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 …

The traditional deep learning-based bearing fault diagnosis approaches assume that the
training and test data follow the same distribution. This assumption, however, is not always …

Simple Summary Deep learning has succeeded greatly in medical image-based cancer
diagnosis. To help readers better understand the current research status and ideas, this …

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

Cross-domain machinery fault diagnosis aims to transfer enriched diagnosis knowledge
from a labeled source domain to a new unlabeled target domain. Most existing methods …

The scope of data-driven fault diagnosis models is greatly extended through deep learning
(DL). However, the classical convolution and recurrent structure have their defects in …

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 …

Digital twin can be defined as a virtual representation of a physical asset enabled through
data and simulators for real-time prediction, optimization, monitoring, controlling, and …

Recently, intelligent fault diagnosis has made great achievements, which has aroused
growing interests in the field of bearing fault diagnosis due to its strong feature learning …

A smart factory is a highly digitized and connected production facility that relies on smart
manufacturing. Additionally, artificial intelligence is the core technology of smart factories …