学术专著
D. Li (2018). Rail crack monitoring using acoustic emission technique (基于声发射的钢轨裂纹监测). Springer, ISBN: 978-981-10-8347-1.
代表性学术论文
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，JCR Q1，IF=10.3)
D. Li, J.H. Nie, H. Wang*, W.X. Ren (2023). 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，JCR Q1，IF=8.4，ESI高被引论文)
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，JCR Q1，IF=5.5，ESI高被引论文)
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，JCR Q1，IF=5.5)
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. (JCR Q1，IF=6.6，期刊Most Cited Articles)
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. (JCR Q1，IF=5.6)
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. (JCR Q1，IF=6.6)
学术会议报告
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 (ICSIC), 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.
