Induction motor diagnostics based on electrical signals analysis using cloud technologies

• Autorzy: Mamchur Dmytro , Kasich Oleksandr , Kalinov Andrii

Identyfikatory

DOI

10.15199/48.2024.10.25

Warianty tytułu

PL

Diagnostyka silnika indukcyjnego oparta na analizie sygnałów elektrycznych przy wykorzystaniu technologii chmurowych

• Języki publikacji: EN

Abstrakty

EN

The paper discusses implementation latest advanced in computational and data processing technologies to induction motors monitoring and diagnostics. As a diagnostic criterion, a Motor Current Signature Analysis was chosen. Typical frequencies related to most frequently caused damage types visible in stator current signal were described. A possible solution for implementation cloud computing to improve quality of induction motors health monitoring was proposed and its main components are described.

PL

W artykule omówiono wdrażanie najnowszych zaawansowanych technologii obliczeniowych i przetwarzania danych do monitorowania i diagnostyki silników indukcyjnych. Jako kryterium diagnostyczne wybrano analizę sygnału prądu silnika. Opisano typowe częstotliwości związane z najczęściej powodowanymi uszkodzeniami widocznymi w sygnale prądowym stojana. Zaproponowano możliwe rozwiązanie wdrożenia chmury obliczeniowej w celu poprawy jakości monitorowania stanu silników indukcyjnych oraz opisano jego główne elementy.

Słowa kluczowe

EN

motor current signature analysis; diagnostic; cloud computing

PL

analiza sygnału prądu silnika; diagnostyka; przetwarzanie w chmurze

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2024
• Tom: R. 100, nr 10
• Strony: 136--139
• Opis fizyczny: Bibliogr. 23 poz., rys.

Twórcy

autor

Mamchur Dmytro

• Kremenchuk Mykhailo Ostrohradskyi National University, Ukraine, vul. Universytetska, 20, 39600, Kremenchuk

• https://orcid.org/0000-0002-2851-878X

autor

Kasich Oleksandr

• Kremenchuk Mykhailo Ostrohradskyi National University, Ukraine, vul. Universytetska, 20, 39600, Kremenchuk

• https://orcid.org/0009-0005-4103-3030

autor

Kalinov Andrii

• Kremenchuk Mykhailo Ostrohradskyi National University, Ukraine, vul. Universytetska, 20, 39600, Kremenchuk

