This comprehensive survey explored the evolving landscape of generative Artificial
Intelligence (AI), with a specific focus on the transformative impacts of Mixture of Experts …

Sparse regularization has been attracting much attention in industrial applications over the
past few decades. By exploiting the latent data structure in low-dimensional subspaces, a …

End-to-end intelligent diagnosis of rotating machinery under speed fluctuation and limited
samples is challenging in industrial practice. The existing limited samples methods usually …

With the rapid development of industrial informatization and deep learning technology,
modern data-driven fault diagnosis (MIFD) methods based on deep learning have been …

Event-based cameras are the emerging bioinspired technology in vision sensing. Different
from the traditional standard cameras, the event-based cameras asynchronously record the …

Deep learning-based fault diagnosis methods have made tremendous progress in recent
years; however, most of these methods are coarse grained and data demanding that cannot …

Mechanical fault diagnosis is crucial to ensure the safe operations of equipment in intelligent
manufacturing systems. Deep learning-based methods have been recently developed for …

Fault diagnosis of bearing under variable working conditions is widely required in practice,
and the combination of working conditions and fault fluctuations increases the complexity of …

Deep learning-based fault diagnosis models constructed from imbalanced datasets would
meet severe performance degradation when the number of samples for fault classes is much …

In recent years, intelligent fault diagnosis based on deep learning has achieved vigorous
development thanks to its powerful feature representation ability. However, scarcity of high …