Data fusion of Laser Induced Breakdown Spectroscopy and Diffuse Reflectance for improved analysis of mineral species in copper concentrates
Minerals Engineering, ISSN: 0892-6875, Vol: 173, Page: 107193
2021
- 16Citations
- 7Captures
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Article Description
Copper concentrates is an intermediate product of the copper production process, which can be sold or further processed by pyrometallurgical and electrolytic processes to obtain copper with a grade of 99.99%. The mineralogical analysis of these concentrates is very important for quality control and monitoring the feed of smelters. The use of spectroscopy provides a means to carry out this analysis by measuring the reflected or emitted spectra when the samples are illuminated by different light sources. Diffuse Reflectance (DRS) and Laser Induced Breakdown Spectroscopy (LIBS) provide key complementary information for identifying and quantifying mineralogical components. Combining the information of these spectra is crucial to perform the measurements at the same spatial domain. This contribution presents the analysis of copper concentrates using a multi-purpose set-up, measuring both spectra at the same spatial position, and the use of data fusion techniques for blending the information. Low and mid-level data fusion strategies are compared in terms of their effectiveness. In this application, the experimental results show that mid-level data fusion provides the best result outperforming the predictions done by the separated information sources. These results indicate that the spectral measurements obtained by LIBS and DRS from the same measuring point with high spatial resolution can be combined for enhancing the mineralogical analysis of copper concentrates.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S0892687521004222; http://dx.doi.org/10.1016/j.mineng.2021.107193; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85115892912&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S0892687521004222; https://dx.doi.org/10.1016/j.mineng.2021.107193
Elsevier BV
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