A Method for Studying Inhomogeneous States of Induction Motors
DOI:
https://doi.org/10.24160/1993-6982-2021-3-41-50Keywords:
induction motor, operational state, vector space, operational diagnostics, topological approachAbstract
The presented study is aimed at carrying out scientifically grounded assessments of the current technical state of induction motors (IMs). The existing classical theory of IMs has insufficient generality for solving this problem. It does not cover the state of IMs that feature manufacturing and technological deviations, as well as states with operational damages or ageing. The variety of IM operational states and design versions generates the need to widen the classical framework of analysis to the level of multidimensional representations.
Such study was carried out within the framework of a topological approach. According to this approach, an IM is considered as a multidimensional inhomogeneous electromechanical system that can be in homogeneous or inhomogeneous states. From the methodological point of view, the topological approach is based on observing and analyzing the formal properties of a mathematical model with transferring their results to the real object. The rules and a systematized conceptual and terminological framework presented in the article play an essential role. In addition, the method of a topological study and its examples are given. Thus, the study covers all components of the scientific approach focused on a multidimensional representation of the IM operational states.
The topological approach forms a scientific and methodological platform for setting up a system for monitoring the current technical state of IMs during their operation. It is pointed out that the existing diagnostic methods are focused on recording external manifestations of parametric heterogeneity. In view of this circumstance, they cannot serve as a reliable basis for drawing up conclusions on the current technical state of IMs. The topological method of operational diagnostics is focused on recording and analyzing changes in the internal properties of an object and is practically independent of the influence of external factors.
This feature guarantees high reliability of the results obtained from applying the topological diagnostics method for estimating the current technical state of IMs.
References
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28. Петухов В.С. Спектральный анализ модулей векторов Парка тока и напряжения // Новости электротехники. 2008. № 2(50). С. 43—49.
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30. Shprekher D.M., Kolesnikov E.B. The Remote Method of Diagnosing the Technical Condition of Complex Electromechanical Systems // 2018 Intern. Multi-conf. Industrial Eng. and Modern Technol. 2018. Pp. 1—3.
31. Ming Yu , Mengxin Li. Fault Detection and Isolation in a Nonlinear Electromechanical System // Intern. Conf. Sensing, Diagnostics, Prognostics, and Control. 2017. Pp. 1—3.
32. Veresnikov G.S., Skryabin A.V. The Electromechanical Actuator Technical Condition Monitoring System Based on Data Mining Methods // Proc. XI Intern. Conf. Management of Large-scale System Development. 2018. Pp. 1—4.
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34. Kurilin S.P., Denisov V.N. The Development of Topological Diagnostic Methods of Asynchronous Electric Machines // Diagnostics, Resource and Mechanics of Materials and Structures. 2018. Iss. 6. Pp. 214—221.
35. Kurilin S.P., Denisov V.N., Dli M.I., Bobkov V.I. Vector Space as an Area of the Operation Risks Characteristics for Asynchronous Electric Machines // Mechanical Sci. and Technol. Update. 2019. V. 1260. P. 052017.
36. Kurilin S.P., Denisov V.N., Dli M.I., Bobkov V.I. A Method for the Operational Diagnostics of Induction Motors. // Proc. XIII Intern. Conf. Mechanics, Resource and Diagnostics of Materials and Structures. 2019. V. 2176. No. 1. P. 04008.
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Для цитирования: Курилин С.П., Денисов В.Н. Метод исследования неоднородных состояний асинхронных электродвигателей // Вестник МЭИ. 2021. № 3. С. 41—50. DOI: 10.24160/1993-6982-2021-3-41-50.
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Работа выполнена при поддержке: РФФИ (проект № 20-01-00283)
#
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2. Ivanov-Smolenskiy A.V. Elektricheskie Mashiny. T. 2. M.: Izdat. Dom MEI, 2006. (in Russian).
3. Kurilin S.P., Denisov V.N. Topologicheskie Aspekty Teorii Asinkhronnykh Elektricheskikh Mashin. Smolensk: Universum, 2019. (in Russian).
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21. Aksenov Y., Arces I., Noe G. On-line PD Diagnostic on Medium Voltage Motors and Cable Lines: Useful Tool for the Maintenance Manager. Proc. Intern. Symp. Electrical Insulation. 2004:151—153.
