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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">probener</journal-id><journal-title-group><journal-title xml:lang="ru">Известия высших учебных заведений. ПРОБЛЕМЫ ЭНЕРГЕТИКИ</journal-title><trans-title-group xml:lang="en"><trans-title>Power engineering: research, equipment, technology</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">1998-9903</issn><issn pub-type="epub">2658-5456</issn><publisher><publisher-name>Kazan State Power Engineering  University</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.30724/1998-9903-2026-28-3-112-127</article-id><article-id custom-type="elpub" pub-id-type="custom">probener-3914</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>ЭЛЕКТРОТЕХНИЧЕСКИЕ КОМПЛЕКСЫ И СИСТЕМЫ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>ELECTROTECHNICAL COMPLEXES AND SYSTEMS</subject></subj-group></article-categories><title-group><article-title>Оценка технического состояния электромеханической системы на основе вибрационных показателей в режиме пуска</article-title><trans-title-group xml:lang="en"><trans-title>Assessment of the technical condition of an electromechanical system based on vibration indicators in start-up mode</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-5801-7081</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Деркачёв</surname><given-names>С. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Derkachev</surname><given-names>Sergey V.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Деркачёв Сергей Владимирович – канд. техн. наук, ведущий научный сотрудник – руководитель молодежной научной лаборатории «Приборостроение и станкостроение»</p><p>г. Донецк</p></bio><bio xml:lang="en"><p>Donetsk</p></bio><email xlink:type="simple">sergey_derkachev@mail.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-6794-7838</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Сидоров</surname><given-names>В. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Sidorov</surname><given-names>Vladimir A.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Сидоров Владимир Анатольевич – д-р техн. наук, доцент, профессор кафедры «Механическое оборудование заводов чёрной металлургии» </p><p>г. Донецк</p></bio><bio xml:lang="en"><p>Donetsk</p></bio><email xlink:type="simple">sidorov_va58@mail.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Донецкий национальный технический университет</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Donetsk National Technical University</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2026</year></pub-date><pub-date pub-type="epub"><day>24</day><month>06</month><year>2026</year></pub-date><volume>28</volume><issue>3</issue><fpage>112</fpage><lpage>127</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Деркачёв С.В., Сидоров В.А., 2026</copyright-statement><copyright-year>2026</copyright-year><copyright-holder xml:lang="ru">Деркачёв С.В., Сидоров В.А.</copyright-holder><copyright-holder xml:lang="en">Derkachev S.V., Sidorov V.A.</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://www.energyret.ru/jour/article/view/3914">https://www.energyret.ru/jour/article/view/3914</self-uri><abstract><p>Развитие промышленного оборудования во многом обеспечивается использованием электромеханических систем, включающих приводной элемент – асинхронный двигатель. Техническое состояние электромеханической системы обеспечивает непрерывность и эффективность технологического процесса, что определяет актуальность применения различных методов диагностирования в практике эксплуатации. Проведенный краткий литературный обзор исследований в данном направлении указывает на общую тенденцию использования визуализации акустико-вибрационных сигналов, наряду с методами термографии для широкого применения. Известным фактом является то, что для диагностирования фактического состояния электромеханической системы высокой информативностью обладают переходные процессы. В проведенном исследовании оценка состояния проводилась на основе фиксации временных реализаций виброускорения в период запуска электромеханической системы (вентиляторного типа) в трех взаимно перпендикулярных