Modernizing the Mining Industry

The KAIVOS (Efficient & safe identification of minerals) project was established as a Business Finland funded venture with FGI (Finnish Geodetic Research Institute / Paikkatietokeskus), Aalto University and VTT, with the final goal to realize a fully automated mineral recognition and positioning system to help mines locate and differentiate between minerals and know their locations at all times with unpresented accuracy.

Sanna Kaasalainen (on left) and Julian Ilinca.This type of knowledge has potential in not only greatly improving safety and efficiency, but also reducing emissions and fully revolutionizing the mining industry from prospecting to separating minerals from gangue.

To gain firsthand knowledge about the needs and requirements of the industry our partners (Agnico Eagle Oy, Cybercube Oy, Grundium Oy, Robit Oy and Outokumpu Kemi Mine) have provided us with invaluable information and opportunities helping us all to take the next step to a more efficient and sustainable future in mining. For example, knowing where workers are situated in mines and giving them essential information to ease their varying daily activities is crucial to improve both efficiency and safety hundreds of meters underground.

Getting Closer to the Goal

This collaboration has already led to two new functional instruments capable of mineral recognition in underground mining tunnels, namely the FGI-HSL (Finnish Geospatial Research Institute Hyperspectral LiDAR) and VTT's Active Hyperspectral Sensor. The FGI-HSL utilizes a supercontinuum source and an array of sensors to provide 3D point clouds augmented with positional information of minerals, while the Active Hyperspectral Sensor differentiates between mineral types using a Fabry-Pérot interferometer.

Subterranean navigation with precise position information has been a challenge for the mining industry, since satellite based positioning does not work underground. While relatively good positional information can be achieved with an accuracy of approximately 10m with currently employed technology, mining vehicles require a much higher accuracy to become fully autonomous in the future. By combining Hyperspectral material recognition, LiDAR mapping, Ultra-wideband positioning technology along with inertial sensors referenced with a satellite derived position outside the mine we aim to provide sub meter accuracy in any location underground.

Measurement Campaigns

Laboratory measurements for material recognition were started already in early 2017 with prototype instruments which gradually have developed to fully functional equipment. After this, two measurement campaigns have been conducted in mines and data has been also gathered using the UWB system and sensors.

The FGI-HS-LiDAR has also participated in a joint venture with Helsinki University to gather data concerning vegetation health. During the last years we have made multiple peer-reviewed publications and participated in various remote-sensing, positioning and mining related conferences and events around the world.

Toward the Future

We are currently presenting our results to the mining industry by, e.g., attending the FinnMateria mining fair in November 2018. We have also shared the news on the project in the Materia magazine of the Finnish Association of Mining and Metallurgical Engineers. The interest in our collaborative efforts is constantly growing and we have already demonstrated our capability to achieve significant results. More information and updates about our advances can be found on our webpage.

 

This blog was written by Julian Ilinca and Sanna Kaasalainen. Julian is working as a research scientist at the
Finnish Geospatial Research Institute of the National Land Survey of Finland at the department navigation specializing in RF. Sanna Kaasalainen is a Research Professor at the Finnish Geospatial Research Institute of the National Land Survey of Finland and is the head of the Department of Navigation. 

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