22. Joksimovic G.M., Ðurovic J.P. The Detection of Inter-turn Short Circuits in the Stator Windings of Operating Motors. IEEE Trans. Industrial Electronics. 2000;47(5):1078—1084.
23. Bellini A., Filippeti F., Tassoni C., Kliman G.B. Quantitative Evaluation of Induction Motor Broken Bars by Means of Electrical Signature Analysis. IEEE Trans. Industry Appl. 2001;37:1248—1255.
24. Filho P.S.M.L., Pederiva R., Brito J.N. Detection of Stator Winding Faults in Induction Machines Using Flux and Vibration Analysis. IEEE Intern. Symp. Diagnostics for Electric Machines, Power Electronics and Drives. 2007:432—437.
25. Aksenov Y., Yaroshenko I., Noe G., Andreev A. Diagnostic Technology for Transformers: Methods Synergy and Double-Coordinate Location. IEEE Intern. Symp. Diagnostics for Electric Machines, Power Electronics and Drives. 2009:1—7.
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30. Shprekher D.M., Kolesnikov E.B. The Remote Method of Diagnosing the Technical Condition of Complex Electromechanical Systems. 2018 Intern. Multi-conf. Industrial Eng. and Modern Technol. 2018:1—3.
31. Ming Yu , Mengxin Li. Fault Detection and Isolation in a Nonlinear Electromechanical System. Intern. Conf. Sensing, Diagnostics, Prognostics, and Control. 2017:1—3.
32. Veresnikov G.S., Skryabin A.V. The Electromechanical Actuator Technical Condition Monitoring System Based on Data Mining Methods. Proc. XI Intern. Conf. Management of Large-scale System Development. 2018:1—4.
33. Jinyeong Moon, Leeb S.B. Wire Less Sensors for Electromechanical Systems Diagnostics. IEEE Trans. Instrumentation and Measurement. 2018;67;9:1—12.
34. Kurilin S.P., Denisov V.N. The Development of Topological Diagnostic Methods of Asynchronous Electric Machines. Diagnostics, Resource and Mechanics of Materials and Structures. 2018;6:214—221.
35. Kurilin S.P., Denisov V.N., Dli M.I., Bobkov V.I. Vector Space as an Area of the Operation Risks Characteristics for Asynchronous Electric Machines. Mechanical Sci. and Technol. Update. 2019;1260:052017.
36. Kurilin S.P., Denisov V.N., Dli M.I., Bobkov V.I. A Method for the Operational Diagnostics of Induction Motors.. Proc. XIII Intern. Conf. Mechanics, Resource and Diagnostics of Materials and Structures. 2019;2176;1:04008.
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For citation: Kurilin S.P., Denisov V.N. A Method for Studying Inhomogeneous States of Induction Motors. Bulletin of MPEI. 2021;3:41—50. (in Russian). DOI: 10.24160/1993-6982-2021-3-41-50.
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The work is executed at support: RFBR (Project No. 20-01-00283)
2. Иванов-Смоленский А.В. Электрические машины. Т. 2. М.: Издат. дом МЭИ, 2006.
3. Курилин С.П., Денисов В.Н. Топологические аспекты теории асинхронных электрических машин. Смоленск: Универсум, 2019.
4. Курилин С.П., Денисов В.Н. Математическая модель неявнополюсной электрической машины в матричной форме // Электричество. 2014. № 4. С. 43—49.
5. Вольдек А.И. Электрические машины. М.: Альянс, 2017.
6. Kurilin S.P, Denisov V.N, Bobkov V. Risk Assessment for Rotors Operational Integrity Loss of Asynchronous Electrical Machines in Heat Power Engineering Systems // Proc. Intern. Russian Automation Conf. 2019. Pp. 1—5.
7. Kurilin S.P, Denisov V.N, Fedulov A.S., Dli M.I. Scientific Basis of Methods for Topological Diagnostics of Asynchronous Electric Machines // Proc. AIP Conf. 2018. V. 2053(1). P. 030031.
8. Kurilin S.P, Denisov V.N., Dli M.I. Mathematical and Visual Models of Asynchronous Electric Machines Energy Fields // Proc. III Intern. Sci. and Techn. Conf. Energy Systems. 2019. V. 552. No. 1. P. 012015.
