Image analysis algorithm and verification for on-line molecular sieve size and shape inspection

An online machine vision inspection method is proposed to implement feedback control of molecular sieve growth process in rotary drum granulation. An experimental platform, comprising of a high-resolution digital camera and an image analysis system, has been developed to confirm the validity of the method on particle size distribution (PSD) and sphericity measurements. Experiments were performed with non-uniform molecular sieve particles (1–3 mm diameter) obtained from production line. The particle images are first obtained through digital camera and are then processed by image analysis system. After separating the overlap particles and removing non-target particles of the images, the molecular sieve size and shape are computed in less than 0.9 s. The validity of the size measuring accuracy is confirmed through comparing with the results from micrometer. The experimental results show that the repetitive precision of the proposed inspection system is about ±1%, the diameter measurement error between image method and micrometer is about ±3%, single image inspection speed is around 0.9 s/frame. The proposed method is reliable to provide feedback information for control system in rotary drum granulation.