Continuous fragmentation monitoring for underground mining operations

Purpose and goal:

The motivation for this study is to develop an integrated fragmentation analysis tool as part of underground equipment transporting ore. Exteroceptive sensing are ill-suited for underground operations due to dusty conditions as well as their inability to see below the rock pile surface. Our approach uses proprioceptive sensing coupled with machine learning tools for fragmentation analysis where the mentioned limitations are mitigated and a continuous monitoring can be provided.

Expected results and effects: The results and expected effects are: • Efficient Ore Extraction by ensuring proper fragmentation, enabling easier transport and process. • Safety: Well-controlled fragmentation can help to minimize the risk of rockfalls, collapses, and other hazards.

• Dilution Control: Proper fragmentation is also an indicator of controlled dilution (unwanted waste material mixed with ore), often corresponding to minimal overbreak such that the excavated geometry conforms to the planned geometry. Approach and implementation: The study is divided in work packages as follows:

WP1 Requirements for a fragmentation analysis tool for underground operations. WP2 sets out to develop prototype hardware and software that can be used for experimentation. WP3 sets out to assess the accuracy of the developed fragmentation analysis technology. WP4 sets out to build the consortium and develop a draft project proposal for a larger follow-on project.