Detailed Analysis of the Strengths of EEMD and VMD Techniques for Bearing Fault Detection
The detection of faults in induction machines (IMs) is crucial for maintaining their optimal performance and extending their lifespan. Bearing faults, in particular, can have a significant impact on the efficiency and reliability of these machines. Ensemble Empirical Mode Decomposition (EEMD) is an appropriate technique for monitoring bearing health in IMs. This work is to evaluate the effectiveness of EEMD. The aim is to see in which level this technique can enhance the efficiency of bearing fault diagnosis. Our experimental findings indicate that EEMD exhibits greater effectiveness than VMD.
Authors
- Salim Sbaa (ORCID: https://orcid.org/0000-0003-4256-8641)
- Noureddine Bessous (ORCID: https://orcid.org/0000-0002-7290-6683)
- Ahmed Chaouki Megherbi (ORCID: https://orcid.org/0000-0002-9262-6806)
- Yasser Damine (ORCID: https://orcid.org/0000-0002-8480-8378)
Institutions
- University of Biskra (DZ)
- Centre Hospitalo-Universitaire Bab El Oued (DZ)
Publication Details
- Journal
- Algerian Journal of Signals and Systems
- Published
- 2024-12-30
- DOI
- https://doi.org/10.51485/ajss.v9i4.246
- Primary Topic
- Machine Fault Diagnosis Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00