Due to the growing interest for increasing productivity and cost reduction in industrial
environment, new techniques for monitoring rotating machinery are emerging. Artificial …

The monitoring of rotating machinery is an essential task in today's production processes.
Currently, several machine learning and deep learning-based modules have achieved …

Analyzing vibration data using deep neural networks is an effective way to detect damages
in rotating machinery at an early stage. However, the black-box approach of these methods …

Rotating machinery plays a key role in mechanical equipment, and the fault diagnosis of
rotating machinery is a popular research topic. To overcome the dependency on expert …

Intelligent fault diagnosis achieves tremendous success in machine fault diagnosis because
of its outstanding data-driven capability. However, the severely imbalanced dataset in …

The imbalanced dataset in actual engineering negatively affects the precision of fault
diagnosis because of the severe lack of collected fault data. To effectively address this issue …

Fault diagnosis plays an essential role in reducing the maintenance costs of rotating
machinery manufacturing systems. In many real applications of fault detection and …

The fault diagnostics of rotating components are crucial for most mechanical systems since
the rotating components faults are the main form of failures of many mechanical systems. In …

Recently, substantial research has explored the development of deep-learning-based
methods to diagnose faults in rotating machinery. For these diagnosis methods, it is difficult …

As failures in rotating machines can have serious implications, the timely detection and
diagnosis of faults in these machines is imperative for their smooth and safe operation …