A survey on fault diagnosis of rolling bearings
The failure of a rolling bearing may cause the shutdown of mechanical equipment and even
induce catastrophic accidents, resulting in tremendous economic losses and a severely …
induce catastrophic accidents, resulting in tremendous economic losses and a severely …
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 …
A novel method based on meta-learning for bearing fault diagnosis with small sample learning under different working conditions
H Su, L Xiang, A Hu, Y Xu, X Yang - Mechanical Systems and Signal …, 2022 - Elsevier
Recently, intelligent fault diagnosis has made great achievements, which has aroused
growing interests in the field of bearing fault diagnosis due to its strong feature learning …
growing interests in the field of bearing fault diagnosis due to its strong feature learning …
Meta-learning as a promising approach for few-shot cross-domain fault diagnosis: Algorithms, applications, and prospects
Y Feng, J Chen, J Xie, T Zhang, H Lv, T Pan - Knowledge-Based Systems, 2022 - Elsevier
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 …
strong capability of automatic feature extraction and accurate identification for fault signals …
A fault diagnosis method using improved prototypical network and weighting similarity-Manhattan distance with insufficient noisy data
C Wang, J Yang, B Zhang - Measurement, 2024 - Elsevier
Currently, few samples and the inevitable noise poses a severe test on deep learning
methods. To solve the above problems, a novel fault diagnosis network based on a refined …
methods. To solve the above problems, a novel fault diagnosis network based on a refined …
Meta-learning approaches for learning-to-learn in deep learning: A survey
Y Tian, X Zhao, W Huang - Neurocomputing, 2022 - Elsevier
Compared to traditional machine learning, deep learning can learn deeper abstract data
representation and understand scattered data properties. It has gained considerable …
representation and understand scattered data properties. It has gained considerable …
Task-sequencing meta learning for intelligent few-shot fault diagnosis with limited data
Recently, deep learning-based intelligent fault diagnosis methods have been developed
rapidly, which rely on massive data to train the diagnosis model. However, it is usually …
rapidly, which rely on massive data to train the diagnosis model. However, it is usually …
Few-shot fault diagnosis of turnout switch machine based on semi-supervised weighted prototypical network
The turnout switch machine is a critical equipment of the signal system, which has a
significant influence on the safety of train. However, it is difficult to obtain a mass of labeled …
significant influence on the safety of train. However, it is difficult to obtain a mass of labeled …
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 …