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Industrial Automatic Control Systems and Controllers

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Development of a Neural Network to Control the Synthesis Process of the Stabilizer VS-1 and Octophore-N Using a Virtual Analyzer
Ye.A. Muraveva, A.V. Buzaev, A.I. Nikolaeva

Importance. At the moment, the control system of the synthesis node of the VS-1 stabilizer and the octophore-N in the open joint stock company «Synthesis-Rubber» is built mainly on devices and automation tools that are morally and technically outdated, which do not allow full control of the technological process. The quality of stabilizer synthesis is controlled by sampling, which does not allow continuous monitoring of the results obtained. During the development of the project, it is planned to replace outdated sensors and automation tools in order to improve the accuracy and reliability of the process.
The introduction of automatic quality control by continuously measuring the concentration of urotropin in alkylphenol at the stages of the process will increase the degree of automation and reduce the risks of obtaining a low-quality product [1].
Synthesis of the BC-1 stabilizer and octophore-N is an important node in the production, the BC-1 stabilizer, which is a solution of an aminophenol-type stabilizer in mineral oil, is used as an antioxidant of oil-filled styrene-butadiene (alphamethyl styrene) rubbers. The quality of synthesis directly aff ects the quality of the resulting rubber.
Objectives. During the development of the project, it is necessary to investigate the mathematical model of the virtual analyzer and design its working model based on known production data. Based on the concentration of urotropin in alkylphenol calculated by the virtual analyzer, as well as other technological parameters, such as synthesis temperature and urotropin consumption, it is necessary to develop a neural network to regulate these parameters. The resulting models will increase the degree of automation and control of the technological process.
Methods. In the process of studying the problem of improving the quality of the resulting product during the synthesis of the VS-1 stabilizer and the octophore-N, methods of studying the mathematical model of the virtual analyzer and designing its working model in the Simulink Matlab environment were used.
Results. As a result of the project, a virtual analyzer was developed that continuously predicts the process quality indicator in the form of a mass fraction of urotropin after synthesis and a neural network for regulating the technological parameters of the synthesis of the VS-1 stabilizer and the octophore-N.
Conclusions. It is concluded that the combined work of the virtual analyzer and the neural network allows to improve the quality of the technological process, as well as the degree of its automation.
Keywords: analyzer, virtual, network, neural network, synthesis.


DOI: 10.25791/asu.8.2022.1379

Pp. 12-20.

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