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Rotor Fault Detection in Squirrel Cage Induction Motors using MCSA and DWT Techniques
Noureddine Bessous, Salim Sbaa, Remus Pusca, Raphaël Romary

Rotor Fault Detection in Squirrel Cage Induction Motors using MCSA and DWT Techniques

Science & Mathematics Published 2021 Verification Pending

Overview & Synopsis

This article presents the fault detection of broken rotor bar (BRB) faults in squirrel cage induction motors (SCIMs). This work applied two diagnostic methods on stator current signal. It is necessary to verify the machine health to avoid any catastrophic damage. The first method uses the fast Fourier transform (FFT) which is generally called motor current signature analysis (MCSA). We carefully verified the spectral content of the stator current to detect BRB fault. The new harmonics allows us to take a good decision about BRB fault. The second method is based on the discrete wavelet transform (DWT). This technique is widely used in the diagnosis field of rotating machinery. According to DWT method, we used the mean square error (MSE) as a good indicator. An experimental test with different conditions of the induction motor has been performed. The experimental results have been exploited using MCSA and DWT methods to achieve a good decision.

Indexed from repository: HAL Open Science (hal.science)
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Document Information

Document Title Rotor Fault Detection in Squirrel Cage Induction Motors using MCSA and DWT Techniques
Author / Organization Noureddine Bessous, Salim Sbaa, Remus Pusca, Raphaël Romary
Subject & Discipline Multidisciplinary Academic Open Research
Categories Science & Mathematics
Publication Year 2021
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website HAL Open Science (hal.science)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-193776
Original Source Link Visit Source Page on hal.science »