Electric motors find widespread application across various industrial fields. The pursuit of
enhanced comprehensive electric motors performance has consistently drawn significant …

This article provides a comprehensive overview of state-of-the-art techniques for detecting
and diagnosing stator winding inter-turn short faults (ITSFs) in permanent-magnet …

Health condition monitoring of induction motors is important because of their vital role and
wide us in a variety of industries. A stator inter-turn fault (SITF) is considered to be the most …

The three-phase induction motor is well suited for a wide range of mobile drives, specifically
for electric vehicle powertrain. During the entire life cycle of the electric motor, some types of …

This paper presents an investigation study of seven Machine Learning Algorithms (MLAs) for
Breast Cancer (BC) diagnosis. These algorithms are: Decision Tree (DT), Discriminated …

Induction motor fault diagnosis and condition monitoring are on the anvil of researchers,
who have reported many studies and developments in the literature. However, the reported …

The locally optimized chirplet spectrogram (LOCS) is a novel method proposed in this work
for generating a high-resolution and cost-effective spectrogram of the induction machine (IM) …

Detecting stator failure is crucial for maintaining reliability in manufacturing processes. The
diagnosis in the early stages is challenging, and the industrial environment imposes even …

This paper introduces an active fault-tolerant control system designed to effectively detect
and mitigate inter-turn short-circuit (ITSC) faults in asynchronous machines. Utilizing the …

This paper aims to diagnose the Broken Rotor Bars (BRBs) fault in a three-phase induction
machine using seven Machine Learning Algorithms (MLAs), which are respectively Support …