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A Novel Mode Un-Mixing Approach in Variational Mode Decomposition for Fault Detection in Wound Rotor Induction Machines

Author

Listed:
  • Reza Bazghandi

    (Department of Electrical Engineering and Robotic, Shahrood University of Technology, Shahrood 36199-95161, Iran)

  • Mohammad Hoseintabar Marzebali

    (Department of Electrical Engineering and Robotic, Shahrood University of Technology, Shahrood 36199-95161, Iran)

  • Vahid Abolghasemi

    (School of Computer Science and Electronic Engineering, University of Essex, Colchester CO4 3SQ, UK)

  • Shahin Hedayati Kia

    (Laboratory MIS UR4290, University of Picardie “Jules Verne”, 33 rue St Leu, 80039 Amiens, France)

Abstract

Condition monitoring of induction machines (IMs) with the aim of increasing the machine’s lifetime, improving the efficiency and reducing the maintenance cost is necessary and inevitable. Among different types of methods presented for mechanical and electrical fault tracing in induction machines, stator current signature analysis has attracted great attention in recent decades. This popularity is mainly due to the non-invasive nature of this technique. A non-recursive method named variational mode decomposition (VMD) is used for the decomposition of any signal into several intrinsic mode functions (IMFs). This technique can be employed for detection of faulty components in a current signature. However, mode mixing of extracted IMFs makes the mechanical and electrical fault detection of IMs complicated, especially in the case where fault indices emerge close to the supply frequency. To achieve this, we rectify the signal of stator current prior to applying VMD. The main advantage of the presented approach is allowing the fault indices to be properly demodulated from the main frequency to avoid mode mixing phenomenon. The method shows that the dominant frequencies of the current signal can be isolated in each IMFs, appropriately. The proposed strategy is validated to detect the rotor asymmetric fault (RAF) in a wound rotor induction machine (WRIM), in both transient and steady-state conditions.

Suggested Citation

  • Reza Bazghandi & Mohammad Hoseintabar Marzebali & Vahid Abolghasemi & Shahin Hedayati Kia, 2023. "A Novel Mode Un-Mixing Approach in Variational Mode Decomposition for Fault Detection in Wound Rotor Induction Machines," Energies, MDPI, vol. 16(14), pages 1-17, July.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:14:p:5551-:d:1200173
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    References listed on IDEAS

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    1. Vicente Biot-Monterde & Ángela Navarro-Navarro & Jose A. Antonino-Daviu & Hubert Razik, 2021. "Stray Flux Analysis for the Detection and Severity Categorization of Rotor Failures in Induction Machines Driven by Soft-Starters," Energies, MDPI, vol. 14(18), pages 1-18, September.
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    4. Sudip Halder & Sunil Bhat & Daria Zychma & Pawel Sowa, 2022. "Broken Rotor Bar Fault Diagnosis Techniques Based on Motor Current Signature Analysis for Induction Motor—A Review," Energies, MDPI, vol. 15(22), pages 1-20, November.
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    8. Yuriy Zhukovskiy & Aleksandra Buldysko & Ilia Revin, 2023. "Induction Motor Bearing Fault Diagnosis Based on Singular Value Decomposition of the Stator Current," Energies, MDPI, vol. 16(8), pages 1-23, April.
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