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Proposal of a Method for Measuring Gas Flow in a Heating Furnace: A Simulation Study

Pástor Marcel, Durdán Milan, Kačur Ján, Laciak Marek, Flegner Patrik

Advances in Science and Technology. Research Journal

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2021

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Vol. 15, no 2

1--12

EN

Metallurgy, as one of the oldest industries, is currently experiencing a technological boom in an effort to increase production efficiency with the least possible impact on the environment. Modeling methods make it possible to design and simulate a technological process or technological equipment for conditions that take into account the above-mentioned aspects. For this reason, the article focuses on the use of simulation modeling using accessible computer technologies in order to improve the operation of heating aggregates with the metal-bearing batch, such as a continuous heating furnace. The paper describes the methodology for modeling the flow of flue gases in the working space of a gas heating furnace, which results in their enthalpy representation. A simulation study was performed for a gas-fired furnace used to heat gates. Three case studies were simulated with set values of on and off burners and fuel flow to them. The effect of these parameters on the total amount of recirculated flue gas was investigated. The results showed that the fuel flow regulation to the burners at the material inlet into the furnace had a higher effect on the overall recirculation than the switching on and off the burners on the furnace's outlet side. The results pointed to critical points on the inner shell of the furnace, which could be the most critically thermally stressed, for example, in the places of the collision of opposing flue gas flows.

2

Heuristic Adaptive Control of Waste Gas Exhausting in Coke Making

Kačur Ján, Flegner Patrik, Durdán Milan, Laciak Marek

Advances in Science and Technology. Research Journal

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2020

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Vol. 14, no 4

195--212

EN

Stabilization of the carbon monoxide (CO) in the waste gas is a common technical problem in many industrial plants. Stabilization can be performed continuously by regulating the fuel input or by regulating the exhaust gas draught. This paper proposes an adaptive control system for CO stabilization in waste gases based on a discrete controller. Heuristic adaptation of a discrete controller is based on continuous optimization of controller parameters. The advantage of this solution is that the control system does not need to perform the identification of the controlled system repeatedly. The parameters of the controller are dynamically optimized during the production process. By regulating the under-pressure, we change the amount of air supplied to the combustion chambers, which affects the combustion of gaseous fuel and also the concentration of CO in the waste flue gas. The control algorithm was verified for the combustion process in coke making. The proposed control achieved good stabilization quality when verified in simulation and also in an industry operation. The CO level at which the waste gas temperature was highest was selected as the setpoint. It was found that the stabilization of CO in waste gas to lower values is possible to achieve higher waste gas temperature and by that, higher temperatures in heating chambers.

3

Soft-Sensing in Batch Annealing Based on Finite Differential Method and Support Vector Regression

Kačur Ján, Durdán Milan, Laciak Marek, Flegner Patrik

Advances in Science and Technology. Research Journal

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2019

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Vol. 13, no 4

70--86

EN

The temperature of annealed steel coils is a determining variable of the future steel sheets quality. This variable also determines the energy consumption in operation. Unfortunately, the monitoring of coil inner temperature is problematic due to the furnace environment with high temperature, coil structure, and annealing principle. Currently, there are no measuring principles that can measure the temperature inside the heat-treated product in a non-destructive manner. In this paper, the soft sensing of inner temperature based on the theory of non-stationary heat conduction and approach based on Support Vector Regression (SVR) was presented. The results showed that a black-box approach based on the SVR could replace an analytic approach, though with lesser performance. Several annealing experiments were performed to create a training data set and model performance improvement in the estimation of inner coil temperatures. The proposed software based on non-stationary heat conduction can calculate the behavior of inner coil temperature from the measured boundary temperatures that are measured by thermocouples. The soft-sensing principles presented in this paper were verified under laboratory conditions and on the data obtained from a real annealing plant.