Control of granule growth in fluidized bed granulation by an image processing system

Abstract

In this paper, the control of granule growth in fluidized bed granulation was carried out using a newly developed image processing system. Granule images measured by a particle image probe were digitized by an image processing system during granulation to continuously calculate granule size distribution. To avoid excessive granule growth, fuzzy logic using a linguistic algorithm employing if-then rules with a process lag element taken into consideration was adopted for the control algorithm. This newly developed system was applied to actual fluidized bed granulation under various powder samples and operating conditions, and the validity of the system was investigated. It was found that the system could control granule growth with high accuracy, regardless of changes in powder samples and operating conditions.