плоскостях, что было реализовано с помощью прикладных программ к смартфону. В результате сформулированы основные признаки проявления неисправностей электрической и механической частей электромеханической системы при измерении виброускорения на корпусе электродвигателя – приводного элемента в режиме пуска, возникающие при этом сложности в формализации временных реализаций компенсируются пониманием физических процессов, сопровождающих процесс пуска, а также формированием справочника проявления признаков неисправностей. Полученные результаты использовались для принятия решений о целесообразности проведения ремонтных работ и показали достаточную точность безразборного диагностирования указанным методом при использовании относительной и взаимной оценки. </p></abstract><trans-abstract xml:lang="en"><sec><title>Object</title><p>Object: This research aims to develop and validate a practical, low-cost methodology for the prompt technical condition assessment of electromechanical systems (EMS) during the startup transient. The primary goal is to enable binary classification ("satisfactory" or "unsatisfactory") of an EMS's state using vibration signals acquired solely via a smartphone's built-in accelerometer, facilitating widespread on-site screening without specialized equipment.</p></sec><sec><title>Methods</title><p>Methods: The diagnostic approach is based on recording triaxial vibration acceleration time histories during the startup of industrial asynchronous motors driving screw compressors and exhaust fans. Using a dedicated mobile application (AccelerometerMeter), measurements were taken in three orthogonal directions (axial, horizontal, vertical) relative to the motor housing. The methodology relies on relative and mutual comparison of the recorded signals, focusing on transient characteristics rather than absolute metric values. Results were benchmarked against conventional vibration analysis conducted with professional equipment according to ISO standards and post-maintenance teardown inspections.</p></sec><sec><title>Results</title><p>Results: The analysis of startup vibration patterns successfully identified distinctive fault signatures. Key diagnostic indicators included anomalous peak amplitudes, sustained instability, and the presence of characteristic beats and shock impulses, particularly during star-delta switching. Empirical correlations were established between the spatial dominance of vibration (e.g., predominant axial vibration indicating misalignment, high vertical components suggesting foundation issues) and specific mechanical or electromagnetic faults. The smartphone-based method effectively differentiated between properly functioning systems and those with confirmed defects, such as bearing degradation or rotor imbalance, with conclusions corroborated by standard vibration severity assessments.</p></sec><sec><title>Conclusions</title><p>Conclusions: Utilizing a smartphone for vibration analysis during the startup transient proves to be a highly effective and accessible tool for preliminary condition monitoring and screening of electromechanical assets. It provides a viable means for early fault detection in field conditions, allowing maintenance personnel to prioritize equipment for further detailed investigation using advanced diagnostic techniques. The study confirms the high informational content of transient processes for diagnostics and establishes a foundation for a structured, two-level monitoring strategy: initial rapid screening with mobile devices followed by targeted expert analysis, thereby optimizing maintenance resources and enhancing operational reliability.</p></sec></trans-abstract><kwd-group xml:lang="ru"><kwd>электромеханическая система</kwd><kwd>диагностирование</kwd><kwd>временная реализация</kwd><kwd>виброускорение</kwd><kwd>оценка состояния</kwd><kwd>переходный процесс</kwd></kwd-group><kwd-group xml:lang="en"><kwd>electromechanical systems</kwd><kwd>condition monitoring</kwd><kwd>vibration analysis</kwd><kwd>startup transient</kwd><kwd>smartphone diagnostics</kwd><kwd>predictive maintenance</kwd></kwd-group><funding-group><funding-statement xml:lang="ru">Результаты работы, представленные в статье, получены в ходе выполнения НИР в рамках Госзадания (FRRF-2024-0011).