Multidimensional characterization of separation processes – Part 1: Introducing kernel methods and entropy in the context of mineral processing using SEM-based image analysis. (15th June 2019)

• Record Type: Journal Article
• Authors: Schach, Edgar; Buchmann, Markus; Tolosana-Delgado, Raimon; Leißner, Thomas; Kern, Marius; Gerald van den Boogaart, K.; Rudolph, Martin; Peuker, Urs A.
• Is Part Of: Minerals engineering. Volume 137(2019)
• Page Start: 78
• Page End: 86
• Publication Date: 2019-06-15
• Subjects: Multidimensional characterization -- Partition curve -- Separation process -- Mineral processing -- Kernel density estimation -- Entropy -- Bootstrap resampling; Mines and mineral resources -- Periodicals; Ressources minérales -- Périodiques; Mines and mineral resources; Periodicals; Electronic journals; 622
• DOI: 10.1016/j.mineng.2019.03.026
• Languages: English
• ISSNs: 0892-6875

Abstract

Highlights: Kernel methods are used to overcome limitations of discrete property classes. Statistically robust information is obtained by kernel methods. Kernels can be weighted by e.g. particle number, particle mass or mineral content. Calculation of multidimensional partition curves based on kernel methods. Entropy as local/ global criteria to assess multidimensional separation efficiency. Abstract: An alternative method for the particle tracking approach for scanning electron microscopy-based image analysis is introduced, using kernel density estimates instead of discrete bins. This allows for information that is more robust. Uncertainties of the data are assessed using the bootstrap resampling method. The presented methodology enables the calculation of multidimensional partition curves, which can be used for a detailed analysis of separation processes. It has been found that the statistical entropy is a helpful tool to evaluate the separation efficiency of these partition maps. The methodology was applied to a density separation process of a cassiterite-bearing skarn ore from the Hämmerlein deposit in the Erzgebirge region in Germany, which serves as a case study. A Sepro™ Falcon concentrator was utilized for the density separation.