IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i3p1244-d744645.html
   My bibliography  Save this article

Fast Real-Time RDFT- and GDFT-Based Direct Fault Diagnosis of Induction Motor Drive

Author

Listed:
  • Piotr Kołodziejek

    (Department of Electrical and Control Engineering, Gdansk University of Technology, 80-398 Gdansk, Poland)

  • Daniel Wachowiak

    (Department of Electrical and Control Engineering, Gdansk University of Technology, 80-398 Gdansk, Poland)

Abstract

This paper presents the theoretical analysis and experimental verification of a direct fault harmonic identification approach in a converter-fed electric drive for automated diagnosis purposes. On the basis of the analytical model of the proposed real-time direct fault diagnosis, the fault-related harmonic component is calculated using recursive DFT (RDFT) and Goertzel DFT (GDFT), applied instead of the full spectrum calculations required in the most popular FFT algorithm. The simulation model of an inverter sensorlessly controlled induction motor drive is linked with the induction machine rotor fault model for testing the sensitivity of the GDFT- and RDFT-based fault diagnosis to state variable estimation errors. According to the presented simulation results, the accuracy of the direct identification of a fault-related harmonic is sensitive to the quality of fault harmonic frequency estimation. The sensitivity analysis with respect to RDFT and GDFT algorithms is included. Based on the experimental setup with a sensorlessly controlled induction motor drive with the investigated rotor fault, fault diagnosis algorithms were implemented in the microprocessor by integration with the control system in one microcontroller and experimentally verified. The RDFT and GDFT approach has shown accurate and fast direct automated fault identification at a significantly decreased number of arithmetical operations in the microcontroller, which is convenient for the frequency-domain fault diagnosis in electric drives and supports fault-tolerant control system implementation.

