宋艳
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Paper Publications
- [1] 宋艳. Federated Domain Generalization Based on Gaussian Mapping and Constrained Quadratic Programming for Rotating Machinery Fault Diagnosis. 75, 2026.
- [2] 从霄. Multi-scale Gaussian feature enhancement and prototype graph convolutional network for domain-generalized rolling bearing fault diagnosis. Expert Systems with Applications, 296, 2026.
- [3] . A global information-guided denoising diffusion probabilistic model for fault diagnosis with imbalanced data. Engineering Applications of Artificial Intelligence, 147, 2025.
- [4] 宋艳. Fault Diagnosis in Rolling Bearings Using Multi-Gaussian Attention and Covariance Loss for Single Domain Generalization. 《IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT》, 2025.
- [5] 宋艳. Domain Generalization Combining Covariance Loss With Graph Convolutional Networks for Intelligent Fault Diagnosis of Rolling Bearings. IEEE Transactions on Industrial Informatics, 2024.
- [6] 从霄. Federated domain generalization with global robust model aggregation strategy for bearing fault diagnosis. MEASUREMENT SCIENCE AND TECHNOLOGY, 34, 2023.
- [7] 王代超. Attention-Based Bilinear Feature Fusion Method for Bearing Fault Diagnosis. 《IEEE-ASME TRANSACTIONS ON MECHATRONICS》, 28, 1695-1705, 2022.
- [8] 王代超. Bearing Fault Diagnosis Method Based on Complementary Feature Extraction and Fusion of Multisensor Data. 《IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT》, 71, 2022.
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