Mathematical modeling of technological process in formalin production

Improvement and modernization of the technological process of polyvinyl chloride production requires the appropriate development of computer modelling systems, which ensure the following: identification and maintenance of optimal modes of technological processes that contribute to continuous operation, as well as the use of intelligent systems of modelling and control of technological devices. The article proposes pressure-dependent control of the temperature in the reactor, which affects the quality indicators of the technological process, using the cascade control method during the production of polyvinyl chloride. In this work an imitation model of the technological process was developed.

Section: Methodsmentioning

confidence: 99%

Control of reactor temperature and pressure using cascade control during polyvinyl chloride production

Kadirov,

Boeva,

Eshqobilov

et al. 2023

“…FAHL 04103 04603 devices and locally installed FI 04103 04603 devices monitor the flow of caustic soda solution into the electrolyzers. From the anode compartment with a temperature of no more than 90 ° C comes out: anod -a weak saline solution, with a mass concentration of sodium chloride g/dm 3 and wet chlorine gas. From the cathode compartment with a temperature of no more than 90 °C comes out: catod -a solution of caustic soda with a mass fraction of sodium hydroxide (31-32) % and hydrogen gas.…”

Section: Neural Network Controllermentioning

confidence: 99%

Intellectual control of the electrolysis process in the production of caustic soda

Yusupbekov,

Sattarov,

Akhmatov

et al. 2024

This article is based on the modeling of the operating mode of the membrane electrolyzer in the production of caustic soda through a neural network. In the course of work, a neural network model of the operation of the electrolyzer element was developed. Neural network software was used to create and train neural networks. The purpose of this work is to create an accurate model of the electrolyzer element using the following tasks was to create: the process of designing optimal structures of neural networks and their training, creating an electrolyzer model by training neural networks, as well as processing the modeling results. As a result of this work, a neural network model was developed, which allows to quickly and accurately calculate the result of the operation of the electrolyzer under any initial conditions.

“…Thus, the statement about the need to create a database for all available coals and the development of an algorithm for using this database to configure detectors can be considered fair. The next step in creating an artificial intelligence system to prevent spontaneous combustion of coal should be the organization of information exchange between producers, consumers, coal custodians and other interested enterprises [26][27][28][29][30][31][32][33][34][35][36][37].…”

Section: System For the Prevention Of Spontaneous Combustion Of Coal ...mentioning

confidence: 99%

Use of artificial intelligence to prevent spontaneous combustion of coal

Timofeeva,

Smirnov,

Boboev

et al. 2023

The expediency of using artificial intelligence has been repeatedly confirmed by successful practical solutions in various fields of human activity, including in the field of security. The article considers the possibility of creating a distributed artificial intelligence system designed to prevent spontaneous combustion of coal in the places of its extraction, storage, transportation, as well as processing or burning. The system is a software and hardware complex, which includes research laboratories, equipment manufacturers and protected facilities. The algorithm of operation of both the system as a whole and its individual elements is proposed. The algorithm of operation of individual elements is based on the design of a specialized fire detector developed and patented by the authors and in accordance with the laws of the development of the processes of selfheating and spontaneous combustion of coal.