Using artificial intelligence elements in research of physical and chemical processes of production of converter steel
The article is devoted to the presentation of the results of applying the methods of mathematical statistics to establish the possibility of calculating the carbon content in a metal melt after oxygen conversion of cast iron in converters with a capacity of 300 tons with combined blowing. The creati...
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| Format: | Article |
| Language: | English |
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LTD “Pro Format”
2020-01-01
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| Series: | Металл и литье Украины |
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| Online Access: | https://steelcast.com.ua/en/article/using-artificial-intelligence-elements-research-physical-and-chemical-processes-production |
| _version_ | 1818282316926025728 |
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| author | V.I. Bondar S.G. Mel’nik |
| author_facet | V.I. Bondar S.G. Mel’nik |
| author_sort | V.I. Bondar |
| collection | DOAJ |
| description | The article is devoted to the presentation of the results of applying the methods of mathematical statistics to establish the possibility of calculating the carbon content in a metal melt after oxygen conversion of cast iron in converters with a capacity of 300 tons with combined blowing. The creation of converter smelting control systems depends on the search for adequate
models that take into account the patterns of steelmaking processes. For the full computerization of converter smelting, it is necessary that the found models predict the output with a minimum error.
In order to assess the influence of technological parameters and the chemical composition of the metal melt on the decarburization of the melt, methods of mathematical statistics were used to process the input data. To achieve this goal, we used the StatSoftStatistica 10 application software package, namely, modules for descriptive statistics, correlation and nonlinear
regression analysis. The use of elements of artificial intelligence in solving the problem allowed obtaining an algorithm that provides a gradual transition from a linear model to non-linear model. The preference of the latter is proved. As a result, it was possible to propose for practical use a regression equation of the power series, reduced to a linear form and allowing
calculating the carbon content in the melt after completion of the oxygen conversion action. The adequacy of the equation and the significance of the regression coefficients are confirmed, including the analysis of residues. The latter behave rather randomly, and there is no regularity in the alternation of their signs. In this case, the absolute error in determining the carbon content in the melt does not exceed 5 % level. For the practical use of the obtained equation, measurements of the oxidation of the melt in the converter with an available lance probe are sufficient. |
| first_indexed | 2024-12-13T00:19:05Z |
| format | Article |
| id | doaj.art-456e4f5890c74f6287a6b32db22aa959 |
| institution | Directory Open Access Journal |
| issn | 2077-1304 2706-5529 |
| language | English |
| last_indexed | 2024-12-13T00:19:05Z |
| publishDate | 2020-01-01 |
| publisher | LTD “Pro Format” |
| record_format | Article |
| series | Металл и литье Украины |
| spelling | doaj.art-456e4f5890c74f6287a6b32db22aa9592022-12-22T00:05:41ZengLTD “Pro Format”Металл и литье Украины2077-13042706-55292020-01-01281242910.15407/steelcast2020.01.024Using artificial intelligence elements in research of physical and chemical processes of production of converter steelV.I. Bondar0S.G. Mel’nik1Priazov State Technical University (Mariupol, Ukraine)Priazov State Technical University (Mariupol, Ukraine)The article is devoted to the presentation of the results of applying the methods of mathematical statistics to establish the possibility of calculating the carbon content in a metal melt after oxygen conversion of cast iron in converters with a capacity of 300 tons with combined blowing. The creation of converter smelting control systems depends on the search for adequate models that take into account the patterns of steelmaking processes. For the full computerization of converter smelting, it is necessary that the found models predict the output with a minimum error. In order to assess the influence of technological parameters and the chemical composition of the metal melt on the decarburization of the melt, methods of mathematical statistics were used to process the input data. To achieve this goal, we used the StatSoftStatistica 10 application software package, namely, modules for descriptive statistics, correlation and nonlinear regression analysis. The use of elements of artificial intelligence in solving the problem allowed obtaining an algorithm that provides a gradual transition from a linear model to non-linear model. The preference of the latter is proved. As a result, it was possible to propose for practical use a regression equation of the power series, reduced to a linear form and allowing calculating the carbon content in the melt after completion of the oxygen conversion action. The adequacy of the equation and the significance of the regression coefficients are confirmed, including the analysis of residues. The latter behave rather randomly, and there is no regularity in the alternation of their signs. In this case, the absolute error in determining the carbon content in the melt does not exceed 5 % level. For the practical use of the obtained equation, measurements of the oxidation of the melt in the converter with an available lance probe are sufficient.https://steelcast.com.ua/en/article/using-artificial-intelligence-elements-research-physical-and-chemical-processes-productionmetal meltconverter smeltingregression analysismodeladequacysignificancerelative error |
| spellingShingle | V.I. Bondar S.G. Mel’nik Using artificial intelligence elements in research of physical and chemical processes of production of converter steel Металл и литье Украины metal melt converter smelting regression analysis model adequacy significance relative error |
| title | Using artificial intelligence elements in research of physical and chemical processes of production of converter steel |
| title_full | Using artificial intelligence elements in research of physical and chemical processes of production of converter steel |
| title_fullStr | Using artificial intelligence elements in research of physical and chemical processes of production of converter steel |
| title_full_unstemmed | Using artificial intelligence elements in research of physical and chemical processes of production of converter steel |
| title_short | Using artificial intelligence elements in research of physical and chemical processes of production of converter steel |
| title_sort | using artificial intelligence elements in research of physical and chemical processes of production of converter steel |
| topic | metal melt converter smelting regression analysis model adequacy significance relative error |
| url | https://steelcast.com.ua/en/article/using-artificial-intelligence-elements-research-physical-and-chemical-processes-production |
| work_keys_str_mv | AT vibondar usingartificialintelligenceelementsinresearchofphysicalandchemicalprocessesofproductionofconvertersteel AT sgmelnik usingartificialintelligenceelementsinresearchofphysicalandchemicalprocessesofproductionofconvertersteel |