9. Борисов В.В., Курилин С.П., Черновалова М.В. Топологический подход к исследованию неоднородных электромеханических систем // Математические методы в технике и технологиях: Cб. трудов Междунар. науч. конф. СПб. Изд-во Политехн. ун-та, 2020. Т. 7. С. 93—96.
10. Копылов И.П. Электрические машины. М.: Высшая школа, 2004.
11. Беспалов В.Я., Котеленец Н.Ф. Электрические машины. М.: Академия, 2006.
12. Нос О.В. Математическая модель асинхронного двигателя в линейных пространствах, связанных со статором и ротором // Известия вузов. Серия «Электромеханика». 2008. № 2. С. 14—20.
13. Кацман М.М. Справочник по электрическим машинам. М.: Академия, 2005.
14. Электротехнический справочник. Т. 4. Использование электрической энергии / Под общ. ред. В.Г. Герасимова и др. М.: Изд-во МЭИ, 2004.
15. Копылов И.П. и др. Проектирование электрических машин. М.: Альянс, 2016.
16. Гольдберг О.Д., Макаров Л.Н., Хелемская С.П. Инженерное проектирование электрических машин. М.: Издат. дом «Бастед», 2016.
17. Гантмахер Ф.Р. Теория матриц. М.: Физматлит, 2010.
18. Smolin V.I., Topolskaya I.G., Volovich G.I. The Energy Method for Monitoring the Instantaneous State and the Formation of a Synchronous Motor Control Variables // Proc. II Intern. Conf. Industrial Eng., Appl. and Manufacturing. 2016. Pp. 1—4.
19. Farhani F., Zaafouri A., Chaari A. Real Time Induction Motor Efficiency Optimization // J. Franklin Institute. 2017. V. 354(8). Pp. 3289—3304.
20. Aksenov Y., Yaroshenko I., Noe G., Andreev A. On-line Diagnostics Technology and Repair Results for Midium Voltage Motors // IEEE Intern. Symp. Diagnostics for Electric Machines, Power Electronics and Drives. 2009. Pp. 1—7.
21. Aksenov Y., Arces I., Noe G. On-line PD Diagnostic on Medium Voltage Motors and Cable Lines: Useful Tool for the Maintenance Manager // Proc. Intern. Symp. Electrical Insulation. 2004. Pp. 151—153.
22. Joksimovic G.M., Ðurovic J.P. The Detection of Inter-turn Short Circuits in the Stator Windings of Operating Motors // IEEE Trans. Industrial Electronics. 2000. V. 47(5). Pp. 1078—1084.
23. Bellini A., Filippeti F., Tassoni C., Kliman G.B. Quantitative Evaluation of Induction Motor Broken Bars by Means of Electrical Signature Analysis // IEEE Trans. Industry Appl. 2001. V. 37. Pp. 1248—1255.
24. Filho P.S.M.L., Pederiva R., Brito J.N. Detection of Stator Winding Faults in Induction Machines Using Flux and Vibration Analysis // IEEE Intern. Symp. Diagnostics for Electric Machines, Power Electronics and Drives. 2007. Pp. 432—437.
25. Aksenov Y., Yaroshenko I., Noe G., Andreev A. Diagnostic Technology for Transformers: Methods Synergy and Double-Coordinate Location // IEEE Intern. Symp. Diagnostics for Electric Machines, Power Electronics and Drives. 2009. Pp. 1—7.
26. De la Barrera P.M. e. a. Experimental Generation and Quantification of Stator Core Faults on Induction Motors // Ibid. Pp. 8— 14.
27. Петухов В.С., Соколов В.А. Диагностика состояния электродвигателей. Метод спектрального анализа потребляемого тока // Новости электротехники. 2005. № 1(31). С. 23—28.
28. Петухов В.С. Спектральный анализ модулей векторов Парка тока и напряжения // Новости электротехники. 2008. № 2(50). С. 43—49.
29. Степанов В.М., Свистунов Н.А. Диагностика и управление режимами работы электромеханических и электротехнических систем автономных источников электроэнергии для собственных нужд газораспределительных объектов // Известия Тульского гос. ун-та. Серия «Технические науки». 2018. № 12. С. 96—99.
