Optimizing the Bulk X-ray Fluorescence Scanning Parameters for Ore Grade Predictions

MineSense Technologies Ltd. is revolutionizing grade control at mining operations by installing ShovelSense® sensors on buckets that measure the grade of every load before it is dumped in the truck. ShovelSense® measures the elemental grade in each mining shovel bucket by scanning the rocks with X-ray fluorescence (XRF) sensors as the bucket is filled. This allows mines to divert trucks significantly reducing the amount of ore loss to the waste stream and removing waste from material destined for processing. This research project will take place in a lab-controlled setting to investigate how different scanning parameters affect the predicted XRF metal grade for different mine rock samples. Exploring and optimizing these XRF scanning parameters will improve the XRF grade predictions at the mine face and result in a more accurate classification of ore and waste which has both economic and environmental benefits.

Faculty Supervisor:

Alexander Braun

Student:

Partner:

MineSense Technologies Ltd

Discipline:

Earth science

Sector:

Mining

University:

Queen's University

Program: