Monitoring of industrial crystallization processes through image sequence segmentation and characterization

Abstract

To enhance control and monitoring of industrial crystallization processes, we propose an innovative nondestructive imaging method utilizing in situ 2D vision sensors. This approach enables the acquisition of 2D videos depicting crystal aggregates throughout the batch crystallization process. Our approach is built upon experimental observations, specifically regarding the process dynamics and sensor fouling. It involves dynamic segmentation of observed aggregates, from which quantitative analyses are derived. Notably, our method allows for tracking the evolution of the particle size distribution of crystal aggregates over time and the determination of the growth kinetics of crystals that agglomerate at the sensor air gap. This enables the detection of key stages in the crystallization process and the geometric characterization of crystal aggregate production.