IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2019i1p101-d301498.html
   My bibliography  Save this article

Characteristics Analysis and Measurement of Inverter-Fed Induction Motors for Stator and Rotor Fault Detection

Author

Listed:
  • Jing Tang

    (School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China)

  • Yongheng Yang

    (Department of Energy Technology, Aalborg University, 9220 Aalborg, Denmark)

  • Jie Chen

    (School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China)

  • Ruichang Qiu

    (School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China)

  • Zhigang Liu

    (School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China
    Beijing Engineering Research Center for Electrical Rail Transit, Beijing 100044, China)

Abstract

Inverter-fed induction motors (IMs) contain a serious of current harmonics, which become severer under stator and rotor faults. The resultant fault components in the currents affect the monitoring of the motor status. With this background, the fault components in the electromagnetic torque under stator faults considering harmonics are derived in this paper, and the fault components in current harmonics under rotor faults are analyzed. More importantly, the monitoring based on the fault characteristics (both in the torque and current) is proposed to provide reliable stator and rotor fault diagnosis. Specifically, the fault components induced by stator faults in the electromagnetic torque are discussed in this paper, and then, fault components are characterized in the torque spectrum to identify stator faults. To achieve so, a full-order flux observer is adopted to calculate the torque. On the other hand, under rotor faults, the sidebands caused by time and space harmonics in the current are analyzed and exploited to recognize rotor faults, being the motor current signature analysis (MCSA). Experimental tests are performed on an inverter-fed 2.2 kW/380 V/50 Hz IM, which verifies the analysis and the effectiveness of the proposed fault diagnosis methods of inverter-fed IMs.

Suggested Citation

  • Jing Tang & Yongheng Yang & Jie Chen & Ruichang Qiu & Zhigang Liu, 2019. "Characteristics Analysis and Measurement of Inverter-Fed Induction Motors for Stator and Rotor Fault Detection," Energies, MDPI, vol. 13(1), pages 1-17, December.
    • Handle: RePEc:gam:jeners:v:13:y:2019:i:1:p:101-:d:301498
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/1/101/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/1/101/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wen Wu & Xuezhi Wu & Jingyuan Yin & Long Jing & Shuai Wang & Jinke Li, 2017. "Characteristic Analysis and Fault-Tolerant Control of Circulating Current for Modular Multilevel Converters under Sub-Module Faults," Energies, MDPI, vol. 10(11), pages 1-22, November.
    2. Pedro Gonçalves & Sérgio Cruz & André Mendes, 2019. "Finite Control Set Model Predictive Control of Six-Phase Asymmetrical Machines—An Overview," Energies, MDPI, vol. 12(24), pages 1-42, December.
    3. Carlos Candelo-Zuluaga & Jordi-Roger Riba & Carlos López-Torres & Antoni Garcia, 2019. "Detection of Inter-Turn Faults in Multi-Phase Ferrite-PM Assisted Synchronous Reluctance Machines," Energies, MDPI, vol. 12(14), pages 1-15, July.
    4. 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.
    5. Zia Ullah & Jin Hur, 2018. "A Comprehensive Review of Winding Short Circuit Fault and Irreversible Demagnetization Fault Detection in PM Type Machines," Energies, MDPI, vol. 11(12), pages 1-27, November.
    6. Camila Paes Salomon & Claudio Ferreira & Wilson Cesar Sant’Ana & Germano Lambert-Torres & Luiz Eduardo Borges da Silva & Erik Leandro Bonaldi & Levy Ely de Lacerda de Oliveira & Bruno Silva Torres, 2019. "A Study of Fault Diagnosis Based on Electrical Signature Analysis for Synchronous Generators Predictive Maintenance in Bulk Electric Systems," Energies, MDPI, vol. 12(8), pages 1-16, April.
    7. Wei Li & Gengyin Li & Rong Zeng & Kai Ni & Yihua Hu & Huiqing Wen, 2018. "The Fault Detection, Localization, and Tolerant Operation of Modular Multilevel Converters with an Insulated Gate Bipolar Transistor (IGBT) Open Circuit Fault," Energies, MDPI, vol. 11(4), pages 1-20, April.
    8. Liling Sun & Boqiang Xu, 2018. "An Improved Method for Discerning Broken Rotor Bar Fault and Load Oscillation in Induction Motors," Energies, MDPI, vol. 11(11), pages 1-15, November.
    9. Hanying Gao & Wen Zhang & Yu Wang & Zhuo Chen, 2019. "Fault-Tolerant Control Strategy for 12-Phase Permanent Magnet Synchronous Motor," Energies, MDPI, vol. 12(18), pages 1-17, September.
    10. Caixia Gao & Yanjie Nie & Jikai Si & Ziyi Fu & Haichao Feng, 2019. "Mode Recognition and Fault Positioning of Permanent Magnet Demagnetization for PMSM," Energies, MDPI, vol. 12(9), pages 1-14, April.
    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. 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.
    2. Muhammed Ali Gultekin & Ali Bazzi, 2023. "Review of Fault Detection and Diagnosis Techniques for AC Motor Drives," Energies, MDPI, vol. 16(15), pages 1-22, July.
    3. Guy Clerc, 2022. "Failure Diagnosis and Prognosis of Induction Machines," Energies, MDPI, vol. 15(4), pages 1-2, February.
    4. Petr Kacor & Petr Bernat & Petr Moldrik, 2021. "Utilization of Two Sensors in Offline Diagnosis of Squirrel-Cage Rotors of Asynchronous Motors," Energies, MDPI, vol. 14(20), pages 1-23, October.