30. Shprekher D.M., Kolesnikov E.B. The Remote Method of Diagnosing the Technical Condition of Complex Electromechanical Systems // 2018 Intern. Multi-conf. Industrial Eng. and Modern Technol. 2018. Pp. 1—3.
31. Ming Yu , Mengxin Li. Fault Detection and Isolation in a Nonlinear Electromechanical System // Intern. Conf. Sensing, Diagnostics, Prognostics, and Control. 2017. Pp. 1—3.
32. Veresnikov G.S., Skryabin A.V. The Electromechanical Actuator Technical Condition Monitoring System Based on Data Mining Methods // Proc. XI Intern. Conf. Management of Large-scale System Development. 2018. Pp. 1—4.
33. Jinyeong Moon, Leeb S.B. Wire Less Sensors for Electromechanical Systems Diagnostics // IEEE Trans. Instrumentation and Measurement. 2018. V. 67. Iss. 9. Pp. 1—12.
34. Kurilin S.P., Denisov V.N. The Development of Topological Diagnostic Methods of Asynchronous Electric Machines // Diagnostics, Resource and Mechanics of Materials and Structures. 2018. Iss. 6. Pp. 214—221.
35. Kurilin S.P., Denisov V.N., Dli M.I., Bobkov V.I. Vector Space as an Area of the Operation Risks Characteristics for Asynchronous Electric Machines // Mechanical Sci. and Technol. Update. 2019. V. 1260. P. 052017.
36. Kurilin S.P., Denisov V.N., Dli M.I., Bobkov V.I. A Method for the Operational Diagnostics of Induction Motors. // Proc. XIII Intern. Conf. Mechanics, Resource and Diagnostics of Materials and Structures. 2019. V. 2176. No. 1. P. 04008.
---
Для цитирования: Курилин С.П., Денисов В.Н. Метод исследования неоднородных состояний асинхронных электродвигателей // Вестник МЭИ. 2021. № 3. С. 41—50. DOI: 10.24160/1993-6982-2021-3-41-50.
---
Работа выполнена при поддержке: РФФИ (проект № 20-01-00283)
#
1. Ivanov-Smolenskiy A.V. Elektricheskie Mashiny. T. 1. M.: Izdat. Dom MEI, 2006. (in Russian).
2. Ivanov-Smolenskiy A.V. Elektricheskie Mashiny. T. 2. M.: Izdat. Dom MEI, 2006. (in Russian).
3. Kurilin S.P., Denisov V.N. Topologicheskie Aspekty Teorii Asinkhronnykh Elektricheskikh Mashin. Smolensk: Universum, 2019. (in Russian).
4. Kurilin S.P., Denisov V.N. Matematicheskaya Model' Neyavnopolyusnoy Elektricheskoy Mashiny v Matrichnoy Forme. Elektrichestvo. 2014;4:43—49. (in Russian).
5. Vol'dek A.I. Elektricheskie Mashiny. M.: Al'yans, 2017. (in Russian).
6. Kurilin S.P, Denisov V.N, Bobkov V. Risk Assessment for Rotors Operational Integrity Loss of Asynchronous Electrical Machines in Heat Power Engineering Systems.. Proc. Intern. Russian Automation Conf. 2019:1—5.
7. Kurilin S.P, Denisov V.N, Fedulov A.S., Dli M.I. Scientific Basis of Methods for Topological Diagnostics of Asynchronous Electric Machines. Proc. AIP Conf. 2018; 2053(1):030031.
8. Kurilin S.P, Denisov V.N., Dli M.I. Mathematical and Visual Models of Asynchronous Electric Machines Energy Fields. Proc. III Intern. Sci. and Techn. Conf. Energy Systems. 2019; 552;1:012015.
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For citation: Kurilin S.P., Denisov V.N. A Method for Studying Inhomogeneous States of Induction Motors. Bulletin of MPEI. 2021;3:41—50. (in Russian). DOI: 10.24160/1993-6982-2021-3-41-50.
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The work is executed at support: RFBR (Project No. 20-01-00283)
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2020-10-06
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Electromechanics and Electrical Apparatus (05.09.01)
