Development of a strategy and interpretation of the NIR spectra for application in automated sorting
Development of a strategy and interpretation of the NIR spectra for application in automated sorting
复制标题
制定用于自动分选的近红外光谱策略和解释
DOI：
10.1016/j.mineng.2018.08.011
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发表时间：
2018
影响因子：
4.8
通讯作者：
Phiri T
中科院分区：
文献类型：
--
作者：
Phiri T
近红外光谱技术是一种新型的矿物分选技术，可用于矿石分选过程中矿物的早期识别和分选。在这项研究中，近红外传感器在自动分选应用的潜力进行了研究，对铜金矿样品。矿石含有大量的含碳物质，这导致在铜提取期间的后续浸出过程中过量的酸消耗。为了将这种不需要的脉石材料（碳酸盐）与有价值的金属（铜）分类，开发了根据铜和碳酸盐含量来识别和区分矿石的策略。测量了矿石颗粒表面的近红外光谱，在2000 ~ 2405 nm的较长波长范围内观察到特征吸收特征。用X射线荧光和X射线衍射仪分别测定了矿石的化学成分和矿物成分，并与测定结果进行了相关性分析。近红外光谱显示了富含碳酸盐的颗粒的独特的特征吸收特征，其将这些颗粒与含铜颗粒区分开，含铜颗粒在较长波长下相当无特征。光谱特征和化学矿物学数据的综合解释表明，基于近红外的分选对这类矿石具有潜力。
The Near Infrared (NIR) spectroscopy is a novel technique that can be used for early identification and separation of minerals from unwanted gangue during ore sorting. In this research, the potential of near infrared sensors for application in automated sorting was investigated on a copper-gold ore sample. The ore contains a substantial amount of carbonaceous material which results in excessive acid consumption in the subsequent leaching process during copper extraction. To classify this unwanted gangue material (carbonate) from the valuable metal (copper), a strategy to identify and distinguish the ore according to copper and carbonate content was developed. The near infrared spectra were measured on the surface of ore particles and characteristic absorption features were observed at a longer wavelength ranging from 2000 nm to 2405 nm. The results were then correlated with the chemical and mineralogical composition of the ore determined using X-Ray fluorescence and X-Ray diffraction equipments respectively. The near infrared spectra showed distinct characteristic absorption features for carbonate rich particles that distinguished these from copper bearing particles, which are fairly featureless at longer wavelengths. Combined interpretation of spectral features and chemical and mineralogical data indicates that near infrared-based sorting has potential for this type of ore.
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影响因子：
4.8
作者：
S. Iyakwari;H. Glass;G. Rollinson;P. Kowalczuk
通讯作者：
S. Iyakwari;H. Glass;G. Rollinson;P. Kowalczuk
通过基于尺寸的分离来剔除粗废物
影响因子：
4.8
作者：
D. J. Bowman;R. Bearman
通讯作者：
R. Bearman
使用基于近红外传感器的分选进行矿物预浓缩
影响因子：
1.5
作者：
S. Iyakwari;H. Glass
通讯作者：
H. Glass
碳酸盐矿物在可见光和近红外（0.35-2.55微米）的光谱反射率：方解石、霰石和白云石
DOI：
--
发表时间：
1986
期刊：
影响因子：
--
作者：
SuseN J. Ger
通讯作者：
SuseN J. Ger
矿物粒度的影响以及使用近红外传感器进行矿石分选的合适参数的选择
影响因子：
4.8
作者：
S. Iyakwari;H. Glass
通讯作者：
H. Glass