Abstract

The article is devoted to the development of a correction control algorithm by temperature mode of a periodic rubber mixing process for JSC Voronezh tire plant. The algorithm is designed to perform in the main controller a section of rubber mixing Siemens S7 CPU319F-3 PN/DP, which forms tasks for the local temperature controllers HESCH HE086 and Jumo dTRON304, operating by tempering stations. To compile the algorithm was performed a systematic analysis of rubber mixing process as an object of control and was developed a mathematical model of the process based on the heat balance equations describing the processes of heat transfer through the walls of technological devices, the change of coolant temperature and the temperature of the rubber compound mixing until discharge from the mixer chamber. Due to the complexity and nonlinearity of the control object – Rubber mixers and the availability of methods and a wide experience of this device control in an industrial environment, a correction algorithm is implemented on the basis of an artificial single-layer neural network and it provides the correction of tasks for local controllers on the cooling water temperature and air temperature in the workshop, which may vary considerably depending on the time of the year, and during prolonged operation of the equipment or its downtime. Tempering stations control is carried out by changing the flow of cold water from the cooler and on/off control of the heating elements. The analysis of the model experiments results and practical research at the main controller programming in the STEP 7 environment at the enterprise showed a decrease in the mixing time for different types of rubbers by reducing of heat transfer process control error.

Highlights

  • Вестник ВГУИТ/Proceedings of VSUET, No 2, 2016 temperature and air temperature in the workshop, which may vary considerably depending on the time of the year, and during prolonged operation of the equipment or its downtime

  • После расчёта динамических характеристик с учётом корректировки величины задания, выявлено снижение времени смешения резины благодаря достижению необходимых параметров процесса за более короткое время

  • CONFLICT OF INTEREST The authors declare no conflict of interest

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Summary

Для цитирования

D. Development of rubber mixing process mathematical model and synthesis of control correction algorithm by process temperature mode using an artificial neural network. Вестник ВГУИТ/Proceedings of VSUET, No 2, 2016 temperature and air temperature in the workshop, which may vary considerably depending on the time of the year, and during prolonged operation of the equipment or its downtime. The analysis of the model experiments results and practical research at the main controller programming in the STEP 7 environment at the enterprise showed a decrease in the mixing time for different types of rubbers by reducing of heat transfer process control error. ChertovDevelopment of rubber mixing process mathematical model and sy nthesis of control correction algorithm by process temperature mode using an artificial neural networ k

Введение и постановка задачи
Для осуществления влияния весовых коэффициентов на вырабатываемое корректирующее
Выводы и рекомендации
КРИТЕРИЙ АВТОРСТВА
Full Text
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