Abstract
The article presents the basics of the functioning of information and measurement systems for optimizing the process of processing wheat grain. The quality of grain processing products is influenced by climatic factors and grinding technologies. The modern development of information technology makes it possible to modernize information and measurement systems for grain processing and developing algorithms for analyzing the grain physical characteristics. Trial grinding of wheat grains by different varieties was carried out at a laboratory mill. The obtained mathematical models made it possible to predict the quality of grain separation in separators. Digitalization of the grain processing industry includes the use of artificial neural networks for the analysis of images of grain mass by computer vision algorithms using the developed software. It is promising to increase the information content of granulometric analysis through the use of modern intelligent systems. To classify wheat by milling properties, it is proposed to use the grain hardness index. Computer vision and artificial neural networks were used to find and systematize grain grinding particles according to geometric properties. The error of the estimation for the hardness is no more than 3.5 %.
Information technologies for the modernization of the grain raw separation