</funding-statement><funding-statement xml:lang="en">The results of the work presented in the article were obtained during the implementation of research in the framework of the State Assignment (FRRF-2024-0011)</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">Баннов Д. М. Метод диагностики обрывов стержней ротора в асинхронных электродвигателях на основе регрессионного анализа модуля результирующего вектора тока статора // Известия Томского политехнического университета. Инжиниринг георесурсов. 2022. № 333(5). С.196-208.</mixed-citation><mixed-citation xml:lang="en">Bannov D. M. Metod diagnostiki obry`vov sterzhnej rotora v asinxronny`x e`lektrodvigatelyax na osnove regressionnogo analiza modulya rezul`tiruyushhego vektora toka statora // Izvestiya Tomskogo politexnicheskogo universiteta. Inzhiniring georesursov. 2022. № 333(5). S.196-208 (In Russ).</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">Abdelhak G, Sid Ahmed B, Djekidel R. Fault diagnosis of induction motors rotor using current signature with different signal processing techniques.// Diagnostyka. 2022. Vol. 23(2). pp. 1 - 9.</mixed-citation><mixed-citation xml:lang="en">Abdelhak G, Sid Ahmed B, Djekidel R. Fault diagnosis of induction motors rotor using current signature with different signal processing techniques.// Diagnostyka. 2022. Vol. 23(2). pp. 1 - 9.</mixed-citation></citation-alternatives></ref><ref id="cit3"><label>3</label><citation-alternatives><mixed-citation xml:lang="ru">Sudip Halder, Sunil Bhat, Daria Zychma, Pawel Sowa Broken Rotor Bar Fault Diagnosis Techniques Based on Motor Current Signature Analysis for Induction Motor—A Review.// Energies. 2022. Vol. 15. pp. 8569</mixed-citation><mixed-citation xml:lang="en">Sudip Halder, Sunil Bhat, Daria Zychma, Pawel Sowa Broken Rotor Bar Fault Diagnosis Techniques Based on Motor Current Signature Analysis for Induction Motor—A Review.// Energies. 2022. Vol. 15. pp.  8569</mixed-citation></citation-alternatives></ref><ref id="cit4"><label>4</label><citation-alternatives><mixed-citation xml:lang="ru">Zafer Doğan Broken Rotor Bar Fault Detection in Induction Motor Based on Spectral Analysis // Balkan Journal of Electrical and Computer Engineering. 2025. Vol.12(4). pp.357363</mixed-citation><mixed-citation xml:lang="en">Zafer Doğan Broken Rotor Bar Fault Detection in Induction Motor Based on Spectral Analysis // Balkan Journal of Electrical and Computer Engineering. 2025. Vol.12(4). pp.357363</mixed-citation></citation-alternatives></ref><ref id="cit5"><label>5</label><citation-alternatives><mixed-citation xml:lang="ru">Казыханов Р. Р. Повышение надежности методом диагностики подшипникового узла электрических машин по спектру потребляемого тока // Новая наука: от идеи к результату. 2025. № 5. С. 186-198.</mixed-citation><mixed-citation xml:lang="en">Kazy`xanov R. R. Povy`shenie nadezhnosti metodom diagnostiki podshipnikovogo uzla e`lektricheskix mashin po spektru potreblyaemogo toka // Novaya nauka: ot idei k rezul`tatu.  2025.  № 5.  S. 186-198 (In Russ).</mixed-citation></citation-alternatives></ref><ref id="cit6"><label>6</label><citation-alternatives><mixed-citation xml:lang="ru">K. Yatsugi, S. E. M. P. Kone and Y. Mizuno, "Faulty Class Diagnosis of Three Phase Induction Motor Bearing Using Stator Current Spectral Features and Machine Learning Algorithms," 2022 9th International Conference on Condition Monitoring and Diagnosis (CMD), Kitakyushu, Japan. 2022. pp. 112-117.</mixed-citation><mixed-citation xml:lang="en">K. Yatsugi, S. E. M. P. Kone and Y. Mizuno, "Faulty Class Diagnosis of Three Phase Induction Motor Bearing Using Stator Current Spectral Features and Machine Learning Algorithms," 2022 9th International Conference on Condition Monitoring and Diagnosis (CMD), Kitakyushu, Japan. 2022. pp. 112-117.</mixed-citation></citation-alternatives></ref><ref id="cit7"><label>7</label><citation-alternatives><mixed-citation xml:lang="ru">Сафиуллин Р. А., Янгиров И. Ф. Исследование вибрации асинхронного электродвигателя // Электротехнические и информационные комплексы и системы. 