Induction motor mechanical defect diagnosis using DWT under different loading levels

Authors

  • Ahcene Bouzida University of Bouira, Faculty of Sciences and Applied Sciences, Department of Electrical Engineering, 10000, Bouira, Algeria
  • Radia Abdelli University of Bejaia, Faculty of Technology, Department of Electrical Engineering, 06000, Bejaia, Algeria
  • Aimad Boudouda University of Boumerdes, Faculty of Technology, Laboratoire Ingénierie des Systèmes et Télécommunications (LIST), 35000, Boumerdes, Algeria

DOI:

https://doi.org/10.14311/AP.2023.63.0001

Keywords:

induction motor, fault diagnosis, eccentricity, misalignment, DWT, energy, loading levels

Abstract

The information extraction capability of the widely used signal processing tool, FFT for diagnosing induction machines, is commonly used at a constant load or at different levels. The loading level is a major influencing factor in the diagnostic process when the coupled load and the machine come with natural mechanical imperfections, and at a low load, the mechanical faults harmonics are strongly influenced. In this context, the main objective of this work is the detection of the mechanical faults and the study of the effect of the loading level on the induction motor diagnostic process. We have employed a diagnosis method based on discrete wavelet transform (DWT) for the multi-level decomposition of stator current and extracting the fault’s energy stored over a wide frequency range. The proposed approach has been experimentally tested on a faulty machine with dynamic eccentricity and a shaft misalignment for three loading levels. The proposed method is experimentally tested and the results are provided to verify the effectiveness of the fault detection and to point out the importance of the coupled load.

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References

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Published

2023-03-02

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How to Cite

Bouzida, A., Abdelli, R., & Boudouda, A. (2023). Induction motor mechanical defect diagnosis using DWT under different loading levels. Acta Polytechnica, 63(1), 1-10. https://doi.org/10.14311/AP.2023.63.0001