The ore content estimation in the mineral processing plant with the aidof the ML process – from classification to measurement

Abstract

The flotation process is crucial for extracting valuable minerals from the ore. The rapid and on-line assessment of the metal content in the flotation froth is very important for the efficiency of metal extraction process in the mineral processing plant. The x-ray measurement systems are commonly used for this task. However, the systems are rather expensive and the process as a whole is time consuming. The paper presents Artificial Intelligence (AI) – algorithms for monitoring of the flotation process in a mineral processing plant. They enable fast and on-line froth content estimation on the basis of the Machine Learning (ML) process. The estimation algorithms are AI supported. They utilize a classification process of the flotation froth images acquired during the flotation process. These estimation algorithms will optimize mineral processing. They have undergone the laboratory tests and have demonstrated their ability to significantly improve the accuracy and efficiency of the flotation process.