秘鲁某金铜铁多金属矿浅部矿预选富集试验

针对秘鲁某金铜铁多金属矿含Cu 0.080%、Au 0.04g/t、S 1.28%、Fe 19.83%的浅部低品位矿石进行了预选富集试验研究。由于该矿前期开采处理的浅部矿主金属铁及铜、金等伴生有价金属品位较低,采用原设计的浮选—磁选工艺流程处理,存在入磨量大、磨选成本高、分选难度大等问题。在矿石工艺矿物学研究特性的基础上,提出采用原矿-25mm干抛—干抛粗精矿高压辊磨细碎—高压辊磨细碎产品湿抛—预抛尾矿分级回收铜铁的工艺进行预选富集。预选富集全流程试验最终可获得铜品位为0.10%、铁品位30.13%、铜回收率73.13%、铁回收率89.83%的预选富集精矿,抛尾产率达到40.19%。研究成果为提高选厂后续磨浮作业的入选品位,降低矿石入磨量和选矿成本,综合回收矿石中铁铜等伴生有价金属创造了良好的前提条件。

预抛—分级回收工艺预选秘鲁某金铜铁多金属矿深部矿石

采用浅部矿的预选工艺对秘鲁某金铜铁多金属矿含Cu 0.127%、Au 0.08 g/t、S 2.08%、Fe 40.56%的深部矿石进行了选矿预选富集试验研究,为该矿石的合理预选工艺提供参考。结果表明,浅部矿的预抛—分级预选工艺(原矿-25 mm干抛—干抛精矿高压辊磨细碎—高压辊磨细碎产品湿抛—预抛尾矿分级回收)对深部矿石具有较好的适应性和预选富集效果,最终获得铜品位0.13%、铁品位48.76%、铜回收率87.49%、铁回收率97.93%的总预选精矿,总预选抛尾率为18.84%。项目成果为该矿石的合理预选工艺选择提供了参考,并为提高选厂后续磨浮作业的矿石入选品位,降低入磨矿量和磨选成本,综合回收矿石中铁铜等伴生有价金属创造了良好的前提条件。

粉煤灰提铁试验研究

针对酒钢公司粉煤灰资源利用率低的问题,开展粉煤灰干式预选富集--湿式精选提铁试验研究,试验分析讨论了预选富集磁场强度、给料量、设备转速和湿式精选段数对铁精矿指标的影响。结果表明,采用一段预选富集三段湿式精选工艺,在预选富集磁场强度350m T、给料量60kg/h、设备转速60r/min,粗精矿三段湿式精选条件下,可获得Fe品位56.20%、SiO_2含量8.43%的铁精矿。

Flotation recovery of vanadium from low-grade stone coal

Pre-concentration of vanadium from low-grade stone coal by the method of desliming-flotation was investigated. The mineral composition and microstructure of stone coal were studied systematically by means of X-ray fluorescence spectrometry （XRF）, X-ray diffraction （XRD） and scanning electron microscopy （SEM）. The results show that selective separation of vanadium-bearing minerals can be achieved by flotation in acidic solution using melamine （EA）. The final vanadium concentrate with V2O5 grade of 1.88% and recovery rate of 76.58% is obtained by desliming-flotation process and 72.51% of the raw ore is rejected as tailings. The pre-concentration of vanadium from low-grade stone coal can increase V2O5 grade and decrease the content of acid consuming minerals, which would enable economical utilization of metallurgical vanadium extraction technology.

Application of reflux classifier with closely spaced inclined channels in pre-concentrate process of fine antimony oxide particles

In this work,the reflux classifier with closely spaced inclined channels is used as the pre-concentration facility to improve the separation efficiency before the shaking table separation.Three operating parameters of reflux classifier(RC)to pre-concentrate fine(0.023−0.15 mm)tailings of antimony oxide were optimized by response surface methodology(RSM)using a three-level Box-Behnken design(BBD).The parameters studied for the optimization were feeding speed,underflow,and ascending water speed.Second-order response functions were produced for the Sb grade and recovery rate of the concentrate.Taking advantage of the quadratic programming,when the factors of feeding,underflow and ascending water are respectively 225,30 and 133 cm^3/min,a better result can be achieved for the concentrate grade of 2.31% and recovery rate of 83.17%.At the same time,70.48% of the tailings with the grade of 0.20% were discarded out of the feeding.The results indicated that the reflux classifier has a good performance in dealing with fine tailings of antimony oxide.Moreover,second-order polynomial equations,ANOVA,and three-dimensional surface plots were developed to evaluate the effects of each parameter on Sb grade and recovery rate of the concentrate.