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<article 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" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" article-type="other" dtd-version="1.2" xml:lang="en"><front><journal-meta><journal-id journal-id-type="publisher-id">Frontier Materials &amp; Technologies</journal-id><journal-title-group><journal-title xml:lang="en">Frontier Materials &amp; Technologies</journal-title><trans-title-group xml:lang="ru"><trans-title>Frontier Materials &amp; Technologies</trans-title></trans-title-group></journal-title-group><issn publication-format="print">2782-4039</issn><issn publication-format="electronic">2782-6074</issn><publisher><publisher-name xml:lang="en">Togliatti State University</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="publisher-id">427</article-id><article-id pub-id-type="doi">10.18323/2782-4039-2022-2-74-83</article-id><article-categories><subj-group subj-group-type="toc-heading" xml:lang="en"><subject>Articles</subject></subj-group><subj-group subj-group-type="toc-heading" xml:lang="ru"><subject>Статьи</subject></subj-group><subj-group subj-group-type="article-type"><subject></subject></subj-group></article-categories><title-group><article-title xml:lang="en">Identification of deformations of cylindrical specimens by optical method using the technique of digital image correlation</article-title><trans-title-group xml:lang="ru"><trans-title>Определение деформаций цилиндрических образцов оптическим способом с использованием метода цифровой корреляции изображений</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-6298-1068</contrib-id><name-alternatives><name xml:lang="en"><surname>Rastorguev</surname><given-names>Dmitry A.</given-names></name><name xml:lang="ru"><surname>Расторгуев</surname><given-names>Дмитрий Александрович</given-names></name></name-alternatives><address><country country="RU">Russian Federation</country></address><bio xml:lang="en"><p>PhD (Engineering), assistant professor of Chair “Equipment and Technologies of Machine Building Production”</p></bio><bio xml:lang="ru"><p>кандидат технических наук, доцент кафедры «Оборудование и технологии машиностроительного производства»</p></bio><email>rast_73@mail.ru</email><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-0397-4009</contrib-id><name-alternatives><name xml:lang="en"><surname>Semenov</surname><given-names>Kirill O.</given-names></name><name xml:lang="ru"><surname>Семенов</surname><given-names>Кирилл Олегович</given-names></name></name-alternatives><address><country country="RU">Russian Federation</country></address><bio xml:lang="en"><p>postgraduate student of Chair “Equipment and Technologies of Machine Building Production”</p></bio><bio xml:lang="ru"><p>аспирант кафедры «Оборудование и технологии машиностроительного производства»</p></bio><email>semen-tgu@yandex.ru</email><xref ref-type="aff" rid="aff1"/></contrib></contrib-group><aff-alternatives id="aff1"><aff><institution xml:lang="en">Togliatti State University, Togliatti</institution></aff><aff><institution xml:lang="ru">Тольяттинский государственный университет, Тольятти</institution></aff></aff-alternatives><pub-date date-type="pub" iso-8601-date="2022-06-30" publication-format="electronic"><day>30</day><month>06</month><year>2022</year></pub-date><issue>2</issue><issue-title xml:lang="en"/><issue-title xml:lang="ru"/><fpage>74</fpage><lpage>83</lpage><history><date date-type="received" iso-8601-date="2022-06-30"><day>30</day><month>06</month><year>2022</year></date></history><permissions><ali:free_to_read xmlns:ali="http://www.niso.org/schemas/ali/1.0/"/></permissions><self-uri xlink:href="https://vektornaukitech.ru/jour/article/view/427">https://vektornaukitech.ru/jour/article/view/427</self-uri><abstract xml:lang="en"><p>A provision of location tolerances and their retention in the postoperative period is one of the main hard-hitting process tasks when producing long-length low-rigidity shaft-type parts. Mixed treatment – tensile straightening or thermal-power treatment is one of the technological methods intended to provide this group of geometrical indicators, including axle linearity. The efficiency improvement of this technology is impossible without knowing the features of the formation of plastic deformations distribution along the length of long-length blank parts. The paper considers the application of an optical method for controlling deformation on the surface using the method of digital image correlation at axial deformation of cylindrical parts. The work describes an experimental device for optic