Applications of unsupervised deep transfer learning to intelligent fault diagnosis: A survey and comparative study
Recent progress on intelligent fault diagnosis (IFD) has greatly depended on deep
representation learning and plenty of labeled data. However, machines often operate with …
representation learning and plenty of labeled data. However, machines often operate with …
A review of data-driven machinery fault diagnosis using machine learning algorithms
J Cen, Z Yang, X Liu, J Xiong, H Chen - Journal of Vibration Engineering & …, 2022 - Springer
Purpose This article aims to systematically review the recent research advances in data-
driven machinery fault diagnosis based on machine learning algorithms, and provide …
driven machinery fault diagnosis based on machine learning algorithms, and provide …
Collaborative fault diagnosis of rotating machinery via dual adversarial guided unsupervised multi-domain adaptation network
Most of the existing research on unsupervised cross-domain intelligent fault diagnosis is
based on single-source domain adaptation, which fails to simultaneously utilize various …
based on single-source domain adaptation, which fails to simultaneously utilize various …
Novel joint transfer network for unsupervised bearing fault diagnosis from simulation domain to experimental domain
Unsupervised cross-domain fault diagnosis of bearings has practical significance; however,
the existing studies still face some problems. For example, transfer diagnosis scenarios are …
the existing studies still face some problems. For example, transfer diagnosis scenarios are …
Out-of-distribution detection-assisted trustworthy machinery fault diagnosis approach with uncertainty-aware deep ensembles
Recent intelligent fault diagnosis technologies can effectively identify the machinery health
condition, while they are learnt based on a closed-world assumption, ie, the training and …
condition, while they are learnt based on a closed-world assumption, ie, the training and …
Bayesian variational transformer: A generalizable model for rotating machinery fault diagnosis
Transformer has been widely applied in the research of rotating machinery fault diagnosis
due to its ability to explore the internal correlation of vibration signals. However, challenges …
due to its ability to explore the internal correlation of vibration signals. However, challenges …
Fault transfer diagnosis of rolling bearings across multiple working conditions via subdomain adaptation and improved vision transformer network
P Liang, Z Yu, B Wang, X Xu, J Tian - Advanced Engineering Informatics, 2023 - Elsevier
Due to often working in the environment of variable speeds and loads, it is an enormous
challenge to achieve high-accuracy fault diagnosis (FD) of rolling bearings (RB) via existing …
challenge to achieve high-accuracy fault diagnosis (FD) of rolling bearings (RB) via existing …
A multi-source weighted deep transfer network for open-set fault diagnosis of rotary machinery
In real industries, there often exist application scenarios where the target domain holds fault
categories never observed in the source domain, which is an open-set domain adaptation …
categories never observed in the source domain, which is an open-set domain adaptation …
Multisource domain feature adaptation network for bearing fault diagnosis under time-varying working conditions
Intelligent fault diagnosis methods based on domain adaptation (DA) have been extensively
employed for tackling domain shift problems, and the basic diagnosis tasks under time …
employed for tackling domain shift problems, and the basic diagnosis tasks under time …
Intelligent fault diagnosis of rolling bearings under varying operating conditions based on domain-adversarial neural network and attention mechanism
H Wu, J Li, Q Zhang, J Tao, Z Meng - ISA transactions, 2022 - Elsevier
As a domain adaptation method, the domain-adversarial neural network (DANN) can utilize
the adversarial learning of the feature extractor and domain discriminator to extract the …
the adversarial learning of the feature extractor and domain discriminator to extract the …