姓名: 陈美,工学博士,副教授
Email: chenmei950818@163.com
科研和研究生招生方向:
1、人工智能与数据挖掘
2、大数据分析与信号处理
3、铁路基础设施状态监测与故障诊断
个人简介:
陈美,工学博士,yL23411永利官网登录副教授,硕士生导师。2022年7月博士毕业于西南交通大学牵引动力国家重点实验室,师从中国科学院院士、美国工程院外籍院士翟婉明教授,长期从事机器学习算法及其在高速铁路基础结构服役状态监测与损伤智能识别中的应用等研究工作。博士期间作为国家公派联合培养博士生赴日本东京大学(The University of Tokyo)留学12个月,师从车辆动力学与控制研究领域国际权威专家Yoshihiro SUDA教授,期间从事机器学习与大数据分析、车辆异常状态及脱轨检测等研究工作。博士期间获博士研究生国家奖学金、唐立新奖学金、西南交通大学优秀研究生标兵等荣誉奖励。
陈美博士主持国家自然科学基金青年基金项目,四川省自然科学基金青年基金项目,牵引动力国家重点实验室开放课题项目共3项,参与国家自然科学基金重大、重点、面上项目4项。已在《Construction and Building Materials》、《Engineering Structures》、《Wear》、《Journal of Sound and Vibration》、《Vehicle System Dynamics》、《科学通报》等国内外著名期刊与学术会议上发表学术论文13篇(中科院1区TOP期刊3篇,中科院2区期刊3篇,EI检索论文5篇,国际会议论文1篇),获2项发明专利授权(1项排名第1)。目前担任《Engineering Structures》、《Vehicle System Dynamics》、《International Journal of Rail Transportation》、《Measurement》等国际学术期刊审稿人。
承担科研项目:
1. 国家自然科学基金青年基金项目,52402511,30万元,主持
2. 四川省自然科学基金青年基金项目,2024NSFSC0940,10万元,主持
3. 牵引动力国家重点实验室开放课题项目,TPL2312,10万元,主持
目前授课:
1. 《人工智能导论》(双语),本科生
2. 《数据挖掘与应用》、《数据挖掘实践项目》,本科生
3. 《大学计算机基础》,本科生
4. 《论文写作》,研究生
近5年发表论文(*为通信作者):
1. Mei Chen, Shengyang Zhu, Wanming Zhai*, Yu Sun, Qinglai Zhang. Inversion and identification of vertical track irregularities considering the differential subgrade settlement based on fully convolutional encoder-decoder network. Construction and Building Materials, 2023, 367: 130057. (SCI,中科院1区Top期刊,JCR-Q1区)
2. Mei Chen, Yu Sun, Shengyang Zhu, Wanming Zhai*. Dynamic performance comparison of different types of ballastless tracks using vehicle-track-subgrade coupled dynamics model. Engineering Structures, 2021, 249: 113390. (SCI,中科院1区Top期刊,JCR-Q1区)
3. Mei Chen, Wanming Zhai, Shengyang Zhu*, Lei Xu, Yu Sun. Vibration-based damage detection of rail fastener using fully convolutional networks. Vehicle System Dynamics, 2022, 60(7): 2191-2210. (SCI, 中科院2区,JCR-Q2区)
4. Mei Chen, Yu Sun, Yu Guo, Wanming Zhai*. Study on effect of wheel polygonal wear on high-speed vehicle-track-subgrade vertical interactions. Wear, 2019, 432: 102914.(SCI,中科院1区Top期刊,JCR-Q1区)
5. Mei Chen, Yu Sun, Wanming Zhai*. High efficient dynamic analysis of vehicle-track-subgrade vertical interaction based on Green function method. Vehicle System Dynamics, 2020, 58(7): 1076-1100.(SCI, 中科院2区,JCR-Q2区)
6. Yu Sun, Mei Chen*. Modelling of periodic slab track using time-frequency hybrid Green’s function method and its application to vehicle-track dynamic interaction. Journal of Sound and Vibration, 2021, 511: 116327. (SCI,中科院2区Top期刊,JCR-Q1区)
7. 陈美, 翟婉明*, 閣鑫, 孙宇. 高速铁路多边形车轮通过钢轨焊接区的轮轨动力特性分析. 科学通报, 2019, 64(25): 2573-2582.(EI,中文高水平期刊)
8. Mei Chen, Wanming Zhai*, Yu Sun. Investigation on effect of wheel polygonal wear on high-speed vehicle-track-subgrade interaction based on green function method. Proceedings of the 11th International Conference on Contact Mechanics and Wear of Rail/Wheel Systems, 2018, 147-154.(EI)
9. Mei Chen, Yu Sun, Wanming Zhai*. Effect of polygonal wheel on dynamic performances of high-speed vehicle-slab track system. Proceedings of the 1st International Conference on Rail Transportation, 2018, 929-937.(EI)
10. Shihpin Lin, Yu Wang, Yoshihiro Suda*, Mei Chen. Attempt about the real thing considering digital and post-pandemic on the chiba test line. The Proceedings of the Transportation and Logistics Conference, 2021, 30: SS2-3-6.(国际会议)
11. Yu Sun, Yu Guo, Kaikai Lv, Mei Chen, Wanming Zhai*. Effect of hollow-worn wheels on the evolution of rail wear. Wear, 2019, 436: 203032. (SCI,中科院1区Top期刊,JCR-Q1区)
12. Yu Sun, Yu Guo, Mei Chen, Wanming Zhai*. A three-dimensional vehicle-track coupled dynamic model based on the Green’s function method. Proceedings of the Stephenson Conference: Research for Railways, 2017, 463-472.(EI)
13. Qinglai Zhang, Shengyang Zhu*, Zhandong Yuan, Mei Chen. Compound damage discrimination for steel-spring floating-slab track using 1D convolutional neural network. Proceedings of the 2nd International Conference on Rail Transportation, 2021, 33-40.(EI)
发明专利:
1. 陈美, 翟婉明, 孙宇. 一种计算车辆-轨道耦合系统动力学的方法. 发明专利, 授权专利号: ZL201710960298.4
2. 袁站东, 朱胜阳, 翟婉明, 袁玄成, 陈美, 张庆铼. 一种基于卷积神经网络的铁路扣件系统损伤检测方法. 发明专利, 授权专利号: ZL201910533149.9