Управление качеством продуктов переработки зерна и зерномучных товаровThe article offers a comprehensive study of the technological properties of wheat grain affecting the quality of pasta products. The developed system of grinding process monitoring allows determining the parameters of grinding in real time mode, and predicting and controlling the quality of grain processing and grain products due to a kind of feedback. Samples of wheat of different varieties were chosen as the objects of research. Fractographic analysis was used to examine wheat grinding that allowed considering not only the linear dimensions of the grinding particles, but also their shape features. Well-known technique based on computer-vision algorithms was used. The characteristic of the basic analysis parameters is given. Analysis accuracy is provided by taking into account at least 5000 grinded particles. Discovered relationships and developed mathematical model for data analysis allow rapid assessment of grain characteristics of grain, flour and finished products for both research and practical purposes.

The paper describes an automatic system for controlling and assessing the technological properties of grain processing products during milling by computer vision methods. Optimal technological characteristics of the system are empirically established ensuring its maximum efficiency. The combined action of electrostatic fields (with voltage of 24 kV) and vibration (with frequency of 45 Hz) in the assembled testbed allows negating the conglomeration of grain milled particles. Such fast estimation of the technological properties of grain processing products allows interrupting and correcting the milling process for increased efficiency.

The article presents the results of a comparative assessment of the elasticity and rigidity of various morphological elements of wheat grain depending on the nature of the grain (normal, frosted, after drying, after scouring machines). The dependences of the rigidity of wheat grain on the structure, chemical composition and humidity are described. A close correlation was revealed between the structural and mechanical properties of wheat, assessed by microhardness, strength index, and the results of laboratory and industrial grinding of wheat grains of various consistencies. For different consistency of wheat grain, microhardness was determined using the microhardometer “Miniload”, and the strength index was determined using the Brabender’s hardness tester. At relatively low stresses, the shells have flexural elasticity. IT was detected that with increasing humidity, the rigidity of the shells during bending decreases. It was found that for hard and hard-grained varieties of soft wheat, the compression force is required 2-4 times more than for soft-grained varieties. It is shown that the microhardness of glassy grains of hard-grained and soft-grained wheat varieties is basically at the same level. At the same time, with increasing humidity, the microhardness of the grain decreases regardless of the variety, area of growth and vitrescence of wheat.

The paper discusses the basic operation principles of information-measuring systems for optimization wheat grain processing. The quality of grain processing products (cereals, flour, etc.) is influenced by both weather and climatic factors and grinding technologies. The modern development of information technologies makes it possible to modernize the existing information-measuring systems for grain processing and create new ones through the development of algorithms for analyzing the physical characteristics of the grain mass. During the study, test grinding of wheat grains of different varieties was carried out in a laboratory mill. To increase the yield of the finished product, digitalization of the selection of optimal grain separation modes was used. The obtained mathematical models allow predicting the quality of grain separation in separators of various types. The digitalization of the grain processing industry includes the use of artificial neural networks to analyze images of the grain mass using computer vision algorithms. It is promising to increase the information content of granulometric analysis using modern intelligent (information-measuring) systems. For the classification of wheat according to the milling properties, it is proposed to use the grain hardness. The studies used computer vision and artificial neural networks to find and organize the particles of grain grinding by geometric properties. The characteristics of the contours of the images of the grinding particles were taken into account. The values obtained by the developed information-measuring system were compared with that obtained using the Russian State Standard GOST methods. The error in assessing the grain hardness by the new method does not exceed 3.5%. The use of modern information tools allows improving the quality of wheat grain processing.

No abstract