李 丹


通讯方式:lidan@seu.edu.cn

研究方向:

(1)结构健康监测与隐蔽病害识别

(2)声发射与超声无损检测

(3)大跨度桥梁智能运维

(4)信号处理与深度学习


办公地点:3522vip浦京集团官网九龙湖校区土木教学科研楼1014

 

 

个人简介

,副教授、博士生导师,入选江苏省科协青年科技人才托举工程、江苏省“双创博士”。博士毕业于新加坡国立大学,主要从事结构健康监测与损伤识别、声发射与超声无损检测、桥梁智能建造与运维等方向研究。主持国家自然科学基金面上项目、青年基金项目等课题10余项,在Automation in Construction、Mechanical Systems and Signal Processing、Engineering Structures、Structural Health Monitoring等国内外期刊发表学术论文40余篇(高被引3篇、热点论文2篇)出版英文专著1部,授权专利软著7项,参编省级标准1部。荣获Springer Theses Award 施普林格国际优秀博士论文奖、中国振动工程学会科技进步一等奖、中国公路学会科技进步二等奖、江苏省工程师学会科技进步特等奖等荣誉。

教育经历

  • 2012.08 – 2017.01  新加坡国立大学,土木工程,博士

  • 2009.09 – 2012.06  中南大学,土木工程(桥梁),硕士

  • 2005.09 – 2009.06  中南大学,土木工程(桥梁),本科

工作经历

  • 2022.08 – 至今       3522vip浦京集团官网,3522vip浦京集团官网,副教授

  • 2017.02 – 2022.07  合肥工业大学,土木与水利工程学院,讲师、副教授

学术兼职
  • 中国振动工程学会随机振动专业委员会委员

  • 中国建筑学会城市安全分会理事

  • 美国声发射工作组成员

  • 江苏省工程师学会风工程专委会委员

  • 《3522vip浦京集团官网学报(自然科学版)》期刊青年编委

  • 《应用基础与工程科学学报》期刊青年编委

  • 《Smart Construction》期刊青年编委

  • 《交通科学与工程》期刊青年编委

  • Measurement Science and Technology等期刊客座编辑

  • Automation in Construction、Mechanical Systems and Signal Processing、Engineering StructuresStructural Health Monitoring、Measurement、Applied Acoustics等期刊审稿人

教学课程
  • 桥梁工程(B0510151本科生课程)

  • 结构试验与检测(MS005131硕士生课程)

  • 高等桥梁结构分析理论(DB005114博士生课程)

科研、教改项目
  • 家自然科学基金面上项目,“基于声发射的桥梁高强螺栓群损伤精准识别及演化机理研究”,2024-2027,主持

  • 国家自然科学基金青年基金项目,“基于声发射信号改进经验小波分析的钢桥面板疲劳裂纹定量监测方法研究”,2018-2020,主持

  • 国家重点研发计划,“城市建筑外围护结构高效率智能化损伤诊断技术和装备研发”,2025-2027,子课题负责人

  • 国家自然科学基金重点项目,“物理模型-实测数据协同驱动的大跨索承桥梁特异风效应与灾变机理研究”,2024-2028,参与

  • 国家自然科学基金面上项目,“基于长期监测数据和贝叶斯推理的桥梁结构可靠性预后方法研究”,2019-2022,参与

  • 国家自然科学基金面上项目,“基于响应传递比的桥梁结构应变模态参数识别方法研究”,2018-2021,参与

  • 新加坡教育部基金项目,“Rail crack monitoring using smart sensors”,2014-2016,参与

论文和专著

学术专著

  • D. Li (2018). Rail crack monitoring using acoustic emission technique. Springer, ISBN: 978-981-10-8347-1.

代表性论文

  • D. Li, J.H. Nie*, H. Wang*, T. Yu, K.S.C. Kuang (2025). Path planning and topology-aided acoustic emission damage localization in high-strength bolt connections of bridges. Engineering Structures, 332: 120103. (中科院1区TOP)

  • J.H. Nie, D. Li*, H. Wang, T. Yu, K.S.C. Kuang (2025). Acoustic emission source location in orthotropic steel decks based on topology-aided multi-objective optimization and A0 arrival time correction. Mechanical Systems and Signal Processing, 230: 112614. (中科院1区TOP)

  • J.H. Nie, D. Li*, H. Wang*, S.L. Xiang, T. Yu, J.X. Mao (2025). Acoustic emission source location in complex structures based on artificial potential field-guided rapidly-exploring random tree* and genetic algorithm. Mechanical Systems and Signal Processing, 224: 112061. (中科院1区TOP)

  • J.H. Nie, D. Li*, H. Wang*, T. Yu, K.S.C. Kuang (2025). Multi-objective optimization-based acoustic emission damage location in orthotropic steel decks considering complex wave paths. Engineering Structures, 330: 119956. (中科院1区TOP)

  • L. Zhu, X.H. Zhang, D. Li*, J.H. Li, Z. Wang, R.Z. Tian (2025). An experimental and numerical study on the corrosion characteristics of weathering steel-concrete composite beams. Construction and Building Materials, 462: 139893. (中科院1区TOP)

  • D. Li, T. Yu, H. Wang*, C.X. Hu, J.H. Nie, P.F. Cheng, W.Y. He (2025). Spectral element simulation data-driven acoustic emission damage location in orthotropic steel decks. Developments in the Built Environment, 22: 100676.

