Diagnosis of induction motor stator faults around rotor slot harmonics using the Matrix Pencil method

• Utilizes the Matrix Pencil method for high-resolution spectral analysis. • Offers superior frequency resolution, even with short acquisition times and low amplitudes. • Focuses analysis on the first rotor slot harmonics to minimize interference. • Simulation and experimental tests confirm reliability in detecting inter-turn short-circuit faults in stator windings. To improve the monitoring and diagnosis of stator faults at their early stages in induction motors, several methods have been developed, particularly parametric methods. This article thus proposes a new approach based on the Matrix Pencil method for high-resolution spectral analysis. This method aims to avoid the limitations of the classical method based on power spectral density estimation using the periodogram. Indeed, the proposed approach offers very high frequency resolution even for very short acquisition times, thus allowing improved detection even for low amplitudes. Furthermore, to optimize the calculation time of this method, the article suggests focusing the analysis only on the frequency band corresponding to the first rotor slot harmonics. This approach aims to avoid any interference with the frequency signatures of external factors, which are generally present at very low frequencies. The results obtained from simulation and experimental tests demonstrate the effectiveness and reliability of this new approach for detecting inter turns short-circuit faults in stator windings of the induction motor.

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Publication Details

Journal
Results in Engineering
Published
2025-02-03
DOI
https://doi.org/10.1016/j.rineng.2025.104240
Citations
7
Primary Topic
Machine Fault Diagnosis Techniques
Type
article
Field-Weighted Citation Impact
8.50
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article

Diagnosis of induction motor stator faults around rotor slot harmonics using the Matrix Pencil method

Zakaria Chedjara, Hafiz Ahmed, B. S. K. K. Ibrahim, Mohamed Benbouzid et al.
7 citations
Results in Engineering
Machine Fault Diagnosis Techniques
8.50
article

Diagnosis of induction motor stator faults around rotor slot harmonics using the Matrix Pencil method

Zakaria Chedjara, Hafiz Ahmed, B. S. K. K. Ibrahim, Mohamed Benbouzid, Chun‐Lien Su, Josep Maria Guerrero, Mohamed Abdeldjabbar Kouadria
article en
7 citations

Abstract

• Utilizes the Matrix Pencil method for high-resolution spectral analysis. • Offers superior frequency resolution, even with short acquisition times and low amplitudes. • Focuses analysis on the first rotor slot harmonics to minimize interference. • Simulation and experimental tests confirm reliability in detecting inter-turn short-circuit faults in stator windings. To improve the monitoring and diagnosis of stator faults at their early stages in induction motors, several methods have been developed, particularly parametric methods. This article thus proposes a new approach based on the Matrix Pencil method for high-resolution spectral analysis. This method aims to avoid the limitations of the classical method based on power spectral density estimation using the periodogram. Indeed, the proposed approach offers very high frequency resolution even for very short acquisition times, thus allowing improved detection even for low amplitudes. Furthermore, to optimize the calculation time of this method, the article suggests focusing the analysis only on the frequency band corresponding to the first rotor slot harmonics. This approach aims to avoid any interference with the frequency signatures of external factors, which are generally present at very low frequencies. The results obtained from simulation and experimental tests demonstrate the effectiveness and reliability of this new approach for detecting inter turns short-circuit faults in stator windings of the induction motor.

Results in EngineeringVol. 25
Centre National de la Recherche Scientifique (FR), Gulf University for Science & Technology (KW), École nationale d'ingénieurs de Brest (FR), Université IBN Khaldoun Tiaret (DZ), Institut de Recherche Dupuy de Lôme (FR), National Kaohsiung University of Science and Technology (TW), Aalborg University (DK), University of Sheffield (GB)
Affordable and clean energy
Openalex Percentile: Top 2%
Machine Fault Diagnosis Techniques
8.50
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