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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">zhps</journal-id><journal-title-group><journal-title xml:lang="ru">Журнал прикладной спектроскопии</journal-title><trans-title-group xml:lang="en"><trans-title>Zhurnal Prikladnoii Spektroskopii</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">0514-7506</issn><publisher><publisher-name>B. I. Stepanov Institute of Physics of the National Academy of Sciences</publisher-name></publisher></journal-meta><article-meta><article-id custom-type="elpub" pub-id-type="custom">zhps-1877</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>АННОТАЦИИ АНГЛОЯЗЫЧНЫХ СТАТЕЙ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>ABSTRACTS ENGLISH-LANGUAGE ARTICLES</subject></subj-group></article-categories><title-group><article-title>Комбинированный подход, основанный на совместном использовании лазерно-искровой эмиссионной спектроскопии, масс-спектрометрии и нейронных сетей, для контроля продуктов горения резины</article-title><trans-title-group xml:lang="en"><trans-title>Online in situ Diagnosis and Traceability of Rubber Combustion: Utilizing LIBS, Mass Spectrometry, and Machine Learning</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>Tian</surname><given-names>D.</given-names></name><name name-style="western" xml:lang="en"><surname>Tian</surname><given-names>D.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Хуайнань, Нанкин</p></bio><bio xml:lang="en"><p>Dongpeng Tian</p><p>Huainan, Nanjing</p></bio><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Chen</surname><given-names>G.</given-names></name><name name-style="western" xml:lang="en"><surname>Chen</surname><given-names>G.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Хуайнань</p></bio><bio xml:lang="en"><p>Gang Chen</p><p>Huainan, Nanjing</p></bio><email xlink:type="simple">chgmech@mail.ustc.edu.cn</email><xref ref-type="aff" rid="aff-2"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Zhou</surname><given-names>W.</given-names></name><name name-style="western" xml:lang="en"><surname>Zhou</surname><given-names>W.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Нанкин</p></bio><bio xml:lang="en"><p>Wentao Zhou</p><p>Nanjing</p></bio><xref ref-type="aff" rid="aff-3"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Li</surname><given-names>L.</given-names></name><name name-style="western" xml:lang="en"><surname>Li</surname><given-names>L.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Гуанчжоу</p></bio><bio xml:lang="en"><p>Lei Li</p><p>Guangzhou</p></bio><xref ref-type="aff" rid="aff-4"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Liu</surname><given-names>Y.</given-names></name><name name-style="western" xml:lang="en"><surname>Liu</surname><given-names>Y.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Хуайнань, Нанкин</p></bio><bio xml:lang="en"><p>Yuzhu Liu</p><p>Huainan, Nanjing</p></bio><email xlink:type="simple">yuzhu.liu@nuist.edu.cn</email><xref ref-type="aff" rid="aff-5"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Координационный инновационный центр горнодобывающей техники и электрооборудования провинции Аньхой (Аньхойский университет науки и технологий); Государственная лабораторная база по развитию атмосферного оптоэлектронного обнаружения и слияния информации, Центр совместных инноваций в области атмосферной среды и технологий оборудования провинции Цзянсу (CI-CAEET), Нанкинский университет информационных наук и технологий</institution></aff><aff xml:lang="en"><institution>Anhui Mining Machinery and Electrical Equipment Coordination Innovation Center (Anhui University of Science and Technology); State Key Laboratory Cultivation Base of Atmospheric Optoelectronic Detection and Information Fusion, Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology (CICAEET), Nanjing University of Information Science and Technology</institution></aff></aff-alternatives><aff-alternatives id="aff-2"><aff xml:lang="ru"><institution>Координационный инновационный центр горнодобывающей техники и электрооборудования провинции Аньхой (Аньхойский университет науки и технологий)</institution></aff><aff xml:lang="en"><institution>Anhui Mining Machinery and Electrical Equipment Coordination Innovation Center (Anhui University of Science and Technology)</institution></aff></aff-alternatives><aff-alternatives id="aff-3"><aff xml:lang="ru"><institution>Государственная лабораторная база по развитию атмосферного оптоэлектронного обнаружения и слияния информации, Центр совместных инноваций в области атмосферной среды и технологий оборудования провинции Цзянсу (CI-CAEET), Нанкинский университет информационных наук и технологий</institution></aff><aff xml:lang="en"><institution>State Key Laboratory Cultivation Base of Atmospheric Optoelectronic Detection and Information Fusion, Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology (CICAEET)</institution></aff></aff-alternatives><aff-alternatives id="aff-4"><aff xml:lang="ru"><institution>Институт масс-спектрометрии и атмосферной среды, Инженерный исследовательский центр распределения источников загрязнения воздуха в режиме реального времени провинции Гуандун, Университет Цзинань</institution></aff><aff xml:lang="en"><institution>Institute of Mass Spectrometer and Atmospheric Environment, Guangdong Provincial Engineering Research Center for On-line Source Apportionment System of Air Pollution, Jinan University</institution></aff></aff-alternatives><aff-alternatives id="aff-5"><aff xml:lang="ru"><institution>Координационный инновационный центр горнодобывающей техники и электрооборудования провинции Аньхой (Аньхойский университет науки и технологий); Государственная лабораторная