宋艳
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Paper Publications
- [1] . A global information-guided denoising diffusion probabilistic model for fault diagnosis with imbalanced data. Engineering Applications of Artificial Intelligence, 147, 2025.
- [2] 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.
- [3] 宋艳. Domain Generalization Combining Covariance Loss With Graph Convolutional Networks for Intelligent Fault Diagnosis of Rolling Bearings. IEEE Transactions on Industrial Informatics, 2024.
- [4] 从霄. Federated domain generalization with global robust model aggregation strategy for bearing fault diagnosis. MEASUREMENT SCIENCE AND TECHNOLOGY, 34, 2023.
- [5] 宋艳. Federated domain generalization for intelligent fault diagnosis based on pseudo-siamese network and robust global model aggregation. International Journal of Machine Learning and Cybernetics, 2023.
- [6] 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.
- [7] 王代超. Attention-Based Bilinear Feature Fusion Method for Bearing Fault Diagnosis. 《IEEE-ASME TRANSACTIONS ON MECHATRONICS》, 28, 1695-1705, 2022.
- [8] Song, Y., Gao, S., Li, Y.*, Jia, L.*, Li, Q., & Pang, F.. Distributed Attention-Based Temporal Convolutional Network for Remaining Useful Life Prediction. IEEE Internet of Things Journal, 8, 9594-9602, 2021.
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