Identification of Valuable Minerals or Metals in Ores Using Microwave Imaging

This study investigates the potential application of microwave imaging (MWI) in ore sorting systems for mineral processing. Modern sensor-based ore sorting employs various sensing methods, such as X-ray transmission (XRT), X-ray fluorescence (XRF), optical sensing, and inductive sensing. We aim to apply MWI techniques in sensor-based ore sorting to separate ore particles containing valuable minerals or metals from barren particles. Compared to existing ore sensing methods, MWI has the potential to penetrate deeper into rock particles and to be used as a supplementary method for analyzing those ores with high contrast in electromagnetic (EM) properties between valuable minerals/metals and gangue minerals. Microwave scattering simulations are performed on realistic ore models. Measurements on real ore samples are also conducted. The confocal microwave imaging (CMI) algorithm is used for image formation. The simulation and measurement results both successfully identify the presence of valuable minerals or metals in ores, thereby demonstrating the feasibility of applying MWI in ore sorting.