IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i8p2248-d537840.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/8/2248/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/14/8/2248/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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.
    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. 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.

    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. Farnaz Derakhshan & Shamim Yousefi, 2019. "A review on the applications of multiagent systems in wireless sensor networks," International Journal of Distributed Sensor Networks, , vol. 15(5), pages 15501477198, May.
    2. Fang, Zheng & Tan, Xing & Liu, Genshuo & Zhou, Zijie & Pan, Yajia & Ahmed, Ammar & Zhang, Zutao, 2022. "A novel vibration energy harvesting system integrated with an inertial pendulum for zero-energy sensor applications in freight trains," Applied Energy, Elsevier, vol. 318(C).
    3. Liu, Qi & Qin, Weiyang & Zhou, Zhiyong & Shang, Mengjie & Zhou, Honglei, 2023. "Harvesting low-speed wind energy by bistable snap-through and amplified inertial force," Energy, Elsevier, vol. 284(C).
    4. Tan, Ting & Yan, Zhimiao & Zou, Hongxiang & Ma, Kejing & Liu, Fengrui & Zhao, Linchuan & Peng, Zhike & Zhang, Wenming, 2019. "Renewable energy harvesting and absorbing via multi-scale metamaterial systems for Internet of things," Applied Energy, Elsevier, vol. 254(C).
    5. Jijian Lian & Ou Cai & Xiaofeng Dong & Qi Jiang & Yue Zhao, 2019. "Health Monitoring and Safety Evaluation of the Offshore Wind Turbine Structure: A Review and Discussion of Future Development," Sustainability, MDPI, vol. 11(2), pages 1-29, January.
    6. Wang, Zhemin & Du, Yu & Li, Tianrun & Yan, Zhimiao & Tan, Ting, 2021. "A flute-inspired broadband piezoelectric vibration energy harvesting device with mechanical intelligent design," Applied Energy, Elsevier, vol. 303(C).
    7. Liu, Feng-Rui & Zhang, Wen-Ming & Peng, Zhi-Ke & Meng, Guang, 2019. "Fork-shaped bluff body for enhancing the performance of galloping-based wind energy harvester," Energy, Elsevier, vol. 183(C), pages 92-105.
    8. Abderrahman El Idrissi & Aziz Derouich & Said Mahfoud & Najib El Ouanjli & Ahmed Chantoufi & Ameena Saad Al-Sumaiti & Mahmoud A. Mossa, 2022. "Bearing Fault Diagnosis for an Induction Motor Controlled by an Artificial Neural Network—Direct Torque Control Using the Hilbert Transform," Mathematics, MDPI, vol. 10(22), pages 1-32, November.
    9. Sajib Roy & Md Humayun Kabir & Md Salauddin & Miah A. Halim, 2022. "An Electromagnetic Wind Energy Harvester Based on Rotational Magnet Pole-Pairs for Autonomous IoT Applications," Energies, MDPI, vol. 15(15), pages 1-14, August.
    10. Sunil Kr. Jha & Egbe Michael Eyong, 2018. "An energy optimization in wireless sensor networks by using genetic algorithm," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 67(1), pages 113-121, January.
    11. Sudhanshu Tiwari & Gaurav Kumar & Ayush Raj & Prateek & Rajeev Arya, 0. "Water cycle algorithm perspective on energy constraints in WSN," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 0, pages 1-8.
    12. 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.
    13. Qi, Nanjian & Yin, Yajiang & Dai, Keren & Wu, Chengjun & Wang, Xiaofeng & You, Zheng, 2021. "Comprehensive optimized hybrid energy storage system for long-life solar-powered wireless sensor network nodes," Applied Energy, Elsevier, vol. 290(C).
    14. Sun, Rujie & Li, Qinyu & Yao, Jianfei & Scarpa, Fabrizio & Rossiter, Jonathan, 2020. "Tunable, multi-modal, and multi-directional vibration energy harvester based on three-dimensional architected metastructures," Applied Energy, Elsevier, vol. 264(C).
    15. Babayo, Aliyu Aliyu & Anisi, Mohammad Hossein & Ali, Ihsan, 2017. "A Review on energy management schemes in energy harvesting wireless sensor networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 1176-1184.
    16. Liu, Huicong & Fu, Hailing & Sun, Lining & Lee, Chengkuo & Yeatman, Eric M., 2021. "Hybrid energy harvesting technology: From materials, structural design, system integration to applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    17. Deng, Hang & Ye, Jimin & Huang, Dongmei, 2023. "Design and analysis of a galloping energy harvester with V-shape spring structure under Gaussian white noise," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).
    18. S. H. Alsamhi & Ou Ma & Mohd. Samar Ansari & Qingliang Meng, 2019. "Greening internet of things for greener and smarter cities: a survey and future prospects," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 72(4), pages 609-632, December.
    19. Kouton, Jeffrey, 2019. "Information Communication Technology development and energy demand in African countries," Energy, Elsevier, vol. 189(C).
    20. Chung-Jen Chou & Shyh-Biau Jiang & Tse-Liang Yeh & Li-Duan Tsai & Ku-Yen Kang & Ching-Jung Liu, 2020. "A Portable Direct Methanol Fuel Cell Power Station for Long-Term Internet of Things Applications," Energies, MDPI, vol. 13(14), pages 1-13, July.

    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:14:y:2021:i:8:p:2248-:d:537840. 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.