Professor of School of Engineering, Design and Built Environment, Western Sydney University, Australia. His research interests cover Industry 4.0, Additive Manufacturing, Advanced Engineering Materials and Structures (Metals and Composites), Multi-scale Modelling of Materials and Structures, Metal Forming and Metal Surface Treatment.
Abstract— The modern mineral fertilizer industry are large-scale factories, which produce dozens of tons of product hourly. At the same time, there are practically no robotic systems of quality control of the ongoing technological processes. In present paper, main stages of mineral fertilizer production are described, and the solution to the problem of robotic online particle size control was proposed. The general scheme and algorithm of the device functioning work were given. The developed system consists of three main units: a sampling unit, a sample delivery to the analysis area unit and a control unit with optical detection of granules. Sampling is carried out by a rotary system and further, the sample is delivered to the analysis area through linear vibrations. The entire sampling and sample delivery circuit is controlled by a computer, which built into the analysis unit. The software also allows to determine the physical parameters of the granules in the analysis area (size, color, and shape). The calculation algorithm of granule parameters consists of obtaining an optoelectronic image, its pre-processing, calculation of closed contours, approximation of found contours by ellipses and calculation of ellipse parameters. The system has an algorithm for self-diagnosis and response to external conditions. Different solutions of the sampling system are given for two different forms of a fertilizer flow (on a conveyor belt and in a closed pipe) and they statistical characteristics (mean and standard deviation) were calculated. The obtained results are compared with similar laboratory granulometric composition control devices (Camsizer P4).
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