Interpretable physics-informed domain adaptation paradigm for cross-machine transfer diagnosis
C He, H Shi, X Liu, J Li - Knowledge-Based Systems, 2024 - Elsevier
While transfer learning-based intelligent diagnosis has achieved significant breakthroughs,
the performance of existing well-known methods still needs urgent improvement, given the …
the performance of existing well-known methods still needs urgent improvement, given the …
A novel noise-aided fault feature extraction using stochastic resonance in a nonlinear system and its application
The fault features of rolling bearings under time-varying speed conditions (TVSCs) are often
submerged in strong noise. For one thing, the system parameters of stochastic resonance …
submerged in strong noise. For one thing, the system parameters of stochastic resonance …
Interpretable modulated differentiable STFT and physics-informed balanced spectrum metric for freight train wheelset bearing cross-machine transfer fault diagnosis …
C He, H Shi, R Li, J Li, ZJ Yu - arXiv preprint arXiv:2406.11917, 2024 - arxiv.org
The service conditions of wheelset bearings has a direct impact on the safe operation of
railway heavy haul freight trains as the key components. However, speed fluctuation of the …
railway heavy haul freight trains as the key components. However, speed fluctuation of the …
Classifier-guided neural blind deconvolution: a physics-informed denoising module for bearing fault diagnosis under heavy noise
Blind deconvolution (BD) has been demonstrated as an efficacious approach for extracting
bearing fault-specific features from vibration signals under strong background noise. Despite …
bearing fault-specific features from vibration signals under strong background noise. Despite …
Residual Shrinkage ViT with Discriminative Rebalancing Strategy for Small and Imbalanced Fault Diagnosis
L Zhang, S Gu, H Luo, L Ding, Y Guo - Sensors, 2024 - mdpi.com
In response to the challenge of small and imbalanced Datasets, where the total Sample size
is limited and healthy Samples significantly outweigh faulty ones, we propose a diagnostic …
is limited and healthy Samples significantly outweigh faulty ones, we propose a diagnostic …
PSNN-TADA: Prototype and Stochastic Neural Network Based Twice Adversarial Domain Adaptation for Fault Diagnosis Under Varying Working Conditions
X Yang, X Yuan, T Ye, W Zhu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The varying working conditions of rolling bearings lead to data distribution shifts, which
presents an obstacle to intelligent fault diagnosis. To alleviate the performance degradation …
presents an obstacle to intelligent fault diagnosis. To alleviate the performance degradation …
Modulated differentiable STFT and balanced spectrum metric for freight train wheelset bearing cross-machine transfer monitoring under speed fluctuations
C He, H Shi, R Li, J Li, ZJ Yu - Advanced Engineering Informatics, 2024 - Elsevier
The service conditions of wheelset bearings has a direct impact on the safe operation of
railway heavy haul freight trains as the key components. However, speed fluctuation of the …
railway heavy haul freight trains as the key components. However, speed fluctuation of the …
Heterogeneous Federated Domain Generalization Network With Common Representation Learning for Cross-Load Machinery Fault Diagnosis
Various federated transfer learning (FTL) methods have been proposed to address domain
shift and safeguard data privacy in the field of fault diagnosis. However, the effectiveness of …
shift and safeguard data privacy in the field of fault diagnosis. However, the effectiveness of …
Towards multi-scene learning: A novel cross-domain adaptation model based on sparse filter for traction motor bearing fault diagnosis in high-speed EMU
Fault diagnosis of traction motor bearing is of great significance to improve the reliability and
safety of high-speed electric multiple units (EMU). While the fault diagnosis method based …
safety of high-speed electric multiple units (EMU). While the fault diagnosis method based …
ISEANet: An interpretable subdomain enhanced adaptive network for unsupervised cross-domain fault diagnosis of rolling bearing
B Liu, C Yan, Y Liu, M Lv, Y Huang, L Wu - Advanced Engineering …, 2024 - Elsevier
Abstract Unsupervised Domain Adaptation (UDA) has gained widespread application in
bearing fault diagnosis across various operational conditions, attributed to its commendable …
bearing fault diagnosis across various operational conditions, attributed to its commendable …