With the rapid development of industry, fault diagnosis plays a more and more important role
in maintaining the health of equipment and ensuring the safe operation of equipment. Due to …

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 …

Rolling bearing fault detection is critical for improving production efficiency and lowering
accident rates in complicated mechanical systems, as well as huge monitoring data, posing …

This article develops new deep learning methods, namely, deep residual shrinkage
networks, to improve the feature learning ability from highly noised vibration signals and …

With the rapid development of manufacturing industry, machine fault diagnosis has become
increasingly significant to ensure safe equipment operation and production. Consequently …

Vibration measurement and monitoring are essential in a wide variety of applications.
Vibration measurements are critical for diagnosing industrial machinery malfunctions …

With the popularization of the intelligent manufacturing, much attention has been paid in
such intelligent computing methods as deep learning ones for machinery fault diagnosis …

The data-driven methods in machinery fault diagnosis have become increasingly popular in
the past two decades. However, the wide applications of this scheme are generally …

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

Accurate fault diagnosis is critical to ensure the safe and reliable operation of rotating
machinery. Data-driven fault diagnosis techniques based on Deep Learning (DL) have …