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A new diagnostic method based on support vector machine for short circuit winding faults in induction motors Hicham Zaimen; Tawfik Thelaidjia; Makhlouf Chouki; Abdurrahman Ünsal
International Journal of Electrical and Computer Engineering (IJECE) Vol 16, No 4: August 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v16i4.pp1735-1754

Abstract

Inter-turn short circuits (ITSCs) in induction motor (IM) windings are among the most critical and frequent faults in industrial environments, as they can rapidly evolve into severe damage, leading to unplanned downtime and costly maintenance. To enhance the reliability of IMs, this paper proposes a machine learning–based diagnosis method dedicated to ITSC failures. The developed diagnostic tool combines a support vector machine (SVM) classifier with Fisher’s ratio (FR)-based feature selection. The proposed framework uses experimentally acquired current signals under healthy conditions and five ITSC fault severity levels (1%–5%), evaluated across four load conditions (25%, 50%, 75%, and 100%). Each signal is segmented into 200 non-overlapping segments (500 samples each), from which nine time-domain features are extracted to capture fault-related characteristics. These features are then used for training and testing a SVM classifier capable of distinguishing between healthy states and levels of severity of ITSC faults. To optimize the classification process, the Fisher’s ratio (FR) algorithm is employed to select the most informative features while discarding those with low relevance. Our findings unveiled that the proposed hybrid FR-SVM-based diagnosis achieves high diagnostic accuracy ranging from 99.54% to 100%. Furthermore, the outcomes prove that the integrated technical framework (time-domain features + FR + SVM) provides zero false alarms and a balanced diagnostic system that combines computational speed with high precision.
Impact of an SVC device on voltage and transient stability in power systems Makhlouf Chouki; Hicham Zaimen; Hassen Belila
International Journal of Applied Power Engineering (IJAPE) Vol 15, No 3: September 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v15.i3.pp975-984

Abstract

The increasing complexity of modern electrical networks, driven by the expansion of transmission networks along with the increasing penetration of renewable-based generation, has intensified concerns regarding voltage control performance and rotor-angle stability. Flexible AC transmission system (FACTS) technology, particularly the shunt-connected static var compensator (SVC), offers effective solutions for enhancing system performance through dynamic reactive power support. This study examines the effect of SVC integration on voltage regulation performance as well as rotor-angle stability within electrical transmission networks. The study is conducted using MATLAB and the electrical network analysis toolbox (PSAT) on IEEE 5-bus, 14-bus, and 9-bus benchmark systems. Voltage stability performance is evaluated under transmission line outage conditions, while rotor-angle stability is assessed through critical clearing time (CCT) analysis during balanced three-phase faults. The simulation results demonstrate that the incorporation of an SVC considerably improves voltage profiles, reduces active and reactive power losses, and enhances system resilience under disturbed operating conditions. Furthermore, the SVC increases the critical clearing time and improves post-fault dynamic behavior, contributing to better preservation of generator synchronism. The presented results confirm that SVC-based compensation provides an effective and practical solution for strengthening both voltage control performance and rotor-angle stability reserves in power transmission systems.