control of deformations when loading a specimen using digital cameras. The authors studied the influence of various modes of paint deposition to a sample (deposition rate, distance, deposition mode – continuous or pulsed) on the features of a produced speckle in the form of random distribution of mixed-size paint spots over the specimen surface; obtained histograms of the intensity distribution of various speckles. The authors carried out the experiments to identify deformations based on the technology of the local gradient digital image correlation method for the specimens of polymer tubes with different speckle types. The study identified the distribution of the deformation over the length of samples within the deformable area selected for analysis with the specified degree of smoothing provided by choice of correlation kernel size and the choice of its displacement step for fixing deformation processes with a precise error. The authors obtained distributions of axial deformations along the length of specimens and errors of deformations determination depending on a speckle nature. The study specifies necessary speckle parameters ensuring minimal error for long-length samples up to 200 mm in length and appropriate technology for paint depositing. It is a speckle with a wide range of spot sizes rarefied with their locations and the Gaussian filter image smoothing before the analysis.</p></abstract><trans-abstract xml:lang="ru"><p>Обеспечение допусков расположения и их сохранение в послеоперационный период является одной из основных и труднодостижимых технологических задач при изготовлении длинномерных маложестких деталей типа вал. Одним из технологических методов, направленных на обеспечение данной группы геометрических показателей, включая прямолинейность оси, является комбинированная обработка – правка растяжением или термосиловая обработка. Повышение эффективности данной технологии невозможно без знания особенностей формирования распределения пластических деформаций по длине длинномерных заготовок. В статье рассмотрено применение оптического способа контроля деформации по поверхности с использованием метода корреляции цифровых изображений при осевом деформировании цилиндрических образцов. Приведено описание экспериментальной установки для оптического контроля деформаций при нагружении образца с использованием цифровых камер. Исследовано влияние различных режимов нанесения краски на образец (скорость нанесения, расстояние, характер нанесения – непрерывный или импульсный) на особенности полученного спекла в виде случайного распределения пятен краски различного размера по поверхности образца. Получены гистограммы распределения яркости различных спеклов. Проведены эксперименты по определению деформаций на основе метода локального градиентного способа корреляции цифровых изображений для образцов из полимерных трубок с различным характером спекла. Определены распределения деформаций по длине для образцов по выбранной для анализа деформируемой области с заданной степенью сглаживания, обеспечиваемой выбором размера окна корреляции и выбором шага его смещения для фиксации деформационных процессов с определенной погрешностью. Получены распределения осевых деформаций по длине образцов и ошибки определения деформаций в зависимости от вида спекла. Определены необходимые параметры спекла, обеспечивающие минимальную погрешность для длинномерных образцов до 200 мм длиной, и соответствующая технология нанесения краски. Это спекл с широким диапазоном размеров пятен, разреженным их расположением и сглаживанием изображения фильтром Гаусса перед началом анализа.</p></trans-abstract><kwd-group xml:lang="en"><kwd>digital image</kwd><kwd>digital image correlation</kwd><kwd>correlation analysis</kwd><kwd>speckle</kwd><kwd>axial deformation</kwd><kwd>optical control</kwd></kwd-group><kwd-group xml:lang="ru"><kwd>цифровое изображение</kwd><kwd>цифровая корреляция изображений</kwd><kwd>корреляционный анализ</kwd><kwd>спекл</kwd><kwd>продольная деформация</kwd><kwd>оптический контроль</kwd></kwd-group><funding-group><funding-statement xml:lang="en">The study was financially supported by the Russian Foundation for basic Research within the scientific project No. 20-38-90148.</funding-statement><funding-statement xml:lang="ru">Исследование выполнено при финансовой поддержке РФФИ в рамках научного проекта № 20-38-90148.</funding-statement></funding-group></article-meta></front><body></body><back><ref-list><ref id="B1"><label>1.</label><citation-alternatives><mixed-citation xml:lang="en">Sciammarella C.A. 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