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 …

The research on intelligent fault diagnosis has yielded remarkable achievements based on
artificial intelligence-related technologies. In engineering scenarios, machines usually work …

As one of the representative unsupervised data augmentation methods, generative
adversarial networks (GANs) have the potential to solve the problem of insufficient samples …

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 …

Although the existing generative adversarial networks (GAN) have the potential for data
augmentation and intelligent fault diagnosis of planetary gearbox, it remains difficult to deal …

The existing intelligent fault diagnosis methods of rotor-bearing system mainly focus on
vibration analysis under steady operation, which has low adaptability to new scenes. In this …

Prognostics and health management (PHM) is an enabling technology used to maintain the
reliable, efficient, economic and safe operation of engineering equipment, systems and …

Deep learning applications have been thriving over the last decade in many different
domains, including computer vision and natural language understanding. The drivers for the …

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

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 …