Motors are the higher energy-conversion devices that consume around 40% of the global
electrical generated energy. Induction motors are the most popular motor type due to their …

In this paper, a hybrid approach is proposed to detect the broken rotor bar and rotor mixed
eccentricity faults of three-phase squirrel cage induction motors based on one phase of the …

Most of the published research studies for detecting induction motor broken bar faults (BBFs)
use a time-frequency (tf) decomposition tool to characterize the fault-related components …

In this article, a fault detection method based on chaos is proposed for doubly fed induction
generator (DFIG). First, the nonlinear differential equation of the DFIG is established by the …

This paper presents a design of a low-cost integrated system for the preventive detection of
unbalance faults in an induction motor. In this regard, two non-invasive measurements were …

This article addresses the issue of broken rotor bar (BRB) fault detection for induction motors
(IMs). The widely used fast Fourier transform (FFT)-based methods are sensitive to noise …

Training the load identification algorithm for a power-system monitor (PSM) begins with
characterization or observation of the loads. This article demonstrates a phase-controlled …

In this paper, an effective procedure for broken rotor bar (BRB) fault detection in a three-
phase squirrel-cage induction machine (SCIM) is proposed. This approach relies on a motor …

Ethanol adulterations include the addition of hydrated ethanol with anhydrous ethanol,
methanol, or even water. These alterations are visually imperceptible but can affect the …

This paper proposes a new Motor Image Classification (MIC) approach based on a multi-
signal conversion technique using Convolutional Neural Network (CNN). In this regard, two …