pimiПриборы и методы измеренийDevices and Methods of Measurements2220-95062414-0473BNTU10.21122/2220-9506-2025-16-2-158-167pimi-962Research ArticleМетоды измерений, контроля, диагностикиMethods of measurements, monitoring, diagnosticsМетод неразрушающего контроля состояния однофазных и трёхфазных трансформаторов на основе частотных характеристикMethod of Non-Destructive Control of Single-Phase and Three-Phase Transformers's Condition on the Basis of Frequency CharacteristicsГромыкоИ. Л.HramykaI. L.

Адрес для переписки:Громыко И.Л.–Белорусский государственный университет транспорта, ул. Кирова, 34, г. Гомель 246653, Беларусьe-mail: ivangromyko95@mail.ru

Address for correspondence:Hramyka I.L.–Belarusian State University of Transport,Kirova str., 34, Gomel 246653, Belarus e-mail: ivangromyko95@mail.ru

ivangromyko95@mail.ruГалушкоВ. Н.GalushkoV. N.

ул. Кирова, 34, г. Гомель 246653

Kirova str., 34, Gomel 246653

Белорусский государственный университет транспортаБеларусьBelarusian State University of TransportBelarus202502072025162158167Copyright © Громыко И.Л., Галушко В.Н., 20252025Громыко И.Л., Галушко В.Н.Hramyka I.L., Galushko V.N.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://pimi.bntu.by/jour/article/view/962

Cуществуют различные методы диагностики трансформаторов. Анализ используемых методов и диагностических систем указывает на достижение определённой сложности дальнейшего развития существующих методов и диагностических систем. Это обусловлено сложностью входных сигналов, достаточно большим числом параметров, нелинейными множественными динамическими взаимосвязями. Одним из наиболее перспективных видов диагностики, на сегодняшний момент, является анализ частотных характеристик трансформатора. Целью данной работы являлось выявление различных дефектов трансформатора с помощью анализа частотных характеристик. В данной работе для обнаружения дефектов сердечника и обмоток использован анализ частотных характеристик на основе метода трёх вольтметров. В результате проведения серии экспериментов получены импедансные и фазо-частотные характеристики трансформаторов с дефектами сердечника и обмоток. Данные характеристики показывают значительные различия между нормальным и аварийным состояниями трансформаторов. Полученные характеристики в виде изображений являются исходными данными для свёрточной нейронной сети, определяющей вид дефекта. Использование частотных характеристик однофазных и трёхфазных трансформаторов при диагностировании предотказных состояний и отказов позволит создать универсальный программно-аппаратный комплекс диагностики для трансформаторов различных типов и номинальных данных.

Nowadays, there are many different methods of transformer diagnostics. The analysis of used methods and diagnostic systems indicates that a certain complexity of further development of existing methods and diagnostic systems has been achieved. This is due to the complexity of input signals, quite a large number of input factors, nonlinear multiple dynamic interrelationships with other parameters. One of the most promising types of diagnostics, to date, is frequency response analysis. The objective of this paper was to identify various transformer defects by analysing the frequency response. In this paper, frequency response analysis based on the three voltmeter method is used to detect core and winding defects. In a series of experiments, impedance and phase-frequency characteristics of transformers with core and winding defects are obtained. These characteristics show significant differences between the normal and emergency states of the transformers. The obtained characteristics in the form of pictures are the initial data for the convolutional neural network, which determines the type of defect. The use of frequency characteristics of single-phase and three-phase transformers in diagnostics of pre-failure states and failures will allow to create a universal hardware-software complex of diagnostics for transformers of different types and nominal data.

