Fuzzy Logic Approach for Modeling of Heating and Scale Formation in Industrial Furnaces

Heating steel charges is essential for proper charge formation. At the same time, it is a highly energy-intensive process. Limiting the scale formed is critical for reducing heat consumption in this process. This paper applies fuzzy logic to model heating and scale formation in industrial re-heating...

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Bibliographic Details
Published in:Materials 2024-11, Vol.17 (21), p.5355
Main Authors: Krzywanski, Jaroslaw, Boryca, Jaroslaw, Urbaniak, Dariusz, Otwinowski, Henryk, Wylecial, Tomasz, Sosnowski, Marcin
Format: Article
Language:English
Subjects:
Consumption
Current carriers
Efficiency
Energy consumption
Energy industry
Furnaces
Fuzzy algorithms
Fuzzy logic
Fuzzy systems
Heat conductivity
Heat detection
Heat transfer
Heating furnaces
Hot rolling
Hot rolling mills
Mathematical models
Oxidation
Pump jacks
Scale formation
Steel production
Temperature
Thickness measurement
Walking beam furnaces
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Summary:Heating steel charges is essential for proper charge formation. At the same time, it is a highly energy-intensive process. Limiting the scale formed is critical for reducing heat consumption in this process. This paper applies fuzzy logic to model heating and scale formation in industrial re-heating furnaces. Scale formation depends on the temperature of the initial charge, heating time, excess air coefficient value, and initial scale thickness. These parameters were determined based on experimental tests, which are also the inputs in the model of the analyzed process. The research was carried out in walking beam furnaces operating in hot rolling mill departments. To minimize the excess energy consumption for heating a steel charge in an industrial furnace before forming, a heating and scale formation (HSF) model was developed using the fuzzy logic-based approach. The developed model allows for the prediction of the outputs, i.e., the charge's final surface temperature and the scale layer's final thickness. The comparison between the measured and calculated results shows that the model's accuracy is acceptable.
ISSN:1996-1944
1996-1944
DOI:10.3390/ma17215355