Intelligent fault diagnosis (IFD) refers to applications of machine learning theories to
machine fault diagnosis. This is a promising way to release the contribution from human …

In this survey paper, we systematically summarize existing literature on bearing fault
diagnostics with deep learning (DL) algorithms. While conventional machine learning (ML) …

Deep learning (DL) architecture, which exploits multiple hidden layers to learn hierarchical
representations automatically from massive input data, presents a promising tool for …

The paper presents description of bearing, stator and rotor fault diagnostic methods of a
single-phase induction motor. The presented methods use acoustic signals. Five states of …

Efficient fault diagnosis of electrical and mechanical anomalies in induction motors (IMs) is
challenging but necessary to ensure safety and economical operation in industries …

Smart Grid (SG) is a multidisciplinary concept related to the power system update and
improvement. SG implies real-time information with specific communication requirements …

Faults and failures in the system components are two main reasons for the instability and the
degradation in control performance. In recent decades, fault-tolerant control (FTC) …

In this paper, we review the state of the art in the detection, location, and diagnosis of faults
in electrical wiring interconnection systems (EWIS) including in the electric power grid and …

Induction motor is a major component in the industrial sector. It is experiencing great
development concerning size, market share, and technological design. Any sudden failure …

Abstract Intelligent Fault-Tolerant Control (IFTC) refers to the applications of machine
learning algorithms for fault diagnosis and design of Fault-Tolerant Control (FTC). The …