宋艳
副教授
所属院部: 海洋研究院
访问次数:
基本信息
  • 教师拼音名称:
    songyan
  • 入职时间:
    2018-07-17
  • 所在单位:
    海洋研究院
  • 学历:
    研究生(博士)毕业
  • 性别:
  • 联系方式:
    ysong@sdu.edu.cn
  • 学位:
    博士生
  • 在职信息:
    在职
  • 毕业院校:
    中国海洋大学
  • 硕士生导师
教育经历
  • 2012-8 — 2015-6
    中国海洋大学
    信息与通信系统
    工学硕士学位
  • 2015-9 — 2018-6
    中国海洋大学
    智能信息与通信系统
    工学博士学位
工作经历
  • 2018-7 — 2023-3
    山东大学海洋研究院
研究领域

宋艳,女,现为山东大学海洋研究院副教授,主要开展机器学习、深度学习在海洋声呐数据处理、机械设备故障诊断与剩余寿命预测中的应用研究,目前发表SCI/EI论文10余篇。


科研成果
论文

1.  从霄. Federated domain generalization with global robust model aggregation strategy for bearing fault diagnosis.  MEASUREMENT SCIENCE AND TECHNOLOGY,  34,  2023. 

2.  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. 

3.  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. 

4.  王代超. Attention-Based Bilinear Feature Fusion Method for Bearing Fault Diagnosis.  《IEEE-ASME TRANSACTIONS ON MECHATRONICS》,  28,  1695-1705, 2022. 

5.  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. 

6.  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. 

7.  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. 

8.  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. 

9.  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. 

10.  Song, Y.*, & Liu, P.. Segmentation of sonar images with intensity inhomogeneity based on improved MRF.  Applied Acoustics,  158,  2020. 

11.  Liu, P., & Song, Y.*. Segmentation of sonar imagery using convolutional neural networks and Markov random field.  Multidimensional Systems and Signal Processing,  31,  21, 2020. 

12.  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, 

13.  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,

14.  Song, Y., He, B.*, Liu, P., & Yan, T.. Side Scan Sonar Image Segmentation and Synthesis Based on Extreme Learning Machine.  Applied Acoustics,  2019. 

专利
学生信息
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