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Browsing by Author Dalm, M.

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  • Applicability of near - infrared hyperspectral imagery (NIR-HI) for sensor based sorting of an epithermal AU-AG ore

    • Authors: Dalm, M.;  Advisor: -;  Participants: - (2015)

  • In the presented study test work was performed with near-infrared hyperspectral imagery (NIR-HI) on 36 ore samples from a South-American epithermal Au-Ag mine. The aim of the test work was to investigate if NIR-HI provides information about the alteration mineralogy of samples that can be used to predict their economic value. Mineral distribution maps were produced from the hyperspectral images by using correlation coefficients between the image pixels and a set of reference spectra. These maps showed that detection of mineralogy with NIR-HI can be used to distinguish; i) ore particles with low Au and Ag grades, ii) ore particles with high carbon contents, iii) ore particles with high...
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  • Application of near - infrared (NIR) spectroscopy to sensor based sorting of an epithermal AU - AG ore

    • Authors: Dalm, M.;  Advisor: -;  Participants: - (2015)

  • Test work was performmed with near-infrared (NIR) spectrocopy on 94 ore samples from a South-American Au - Ag mne. The aim of the test work was to investigate if alteration minerals can be detected with the NIR sensor that can be use as indicators of ore value. Partial least squares discriminant analysis (PLS-DA) was applied to the spectral data to make classification models that use the measured NIR spectra to distinguish samples with certain Au, S or C grades. This showed that detection of mineralogy with NIR spectroscopy can be used to discriminate on i ) ore particles with low Au and Ag grades ii) ore particles with high carbon contents iii) ore particle with high sulphide content...
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  • Ore–Waste Discrimination in Epithermal Deposits Using Near-Infrared to Short-Wavelength Infrared (NIR-SWIR) Hyperspectral Imagery

    • Authors: Dalm, M.;  Advisor: -;  Participants: Buxton, M. W. N.; Van Ruitenbeek, F. J. A. (2019)

  • The results showed that NIR-SWIR hyperspectral imagery could be used to segment a population of waste samples by detecting occurrences of pyrophyllite, dickite and/or illite. This result can be explained by the fact that these minerals are commonly deposited further away from the ore-bearing epithermal veins, while the absence of SWIR-active minerals or detected occurrences of alunite are more closely associated with these structures. The ability to identify waste with NIR-SWIR spectral sensors means there is potential that sensor-based sorting can be used to remove this waste from mineral processing operations. Additional research is still required to assess the economic feasibility...