    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. Carlos Candelo-Zuluaga & Jordi-Roger Riba & Dinesh V. Thangamuthu & Antoni Garcia, 2020. "Detection of Partial Demagnetization Faults in Five-Phase Permanent Magnet Assisted Synchronous Reluctance Machines," Energies, MDPI, vol. 13(13), pages 1-17, July.
    2. Piotr Mynarek & Janusz Kołodziej & Adrian Młot & Marcin Kowol & Marian Łukaniszyn, 2021. "Influence of a Winding Short-Circuit Fault on Demagnetization Risk and Local Magnetic Forces in V-Shaped Interior PMSM with Distributed and Concentrated Winding," Energies, MDPI, vol. 14(16), pages 1-16, August.
    3. Yiqi Liu & Danhua Li & Yu Jin & Qingbo Wang & Wenlong Song, 2018. "Research on Unbalance Fault-Tolerant Control Strategy of Modular Multilevel Photovoltaic Grid-Connected Inverter," Energies, MDPI, vol. 11(6), pages 1-18, May.
    4. 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.
    5. 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.
    6. Marwa Ben Slimene & Mohamed Arbi Khlifi, 2022. "Investigation on the Effects of Magnetic Saturation in Six-Phase Induction Machines with and without Cross Saturation of the Main Flux Path," Energies, MDPI, vol. 15(24), pages 1-18, December.
    7. Konrad Urbanski & Dariusz Janiszewski, 2021. "Position Estimation at Zero Speed for PMSMs Using Artificial Neural Networks," Energies, MDPI, vol. 14(23), pages 1-17, December.
    8. Karol Wróbel & Piotr Serkies & Krzysztof Szabat, 2020. "Model Predictive Base Direct Speed Control of Induction Motor Drive—Continuous and Finite Set Approaches," Energies, MDPI, vol. 13(5), pages 1-15, March.
    9. Yongda Li & Pingping Gong, 2023. "Fault-Tolerant Control of Induction Motor with Current Sensors Based on Dual-Torque Model," Energies, MDPI, vol. 16(8), pages 1-15, April.
    10. Qinyue Zhu & Wei Dai & Lei Guan & Xitang Tan & Zhaoyang Li & Dabo Xie, 2019. "A Fault-Tolerant Control Strategy of Modular Multilevel Converter with Sub-Module Faults Based on Neutral Point Compound Shift," Energies, MDPI, vol. 12(5), pages 1-22, March.
    11. Mariusz Korkosz & Jan Prokop & Bartlomiej Pakla & Grzegorz Podskarbi & Piotr Bogusz, 2020. "Analysis of Open-Circuit Fault in Fault-Tolerant BLDC Motors with Different Winding Configurations," Energies, MDPI, vol. 13(20), pages 1-27, October.
    12. Barbosa de Santis, Rodrigo & Silveira Gontijo, Tiago & Azevedo Costa, Marcelo, 2021. "Condition-based maintenance in hydroelectric plants: A systematic literature review," MPRA Paper 115912, University Library of Munich, Germany.
    13. Apostolos Lamprokostopoulos & Epameinondas Mitronikas & Alexandra Barmpatza, 2022. "Detection of Demagnetization Faults in Axial Flux Permanent-Magnet Synchronous Wind Generators," Energies, MDPI, vol. 15(9), pages 1-15, April.
    14. Kyunghwan Choi & Kyung-Soo Kim & Seok-Kyoon Kim, 2019. "Proportional-Type Sensor Fault Diagnosis Algorithm for DC/DC Boost Converters Based on Disturbance Observer," Energies, MDPI, vol. 12(8), pages 1-14, April.
    15. Sandra Eriksson, 2019. "Permanent Magnet Synchronous Machines," Energies, MDPI, vol. 12(14), pages 1-5, July.
    16. Dae-Seak Cha & Jung-Sik Choi & Seung-Yeol Oh & Hyun-Jin Ahn & Young-Cheol Lim, 2018. "Hot-Swappable Modular Converter System Control for Heterogeneous Batteries and ESS," Energies, MDPI, vol. 11(2), pages 1-19, February.
    17. Yinquan Yu & Haixi Gao & Qiping Chen & Peng Liu & Shuangxia Niu, 2022. "Demagnetization Fault Detection and Location in PMSM Based on Correlation Coefficient of Branch Current Signals," Energies, MDPI, vol. 15(8), pages 1-17, April.
    18. 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.
    19. Petr Kacor & Petr Bernat & Petr Moldrik, 2021. "Utilization of Two Sensors in Offline Diagnosis of Squirrel-Cage Rotors of Asynchronous Motors," Energies, MDPI, vol. 14(20), pages 1-23, October.
    20. Jingyuan Yin & Wen Wu & Tongzhen Wei & Xuezhi Wu & Qunhai Huo, 2018. "A Novel Fault-Tolerant Control of Modular Multilevel Converter under Sub-Module Faults Based on Phase Disposition PWM," Energies, MDPI, vol. 12(1), pages 1-17, December.

    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:13:y:2019:i:1:p:101-:d:301498. 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.