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 ânon-gradeâ 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:
â¢ Improve the ability of sensors to respond to different mineralogical compositions of an ore/orebody
â¢ 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
â¢ 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:

Bern Klein;David Poole;Lee Groat

Student:

Lindsey Abdale;Natalia Martino

Partner:

MineSense Technologies

Discipline:

Engineering

Sector:

Mining and quarrying

University:

Program: