Видання НТУ "ХПІ"
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Документ Intelligent models for control of jet hydro-processing of rolled steel defects(Національний технічний університет "Харківський політехнічний інститут", 2023) Ilyunin, O.; Khodak, M.; Pyrohov, V.; Pasholoc, O.; Tryhuba, M.; Serdiuk, S.The structure of an intelligent control system for the hydro-processing of surface defects in rolled products is presented, which corresponds to the concept of the European program "Industry 4.0" in the direction of energy saving and total automation of processes. The considered local RBNN hydro-processing models are tuned using the KaczmarzWidrow-Hoff algorithm. The model for identifying the current task of the pressure of the processing fluid takes into account the relationship between the thickness of the processed defect, changes in the composition of the working fluid and, as a result, its abrasive properties. To form a given pressure in the corresponding jet, the following neural model estimates the duration and polarity of the voltage that controls the electric drive of the jet control valve in real time. The small-dimensional models’ conveyor is a promising solution for controlling waterjet processing of metals in such areas as rounding sharp edges; grinding and polishing complex surfaces; deburring and cleaning of welds; surface preparation for coating; removal of defects from the surface; high-precision waterjet cutting of metals. The solution will increase the speed of TP from 1.2 to 1.96 [m/s]. Taking into account the small dimensions of the models and the relatively low speed of the TP, a software application based on the proposed models can be implemented in the control system for the hydro-processing of rolled metal products in the form of an inexpensive IIOT microcontroller module.Документ Fuzzy estimation procedure of the concentration of the components of a sulfuric acid pickling solution(Національний технічний університет "Харківський політехнічний інститут", 2022) Ilyunin, O.; Khodak, M.; Yurchenko, O.; Sapeha, O.The article is devoted to the issue of determining the level of concentration of individual components of working solutions. The relevance of the topic lies in the fact that some impurities in solutions (for example, when pickling steel) cannot be measured automatically, which reduces the efficiency of the process and increases the load on the solution regeneration section. Also, impurities are hazardous waste for the environment and humans. The development of a method for the operational control of the composition of the pickling solution components in pickling baths is the main task of the work. A detailed substantiation of the choice of the mathematical apparatus of the method is given. The process of fuzzy identification of the composition of the components is carried out by the number of pixels with certain digital color RGB codes from digital images of the control doses of the solution. A set of technical means for providing the method for practical implementation in the technological process is described. A prototype of a graphical user interface (GUI) for the proposed method for identifying the composition of technological liquid solutions, developed in the Processing 3.0 integrated environment using applications from the Open Source Computer Vision Library, is presented. A technique for extracting experimental data for filling the base of a fuzzy classifier with model reference points is proposed. Its essence lies in simultaneous measurements of the concentration of the components of the pickling solution by classical methods of titration and dry residues and the proposed method with a step equal to the regulated accuracy. The results of approbation of the proposed method are presented. The presented technique for obtaining a fuzzy classifier can be used to develop IT tools for the operational control of the composition of various liquid solutions with opaque colored components and color dentification of defects in various flat surfaces, provided that they are color distinguishable and determine the boundaries of RGB - intervals for assessing the color of individual component (defects).