 

трансформаторчастотные характеристикиметод трёх вольтметровtransformerfrequency characteristicsmethod of three voltmetersReferencesMahmoudi N, Samimi MH, Mohseni H. Experiences with transformer diagnosis by DGA: case studies. IET Generation, Transmission & Distribution. 2019;13(23):5431-5439. doi: 10.1049/iet-gtd.2019.1056Mahmoudi N, Samimi MH, Mohseni H. Experiences with transformer diagnosis by DGA: case studies. IET Generation, Transmission & Distribution. 2019;13(23):5431-5439. doi: 10.1049/iet-gtd.2019.1056Behjat V, Mahvi M, Rahimpour E. A new statistical approach to interpret power transformer frequency response analysis: Nonparametric statistical methods. 2015 30th International Power System Conference (PSC), Tehran, Iran. 2015;142-148. doi: 10.1109/IPSC.2015.7827740Behjat V, Mahvi M, Rahimpour E. A new statistical approach to interpret power transformer frequency response analysis: Nonparametric statistical methods. 2015 30th International Power System Conference (PSC), Tehran, Iran. 2015;142-148. doi: 10.1109/IPSC.2015.7827740Samimi MH, Tenbohlen S, Akmal AAS, Mohseni H. Evaluation of numerical indices for the assessment of transformer frequency response. IET Generation, Transmission & Distribution. 2017;11(1):218-227. doi: 10.1049/iet-gtd.2016.0879Samimi MH, Tenbohlen S, Akmal AAS, Mohseni H. Evaluation of numerical indices for the assessment of transformer frequency response. IET Generation, Transmission & Distribution. 2017;11(1):218-227. doi: 10.1049/iet-gtd.2016.0879Zhao Z, Yao C, Li C, Islam S. Detection of Power Transformer Winding Deformation Using Improved FRA Based on Binary Morphology and Extreme Point Variation. IEEE Transactions on Industrial Electronics. 2018;65(4):3509-3519. doi: 10.1109/TIE.2017.2752135Zhao Z, Yao C, Li C, Islam S. Detection of Power Transformer Winding Deformation Using Improved FRA Based on Binary Morphology and Extreme Point Variation. IEEE Transactions on Industrial Electronics. 2018;65(4):3509-3519. doi: 10.1109/TIE.2017.2752135Tarimoradi H, Gharehpetian GB. Novel Calculation Method of Indices to Improve Classifi-cation of Transformer Winding Fault Type, Location, and Extent. IEEE Transactions on Industrial Informatics. 2017;13(4):1531-1540. doi: 10.1109/TII.2017.2651954Tarimoradi H, Gharehpetian GB. Novel Calculation Method of Indices to Improve Classifi-cation of Transformer Winding Fault Type, Location, and Extent. IEEE Transactions on Industrial Informatics. 2017;13(4):1531-1540. doi: 10.1109/TII.2017.2651954Jahan MS, Keypour R, Izadfar HR, Keshavarzi MT. Locating power transformer fault based on sweep frequency response measurement by a novel multistage approach. IET Science, Measurement & Technology. 2018;12(8):949-957. doi: 10.1049/iet-smt.2018.0003Jahan MS, Keypour R, Izadfar HR, Keshavarzi MT. Locating power transformer fault based on sweep frequency response measurement by a novel multistage approach. IET Science, Measurement & Technology. 2018;12(8):949-957. doi: 10.1049/iet-smt.2018.0003Contin A, Rabach G, Borghetto J, Nigris MD, Passaglia R, Rizzi G. Frequency-response analysis of power transformers by means of fuzzy tools. IEEE Transactions on Dielectrics and Electrical Insulation. 2011;18(3):900-909. doi: 10.1109/TDEI.2011.5931079Contin A, Rabach G, Borghetto J, Nigris MD, Passaglia R, Rizzi G. Frequency-response analysis of power transformers by means of fuzzy tools. IEEE Transactions on Dielectrics and Electrical Insulation. 2011;18(3):900-909. doi: 10.1109/TDEI.2011.5931079Bigdeli M, Vakilian M, Rahimpour E. A probabilistic neural network classifier based method for transformer winding fault identification through its transfer function measurement. International Transactions on Electrical Energy Systems. 