Work

Detailed Analysis of the Strengths of EEMD and VMD Techniques for Bearing Fault Detection

Year: 2024

Type: article

Abstract: 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.

Source: Algerian Journal of Signals and Systems

DOI: 10.51485/ajss.v9i4.246

Authors: Yasser Damine, Ahmed Chaouki Megherbi, Salim Sbaa, Noureddine Bessous

Institutions: University of Biskra, University of Eloued

Language: English

Topic: Machine Fault Diagnosis Techniques

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: diamond

OpenAlex ID: W4405901226

FWCI:

Cites: 9

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Related to: 10