As a general and rigid mathematical tool, wavelet theory has found many applications and is
constantly developing. This article reviews the development history of wavelet theory, from …

Fault diagnosis of induction motor is an important task for both the researchers and industry.
The interturn fault is one of the frequented faults and accounts for more than 37% of the …

In this article, a deep learning-based automated framework has been proposed to sense
minor stator winding interturn (MSIT) fault in an induction motor (IM) without having load …

Wind turbines are increasingly expanding worldwide and Doubly‐Fed Induction Generator
(DFIG) is a key component of most of them. Stator winding fault is a major fault in this …

A two-layer soft voting ensemble machine learning based algorithm for the diagnosis of turn-
to-turn faults in the stator winding of three-phase induction motors is presented. The …

Abstract Artificial Neural Network (ANN) has been used extensively and constantly
developed. The combination of wavelet transform theory and the neural network has …

The objective of this article isto developa comprehensive mathematical model of a three-
phase induction motor to facilitate stator interturn (SIT) fault related study. A detailed …

Induction motor fault diagnosis and condition monitoring are on the anvil of researchers,
who have reported many studies and developments in the literature. However, the reported …

Electromagnetic coils are indispensable components for energy conversion and
transformation in various systems across industries. However, electromagnetic coil …

Induction motors are important equipment in industrial production processes. To solve the
problem of characteristic harmonics overlapping when there is deterioration in different parts …