Utilizing Short-Time Fourier Transform for the Diagnosis of Rotor Bar Faults in Induction Motors Under Direct Torque Control
(1) Radouane Bousseksou Mail (University of El-Oued, Algeria)
(2) Noureddine Bessous Mail (University of El-Oued, Algeria)
(3) I. M. Elzein Mail (University of Doha for Science and Technology, Qatar)
(4) Mohamed Metwally Mahmoud Mail (Aswan University, Egypt)
(5) Alfian Ma'arif Mail (Universitas Ahmad Dahlan, Indonesia)
(6) * Ezzeddine Touti Mail (Northern Border University, Saudi Arabia)
(7) Ayman Al-Quraan Mail (Yarmouk University, Jordan)
(8) Noha Anwer Mail (The High Institute of Engineering and Technology, Egypt)
*corresponding author

Abstract


Industrial applications rely heavily on induction motors (IMs). Even though any IM problem can seriously impair operation, rotor bar failures (RBFs) are among the toughest to identify because of their detection challenges. RBFs in IMs can significantly impact performance, leading to reduced efficiency, increased vibrations, and potential IM failure. This research provides a thorough analysis of diagnosing these issues by detecting RBFs and evaluating their severity using three sophisticated signal processing techniques (Fast Fourier Transform (FFT), Short-Time Fourier Transform (STFT), and Discrete Wavelet Transform (DWT)). The three techniques (FFT, DWT, and STFT) are used in this work to assess the stator currents. An accurate mathematical model of the IM under RBFs serves as the basis for the simulation. The robustness of Direct Torque Control (DTC) is assessed by examining the IM's behavior in both normal and malfunctioning situations. Although the results show that DTC successfully preserves motor stability even when there are flaws, the current analysis offers some significant variation. The findings show that when it comes to identifying RBFs in IMs and determining their severity, the STFT performs better than FFT and DWT. The suggested method maintains low estimation errors and strong performance under various operating situations while providing high failure detection accuracy and the ability to discriminate between RBFs.

Keywords


Induction Motors; Signal Processing; Fault Diagnosis; Fault Severity Assessment; Direct Torque Control; Short-Time Fourier Transform (STFT)

   

DOI

https://doi.org/10.31763/ijrcs.v5i2.1886 		      

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References


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International Journal of Robotics and Control Systems
e-ISSN: 2775-2658
Website: https://pubs2.ascee.org/index.php/IJRCS
Email: ijrcs@ascee.org
Organized by: Association for Scientific Computing Electronics and Engineering (ASCEE), Peneliti Teknologi Teknik Indonesia, Department of Electrical Engineering, Universitas Ahmad Dahlan and Kuliah Teknik Elektro
Published by: Association for Scientific Computing Electronics and Engineering (ASCEE)
Office: Jalan Janti, Karangjambe 130B, Banguntapan, Bantul, Daerah Istimewa Yogyakarta, Indonesia