Domain generalization for cross-domain fault diagnosis: An application-oriented perspective and a benchmark study
Most data-driven methods for fault diagnostics rely on the assumption of independently and
identically distributed data of training and testing. However, domain shift between the …
identically distributed data of training and testing. However, domain shift between the …
A systematic literature review on transfer learning for predictive maintenance in industry 4.0
The advent of Industry 4.0 has resulted in the widespread usage of novel paradigms and
digital technologies within industrial production and manufacturing systems. The objective of …
digital technologies within industrial production and manufacturing systems. The objective of …
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 …
An integrated multitasking intelligent bearing fault diagnosis scheme based on representation learning under imbalanced sample condition
Accurate bearing fault diagnosis is of great significance of the safety and reliability of rotary
mechanical system. In practice, the sample proportion between faulty data and healthy data …
mechanical system. In practice, the sample proportion between faulty data and healthy data …
Explainable graph wavelet denoising network for intelligent fault diagnosis
Deep learning (DL)-based intelligent fault diagnosis methods have greatly promoted the
development of the field of fault diagnosis due to their powerful feature extraction ability for …
development of the field of fault diagnosis due to their powerful feature extraction ability for …
A domain generalization network combing invariance and specificity towards real-time intelligent fault diagnosis
Abstract Domain adaptation-based fault diagnosis (DAFD) methods have been explored to
address cross-domain fault diagnosis problems, where distribution discrepancy exists …
address cross-domain fault diagnosis problems, where distribution discrepancy exists …
Cross-domain augmentation diagnosis: An adversarial domain-augmented generalization method for fault diagnosis under unseen working conditions
Intelligent fault diagnosis based on domain adaptation has recently been extensively
researched to promote reliability of safety-critical assets under different working conditions …
researched to promote reliability of safety-critical assets under different working conditions …
Domain fuzzy generalization networks for semi-supervised intelligent fault diagnosis under unseen working conditions
In recent years, domain adaptation methods have made remarkable achievements in fault
diagnosis under variable working conditions. However, the methods usually fail when target …
diagnosis under variable working conditions. However, the methods usually fail when target …
Federated adversarial domain generalization network: A novel machinery fault diagnosis method with data privacy
Abstract Domain generalization (DG) methods have been successfully proposed to enhance
the generalization ability of the intelligent diagnosis model. However, these methods hardly …
the generalization ability of the intelligent diagnosis model. However, these methods hardly …
Domain augmentation generalization network for real-time fault diagnosis under unseen working conditions
Y Shi, A Deng, M Deng, M Xu, Y Liu, X Ding… - Reliability Engineering & …, 2023 - Elsevier
Recent years have witnessed the successful development of domain adaptation methods to
tackle cross-domain fault diagnosis problems. However, these methods require the target …
tackle cross-domain fault diagnosis problems. However, these methods require the target …