| Summary: | The article presents algorithms for the operation of an information and measurement system describing the technology of grinding wheat grain. The properties of grain processing products are determined by the influence of natural and climatic factors, and in addition by the method of grinding. The spread of information technologies has made it possible to improve the existing algorithms of information and measurement systems for wheat processing, as well as to form new processing methods due to a more accurate assessment of grain properties. Various wheat varieties were studied, trial grinds of which were produced at a laboratory mill. The increase in the output of industry enterprises is ensured by heuristic selection of the most accurate operating mode of separators of various types. Empirical models serve the purpose of predicting the quality indicators of grain mass after its separation. Digitalization of the grain industry has made it possible to improve the accuracy of granulometric analysis in the field of grain particle classification by shape and size. Artificial neural networks and technical vision algorithms as part of an intelligent system were used to process the appearance of grain after grinding. Appropriate software has been developed for this purpose. To divide wheat into classes, it is proposed to use grain hardness indicators. A systematic approach was used to detect and distribute grain particles after grinding according to geometric characteristics. A brief description of the algorithm of operation of such a system consists in finding the contours of crushed grain particles and measuring their size and shape. The accuracy of using such an intelligent system when measuring grain hardness in comparison with traditional methods, as experiments have shown, is less than 3.5%. The introduction of such intelligent systems at industrial facilities of the food industry will improve the quality of the enterprise and the output of finished products.
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