Reduction of Energy and Water consumption of mining Operations by fusion of sorting technologies LIBS and ME-XRT

Reference number
Coordinator Luleå tekniska universitet - Avdelningen för Geovetenskap och miljöteknik
Funding from Vinnova SEK 1 010 000
Project duration May 2018 - April 2021
Status Ongoing

Purpose and goal

This project, involving an international consortium of four partners, has four primary objectives: 1. Improvement of ore sorting capabilities by sensor fusion of laser-induced breakdown spectroscopy (LIBS) and multi-energy X-ray transmission (ME-XRT). 2. Identification of the ideal particle size distribution required to optimize pre-concentration of ores. 3. Improvement of rock selection strategies to optimize separation results at high treatment capacities. 4. Implementation of sensor fusion data in the 3D geological characterization of the mined rock volume.

Expected results and effects

- Save consumables such as water, energy and processing reagents by an increased separability of ore from gangue material. - Increase the efficiency of the separation process and reduce operating costs, as well as environmental and local societal impact. - Reduce the uncertainty behind the separation of valuable material. - Improve the quality of 3D geomodels as a basis for successful mine planning regarding the statistical accuracy, objectivity and time-efficient update of the models.

Planned approach and implementation

Two different sensor technologies, LIBS and ME-XRT will be employed and combined. Data fusion algorithms will be developed, involving deep neural network strategies.The detectability of metallurgical and geological factors such as particle size distribution, ore textures, material composition and mechanical properties of the processed ore will be analyzed. An universally applicable on-line feed technique of the acquired sensor data into 3D geomodels will be developed.

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 8 March 2018

Reference number 2018-00601

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