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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">blackmet</journal-id><journal-title-group><journal-title xml:lang="ru">Известия высших учебных заведений. Черная Металлургия</journal-title><trans-title-group xml:lang="en"><trans-title>Izvestiya. Ferrous Metallurgy</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">0368-0797</issn><issn pub-type="epub">2410-2091</issn><publisher><publisher-name>National University of Science and Technology "MISIS"</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.17073/0368-0797-2021-5-374-381</article-id><article-id custom-type="elpub" pub-id-type="custom">blackmet-2108</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>ИНФОРМАЦИОННЫЕ ТЕХНОЛОГИИ И АВТОМАТИЗАЦИЯ В ЧЕРНОЙ  МЕТАЛЛУРГИИ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>INFORMATION TECHNOLOGIES AND AUTOMATIC CONTROL IN FERROUS METALLURGY</subject></subj-group></article-categories><title-group><article-title>Статистическое моделирование температурных режимов работы нагревательных печей листовых станов горячей прокатки</article-title><trans-title-group xml:lang="en"><trans-title>Statistical modeling of temperature operating modes of heating furnaces for hot strip mills</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Богатова</surname><given-names>М. Ж.</given-names></name><name name-style="western" xml:lang="en"><surname>Bogatova</surname><given-names>M. Zh.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Майя Жемлейловна Богатова, аспирант кафедры энергоэффективных и ресурсосберегающих промышленных технологий</p><p>119049, Москва, Ленинский пр., 4)</p></bio><bio xml:lang="en"><p>Maiya Zh. Bogatova, Postgraduate of the Chair “Energy-Efficient and Resource-Saving Industrial Technologies”</p><p>4 Leninskii Аve., Moscow 119049</p></bio><email xlink:type="simple">ma95bers@gmail.com</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Чибизова</surname><given-names>С. И.</given-names></name><name name-style="western" xml:lang="en"><surname>Chibizova</surname><given-names>S. I.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Светлана Игоревна Чибизова, кандидат технических наук, доцент кафедры энергоэффективных и ресурсосберегающих промышленных технологий</p><p>119049, Москва, Ленинский пр., 4)</p></bio><bio xml:lang="en"><p>Svetlana I. Chibizova, Cand. Sci. (Eng.), Assist. Prof. of the Chair “Energy-Efficient and Resource-Saving Industrial Technologies”</p><p>4 Leninskii Аve., Moscow 119049</p></bio><email xlink:type="simple">s_kalimulina@mail.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Национальный исследовательский технологический университет «МИСиС»</institution><country>Россия</country></aff><aff xml:lang="en"><institution>National University of Science and Technology “MISIS”</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2021</year></pub-date><pub-date pub-type="epub"><day>03</day><month>06</month><year>2021</year></pub-date><volume>64</volume><issue>5</issue><fpage>374</fpage><lpage>381</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Богатова М.Ж., Чибизова С.И., 2021</copyright-statement><copyright-year>2021</copyright-year><copyright-holder xml:lang="ru">Богатова М.Ж., Чибизова С.И.</copyright-holder><copyright-holder xml:lang="en">Bogatova M.Z., Chibizova S.I.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://fermet.misis.ru/jour/article/view/2108">https://fermet.misis.ru/jour/article/view/2108</self-uri><abstract><p>В статье предложен способ совершенствования тепловой работы нагревательных печей с шагающими балками станов горячей прокатки при помощи статистической математической модели нагрева металла. Объектом исследования является тепловая работа методической печи с шагающими балками для нагрева слябов перед прокаткой. Предметом исследования – статистическое моделирование нагрева металла в печи данного типа. Создание статистической математической модели основано на отборе факторов, построении регрессионной модели, корреляционном анализе и оценке значимости переменных, построении регрессионной модели с учетом скорректированных факторов, получении уравнений регрессии. На базе результатов, полученных в ходе проведения 15 автоматизированных направленных промышленных экспериментов на методических печах станов горячей прокатки российских металлургических предприятий, разработана статистическая модель, описывающая с допустимой точностью процесс нагрева стальных заготовок. Проведена адаптация статистической модели с использованием результатов промышленных экспериментов. Приведены графики сравнения реальных температурных значений и температур, рассчитанных на основании штатной математической и разработанной статистической модели для одного из экспериментов. Проведен расчет погрешностей созданной модели. Сформулированы основные выводы, базирующиеся на результатах проделанного исследования. Впервые в металлургической практике разработана статистическая модель, описывающая процесс нагрева металла в пятизонной методической печи листового стана горячей прокатки с восемью нагревательными подзонами. Поскольку функция регрессии определена, интерпретирована и обоснована, и оценка точности регрессионного анализа соответствует требованиям, можно считать, что построенная модель и прогнозные значения обладают достаточной надежностью.</p></abstract><trans-abstract xml:lang="en"><p>The article provides a method of mathematical modeling to improve temperature operating modes of heating furnaces for hot strip mills. The object of the research is the thermal operation of a continuous walking beam furnace for heating slabs before rolling. The subject of the research is statistical modeling of metal heating in furnaces of this type. The creation of a statistical model consists of factors selection, construction of regression model, correlation analysis and assessment of the variables signiﬁcance, adjustment of factors and obtaining regression equations. The main part of the research refers to a statistical model based on a comprehensive analysis. This model is based on the results of 15 automated industrial experiments on Russian heating furnaces of hot strip mills and describes the heating process in walking-beam furnace with acceptable accuracy. The adaptation of the statistical model and error calculation has been carried out. The article contains graphs comparing real temperatures and temperatures calculated on the basis of mathematical and statistical models for one of the experiments. The main conclusions are formulated based on the results of the research done. For the ﬁrst time in metallurgical practice, a statistical model has been developed that describes the process of metal heating in a ﬁve-zone continuous furnace with eight heating subzones. Since the regression function is deﬁned, interpreted and justiﬁed, and the assessment of the accuracy of the regression analysis meets the requirements, it can be assumed that the model and predicted values have suﬃcient reliability.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>математическая модель</kwd><kwd>статистическая модель</kwd><kwd>направленный промышленный эксперимент</kwd><kwd>нагревательная печь с шагаю- щими балками</kwd><kwd>система мониторинга</kwd><kwd>температурный режим</kwd><kwd>совершенствование тепловой работы</kwd></kwd-group><kwd-group xml:lang="en"><kwd>mathematical model</kwd><kwd>statistical model</kwd><kwd>directed industrial experiment</kwd><kwd>walking-beam heating furnace</kwd><kwd>monitoring system</kwd><kwd>temperature mode</kwd><kwd>thermal operation improvement</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Беленький А.М., Бурсин А.Н., Улановский А.А., Чибизова С.И. 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