In this paper, the motor current/voltage signature analysis and linear discriminant analysis
(LDA) are evaluated with respect to the accuracy to detect the status of permanent magnet …

In this article, an effective machine learning-based fault diagnosis method is developed for
induction motors driven by variable frequency drives (VFDs). Two identical 0.25 HP …

Broken rotor bar/end-ring and eccentricity are common faults in squirrel-cage induction
motors and have been thoroughly investigated in the case of ac grid supply. In this paper …

In this study, a new method was presented for the detection of a static eccentricity fault in a
closed loop operating induction motor driven by inverter. Contrary to the motors supplied by …

The main objective of this paper is to propose a method to detect the presence of a fault in
Permanent Magnet Synchronous Machines (PMSMs), determine the type of that fault and …

In this article, an analysis of variance (ANOVA)-based fault diagnosis approach using
experimental data is proposed for variable frequency drive (VFD)-fed induction motors. Line …

In this paper, an effective machine learning based fault diagnosis method is developed for
induction motors fed by variable frequency drives (VFDs). Two identical 0.25 HP induction …

DOI: 10.5152/iujeee. 2018.1821 In this paper, a 2.2 kW squirrel cage induction motor having
different degrees of static eccentricity is analyzed for fault detection using multi-resolution …

The paper performs a comparative study of Arti-ficial Neural Networks (ANNs) and
Convolutional Neural Networks (CNNs) for the classification of Static Eccentricity (SE) and …

Preventing mechanical faults in motors is often impossible, early detection of air gap
eccentricity faults in induction motors is critical in preventing damage to the machine …