海洋测控研究团队
研究人员
宋艳
发布时间:2018年11月25日 21:30    作者:    点击:[]

个人简介:

宋艳,女,现为山东大学海洋研究院助理研究员,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。目前主持国家自然科学基金青年项目1项、中央高校科研业务费项目1项。

E-mail: ysong@sdu.edu.cn

Abstract:

Dr. Yan Song is working as a research assistant in Institute of Marine Science and Technology at Shandong University. Her research interests involve underwater object detection using side scan sonar and intelligent fault diagnosis based on deep learning and machine learning. Dr. Song has published more than 10 papers in top journals such as IEEE Transactions on Industrial Informatics, IEEE Internet of Things Journal, IEEE Journal of Oceanic Engineering, and Neurocomputing.

学习工作经历:

中国海洋大学博士(2018

山东大学助理研究员(2018.07-

Experiences:

Ph.D., Ocean University of China (2018)

Research assistant, Shandong University (2018.07-)

研究方向:

声呐图像分割;故障诊断;剩余使用寿命预测;深度学习;机器学习

Research Interests:

Sonar image segmentation; fault diagnosis; remaining useful life prediction; deep learning; machine learning

代表性著作/Selected Publications

[1] Li, Yibin, Yan Song*, Lei Jia, S. Gao, Qiqiang Li and Meikang Qiu. “Intelligent Fault Diagnosis by Fusing Domain Adversarial Training and Maximum Mean Discrepancy via Ensemble Learning.” IEEE Transactions on Industrial Informatics 17 (2021): 2833-2841.

[2] Song, Yan, S. Gao, Yibin Li*, Lei Jia, Qiqiang Li and Fuzhen Pang. “Distributed Attention-Based Temporal Convolutional Network for Remaining Useful Life Prediction.” IEEE Internet of Things Journal (2020): 1-1.

[3] Song, Y., B. He* and Peng Liu. “Real-Time Object Detection for AUVs Using Self-Cascaded Convolutional Neural Networks.” IEEE Journal of Oceanic Engineering 46 (2021): 56-67.

[4] Song, Y., Yibin Li*, Lei Jia and Meikang Qiu. “Retraining Strategy-Based Domain Adaption Network for Intelligent Fault Diagnosis.” IEEE Transactions on Industrial Informatics 16 (2020): 6163-6171.

[5] Song, Y. and Peng Liu. “Segmentation of sonar images with intensity inhomogeneity based on improved MRF.” Applied Acoustics 158 (2020): 107051.

[6] Song, Yan, B. He*, Peng Liu and T. Yan. “Side scan sonar image segmentation and synthesis based on extreme learning machine.” Applied Acoustics 146 (2019): 56-65.

[7] Liu, P. and Y. Song*. “Segmentation of sonar imagery using convolutional neural networks and Markov random field.” Multidimensional Systems and Signal Processing 31 (2020): 21-47.

[8] He, B.*#, Y. Song#, Yuemei Zhu, Q. Sha, Y. Shen, T. Yan, Rui Nian and A. Lendasse. “Local receptive fields based extreme learning machine with hybrid filter kernels for image classification.” Multidimensional Systems and Signal Processing (2019): 1-21.

[9] Song, Yan, B. He*, Ying Zhao, Guangliang Li, Q. Sha, Y. Shen, T. Yan, Rui Nian and A. Lendasse. “Segmentation of Sidescan Sonar Imagery Using Markov Random Fields and Extreme Learning Machine.” IEEE Journal of Oceanic Engineering 44 (2019): 502-513.

[10] Song, Y., Shujing Zhang, B. He*, Q. Sha, Y. Shen, T. Yan, Rui Nian and A. Lendasse. “Gaussian derivative models and ensemble extreme learning machine for texture image classification.” Neurocomputing 277 (2018): 53-64.

[11] Zhang, Heng-Guo, L. Wu, Yan Song, Chi-Wei Su, Q. Wang and Fei Su. “An Online Sequential Learning Non-parametric Value-at-Risk Model for High-Dimensional Time Series.” Cognitive Computation 10 (2017): 187-200.

专利:

[1] 宋艳; 李沂滨; 贾磊; 王代超; 郭庆稳. 一种基于集成域自适应的故障诊断方法及系统: 中国, CN202010490493.7[P]. 2020-10-02.

[2] 宋艳; 李沂滨; 高辉; 胡晓平; 王代超; 张天泽. 基于DA-TCN的设备剩余使用寿命的估计方法及系统: 中国, CN202010107734.5[P]. 2020-06-26. (已授权)

[3] 李沂滨; 宋艳; 郭庆稳; 王代超. 一种面向机电设备的智能故障诊断方法及系统: 中国, CN201911000874.6[P]. 2020-06-09.(已授权)

[4] 宋艳; 李沂滨; 何波. 基于自适应像素值约束和MRF的声呐图像分割方法:中国, CN201811474946.6[P]. 2019-05-21.

[5] 宋艳; 李沂滨; 何波. 基于SLIC和自适应滤波的声呐图像均衡化方法: 中国, CN201811474850.X [P]. 2019-05-03.

[6] 何波; 朱越美; 宋艳. 基于数据驱动的自主式水下航行器海底路径规划方法:中国. ZL201810269820.9.(已授权)

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