Using computer vision to assess an electrostatic separation process

For slow-varying processes like particles’ movement in some electrostatic separators, computer vision using a standard camera can be a simple and cost-effective tool for process assessment. This paper is aimed at using video treatment to track particle position as well as evaluate separated material purity in an inclined-plane electrostatic separator. The technique is applied to a 50%–50% binary mixture of polyamide (PA) of blue color and polycarbonate (PC) of orange color. Based on image treatment, each color can define the particle position, allowing a fast mapping of global particles’ distribution. The obtained results have allowed not only particle tracking but also estimation of the purity of recovered materials based on particle counting on both sides of the separator. The calculated purity rates are in good agreement with the measured values.