Work

Early detection of current faults in a squirrel cage motor using Discrete Wavelet Transform (DWT)

Year: 2025

Type: article

Abstract: 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.

Source: International Journal of Computers Communications & Control

DOI: 10.15837/ijccc.2025.3.6919

Authors: Irving García-Martínez, Mario Peña-Cabrera, Roman Osorio-Comparan, Ismael Lopez-Juarez, Oscar Molotla, Gastón Lefranc

Institutions: Universidad Nacional Autónoma de México, Autonomous University of Yucatán, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Pontificia Universidad Católica de Valparaíso

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: gold

Estimated APC paid: $539