Suggested Citation

  • Piotr Kołodziejek & Daniel Wachowiak, 2022. "Fast Real-Time RDFT- and GDFT-Based Direct Fault Diagnosis of Induction Motor Drive," Energies, MDPI, vol. 15(3), pages 1-14, February.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:3:p:1244-:d:744645
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/3/1244/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/3/1244/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mitja Nemec & Vanja Ambrožič & Rastko Fišer & David Nedeljković & Klemen Drobnič, 2019. "Induction Motor Broken Rotor Bar Detection Based on Rotor Flux Angle Monitoring," Energies, MDPI, vol. 12(5), pages 1-17, February.
    2. Marek Adamowicz & Janusz Szewczyk, 2020. "SiC-Based Power Electronic Traction Transformer (PETT) for 3 kV DC Rail Traction," Energies, MDPI, vol. 13(21), pages 1-30, October.
    3. Maciej Skowron & Teresa Orlowska-Kowalska & Marcin Wolkiewicz & Czeslaw T. Kowalski, 2020. "Convolutional Neural Network-Based Stator Current Data-Driven Incipient Stator Fault Diagnosis of Inverter-Fed Induction Motor," Energies, MDPI, vol. 13(6), pages 1-21, March.
    4. Daniel Wachowiak, 2021. "A Universal Gains Selection Method for Speed Observers of Induction Machine," Energies, MDPI, vol. 14(20), pages 1-19, October.
    5. Zuolu Wang & Jie Yang & Haiyang Li & Dong Zhen & Yuandong Xu & Fengshou Gu, 2019. "Fault Identification of Broken Rotor Bars in Induction Motors Using an Improved Cyclic Modulation Spectral Analysis," Energies, MDPI, vol. 12(17), pages 1-20, August.
    6. Miroslaw Wlas & Stanislaw Galla & Abdellah Kouzou & Piotr Kolodziejek, 2022. "Analysis of an Energy Management System of a Small Plant Connected to the Rural Power System," Energies, MDPI, vol. 15(3), pages 1-21, January.
    7. Bohdan Pakhaliuk & Viktor Shevchenko & Jan Mućko & Oleksandr Husev & Mykola Lukianov & Piotr Kołodziejek & Natalia Strzelecka & Ryszard Strzelecki, 2021. "Optimal Rotating Receiver Angles Estimation for Multicoil Dynamic Wireless Power Transfer," Energies, MDPI, vol. 14(19), pages 1-15, September.
    8. Daniel Wachowiak, 2020. "Genetic Algorithm Approach for Gains Selection of Induction Machine Extended Speed Observer," Energies, MDPI, vol. 13(18), pages 1-24, September.
    9. Yuri Merizalde & Luis Hernández-Callejo & Oscar Duque-Perez, 2017. "State of the Art and Trends in the Monitoring, Detection and Diagnosis of Failures in Electric Induction Motors," Energies, MDPI, vol. 10(7), pages 1-34, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chenyun Wu & Rabia Sehab & Ahmad Akrad & Cristina Morel, 2022. "Fault Diagnosis Methods and Fault Tolerant Control Strategies for the Electric Vehicle Powertrains," Energies, MDPI, vol. 15(13), pages 1-7, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Khaled Farag & Abdullah Shawier & Ayman S. Abdel-Khalik & Mohamed M. Ahmed & Shehab Ahmed, 2021. "Applicability Analysis of Indices-Based Fault Detection Technique of Six-Phase Induction Motor," Energies, MDPI, vol. 14(18), pages 1-23, September.
    2. Arkadiusz Duda & Maciej Sułowicz, 2020. "A New Effective Method of Induction Machine Condition Assessment Based on Zero-Sequence Voltage (ZSV) Symptoms," Energies, MDPI, vol. 13(14), pages 1-26, July.
    3. Arkadiusz Duda & Piotr Drozdowski, 2020. "Induction Motor Fault Diagnosis Based on Zero-Sequence Current Analysis," Energies, MDPI, vol. 13(24), pages 1-25, December.
    4. Josue A. Reyes-Malanche & Francisco J. Villalobos-Pina & Efraın Ramırez-Velasco & Eduardo Cabal-Yepez & Geovanni Hernandez-Gomez & Misael Lopez-Ramirez, 2023. "Short-Circuit Fault Diagnosis on Induction Motors through Electric Current Phasor Analysis and Fuzzy Logic," Energies, MDPI, vol. 16(1), pages 1-15, January.
    5. Martin Valtierra-Rodriguez & Juan Pablo Amezquita-Sanchez & Arturo Garcia-Perez & David Camarena-Martinez, 2019. "Complete Ensemble Empirical Mode Decomposition on FPGA for Condition Monitoring of Broken Bars in Induction Motors," Mathematics, MDPI, vol. 7(9), pages 1-19, August.
    6. Cleber Gustavo Dias & Luiz Carlos da Silva & Ivan Eduardo Chabu, 2019. "Fuzzy-Based Statistical Feature Extraction for Detecting Broken Rotor Bars in Line-Fed and Inverter-Fed Induction Motors," Energies, MDPI, vol. 12(12), pages 1-29, June.
    7. Haiyang Li & Zuolu Wang & Dong Zhen & Fengshou Gu & Andrew Ball, 2019. "Modulation Sideband Separation Using the Teager–Kaiser Energy Operator for Rotor Fault Diagnostics of Induction Motors," Energies, MDPI, vol. 12(23), pages 1-16, November.
    8. Wagner Fontes Godoy & Daniel Morinigo-Sotelo & Oscar Duque-Perez & Ivan Nunes da Silva & Alessandro Goedtel & Rodrigo Henrique Cunha Palácios, 2020. "Estimation of Bearing Fault Severity in Line-Connected and Inverter-Fed Three-Phase Induction Motors," Energies, MDPI, vol. 13(13), pages 1-17, July.
    9. Kai Ding & Chen Yao & Yifan Li & Qinglong Hao & Yaqiong Lv & Zengrui Huang, 2022. "A Review on Fault Diagnosis Technology of Key Components in Cold Ironing System," Sustainability, MDPI, vol. 14(10), pages 1-28, May.
    10. Marcin Steczek & Piotr Chudzik & Adam Szeląg, 2020. "Application of a Non-carrier-Based Modulation for Current Harmonics Spectrum Control during Regenerative Braking of the Electric Vehicle," Energies, MDPI, vol. 13(24), pages 1-21, December.
    11. Michał Michna & Filip Kutt & Łukasz Sienkiewicz & Roland Ryndzionek & Grzegorz Kostro & Dariusz Karkosiński & Bartłomiej Grochowski, 2020. "Mechanical-Level Hardware-In-The-Loop and Simulation in Validation Testing of Prototype Tower Crane Drives," Energies, MDPI, vol. 13(21), pages 1-25, November.
    12. Przemyslaw Pietrzak & Marcin Wolkiewicz, 2021. "Comparison of Selected Methods for the Stator Winding Condition Monitoring of a PMSM Using the Stator Phase Currents," Energies, MDPI, vol. 14(6), pages 1-23, March.
    13. Chao Fu & Dong Zhen & Yongfeng Yang & Fengshou Gu & Andrew Ball, 2019. "Effects of Bounded Uncertainties on the Dynamic Characteristics of an Overhung Rotor System with Rubbing Fault," Energies, MDPI, vol. 12(22), pages 1-15, November.
    14. Sebastian Berhausen & Tomasz Jarek, 2021. "Method of Limiting Shaft Voltages in AC Electric Machines," Energies, MDPI, vol. 14(11), pages 1-19, June.
    15. Maciej Skowron & Czeslaw T. Kowalski & Teresa Orlowska-Kowalska, 2022. "Impact of the Convolutional Neural Network Structure and Training Parameters on the Effectiveness of the Diagnostic Systems of Modern AC Motor Drives," Energies, MDPI, vol. 15(19), pages 1-22, September.
    16. Paweł Dworak & Andrzej Mrozik & Agata Korzelecka-Orkisz & Adam Tański & Krzysztof Formicki, 2023. "Energy Self-Sufficiency of a Salmonids Breeding Facility in the Recirculating Aquaculture System," Energies, MDPI, vol. 16(6), pages 1-22, March.
    17. Mitja Nemec & Vanja Ambrožič & Rastko Fišer & David Nedeljković & Klemen Drobnič, 2019. "Induction Motor Broken Rotor Bar Detection Based on Rotor Flux Angle Monitoring," Energies, MDPI, vol. 12(5), pages 1-17, February.
    18. Bon-Gwan Gu, 2022. "Development of Broken Rotor Bar Fault Diagnosis Method with Sum of Weighted Fourier Series Coefficients Square," Energies, MDPI, vol. 15(22), pages 1-12, November.
    19. Federico Gargiulo & Annalisa Liccardo & Rosario Schiano Lo Moriello, 2022. "A Non-Invasive Method Based on AI and Current Measurements for the Detection of Faults in Three-Phase Motors," Energies, MDPI, vol. 15(12), pages 1-19, June.
    20. Camila Paes Salomon & Wilson Cesar Sant’Ana & Germano Lambert-Torres & Luiz Eduardo Borges da Silva & Erik Leandro Bonaldi & Levy Ely de Lacerda De Oliveira, 2018. "Comparison among Methods for Induction Motor Low-Intrusive Efficiency Evaluation Including a New AGT Approach with a Modified Stator Resistance," Energies, MDPI, vol. 11(4), pages 1-21, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:3:p:1244-:d:744645. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.