The problem of failures in induction motors is a large concern due to its significant influence over industrial production. Therefore a large number of detection techniques were presented to avoid this problem. This paper presents the comparison results of induction motor rotor fault detection using three methods: motor current signature analysis (MCSA), surface vibration (SV), and instantaneou...

Induction motors are critical components in industrial processes since their failure usually lead to an unexpected interruption at the industrial plant. The condition monitoring of the induction motors have been a challenging topic for many electrical machine researchers. Indeed, the effectiveness of the fault diagnosis and prognosis techniques depends very much on the quality of the fault feat...

Motor current signature analysis has become a widespread fault diagnosis technique for induction machines (IMs), because it is noninvasive and requires low resources of hardware (a sensor) software fast Fourier transform). Nevertheless, its industrial application faces practical problems. One most challenging scenarios the detection broken bars in IMs working at very slip, like large with small...

The lethal disease amyotrophic lateral sclerosis (ALS) is characterized by the loss of somatic motor neurons. However, not all motor neurons are equally vulnerable to disease; certain groups are spared, including those in the oculomotor nucleus controlling eye movement. The reasons for this differential vulnerability remain unknown. Here we have identified a protein signature for resistant ocul...

This paper proposes a fault-detection system for faulty induction motors (bearing faults, interturn shorts, and broken rotor bars) based on multiresolution analysis (MRA), correlation fitness values-based feature selection (CFFS), artificial neural network (ANN). First, this study compares two feature-extraction methods: the MRA Hilbert Huang transform (HHT) induction-motor-current signature an...

This paper presents a novel approach to current signature analysis based on wavelet transform of the stator current. The proposed method lies in the fact that by using wavelet transform, the inherent non-stationary nature of stator current can be accurately considered. The key characteristics of the proposed method are its ability to provide feature representations of multiple frequency resolut...