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 …

Tool condition monitoring (TCM) in machining operations is crucial to maximise the useful
tool life while reducing the risks associated with tool breakage. Unlike progressive tool wear …

In recent years, swarm intelligence algorithms have received extensive attention and
research. Swarm intelligence algorithms are a biological heuristic method, which is widely …

The tremendous success of deep learning and transfer learning broadened the scope of
fault diagnosis, especially the latter further improved the diagnosis accuracy under multiple …

Attention Mechanism has become very popular in the field of mechanical fault diagnosis in
recent years and has become an important technique for scholars to study and apply. The …

Outstanding steps towards intelligent transportation systems with autonomous vehicles have
been taken in the past few years. Nevertheless, the safety issue in autonomous vehicles is …

The advances of intelligent fault diagnosis in recent years show that deep learning has
strong capability of automatic feature extraction and accurate identification for fault signals …

Intelligent fault diagnosis has been a promising way for condition-based maintenance.
However, the small sample problem has limited the application of intelligent fault diagnosis …

Data-driven methods have prominently featured in the progressive research and
development of modern condition monitoring systems for electrical machines. These …

Aiming at the application of deep learning in fault diagnosis, mechanical rotating equipment
components are prone to failure under complex working environment, and the industrial big …