A novel optical granulometry algorithm for ore particles

Abstract

This paper proposes a novel algorithm to detect the particle size distribution of ores with irregular shapes and dim edges. This optical granulometry algorithm is particularly suitable for blast furnace process control, so its result can be used directly as a reliable basis for control system dynamics optimization. The paper explains the algorithm and its concept, as well as its method, which consists of five steps to detect ore granularity and distribution. A series of comparative experiments under industrial environments proved that this novel algorithm, compared with conventional ones, improves the accuracy of granulometry.

Keywords

• particle size distribution
• optical granulometry
• double circle
• planar subdivision
• region expansion
• computer vision