编号2021JJ40745)。
关键词 粗细粒径差异大 全尾砂脱水 粗细精准分离 large difference of coarse particle size Full tailing dehydration Precise separation of thickness and fine
  • 相关文献

参考文献2

二级参考文献15

  • 1李杰,楚恒,朱维乐,彭静.基于支持向量机和遗传算法的纹理识别[J].四川大学学报(工程科学版),2005,37(4):104-108. 被引量:12
  • 2郑春红,焦李成,郑贵文.基于GA的遥感图像目标SVM自动识别[J].控制与决策,2005,20(11):1212-1215. 被引量:19
  • 3王宏宇,糜仲春,梁晓艳,叶跃祥.一种基于支持向量机回归的推荐算法[J].中国科学院研究生院学报,2007,24(6):742-748. 被引量:13
  • 4Lake P,Boris M E, Gollaher T. High density paste thickener in Siberia[C]//Jewell R, Fourie A. Proceedings of the 13th International Seminar on Paste and Thickened Tailings.Nedlands:Australian Centre for Geomechanics, 2010:411-419.
  • 5Rudman M,Simic K, Paterson D A, et al.Raking in gravity thickeners [J]. International Journal of Minerals Processing, 2008,86 : 114-130.
  • 6Trafalis T B, Oladunni O,Papavassiliou D V.Two-phase flow regime identification with a multiclassification support vector machine (SVM) model[J]. Industrial & Engineering Chemistry Research, 2005,44 (12) :4414-4426.
  • 7Ghemtio L, Soikkeli A, Yliperttula M, et aI. SVM classification and CoMSIA modeling of UGTIA6 interacting molecules[J]. Journal of Chemical Information and Modeling, 2014,54 (4) : 1011-1026.
  • 8Chaturvedi S,Prasad K H,Faruquie T A,et al.Automating pattern discovery for rule based data standardization systems [C]//2013 IEEE 29th International Conference on Data Engineering (ICDE) ,April 8-12,2013,Brisbane,Australia:[S.1.] : IEEE, 2013 : 1231-1241.
  • 9王勇,王洪江,吴爱祥.基于高径比的深锥浓密机底流浓度数学模型[J].武汉理工大学学报,2011,33(8):113-117. 被引量:43
  • 10吴爱祥,焦华喆,王洪江,杨盛凯,姚高辉,刘晓辉.深锥浓密机搅拌刮泥耙扭矩力学模型[J].中南大学学报(自然科学版),2012,43(4):1469-1474. 被引量:23

共引文献17

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部