2013;23(3):392-404. doi: 10.1002/etep.668Bigdeli M, Vakilian M, Rahimpour E. A probabilistic neural network classifier based method for transformer winding fault identification through its transfer function measurement. International Transactions on Electrical Energy Systems. 2013;23(3):392-404. doi: 10.1002/etep.668Гизатулин И.А. Построение системы диагностики и мониторинга силового трансформатора 110 КВ / Гизатулин И.А., Воркунов О.В. // Сборник научных статей по материалам XVI Международной научно-практической конференции (3 декабря 2024 г., г. Уфа). В 3 ч. Ч.1 / – Уфа: Изд. Научно-издательский центр Вестник науки, 2024. – С. 64–68.Gizatulin IA, Vorkunov OV. Construction of the system of diagnostics and monitoring of 110 KV power transformer. Fundamental and applied approaches to solving scientific problems. Collection of scientific articles on the materials of XVI International Scientific and Practical Conference (December 3, 2024, Ufa), In 3 parts., Part.1, Ufa, Bulletin of Science. 2024;64-68.Суходолов, Ю.В. Возможность определения дефектов в обмотках электрических машин частотными методами / Ю.В. Суходолов, А.В. Исаев, В.В. Зеленко, С.В. Сизиков // Метрология и приборостроение. – 2022. – Том 98. – № 3. – С. 10-17.Sukhodolov YV, Isaev AV, Zelenko VV, Sizikov SV. Possibility of defects determination in electric machine windings by frequency methods. Metrology and instrumentation. 2022;98(3):10-17. (In Russ.).Moradzadeh A, Moayyed H, MohammadiIvatloo B, Gharehpetian GB, Aguiar AP. Turn-to-Turn Short Circuit Fault Localization in Transformer Winding via Image Processing and Deep Learning Method. IEEE Transactions on Industrial Informatics. 2022;18(7):44174426. DOI: 10.1109/TII.2021.3105932Moradzadeh A, Moayyed H, MohammadiIvatloo B, Gharehpetian GB, Aguiar AP. Turn-to-Turn Short Circuit Fault Localization in Transformer Winding via Image Processing and Deep Learning Method. IEEE Transactions on Industrial Informatics. 2022;18(7):44174426. DOI: 10.1109/TII.2021.3105932Vosoughi A. and M. Hamed Samimi. Evaluation of the Image Processing Technique in Interpretation of Polar Plot Characteristics of Transformer Frequency Response. 2022 International Conference on Machine Vision and Image Processing (MVIP), Ahvaz, Iran, Islamic Republic of, 2022;1-6. doi: 10.1109/MVIP53647.2022.9738771Vosoughi A. and M. Hamed Samimi. Evaluation of the Image Processing Technique in Interpretation of Polar Plot Characteristics of Transformer Frequency Response. 2022 International Conference on Machine Vision and Image Processing (MVIP), Ahvaz, Iran, Islamic Republic of, 2022;1-6. doi: 10.1109/MVIP53647.2022.9738771Hramyka I. Development of Software and Hardware for Identification of Interturn Short Circuit in Single-Phase Transformers. 2024 Third International Conference on Power, Control and Computing Technologies (ICPC2T), Raipur, India. 2024;241-246. doi: 10.1109/ICPC2T60072.2024.10474962Hramyka I. Development of Software and Hardware for Identification of Interturn Short Circuit in Single-Phase Transformers. 2024 Third International Conference on Power, Control and Computing Technologies (ICPC2T), Raipur, India. 2024;241-246. doi: 10.1109/ICPC2T60072.2024.10474962Galushko VN, Hramyka IL, Ermolenko DV. Development of methodological principles of diagnostics of transformers of the non-pulling railroad power supply system with the help of artificial neural networks. Мonograph, Ministry of Transport and Communications of the Republic of Belarus, Homel, BSUT, 2025, 167 p.Galushko VN, Hramyka IL, Ermolenko DV. Development of methodological principles of diagnostics of transformers of the non-pulling railroad power supply system with the help of artificial neural networks. Мonograph, Ministry of Transport and Communications of the Republic of Belarus, Homel, BSUT, 2025, 167 p.

The authors declare that there are no conflicts of interest present.