2021. Т. 17, № 2. С. 41-54.</mixed-citation><mixed-citation xml:lang="en">Safiullin R. A., Yangirov I. F. Issledovanie vibracii asinxronnogo e`lektrodvigatelya // E`lektrotexnicheskie i informacionny`e kompleksy` i sistemy`. 2021.  T. 17, № 2.  S. 41-54 (In Russ).</mixed-citation></citation-alternatives></ref><ref id="cit8"><label>8</label><citation-alternatives><mixed-citation xml:lang="ru">M. Marczak, K. Górny and W. Pietrowski, "Wavelet Based Vibration Analysis for Detection of Inter-Turn Faults in Induction Motors Using Pearson Correlation," 2025 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA), Poznan. Poland. 2025. pp. 22-27.</mixed-citation><mixed-citation xml:lang="en">M. Marczak, K. Górny and W. Pietrowski, "Wavelet Based Vibration Analysis for Detection of Inter-Turn Faults in Induction Motors Using Pearson Correlation," 2025 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA), Poznan. Poland. 2025. pp. 22-27.</mixed-citation></citation-alternatives></ref><ref id="cit9"><label>9</label><citation-alternatives><mixed-citation xml:lang="ru">Вибродиагностика насосного оборудования тепловых электростанций / А. В. Лукьянов, Д. П. Алейников, А. П. Хоменко, В. А. Налетов // Современные технологии. Системный анализ. Моделирование. 2024. № 4(84). С. 103-116.</mixed-citation><mixed-citation xml:lang="en">Vibrodiagnostika nasosnogo oborudovaniya teplovy`x e`lektrostancij / A. V. Luk`yanov, D. P. Alejnikov, A. P. Xomenko, V. A. Naletov // Sovremenny`e texnologii. Sistemny`j analiz. Modelirovanie. 2024. № 4(84). S. 103-116 (In Russ).</mixed-citation></citation-alternatives></ref><ref id="cit10"><label>10</label><citation-alternatives><mixed-citation xml:lang="ru">Цвяк В. А., Жманков В. М., Штельмашенко О. С Вибрационная диагностика подшипников и центробежного насоса нефтегазового оборудования// Результаты современных научных исследований и разработок: сборник статей XVII Всероссийской научно-практической конференции, Пенза, 17 июня 2022 года. – Пенза: Наука и Просвещение (ИП Гуляев Г.Ю.), 2022. С. 33-35.</mixed-citation><mixed-citation xml:lang="en">Czvyak V. A., Zhmankov V. M., Shtel`mashenko O. S Vibracionnaya diagnostika podshipnikov i centrobezhnogo nasosa neftegazovogo oborudovaniya// Rezul`taty` sovremenny`x nauchny`x issledovanij i razrabotok : sbornik statej XVII Vserossijskoj nauchnoprakticheskoj konferencii, Penza, 17 iyunya 2022 goda. – Penza: Nauka i Prosveshhenie (IP Gulyaev G.Yu.), 2022. S. 33-35 (In Russ).</mixed-citation></citation-alternatives></ref><ref id="cit11"><label>11</label><citation-alternatives><mixed-citation xml:lang="ru">E. Irgat, E. Çinar and A. Ünsal, "The detection of bearing faults for induction motors by using vibration signals and machine learning," 2021 IEEE 13th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives (SDEMPED), Dallas. TX. USA, 2021. pp. 447-453</mixed-citation><mixed-citation xml:lang="en">E. Irgat, E. Çinar and A. Ünsal, "The detection of bearing faults for induction motors by using vibration signals and machine learning," 2021 IEEE 13th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives (SDEMPED), Dallas. TX. USA, 2021. pp. 447-453</mixed-citation></citation-alternatives></ref><ref id="cit12"><label>12</label><citation-alternatives><mixed-citation xml:lang="ru">N. Rajapaksha, S. Jayasinghe, H. Enshaei and N. Jayarathne, "Acoustic Analysis Based Condition Monitoring of Induction Motors: A Review," 2021 IEEE Southern Power Electronics Conference (SPEC). Kigali. Rwanda. 2021. pp. 1-10.</mixed-citation><mixed-citation xml:lang="en">N. Rajapaksha, S. Jayasinghe, H. Enshaei and N. Jayarathne, "Acoustic Analysis Based Condition Monitoring of Induction Motors: A Review," 2021 IEEE Southern Power Electronics Conference (SPEC). Kigali. Rwanda. 2021. pp. 1-10.</mixed-citation></citation-alternatives></ref><ref id="cit13"><label>13</label><citation-alternatives><mixed-citation xml:lang="ru">E. M. Mahani, A. Mirabadi, A. Rezazadeh and A. H. Karamali, "Acoustic Fault Diagnosis of Rolling Bearings in Induction Motors Using Time-Frequency Image Analysis," 2024 4th International Conference on Electrical Machines and Drives (ICEMD), Tehran, Iran, Islamic Republic. 