  • D. Li, Q.F. Chen, H. Wang*, P. Shen, Z.B. Li, W.Y. He (2024). Deep learning-based acoustic emission data clustering for crack evaluation of welded joints in field bridges. Automation in Construction, 165: 105540. (中科院1区TOP)

  • D. Li, J.H. Nie, H. Wang*, W.X. Ren (2024). Loading condition monitoring of high-strength bolt connections based on physics-guided deep learning of acoustic emission data. Mechanical Systems and Signal Processing, 206: 110908. (中科院1区TOP, 高被引、热点论文)

  • D. Li, J.H. Nie, H. Wang*, J.B. Yan, C.X. Hu, P. Shen (2023). Damage location, quantification and characterization of steel-concrete composite beams using acoustic emission. Engineering Structures, 283: 115866. (中科院1区TOP, 高被引、热点论文)

  • D. Li, J.H. Nie, W.X. Ren*, W.H. Ng, G.H. Wang, Y. Wang (2022). A novel acoustic emission source location method for crack monitoring of orthotropic steel plates. Engineering Structures, 253: 113717. (中科院1区TOP)

  • D. Li , Y. Wang, W.J. Yan, W.X. Ren* (2021). Acoustic emission wave classification for rail crack monitoring based on synchrosqueezed wavelet transform and multi-branch convolutional neural network. Structural Health Monitoring, 20(4): 1563-1582. (高被引论文)

  • D. Li, Z.L. Liang, W.X. Ren*, D. Yang, S.D. Wang, S.L. Xiang (2021). Structural damage identification under non-stationary excitations through recurrence plot and multi-label convolution neural network. Measurement, 186: 110101.

  • W.J. Yan*, S.Z. Cao, W.X. Ren, K.V. Yuen, D. Li*, L. Katafygiotis (2021). Vectorization and distributed parallelization of Bayesian model updating based on a multivariate complex-valued probabilistic model of frequency response functions. Mechanical Systems and Signal Processing, 156: 107615. (中科院1区TOP)

  • D. Li*, K.S.C. Kuang, C.G. Koh (2018). Rail crack monitoring based on Tsallis synchrosqueezed wavelet entropy of acoustic emission signals: a field study. Structural Health Monitoring, 17(6): 1410-1424.

  • 李丹, 陈燕秋, 王浩*, 等(2024). 基于声发射的钢桥面板焊接气孔缺陷在线识别. 3522vip浦京集团官网学报(自然科学版), 54(2): 285-293.

  • 李丹, 沈鹏, 贺文宇*, 等 (2024). 基于声发射信号时频图深度学习的桥梁钢桁架焊接节点损伤程度识别. 振动与冲击, 43(1): 107-115. 

代表性报告

  • D. Li, Q.F. Chen, J.H. Nie, H. Wang (2025). Acoustic emission source mechanism identification and damage diagnosis based on physics-guided deep clustering. The 65th Meeting of the Acoustic Emission Working Group (AEWG-65), Chicago, IL, USA.

  • 李丹, 李晓雪,  任伟新 (2024). 基于振动声调制响应多任务学习的高强螺栓节点预紧力诊断. 第十届全国结构抗振控制与健康监测学术会议, 福建, 厦门.

  • D. Li, J.H. Nie, H. Wang (2023). Acoustic emission monitoring of infrastructures based on time-frequency representation and deep learning. The 12th International Conference on Structural Health Monitoring of Intelligent Infrastructure ((SHMII-12)), Hangzhou, China

  • D. Li, J.H. Nie, J.B. Yan, C.X. Hu, P. Shen (2022). Structural health monitoring of steel-concrete composite beams using acoustic emission. The 17th East Asia-Pacific Conference on Structural Engineering & Construction (EASEC17), Singapore.

  • 李丹 (2020). 基于声发射信号改进经验小波分析的钢桥面板疲劳裂纹定量监测方法研究. 国家自然科学基金第三届土木工程青年论坛, 四川, 成都.

  • D. Li, S.P. Xu, Y. Wang, W.X. Ren (2019). Acoustic emission feature extraction and classification for rail crack monitoring. The 12th International Workshop on Structural Health Monitoring (IWSHM 2019), Stanford, CA, USA.

  • D. Li, W.X. Ren (2019). Deep learning-aided rail crack monitoring using acoustic emission. International Conference on Smart Infrastructure and Construction (ICSIC2019), Cambridge, UK.

  • D. Li, K.S.C. Kuang, C.G. Koh (2018). Enhanced synchrosqueezed wavelet transform based acoustic emission feature quantification for rail crack monitoring. The 60th Meeting of the Acoustic Emission Working Group (AEWG-60), Charleston, CS, USA.

荣誉和奖励
  • 荣获中国振动工程学会科技进步一等奖,2022

  • 荣获中国公路学会科技进步二等奖,2023

  • 荣获江苏省工程师学会科技进步特等奖,2024

  • 入选江苏省科协青年科技人才托举工程,2023

  • 入选江苏省“双创博士”,2023

  • 荣获Springer Theses Award施普林格国际优秀博士论文奖,2018

指导学生

欢迎对土木工程、无损检测、人工智能交叉领域感兴趣的同学报考硕士、博士研究生,共同开展创新性研究。