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All Journal Journal Geuthee of Engineering and Energy
Syariffudin, Muhammad Alif Sofi
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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Application of fourier transform for early detection of bearing failures in electric motors Prenata, Giovanni Dimas; Syariffudin, Muhammad Alif Sofi; Widagdo, Reza Sarwo
Journal Geuthee of Engineering and Energy Vol 5, No 1 (2026): Journal Geuthee of Engineering and Energy
Publisher : Geuthèë Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52626/joge.v5i1.69

Abstract

This study presents an analysis of bearing fault conditions in electric motors through stator current measurements and their transformation into the frequency domain. Measurements were conducted under two main bearing conditions: normal and damaged, each tested with three load variations (no load, generator load, and generator load with one lamp). The time-domain current waveforms showed minimal visual distinction between normal and damaged bearing conditions, making classification difficult. Therefore, the current data were transformed into the frequency domain using the Discrete Fourier Transform (DFT). The frequency domain analysis revealed that in normal bearing conditions, the frequency magnitude distribution was relatively stable and symmetrical, with low fluctuation in the frequency index range k = 0 to k = 10. In contrast, damaged bearing conditions exhibited larger and irregular fluctuations in frequency magnitude across different load levels, indicating a distinct signature of bearing failure. Consequently, frequency domain analysis proves to be an effective approach for detecting bearing faults based on the spectral characteristics of motor current signals.
Co-Authors Prenata, Giovanni Dimas Reza Sarwo Widagdo