2024. pp. 1-6</mixed-citation><mixed-citation xml:lang="en">E. M. Mahani, A. Mirabadi, A. Rezazadeh and A. H. Karamali, "Acoustic Fault Diagnosis of Rolling Bearings in Induction Motors Using Time-Frequency Image Analysis," 2024 4th International Conference on Electrical Machines and Drives (ICEMD), Tehran, Iran, Islamic Republic. 2024. pp. 1-6</mixed-citation></citation-alternatives></ref><ref id="cit14"><label>14</label><citation-alternatives><mixed-citation xml:lang="ru">N. Yordanov, M. Zhilevski and M. Mikhov, "Fault Detection in Electric Motors using Acoustic Signals and Image Classification," 2024 International Conference on Applied and Theoretical Electricity (ICATE), Craiova. Romania. 2024. pp. 1-6</mixed-citation><mixed-citation xml:lang="en">N. Yordanov, M. Zhilevski and M. Mikhov, "Fault Detection in Electric Motors using Acoustic Signals and Image Classification," 2024 International Conference on Applied and Theoretical Electricity (ICATE), Craiova. Romania. 2024. pp. 1-6</mixed-citation></citation-alternatives></ref><ref id="cit15"><label>15</label><citation-alternatives><mixed-citation xml:lang="ru">E. Resendiz-Ochoa, J. M. Enriquez-Ugalde, J. J. Saucedo-Dorantes and L. A. Morales-Hernandez, "Broken Rotor Bar Failures Diagnosis with Supervised Learning and Infrared Thermography," 2021 IEEE 13th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives (SDEMPED). Dallas. TX. USA. 2021. pp. 499-504.</mixed-citation><mixed-citation xml:lang="en">E. Resendiz-Ochoa, J. M. Enriquez-Ugalde, J. J. Saucedo-Dorantes and L. A. Morales-Hernandez, "Broken Rotor Bar Failures Diagnosis with Supervised Learning and Infrared Thermography," 2021 IEEE 13th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives (SDEMPED). Dallas. TX. USA. 2021. pp. 499-504.</mixed-citation></citation-alternatives></ref><ref id="cit16"><label>16</label><citation-alternatives><mixed-citation xml:lang="ru">S. Kilickaya, C. Celebioglu, L. Eren and M. Askar, "Thermal Image-Based Fault Diagnosis in Induction Machines via Self-Organized Operational Neural Networks," 2025 IEEE Symposium on Computational Intelligence on Engineering/Cyber Physical Systems (CIES), Trondheim, Norway. 2025. pp. 1-7.</mixed-citation><mixed-citation xml:lang="en">S. Kilickaya, C. Celebioglu, L. Eren and M. Askar, "Thermal Image-Based Fault Diagnosis in Induction Machines via Self-Organized Operational Neural Networks," 2025 IEEE Symposium on Computational Intelligence on Engineering/Cyber Physical Systems (CIES), Trondheim, Norway. 2025. pp. 1-7.</mixed-citation></citation-alternatives></ref><ref id="cit17"><label>17</label><citation-alternatives><mixed-citation xml:lang="ru">Ali A., El-Serafi K., A. K. Mostafa S., El-Sheimy N. Frequency Features Based Fuzzy System for Rotating Machinery Vibration Analysis Using Smartphones Low-Cost MEMS Sensors. Journal of Sensor Technology. 2016. Vol. 6 (3).pp. 56-74.</mixed-citation><mixed-citation xml:lang="en">Ali A., El-Serafi K., A. K. Mostafa S., El-Sheimy N. Frequency Features Based Fuzzy System for Rotating Machinery Vibration Analysis Using Smartphones Low-Cost MEMS Sensors. Journal of Sensor Technology. 2016. Vol. 6 (3).pp. 56-74.</mixed-citation></citation-alternatives></ref><ref id="cit18"><label>18</label><citation-alternatives><mixed-citation xml:lang="ru">Hafizh H., Ali M.N.N., Abdul Majeed A.P.P. Vibration Condition Monitoring of Rotating Machinery with IoT and Smartphone Sensors. In: Tan, A., et al. Advances in Intelligent Manufacturing and Robotics. ICIMR 2023. Lecture Notes in Networks and Systems. 2024. Vol 845. pp. 421-431.</mixed-citation><mixed-citation xml:lang="en">Hafizh H., Ali M.N.N., Abdul Majeed A.P.P. Vibration Condition Monitoring of Rotating Machinery with IoT and Smartphone Sensors. In: Tan, A., et al. Advances in Intelligent Manufacturing and Robotics. ICIMR 2023. Lecture Notes in Networks and Systems. 2024. Vol 845. pp. 421-431.</mixed-citation></citation-alternatives></ref></ref-list><fn-group><fn fn-type="conflict"><p>The authors declare that there are no conflicts of interest present.</p></fn></fn-group></back></article>
