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Tytuł artykułu

Analysis of the correlation between vibrations and the number of shorted turns in the stator winding of a squirrel-cage induction machine

Treść / Zawartość
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This paper presents a method of diagnosing a squirrel-cage induction motor based on the results of machine vibration analysis. The paper considers a fault involving an interturn short circuit in the winding of all phases of the stator. The waveforms of the diagnostic signals were recorded for selected configurations of winding shorts during steady state operation of the motor under constant torque load. In the next step of the study, wavelet packet decomposition was used to analyze the recorded waveforms of the vibration signals. The study focused on determining the correlation between the wavelet analysis results and the number of shorted turns. In addition, the effect of the wavelet used in the wavelet packet analysis on the correlation results was compared. As a result, a method was developed to detect shorted turns in the stator winding of an induction motor based on the results of wavelet packet analysis of the motor vibration.
Rocznik
Strony
341--359
Opis fizyczny
Bibliogr. 18 poz., fot., rys., wykr., wz.
Twórcy
  • Poznan University of Technology, Institute of Industrial Electrical Engineering, Piotrowo 3a, 61-138 Poznań, Poland
  • Poznan University of Technology, Institute of Industrial Electrical Engineering, Piotrowo 3a, 61-138 Poznań, Poland
  • Poznan University of Technology, Institute of Industrial Electrical Engineering, Piotrowo 3a, 61-138 Poznań, Poland
Bibliografia
  • [1] Górny K., Kuwałek P., Pietrowski W., Increasing Electric Vehicles Reliability by Non-Invasive Diagnosis of Motor Winding Faults, Energies, vol. 14, no. 9, 2510 (2021), DOI: 10.3390/en14092510.
  • [2] Górny K., Marczak M., Pietrowski W., Approximation and Extrapolation of Vibrations in Induction Machines as a Function of Numbers of Short-Circuited Turns in Stator Winding, E-pismo dla elektryków i elektroników, AUTOMATYKA, ELEKTRYKA, ZAKŁÓCENIA, vol. 14, no. 1, pp. 10–26 (2023), DOI: 10.17274/AEZ.2023.51.01.
  • [3] Dhamal S.S., Bhatkar M.V., Modelling and Simulation of Three-Phase Induction Motor to Diagnose the Performance on Inter-Turn Short Circuit Fault in Stator Winding, In Proceedings of the 2018 International Conference on Computing, Power and Communication Technologies (GUCON), Greater Noida, India, pp. 1166–1172 (2018).
  • [4] Li Y., Tang B., Jiao S., Zhou Y., Optimized Multivariate Multiscale Slope Entropy for Nonlinear Dynamic Analysis of Mechanical Signals, Chaos, Solitons & Fractals, vol. 179, 114436, ISSN 0960-0779 (2024), DOI: 10.1016/j.chaos.2023.114436.
  • [5] Lee J., Kwon B., Condition Monitoring and Fault Diagnosis of Induction Motors Using Motor Current Signature Analysis (MCSA), Energies, vol. 12, no. 10, 2575 (2019), DOI: 10.3390/en12102575.
  • [6] Report of Large Motor Reliability Survey of Industrial and Commercial Installations, Part I, IEEE Transactions on Industry Applications, vol. IA-21, no. 4, pp. 853–864 (1985), DOI: 10.1109/TIA.1985.349532.
  • [7] Pezzani C., Donolo P., Bossio G., Donolo M., Guzman A., Detecting Broken Rotor Bars with ZeroSetting Protection, 48-th IEEE Industrial & Commercial Power Systems Conference, vol. 50, pp. 1–12 (2014), DOI: 10.1109/ICPS.2012.6229616.
  • [8] Sabah A.N., Jaffery Z.A., Fault Detection of Induction Motor Using Thermal Imaging, 2022 IEEE IAS Global Conference on Emerging Technologies (GlobConET), Arad, Romania, pp. 84–90 (2022), DOI: 10.1109/GlobConET53749.2022.9872516.
  • [9] Xu Z., Tang G., Pang B., An Infrared Thermal Image Few-Shot Learning Method Based on CAPNet and Its Application to Induction Motor Fault Diagnosis, in IEEE Sensors Journal, vol. 22, no. 16, pp. 16440–16450 (2022), DOI: 10.1109/JSEN.2022.3192300.
  • [10] Majid M.H.H.A., Samsuddin N.M., Rahman A.S.A., Nik Ali N.H., Rahiman M.H.F., Partial Discharge Activity Analysis in Rotating Machine Using Phase Resolved Partial Discharge Pattern, 2024 IEEE 4th International Conference in Power Engineering Applications (ICPEA), Pulau Pinang, Malaysia, pp. 201–204 (2024), DOI: 10.1109/ICPEA60617.2024.10498445.
  • [11] Huzmezan M., Reflections on the On-Line Partial Discharge Monitoring and Analysis for Condition Assessment of Large Generators and Motors, 2022 IEEE Electrical Insulation Conference (EIC), Knoxville, TN, USA, pp. 289–293 (2022), DOI: 10.1109/EIC51169.2022.9833159.
  • [12] Kamala K.S., Induvadhani V.V., Lakshmi V.I., Mithra P., Sunil Nag P.V., Kumar C.S., Electrical Signature Analysis (ESA) of a Fault Injection Capable Synchronous Generator for Inter-Turn Stator Faults, 2020 5th International Conference on Communication and Electronics Systems (ICCES), Coimbatore, India, pp. 171–175 (2020), DOI: 10.1109/ICCES48766.2020.9138089.
  • [13] Penrose H.W., Evaluation of Asynchronous Wind Generator Stator Magnetic Slot Wedge and Coil Movement Using Electrical Signature Analysis, 2021 IEEE Electrical Insulation Conference (EIC), Denver, CO, USA, pp. 1–4 (2021), DOI: 10.1109/EIC49891.2021.9612312.
  • [14] Bhole N., Ghodke S., Motor Current Signature Analysis for Fault Detection of Induction Machine–A Review, 2021 4th Biennial International Conference on Nascent Technologies in Engineering (ICNTE), NaviMumbai, India, pp. 1–6 (2021) DOI: 10.1109/ICNTE51185.2021.9487715.
  • [15] Yelpale P.D., Jarial R.K., Patil A.J., Fuzzy-Based Induction Motor Fault Diagnosis Decision-Making System for Motor Current Signature Analysis, 2024 3rd International Conference for Innovation in Technology (INOCON), Bangalore, India, pp. 1–6 (2024), DOI: 10.1109/INOCON60754.2024.10512034.
  • [16] Sułowicz M., Sobczyk T.J., Tulicki J., Stator Current Spectrum Analysis of a Double Cage Induction Motor with Rotor Asymmetry, Archives of Electrical Engineering, vol. 72, no. 2, pp. 357–371 (2023), DOI: 10.1109/XYZ.2023.123456.
  • [17] Wang T., Zheng W., Electric Vehicle Motor Fault Diagnosis Using Improved Wavelet Packet Decomposition and Particle Swarm Optimization Algorithm, Archives of Electrical Engineering, vol. 73, no. 2, pp. 481–498 (2024), DOI: 10.1109/ABC.2024.789101.
  • [18] Morawiec M., Wogi L., Ayana T., Core Loss Resistance Impact on Sensorless Speed Control of an Induction Motor Using Hybrid Adaptive Sliding Mode Observer, Archives of Electrical Engineering, vol. 72, no. 4, pp. 895–913 (2023), DOI: 10.1109/XYZ.2023.456789.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-8bc0cf62-6c4f-4a06-b2de-bcc9994f7cca
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