Integration of X-ray radiography and automated mineralogy data for the optimization of ore sorting routines

[1]  M. Boone,et al.  Spectral Tomography for 3D Element Detection and Mineral Analysis , 2021, Minerals.

[2]  M. Becker,et al.  A Mineral X-ray Linear Attenuation Coefficient Tool (MXLAC) to Assess Mineralogical Differentiation for X-ray Computed Tomography Scanning , 2020 .

[3]  J. Gutzmer,et al.  Optimal sensor selection for sensor-based sorting based on automated mineralogy data , 2019, Journal of Cleaner Production.

[4]  Robben,et al.  Sensor‐Based Ore Sorting Technology in Mining—Past, Present and Future , 2019, Minerals.

[5]  P. Withers,et al.  Time-lapse imaging of particle invasion and deposition in porous media using in situ X-ray radiography , 2019, Journal of Petroleum Science and Engineering.

[6]  Yasuhiro Yamada,et al.  A New Method for Quality Control of Geological Cores by X-Ray Computed Tomography: Application in IODP Expedition 370 , 2019, Front. Earth Sci..

[7]  M. Rudolph,et al.  Froth flotation of scheelite – A review , 2017 .

[8]  Burcu Akça,et al.  The Mass Attenuation Coefficients, Electronic, Atomic, and Molecular Cross Sections, Effective Atomic Numbers, and Electron Densities for Compounds of Some Biomedically Important Elements at 59.5 keV , 2014 .

[9]  Joseph D. Lessard,et al.  Development of ore sorting and its impact on mineral processing economics , 2014 .

[10]  L. von Ketelhodt,et al.  Dual energy X-ray transmission sorting of coal , 2010 .

[11]  Rolf Fandrich,et al.  Modern SEM based mineral liberation analysis , 2007 .

[12]  James A. Finch,et al.  separability curves from image analysis data , 1989 .

[13]  N. Otsu.  A threshold selection method from gray level histograms , 1979 .