база по развитию атмосферного оптоэлектронного обнаружения и слияния информации, Центр совместных инноваций в области атмосферной среды и технологий оборудования провинции Цзянсу (CI-CAEET), Нанкинский университет информационных наук и технологий; Международная объединенная лаборатория по метеорологической фотонике и оптоэлектронному обнаружению провинции Цзянсу, Нанкинский университет информационных наук и технологий</institution></aff><aff xml:lang="en"><institution>Anhui Mining Machinery and Electrical Equipment Coordination Innovation Center (Anhui University of Science and Technology); State Key Laboratory Cultivation Base of Atmospheric Optoelectronic Detection and Information Fusion, Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology (CICAEET), Nanjing University of Information Science and Technology; Jiangsu International Joint Laboratory on Meteorological Photonics and Optoelectronic Detection, Nanjing University of Information Science and Technology</institution></aff></aff-alternatives><pub-date pub-type="collection"><year>2025</year></pub-date><pub-date pub-type="epub"><day>20</day><month>05</month><year>2025</year></pub-date><volume>92</volume><issue>3</issue><fpage>417</fpage><lpage>417</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Tian D., Chen G., Zhou W., Li L., Liu Y., 2025</copyright-statement><copyright-year>2025</copyright-year><copyright-holder xml:lang="ru">Tian D., Chen G., Zhou W., Li L., Liu Y.</copyright-holder><copyright-holder xml:lang="en">Tian D., Chen G., Zhou W., Li L., Liu Y.</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://zhps.ejournal.by/jour/article/view/1877">https://zhps.ejournal.by/jour/article/view/1877</self-uri><abstract><p>На основе лазерно-искровой эмиссионной спектроскопии (LIBS) разработана система для диагностики и отслеживания процесса горения резины в режиме онлайн. В качестве образцов использованы стирол-бутадиеновый каучук, фторкаучук, силиконовый каучук, хлоропреновый каучук и натуральный каучук. По спектрам LIBS горения резины обнаруживаются металлы Ca, Mg и Na. Установлено, что образующийся дым содержит различные элементы для разных видов резины. Для обнаружения образующегося при горении резины дыма использована специально разработанная система масс-спектрометрии с одной частицей аэрозоля. Проведено сравнение данных масс-спектров и LIBS. Комбинированный подход, объединяющий LIBS с анализом главных компонент и нейронной сетью с обратным распространением ошибки, применен для эффективного обнаружения и идентификации различного дыма, а также отслеживания процесса горения резины. Точность идентификации достигает 94.00%. Сочетание LIBS и указанного алгоритма помогает повысить эффективность обработки большого количества спектральных данных. Проанализированы различия элементов резиновых пластин разных типов, подтверждена точность системы диагностики. Продемонстрированы возможности онлайн-диагностики in situ и изучения процесса горения резины с помощью LIBS, а также спектрального анализа для переработки резины различных типов.</p></abstract><trans-abstract xml:lang="en"><p>Аn online in situ detection system based on laser-induced breakdown spectroscopy (LIBS) is developed for the diagnosis and tracing of the rubber combustion process. The feasibility and accuracy of the system are verified by taking styrene-butadiene rubber, fluoro rubber, silicone rubber, chloroprene rubber, and natural rubber as samples. Metallic elements such as Ca, Mg, and Na are detected in the LIBS spectra of rubber combustion. The results show that the smoke produced contains different elements for different kinds of rubbers. Based on the self-developed single particle aerosol mass spectrometry system, the smoke produced by rubber combustion is detected by mass spectrometry. The mass spectrum data are compared and supplemented for LIBS spectral data. Then, the system, combining LIBS with principal component analysis and backpropagation artificial neural network, achieves efficient detection and identification of different rubber smoke, as well as tracking of the rubber combustion process. The identification accuracy reached 94.00%. The combination of LIBS and algorithm helps to improve the efficiency of processing a large amount of spectral information data. Furthermore, the element differences among various types of rubber slabs are analyzed, thereby validating the accuracy of the diagnosis and traceability system. The aforementioned results indicate that the online in situ diagnosis and traceability of the rubber in the combustion process with LIBS is feasible, and using spectral detection for different types of rubber recycling is also promising.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>лазерно-искровая эмиссионная спектроскопия</kwd><kwd>система масс-спектрометрии аэрозоля с одной частицей</kwd><kwd>горение резины</kwd><kwd>анализ главных компонент</kwd><kwd>нейронная сеть с обратным распространением ошибки</kwd></kwd-group><kwd-group xml:lang="en"><kwd>laser-induced breakdown spectroscopy</kwd><kwd>single particle aerosol mass spectrometry system</kwd><kwd>Rubber combustion</kwd><kwd>principal component analysis</kwd><kwd>backpropagation artificial neural network</kwd></kwd-group><funding-group><funding-statement xml:lang="ru">We would like to thank Miss Xiaomeng A for revising the article and Miss Junyi Zhu for assisting in drawing Fig. 1.</funding-statement><funding-statement xml:lang="en">We would like to thank Miss Xiaomeng A for revising the article and Miss Junyi Zhu for assisting in drawing Fig. 1.</funding-statement></funding-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">M. 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