From google gemini to openai q*(q-star): A survey of reshaping the generative artificial intelligence (ai) research landscape
This comprehensive survey explored the evolving landscape of generative Artificial
Intelligence (AI), with a specific focus on the transformative impacts of Mixture of Experts …
Intelligence (AI), with a specific focus on the transformative impacts of Mixture of Experts …
Small data challenges for intelligent prognostics and health management: a review
Prognostics and health management (PHM) is critical for enhancing equipment reliability
and reducing maintenance costs, and research on intelligent PHM has made significant …
and reducing maintenance costs, and research on intelligent PHM has made significant …
Dual-threshold attention-guided GAN and limited infrared thermal images for rotating machinery fault diagnosis under speed fluctuation
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 …
samples is challenging in industrial practice. The existing limited samples methods usually …
Few shot cross equipment fault diagnosis method based on parameter optimization and feature mertic
H Tao, L Cheng, J Qiu… - Measurement Science and …, 2022 - iopscience.iop.org
With the rapid development of industrial informatization and deep learning technology,
modern data-driven fault diagnosis (MIFD) methods based on deep learning have been …
modern data-driven fault diagnosis (MIFD) methods based on deep learning have been …
Attention-based deep meta-transfer learning for few-shot fine-grained fault diagnosis
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 …
years; however, most of these methods are coarse grained and data demanding that cannot …
Intelligent machinery fault diagnosis with event-based camera
Event-based cameras are the emerging bioinspired technology in vision sensing. Different
from the traditional standard cameras, the event-based cameras asynchronously record the …
from the traditional standard cameras, the event-based cameras asynchronously record the …
Prior knowledge-embedded meta-transfer learning for few-shot fault diagnosis under variable operating conditions
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 …
development thanks to its powerful feature representation ability. However, scarcity of high …
Digital twin-assisted enhanced meta-transfer learning for rolling bearing fault diagnosis
L Ma, B Jiang, L Xiao, N Lu - Mechanical Systems and Signal Processing, 2023 - Elsevier
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 …
and the combination of working conditions and fault fluctuations increases the complexity of …
A comprehensive survey of sparse regularization: Fundamental, state-of-the-art methodologies and applications on fault diagnosis
Q Li - Expert Systems with Applications, 2023 - Elsevier
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 …
past few decades. By exploiting the latent data structure in low-dimensional subspaces, a …
Few-shot learning for fault diagnosis with a dual graph neural network
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 …
manufacturing systems. Deep learning-based methods have been recently developed for …