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Vibration Monitoring for Position Sensor Fault Diagnosis in Brushless DC Motor Drives

Author

Listed:
  • Dimitrios A. Papathanasopoulos

    (Department of Electrical and Computer Engineering, University of Patras, 26504 Patras, Greece)

  • Konstantinos N. Giannousakis

    (Department of Electrical and Computer Engineering, University of Patras, 26504 Patras, Greece)

  • Evangelos S. Dermatas

    (Department of Electrical and Computer Engineering, University of Patras, 26504 Patras, Greece)

  • Epaminondas D. Mitronikas

    (Department of Electrical and Computer Engineering, University of Patras, 26504 Patras, Greece)

Abstract

A non-invasive technique for condition monitoring of brushless DC motor drives is proposed in this study for Hall-effect position sensor fault diagnosis. Position sensor faults affect rotor position feedback, resulting in faulty transitions, which in turn cause current fluctuations and mechanical oscillations, derating system performance and threatening life expectancy. The main concept of the proposed technique is to detect the faults using vibration signals, acquired by low-cost piezoelectric sensors. With this aim, the frequency spectrum of the piezoelectric sensor output signal is analyzed both under the healthy and faulty operating conditions to highlight the fault signature. Therefore, the second harmonic component of the vibration signal spectrum is evaluated as a reliable signature for the detection of misalignment faults, while the fourth harmonic component is investigated for the position sensor breakdown fault, considering both single and double sensor faults. As the fault signature is localized at these harmonic components, the Goertzel algorithm is promoted as an efficient tool for the harmonic analysis in a narrow frequency band. Simulation results of the system operation, under healthy and faulty conditions, are presented along with the experimental results, verifying the proposed technique performance in detecting the position sensor faults in a non-invasive manner.

Suggested Citation

  • Dimitrios A. Papathanasopoulos & Konstantinos N. Giannousakis & Evangelos S. Dermatas & Epaminondas D. Mitronikas, 2021. "Vibration Monitoring for Position Sensor Fault Diagnosis in Brushless DC Motor Drives," Energies, MDPI, vol. 14(8), pages 1-24, April.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:8:p:2248-:d:537840
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    References listed on IDEAS

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    1. Tomas Zimnickas & Jonas Vanagas & Karolis Dambrauskas & Artūras Kalvaitis, 2020. "A Technique for Frequency Converter-Fed Asynchronous Motor Vibration Monitoring and Fault Classification, Applying Continuous Wavelet Transform and Convolutional Neural Networks," Energies, MDPI, vol. 13(14), pages 1-21, July.
    2. Tomas Zimnickas & Jonas Vanagas & Karolis Dambrauskas & Artūras Kalvaitis & Mindaugas Ažubalis, 2020. "Application of Advanced Vibration Monitoring Systems and Long Short-Term Memory Networks for Brushless DC Motor Stator Fault Monitoring and Classification," Energies, MDPI, vol. 13(4), pages 1-18, February.
    3. Shaikh, Faisal Karim & Zeadally, Sherali, 2016. "Energy harvesting in wireless sensor networks: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 1041-1054.
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    Citations

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    Cited by:

    1. Siddique Akbar & Toomas Vaimann & Bilal Asad & Ants Kallaste & Muhammad Usman Sardar & Karolina Kudelina, 2023. "State-of-the-Art Techniques for Fault Diagnosis in Electrical Machines: Advancements and Future Directions," Energies, MDPI, vol. 16(17), pages 1-44, September.
    2. Karolina Kudelina & Bilal Asad & Toomas Vaimann & Anton Rassõlkin & Ants Kallaste & Huynh Van Khang, 2021. "Methods of Condition Monitoring and Fault Detection for Electrical Machines," Energies, MDPI, vol. 14(22), pages 1-20, November.
    3. Krzysztof Kolano & Bartosz Drzymała & Jakub Gęca, 2021. "Sinusoidal Control of a Brushless DC Motor with Misalignment of Hall Sensors," Energies, MDPI, vol. 14(13), pages 1-13, June.
    4. Olga A. Filina & Nikita V. Martyushev & Boris V. Malozyomov & Vadim Sergeevich Tynchenko & Viktor Alekseevich Kukartsev & Kirill Aleksandrovich Bashmur & Pavel P. Pavlov & Tatyana Aleksandrovna Panfil, 2023. "Increasing the Efficiency of Diagnostics in the Brush-Commutator Assembly of a Direct Current Electric Motor," Energies, MDPI, vol. 17(1), pages 1-24, December.
    5. Jie Ma & Yingxue Li & Liying Wang & Jisheng Hu & Hua Li & Jiyou Fei & Lin Li & Geng Zhao, 2023. "Stator ITSC Fault Diagnosis for EMU Induction Traction Motor Based on Goertzel Algorithm and Random Forest," Energies, MDPI, vol. 16(13), pages 1-17, June.

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