• https://orcid.org/0000-0002-5613-7992

Bibliografia

• [1] Yousuf, M., Alsuwian, T., Ami n , A.A., Fareed, S. and Hamza, M., IoT-based health monitoring and fault detection of industrial AC induction motor for efficient predictive maintenance. Measurement and Control, 2024, 00202940241231473.
• [2] Benbouz i d , M.E.H., A review of induction motors signature analysis as a medium for faults detection, IEEE transactions on industrial electronics, 47(5), 2000, 984-993.
• [3] Zagirnyak, M., Mamchur, D. and Kalinov, A., Comparison of induction motor diagnostic methods based on spectra analysis of current and instantaneous power signals, Przeglad Elektrotechniczny, 88(2012), nr. 12, 221-224.
• [4] Zagirnyak M., Kal i nov A., Melnykov V., Kochurov I . , Correction of the operating modes of an induction motor with asymmetrical stator windings at vector control, 2015 International Conference on Electrical Drives and Power Electronics (EDPE), Tatranska Lomnica, Slovakia, (2015), 259–265, doi: 10.1109/EDPE.2015.7325303
• [5] Zagi rnyak, M. , Kal inov, A. & Mal iakova, M., Analysis of instantaneous power components of electric circuit with a semiconductor element, Archives of Electrical Engineering, vol. 62, (2013), no. 3, 473–486. DOI: 10.2478/aee-2013-0038
• [6] Zagirnyak, M., Mal i akova, M., Kal i nov, A., Analysis of operation of power components compensation systems at harmonic distortions of mains supply voltage, in proceedings of Joint International Conference - ACEMP 2015: Aegean Conference on Electrical Machines and Power Electronics, OPTIM 2015: Optimization of Electrical and Electronic Equipment and ELECTROMOTION 2015: International Symposium on Advanced Electromechanical Motion Systems, (2016), 355–362.
• [7] Melny kov V. , Kal inov A. , Ar temenko A. , Methods for Adjustment Fault-Tolerant Control Systems for Induction Motors with Damaged Stator Windings, in proc. 2022 IEEE 4th International Conference on Modern Electrical and Energy System (MEES), Kremenchuk, Ukraine, (2022), 1–6, doi: 10.1109/MEES58014.2022.10005700.
• [8] Kumar, R.R., Andriol l o , M., Ci r rincione, G., Ci r r incione, M. , Tor tel la, A. A. , Comprehensive Review of Conventional and Intelligence-Based Approaches for the Fault Diagnosis and Condition Monitoring of Induction Motors. Energies, (2022), no. 15, 8938. https://doi.org/10.3390/en15238938
• [9] Issa, R. , Clerc, G., Hologne-Carpentier, M., Michaud, R., Lorca, E., Magnette, C . , Messadi , A., Review of Fault Diagnosis Methods for Induction Machines in Railway Traction Applications, Energies, (2024), no. 17, 2728. https://doi.org/10.3390/en17112728
• [10] Gubarevych, O., Ger l i c i , J., Kravchenko, O., Mel konova, I . , Melnyk, O., Use of Park’s Vector Method for Monitoring the Rotor Condition of an Induction Motor as a Part of the Built-In Diagnostic System of Electric Drives of Transport, Energies, (2023), no. 16, 5109. https://doi.org/10.3390/en16135109
• [11] Schoen, R. R., Habet l e r, T. G., Kamran, F., Bar t f ield, R. G., Motor bearing damage detection using stator current monitoring. IEEE transactions on industry applications, (1995), no. 31(6), 1274–1279.
• [12] Bouras, A., Bennedjai , S., Bouras, S . , Experimental detection of defects in variable speed fan bearing using stator current monitoring. SN Applied Sciences, (2020), no. 2, 1– 8.
• [13] Jung, J . H . , Lee, J. J., Kwon, B. H., Online diagnosis of induction motors using MCSA. IEEE Transactions on Industrial Electronics, (2006), no. 53(6), 1842–1852.
• [14] Khechekhouche, A., Cherif, H., Benakcha, A. , Menacer, A., Chehaidi a , S. E., Panchal, H. Experimental diagnosis of inter-turns stator fault and unbalanced voltage supply in induction motor using MCSA and DWER, Periodicals of Engineering and Natural Sciences, (2020), no. 8(3), 1202–1216.
• [15] K l iman, G. B. , Stein, J ., Methods of motor current signature analysis, Electric Machines and power systems, (1992), no. 20(5), 463–474.
• [16] Bessous N., Zouzou S. E., Sbaa S., Bentrah W., A comparative study between the MCSA, DWT and the vibration analysis methods to diagnose the dynamic eccentricity fault in induction motors, in proc. 2017 6th International Conference on Systems and Control (ICSC), Batna, Algeria, 2017, 414–421, doi: 10.1109/ICoSC.2017.7958655.
• [17] Liu, Z., Zhang, P., He, S., Huang, J . , A Review of Modeling and Diagnostic Techniques for Eccentricity Fault in Electric Machines. Energies, (2021), no. 14, 4296. https://doi.org/10.3390/en14144296
• [18] Thomson, W. T., Gilmore, R. J., Motor Current Signature Analysis to Detect Faults in Induction Motor Drives- Fundamentals, Data Interpretation, And Industrial Case Histories. In Proceedings of the 32nd turbomachinery Symposium. (2003), Texas A&M University. Turbomachinery Laboratories.
• [19] Drakaki , M., Karnavas, Y. L . , Karlis, A. D., Chasiot is , I . D. , Tz ionas, P. Study on fault diagnosis of broken rotor bars in squirrel cage induction motors: a multiagent system approach using intelligent classifiers. IET Electric Power Applications, (2020), no. 14(2), 245–255.
• [20] Iwawaki, T., Kanemaru, M., Yasuhara, Y., Miyauchi , T. , Fault Detection of Rotor Bars in Inverter-Fed Induction Motors Based on Current Signature Analysis Technique. In PHM Society Asia-Pacific Conference, Vol. 4, (2023, September), No. 1.
• [21] Choudhary, A., Jamwal , S., Goyal , D., Dang, R. K. , Sehgal , S. , Condition monitoring of induction motor using internet of things (IoT). In Recent Advances in Mechanical Engineering: Select Proceedings of NCAME 2019, (2020), 353–365. Springer Singapore.
• [22] Bapir, A., Aydın, İ . Cloud based bearing fault diagnosis of induction motors. Computer Science, (Special), (2021), 141– 146.
• [23] Belahcen, A., Gyf t akis, K. N. , Martinez, J . , Climente-Alarcon, V., Vaimann, T. Condition monitoring of electrical machines and its relation to industrial internet, In 2015 IEEE Workshop on Electrical Machines Design, Control and Diagnosis (WEMDCD), ( 2015, March), 233–241.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki i promocja sportu (2025).