Toward Ore-Specific Sensor-Based Sorting Systems in Mining

A two-year, multi-disciplinary research project requiring MSc, PhD and PDF researchers across Computer Science, Earth and Ocean Science, and Mining Engineering is proposed, working with an industrial sponsor MineSense, focused on the development of new sensors for advanced sensor sorting and so-called ‘non-grade’ applications in previously unaddressed high capacity, low grade mining situations. Specific objectives include, through advanced ore characterization, sensor development, algorithm development (including use of AI) and advanced system design and evaluation to:
• Improve the ability of sensors to respond to different mineralogical compositions of an ore/orebody
• Incorporate knowledge of these characteristics into algorithms for either rock or bulk sorting or grade or non-grade parameters to develop more intelligent sensing, and ultimately sorting, systems
• Integrate developed sensor systems into ore-specific sensing and sorting applications in the industry, including ore recovery, waste rejection and non-grade parameter control.

Faculty Supervisor:

Lee Groat;Bern Klein;David Poole;David Poole;Bern Klein;Lee Groat;Lee A. Groat

Student:

Partner:

MineSense Technologies Inc.;MineSense Technologies Ltd

Discipline:

Engineering

Sector:

Mining; Professional, scientific and technical services

University:

The University of British Columbia

Program: