Early detection of current faults in a squirrel cage motor using Discrete Wavelet Transform (DWT)
This paper presents a new method for early detection of broken rings and bars in induction motors operating in steady state. The approach uses multispectral analysis based on the Discrete Wavelet Transform (DWT) applied to stator current analysis. A comparison is made between the results obtained using Daubechies wavelets of levels 44 and 45 (db44 and db45). The method focuses on the energetic analysis of the high-level signal decomposition coefficients to detect the presence of left sideband components, which indicate rotor faults. The experimental results demonstrate the effectiveness of the method in distinguishing between healthy and faulty motor conditions, even under light load conditions where conventional techniques often struggle.
Authors
- Mario Peña‐Cabrera (ORCID: https://orcid.org/0000-0002-0104-6559)
- Gastón Lefranc (ORCID: https://orcid.org/0000-0001-7920-4548)
- Ismael López-Juárez (ORCID: https://orcid.org/0000-0001-6405-5519)
- Román Osorio-Comparán (ORCID: https://orcid.org/0000-0002-1887-9813)
- Irving García-Martínez
- Oscar Molotla
Institutions
- Pontificia Universidad Católica de Valparaíso (CL)
- Universidad Nacional Autónoma de México (MX)
Publication Details
- Journal
- International Journal of Computers Communications & Control
- Published
- 2025-05-05
- DOI
- https://doi.org/10.15837/ijccc.2025.3.6919
- Primary Topic
- Fault Detection and Control Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Universidad Nacional Autónoma de México