Uninterrupted and trouble-free operation of induction motors (IMs) is the compulsion of the
modern industries. Firstly, the paper reviews the conventional time and spectrum signal …

Background An induction motor is at the heart of every rotating machine and hence it is a
very vital component. Almost in every industry, around 90% of the machines apply an …

The fault monitoring and diagnosis of industrial machineries are very significant in Industry
4.0 revolution but are often complicated and labour intensive. The application of artificial …

The working conditions of rolling bearings usually is very complex, which makes it difficult to
diagnose rolling bearing faults. In this paper, a novel method called the adaptive deep …

Intelligent fault diagnosis techniques cross rotating machines have great significances in
theory and engineering For this purpose, this paper presents a novel method using novel …

It is well known that the most common reason for electrical machines breakdown is the stator
windings' fault occurrence. Indeed, this type of fault represents almost 40% of faults …

This paper proposes an improved diagnosis method for early detection and localization of
Inter-Turn Short Circuit (ITSC) faults in the stator winding of the induction motor (IM). The …

Using deep learning in three-phase induction motor fault diagnosis has gained increasing
interest nowadays. This paper proposes a Convolutional Neural Network (CNN) model to …

Induction motors constitute the largest proportion of motors in industry. This type of motor
experiences different types of failures, such as broken bars, eccentricity, and inter-turn …

This paper proposes an imbalance fault detection method based on data normalization and
Empirical Mode Decomposition (EMD) for variable speed direct-drive Marine Current …