宋艳，女，现任山东大学海洋研究院副教授，主要从事机器学习、深度学习在海洋声呐数据处理以及机械设备故障诊断与剩余寿命预测等方面的应用研究。以第一作者或通讯作者在中科院一区/二区期刊发表SCI论文10余篇，现任IEEE Journal of Oceanic Engineering期刊副主编。
1. 声呐图像分割
2. 智能故障诊断
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.
9. Li, Y., Song, Y.*, Jia, L*., Gao, S., Li, Q., & Qiu, M.. Intelligent Fault Diagnosis by Fusing Domain Adversarial Training and Maximum Mean Discrepancy via Ensemble Learning. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 17, 2833, 2021.
10. Song, Y., He, B.*, & Liu, P.. Real-Time Object Detection for AUVs Using Self-Cascaded Convolutional Neural Networks. IEEE JOURNAL OF OCEANIC ENGINEERING, 46, 56, 2021.
11. Song, Y., Li, Y.*, Jia, L., & Qiu, M.. Retraining Strategy-Based Domain Adaption Network for Intelligent Fault Diagnosis. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 16, 6163, 2020.
12. Guo, Q., Li, Y.*, Song, Y., Wang, D., & Chen, W.. Intelligent Fault Diagnosis Method Based on Full 1-D Convolutional Generative Adversarial Network. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 16, 2044, 2020.
13. Song, Y.*, & Liu, P.. Segmentation of sonar images with intensity inhomogeneity based on improved MRF. Applied Acoustics, 158, 2020.
14. Liu, P., & Song, Y.*. Segmentation of sonar imagery using convolutional neural networks and Markov random field. Multidimensional Systems and Signal Processing, 31, 21, 2020.
15. Song, Y., He, B.*, Zhao, Y., Li, G., Sha, Q., Shen, Y., Yan, T., Nian, R., & Lendasse, A.. Segmentation of Sidescan Sonar Imagery Using Markov Random Fields and Extreme Learning Machine. IEEE Journal of Oceanic Engineering,
16. Song, Y., Zhang, S., He, B.*, Sha, Q., Shen, Y., Yan, T., Nian, R., & Lendasse, A.. Gaussian derivative models and ensemble extreme learning machine for texture image classification. Neurocomputing, 277, 53-64,
17. Song, Y., He, B.*, Liu, P., & Yan, T.. Side Scan Sonar Image Segmentation and Synthesis Based on Extreme Learning Machine. Applied Acoustics, 2019.
1. 一种基于互补决策的开集域适应故障诊断方法及系统
2. 一种基于领域泛化的故障诊断方法及系统
3. 基于联邦学习和双重监督对比学习的故障诊断方法及系统
4. 基于自适应像素值约束和MRF的声呐图像分割方法
5. 基于数据融合的锂电池剩余使用寿命预测方法及装置
6. 基于全局鲁棒加权的联邦域泛化故障诊断方法及系统
7. 一种故障诊断方法、系统、设备及存储介质
8. 一种用于机械设备故障诊断的信号特征提取方法及系统
9. 基于改进型生成对抗网络的设备故障诊断方法及系统
10. 基于模型差异的故障诊断方法、系统、存储介质及设备
11. 基于联邦域泛化的机械故障诊断方法及系统
12. 一种滚动轴承剩余使用寿命预测方法及系统
13. 基于多源数据合成的侧扫声呐图像数据增强方法及系统
14. 一种基于集成域自适应的故障诊断方法及系统
15. 一种锂电池剩余使用寿命预测方法及系统
16. 基于DA-TCN的设备剩余使用寿命的估计方法及系统
17. 一种面向机电设备的智能故障诊断方法及系统
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5. 车用燃料电池氢气喷射泵总体设计技术, 2019/12/01-2023/11/30
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7. 类别不平衡和灰度不均匀条件下侧扫声纳图像实时分割方法研究, 2019/08/16-2022/12/31
1. 随机过程
2. 形势与政策(4)
3. 毕业论文(设计)
4. Python数据分析与展示
5. 概率论与数理统计
1.从霄
2.崔明
